Measurement properties of the Short Form-36 (SF-36) and the Functional Assessment of Cancer Therapy - Anemia (FACT-An) in patients with anemia associated with chronic kidney disease

Measurement properties of the Short Form-36 (SF-36) and the Functional Assessment of Cancer... Background: Anemia is a common and debilitating manifestation of chronic kidney disease (CKD). Data from two clinical trials in patients with anemia of CKD were used to assess the measurement properties of the Medical Outcomes Survey Short Form-36 version 2 (hereafter SF-36) and the Functional Assessment of Cancer Therapy-Anemia (FACT-An). The Vitality and Physical functioning domains of the SF-36 and the FACT-An Total, Fatigue and Anemia subscales were identified as domains relevant to CKD-associated anemia. Methods: A total of 204 patients aged 18–80 years were included in the analyses that included internal consistency (Cronbach’s alpha), test-retest reliability (intraclass correlation coefficients [ICCs]), convergent and known-groups validity, responsiveness, and estimates of important change. Results: Both the SF-36 and the FACT-An had strong psychometric properties with high internal consistency (Cronbach’s alpha: 0.69–0.93 and 0.79–0.95), and test-retest reliability (ICCs: 0.64–0.83 and 0.72–0.88). Convergent validity, measured by correlation coefficients between similar concepts in SF-36 and FACT-An, ranged from 0.52 to 0.77. Correlations with hemoglobin (Hb) levels were modest at baseline; by Week 9, the correlations with Hb were somewhat higher, r= 0.23 (p < 0.05) for SF-36 Vitality, r =0.22 (p < 0.05) for FACT-An Total, r =0.26 (p <0.001) for FACT-Fatigue and r= 0.22 (p < 0.01) for Anemia. Correlations with Hb at Week 13/17 were r =0.28 (p <0. 001) for SF-36 Vitality and r =0.25 (p < 0.05) for Role Physical; FACT-An Total correlation was r =0.33 (p <0. 0001), Anemia was r = 0.28 (p < 0.001), and Fatigue was r =0.30 (p < 0.001). The SF-36 domains and Component Summary scores (p <0.05–p < 0.0001) demonstrated ability to detect change. For the FACT-An, significant differences (p <0.05–p < 0.0001) were observed between responder and non-responder change scores: important change score estimates ranged from 2 to 4 for Vitality and 2–3for Physical functioning. Important change scores were also estimated for the FACT-An Total score (6–9), the Anemia (3–5),and Fatiguesubscale(2–4). Conclusions: Both the SF-36 Vitality and Physical function scales and the FACT-An Total, Fatigue and Anemia scales, are reliable and valid measures for assessing health-related quality of life in anemia associated with CKD. Keywords: Anemia, Chronic kidney disease, Quality of life, Psychometric evaluation, SF-36, FACT-An * Correspondence: fof@comcast.net Yale University, New Haven, CT, USA Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 2 of 13 Background review, and expert input. The Total FACT-An score and Anemia is common among patients with chronic kidney the FACT Anemia and Fatigue score are of particular disease (CKD); the prevalence in US patients is esti- interest for use with anemia associated with CKD. Al- mated to be over 15% [1]. An association between though the tool has been used in many oncology clinical anemia and CKD stage has been identified, with anemia trials, [30–33], data in the CKD population are lacking. increasing in prevalence by disease severity from 8.4% in Both the European Medicines Agency [34]and the Stage 1 to 53.4% in Stage 5. Minutolo et al. [2] reported US Food and Drug Administration [35] require that a 44% prevalence of anemia across all CKD stages in pa- new drugs under consideration for approval be tested tients who were not receiving dialysis, while McFarlane in clinical trials with PRO endpoints that are specific et al. estimated a prevalence of 50 to 70% across all and relevant to the proposed treatment population. stages [3]. Documentation of measurement properties of do- Symptoms of anemia include fatigue, low energy, weak- mains of PRO surveys in the target population is es- ness, dizziness, and dyspnea [4, 5]; symptom severıty var- sential. The purpose of this study is to assess further ies wıth the degree of anemia [6]. Persistent fatigue has the measurement properties of the SF-36 and the been identified as one of the most debilitating symptoms FACT-An with particular focus on domains of vital- both pre-dialysis and in dialysis disease stages [7, 8]. The ity/fatigue, anemia, and physical function, which most impact of fatigue varies widely, from being described as closely relate to CKD anemia. Data from two clinical ‘mild impairment’ to greatly affecting daily functioning in- trials in patients with CKD anemia who were not re- cluding, at times, basic activities of daily living [9]. Dimin- ceiving dialysis or who were newly initiated on dialy- ished aspects of health-related quality of life sis were used to evaluate the validity of SF-36 and (HRQoL), such as functional and ambulatory impair- the FACT-An in this sample. ment, and increased risk of falls, have all been identi- fied as complications of anemia [10–14]. Methods Patient-reported outcome (PRO) measures are fre- Patient sample quently used to assess treatment efficacy in clinical trials Data were derived from two clinical trials that evaluated [15]. Although used in some trials as primary endpoints a hypoxia-inducing factor prolyl hydroxylase (HIF-PH) (eg, a patient report of pain is required in the absence of inhibitor in patients with CKD anemia. The trial designs objective clinical markers), PROs are often used to iden- were similar, but not identical, and allow the evaluation tify additional benefits associated with treatment, includ- of the SF-36 and FACT-An questionnaires in patients ing symptom experience, functioning, and HRQoL. with ESRD. Details of these trials including treatment in- Thus, measurement of HRQoL as a primary outcome of terventions have been published previously [36–38]. treatment interventions in end-stage renal disease Briefly, the first (NCT00761657) was a Phase 2, (ESRD), as well as a tool for clinicians to assess patient open-label, randomized trial in patients with anemia and status, is an increasingly accepted research endpoint. Stage 3 or 4 CKD, who were not on dialysis (non-dialysis While earlier studıes suggested a broad range of group) [36]. The patients were 18–70 years old with an symptom improvement wıth anemia treatment, recent Hb level < 10.5 g/dL and an estimated glomerular filtra- studies indicate that the domains of Vitality and tion rate of > 15 to < 60 mL/min/1.73 m Physical functioning are most beneficially affected by pre-randomization. The second (NCT01244763) was a treatment [6, 16]. Phase 2b, randomized, open-label trial in newly initiated The Medical Outcomes Survey Short Form-36 patients on dialysis (dialysis group) [37, 38]. The patients (SF-36) is a generic, widely validated HRQoL measure were 18–80 years old with a pre-randomization Hb level that has been used in numerous research studies and < 10.0 g/dL. They had received hemodialysis or periton- clinical trials of CKD anemia [11, 17–25] with specific eal dialysis for native kidney ESRD for a minimum of 2 focus on the Vitality and Physical functioning domains weeks and a maximum of 4 months. Patients in both [6, 16, 26]. Measurement properties of SF-36 have studies were not currently and had not previously re- been assessed in patients with CKD, [27] but no corre- ceived an erythropoietin-stimulating agent (ESA) or IV sponding data are available specifically for patients iron within 4 weeks of randomization. with CKD anemia. The Functional Assessment of Cancer Therapy-Anemia Study design (FACT-An) was developed to assess the impact of anemia In the non-dialysis trial, dosing strategies for the on quality of life in patients with cancer-associated anemia HIF-PH inhibitor were employed across six cohorts [28, 29]. Content validity was addressed during the devel- (with 24–25 patients per cohort). Patients attended opment of the FACT-An and was based on interviews weekly study visits during the treatment period (16 weeks with patients with cancer-associated anemia, literature for Cohorts A and B, and 24 weeks for Cohorts C Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 3 of 13 through F). The FACT-An and the SF-36 questionnaires The FACT-An also includes 13 fatigue-specific items were administered at baseline, Week 9, Week 17 (Co- (the Fatigue Subscale) plus an additional 7 items specific horts A–D only for SF-36), and Week 24 (Cohorts C–D to anemia and unrelated to fatigue. Anemia subscales only). such as FACT-An Total and the Fatigue and Anemia In the dialysis trial, approximately 12 patients were en- subscales were of special interest. These last 20 items rolled in each of five HIF-PH inhibitor treatment arms. (13 + 7) combine to form the Anemia subscale. Higher The trial employed a 1:1:1 ratio for the first 36 patients scores indicate better health status. An important to receive no iron supplementation, oral iron supple- change score estimate of 4 points for the Anemia total mentation, and IV iron supplementation. Patients visited score and 3 points for the Fatigue score has previously the clinic weekly during the 12-week treatment period, been reported in patients with cancer [41]. In patients followed by a four-week post-treatment follow-up with CKD, a three-point or greater increase was previ- period. The FACT-An and SF-36 questionnaires were ously identified as a clinically meaningful improvement administered at baseline, Week 9, and Week 13. on the FACT-Fatigue total score [42]. Data used to characterize each patient sample were collected at baseline/during screening for both dialysis Statistical analyses and non-dialysis patients. These included sociodemo- Unless stated otherwise, data from the two clinical trials graphic (date of birth, sex, and race/ethnicity) and clin- were pooled at baseline and at Week 9. Week 17 data ical data (weight and height, pulse rate, blood pressure, from the non-dialysis group were pooled with Week 13 respiratory rate, date of CKD diagnosis, date of anemia data from the dialysis group. Pooling the data from the diagnosis, comorbid conditions, laboratory parameters, two trials provided a sufficiently large sample size and a treatments received, and rescue medication use). Hb greater range of impairment within a CKD patient sam- level was collected at baseline, Week 9, and Week 13/17 ple for more effective testing of the measurement prop- (dialysis/non-dialysis) as well as at other time points. erties of SF-36 and FACT-An. All statistical tests were two-sided and significance level was set at p< 0.05. Patient-reported outcome measures For the SF-36 domain/Component Summary scores The SF-36 is designed to assess health concepts that are and the FACT-An Total and subscale scores, descriptive relevant across age, disease, and treatment groups in statistics (mean, SD, median, and range) were calculated adults [39]. As well as a health transition item, the SF-36 at baseline, Week 9, and Week 13/17. contains eight domains: Physical functioning (10 items), Role-physical (4 items), Bodily Pain (2 items), General Reliability Health (5 items), Vitality (4 items), Social functioning (2 Cronbach’s coefficient alpha was used to assess the in- items), Role-emotional (3 items), and Mental Health (5 ternal consistency of the SF-36 domain scores and Com- items). Two Component Summary scores, the Physical ponent Summary scores and the FACT-An Total and Component Summary (PCS) and the Mental Compo- relevant subscales at baseline. A Cronbach’s alpha ≥0.70 nent Summary (MCS), can also be calculated with all was considered an acceptable minimum value definition scores using the norm-based approach (US population for good reliability [43]. Patterns of item-to-item correla- norm mean score for each domain and summary score tions and item-to-total correlations, and the number of is 50, with a standard deviation [SD] of 10) [40]. items in the subscale, were also considered. Alpha coeffi- Anemia-related domains such as the Vitality and Phys- cients > 0.7 indicated good internal consistency, 0.4–< ical functioning were previously identified to be of spe- 0.69 moderate internal consistency, and < 0.4 low in- cial interest [6, 16]. A four-week recall was used for the ternal consistency reliability [44, 45]. SF-36 in both trials. Suggested important change scores Test-retest reliability was assessed in the subgroup of have been reported by the instrument developers for patients (n = 153) whose Hb level was classified as un- each domain and Component Summary score based on changed (average weekly Hb change within ±0.5 g/dL the 2009 US general population [40]. The suggested between Week 9 and Week 13/17 with no rescue ther- change scores are appropriate for T-scores ranging from apy between these time points). The average weekly 30 to 40. Where the T-score for the population exceeds change in Hb was determined by comparing the weekly this range, increasing the change score is recommended. differences in Hb between Week 9 and every week from The FACT-An is designed to assess aspects of quality Week 10 to Week 13/17. Intraclass correlation coeffi- of life affected by anemia in patients with cancer [28]. cients (ICCs) were calculated to compare the SF-36 do- Using a seven-day recall period, the 27 item main/Component Summary and the FACT-An Total FACT-General (FACT-G) includes four dimensions of and subscale scores at Week 9 and Week 13/17. An well-being: Physical (7 items), Functional (7 items), So- ICC ≥ 0.7 indicated good, 0.4–0.7 moderate, and < 0.4 cial/Family (SWB; 7 items), and Emotional (6 items). poor test-retest reliability [44, 45]. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 4 of 13 Validity Baseline Hb level ≤ 8 g/dL: Hb level > 2.0 g/dL Validity refers to the extent to which an instrument increase at the end of Weeks 7–9 and Weeks 11– measures what it is intended to measure; it is typically 13/15–17 assessed by examining correlations with other indicators b. SF-36 responders of similar/related constructs [46]. Correlations of 0.10 Vitality (SF-36) responders: > 3-point increase in are considered small, correlations between 0.30 and 0.50 SF-36 Vitality score are regarded as moderate, and correlations of 0.50 or Physical functioning (SF-36) responders: > 3-point more are considered large [47]. Spearman’s rank-order increase in SF-36 Physical functioning score correlation coefficients between the SF-36 domain/Com- Physical Component Summary (SF-36) responders ponent Summary scores and the FACT-An Total and -– an increase of two points in SF-36 Physical subscale scores at baseline, Week 9, and Week 13/17 Component Summary score; were used to assess convergent validity. c. FACT-An responders The SF-36 Vitality domain was previously identified as FACT-An Anemia responders: > 4-point increase an important measure of disease impact resulting from in FACT-An Anemia score anemia [6, 16], therefore the FACT-An Fatigue and FACT-An Fatigue responders: > 3-point increase Anemia subscales were expected to correlate more in FACT-An Fatigue subscale score. strongly with Vitality domain than other SF-36 domains. Known-groups validity was assessed to demonstrate the Estimating important change scores ability of the SF-36 and FACT-An instrument domain Methods for interpreting the importance of quality of scores to differentiate between patients with varying life changes in clinical research generally follow two ap- levels of anemia, using Hb levels at baseline. The SF-36 proaches: distribution-based and anchor-based. A and FACT-An domain scores were compared between distribution-based approach is based on statistical char- the scores above and below the median Hb level at base- acteristics of the obtained samples. This approach relies line using analysis of covariance (ANCOVA) with adjust- on the distribution of scores and the related effect size ments for gender and age. Similarly, for assessment of of change scores. An anchor-based approach compares known groups validity, the SF-36 Physical Function and the change in a patient reported outcome, such as pa- Vitality median split domain scores were used to estab- tient judgement of change with a second, external meas- lish the difference in the FACT-AN scores at baseline, ure of change, which serves as the anchor. while the FACT-An, FACT Anemia, and FACT Fatigue Anchor-based assessments offer the advantage of linking subscales median split were used to show that the base- the change in a given score to the patient’s perspective line SF-36 scores differed. Groups were defined by Hb (which is captured by the anchor). Because we had rele- level (< 11 g/dL vs ≥ 11 dg/dL; < median vs ≥ median) or vant clinical anchors, we employed both approaches. relevant SF-36 domain/ score and FACT-An specified A minimally important difference (MID) refers to the domain score (< median vs ≥ median). “smallest difference in score in the domain of interest that patients perceive as important, (either beneficial or Ability to detect change harmful, and which would lead the clinician to consider The focus of this study was to document the ability a change in the patient’s management” [48]. Because de- of each instrument to detect change; thus, all ana- termination of the “minimally” important difference or lyses were conducted using pooled data only, i.e., change can vary by context, and because of some misuse no analyses were performed by treatment or doses. of the concept, this term has fallen out of favor, with Using ANCOVA models, the ability to detect terms such as “important change scores” or “clinically change of the SF-36 domain/Component Summary important differences” increasingly used instead [49]. scores and the FACT-An Total and subscale scores Previously reported important change scores for the was assessed by comparing the mean scores of Hb SF-36 for the general population vary from 2 to 3 [40]. responders and non-responders at baseline to Week Clinically important differences reported for the 9 and baseline to Week 13/17 change scores, con- FACT-An targeted domains have been estimated at 3 trolling for age, gender, and baseline score (FAC- points for the Fatigue subscale, 4 FACT-An points for the T-An and SF-36). Anemia subscale, and 6 points for the Total score [41]. Responders were defined with the same clinical criteria In the present study, the SF-36 Vitality, Physical func- used in the trial protocols: tioning domain, and Physical Component Summary score were used as anchors to estimate important a. Hb responders change scores on the FACT-An. Similarly, FACT-An Baseline Hb level > 8 g/dL: Hb level > 11.0 g/dL scores were used as anchors to estimate important with ≥1.0 g/dL increase change scores on the SF-36. Only patients achieving a Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 5 of 13 pre-defined meaningful change score in these domains caution given the smaller number of patients in the dia- (from baseline to Week 9 or to Week 13/17) were in- lysis group. cluded in the analyses. The mean SF-36 or FACT-An Comorbid conditions and disease history were gener- change scores (from baseline to Week 9 or to Week 13/ ally similar; however, diabetes was more common in the 17) for these patients thereby provided an estimate of an non-dialysis group (61.4% vs 18.6%). A high proportion important change score. The meaningful change score of the non-dialysis group had diabetic (55.9%) or hyper- was defined as 3–4 point increase in the SF-36 Vitality tensive nephropathy (53.1%), whereas in the dialysis score, a 3–4 point increase in the SF-36 Physical func- group, the most common CKD history category was is- tioning score, and a 2–3 point change in the SF-36 Phys- chemic nephropathy (42.4%). Additional details of the ical Component Summary score. two patient groups can be found in respective trial publi- For SF-36 change scores, the first anchor used a 4–7 cations [36, 38]. point increase in the FACT-An Anemia subscale score to define the “minimally improved” category to assess Descriptive statistics the change in the SF-36 domain/Component Summary Low baseline SF-36 domain and Component Summary scores associated with a minimal change in condition. A scores for the total sample were found for Physical func- second anchor used a 3–5 point increase in the tioning, Role-physical, General Health, and Physical Com- FACT-An Fatigue subscale score. ponent Summary score (Table 2). Scores approaching the The SF-36 Vitality domain (important change of 3 2009 general US population mean (50.0) were found for Vi- points) and Physical functioning domain (3 points) and tality, Mental Health, and Mental Component Summary the Physical Component Summary (2 points) were used score. The scores indicate that these patients predominantly to calculate important change score estimates for the experienced physical rather than mental impairments. FACT-An Total score and Fatigue and Anemia sub- Baseline scores were similar for both trial samples for scales. Similarly, the following FACT-An MID anchors Physical functioning, Vitality, and the Physical Component [41] were used for SF-36 linking: FACT-An Total score Summary score, whereas Role-physical, Role-emotional, of 6, FACT-An Anemia subscale score of 4, and a and Mental Health domains, and the Mental Component FACT-An Fatigue subscale score of 3 points. Summary score were all lower in dialysis patients. At baseline, the mean FACT-An Total score was 131.5 Results (SD: 30.0), the mean Fatigue subscale score was 34.2 Patient demographics and clinical characteristics (SD: 11.5), and the mean Anemia subscale score was The mean age of patients was 60.2 years (Table 1). The 53.9 (SD: 15.0). (Table 2) The FACT-An Well-Being sub- gender distribution differed by trial; 63.4% of patients in scales ranged from 17.8 to 21.0. Improvements were the non-dialysis group were female vs 47.5% in the dialy- observed by Week 9 in the FACT-An Total and all sis group. Patients in the non-dialysis group were typic- subscale scores, except for the Social Well-Being ally older than patients in the dialysis group. The where a small decrease was identified. These scores statistically significant differences between the dialysis were relatively stable, with similar mean values re- and non-dialysis groups should be interpreted with ported at Week 13/17. Table 1 Demographic Characteristics for Non-dialysis (NCT00761657) and Dialysis (NCT01244763) Patient Groups and Pooled Total Characteristic NCT00761657 (N = 145) NCT01244763 (N = 59) All Patients (N = 204) Age (years), mean (SD)*** 64.4(11.3) 50.0(15.1) 60.2(14.0) Gender (female), n (%)* 92(63.4%) 28(47.5%) 120(58.8%) Race, n (%)** Asian 6(4.1%) 2(3.4%) 8(3.9%) Black or African-American 42(29.0%) 2(3.4%) 44(21.6%) White 92(63.4%) 54(91.5%) 146(71.6%) Other 5(3.4%) 1(1.7%) 6(2.9%) Ethnicity (N, %)*** Hispanic/Latino 47(32.4%) 1(1.7%) 48(23.5%) Not Hispanic/Latino 98(67.6%) 58(98.3%) 156(76.5%) * < 0.05, ** < 0.001, *** < 0.0001 comparing dialysis and non-dialysis patients a. Subjects with at least one intake of study medication and at least one valid SF-36v2 completion b. Other includes Mexican, mixed, Filipino, Spanish and Latin American SD standard deviation Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 6 of 13 Table 2 Descriptive Statistics for the SF-36 and FACT-An at Baseline Measure N Mean ± SD Range Median Mode Missing N, % SF-36 Physical Functioning 194 38.2 ± 11.1 17.1–57.0 38.1 36.0 0 (0.0%) Role-physical 194 40.1 ± 11.2 17.7–56.9 39.7 37.3 0 (0.0%) Role-emotional 193 41.3 ± 13.7 9.2–55.9 44.2 55.9 1 (0.5%) Vitality 194 47.7 ± 12.0 20.9–70.8 49.0 45.9 0 (0.0%) Mental Health 194 48.4 ± 11.5 19.0–64.1 52.8 52.8 0 (0.0%) Social Functioning 194 45.3 ± 11.5 13.2–56.9 45.9 56.9 0 (0.0%) Bodily Pain 194 47.3 ± 11.2 19.9–62.1 46.1 62.1 0 (0.0%) General Health 194 39.5 ± 9.5 16.2–62.5 38.6 32.9 0 (0.0%) Physical Component Summary 194 40.0 ± 9.4 17.0–64.0 40.7 27.5 0 (0.0%) Mental Component Summary 194 48.0 ± 11.5 14.3–67.3 49.6 32.1 0 (0.0%) FACT-An Total FACT-An score 197 131.5 ± 30.0 44.0–185.0 131.0 122.0 1 (0.5%) Total FACT-G score 197 77.6 ± 17.0 25.0–106.8 78.0 72.0 1 (0.5%) Physical Well Being 198 20.9 ± 5.5 2.0–28.0 22.0 25.0 0 (0.0%) Functional Well Being 197 18.0 ± 6.5 2.0–28.0 18.0 28.0 1 (0.5%) Social Well Being 198 21.0 ± 5.8 2.0–28.0 22.0 28.0 0 (0.0%) Emotional Well Being 197 17.8 ± 4.7 0.0–24.0 19.0 21.0 1 (0.5%) Anemia subscale 198 53.9 ± 15.0 14.0–80.0 54.9 57.0 0 (0.0%) Fatigue subscale 198 34.2 ± 11.5 8.0–52.0 35.5 28.0 0 (0.0%) Trial outcome index 197 92.7 ± 24.6 27.0–136.0 92.0 72.0 1 (0.5%) a. Norm-based score based on 2009 US general population survey Internal consistency and test-retest reliability Overall, Cronbach’s alpha scores were acceptable for Good to excellent reliability coefficients were demon- both measures on all other domains, ranging from 0.76 strated for the SF-36 domain/Component Summary to 0.95. Particularly high Cronbach’s alpha scores were scores except the General Health Domain (0.69) and for observed in the Physical functioning, Role-physical, and the FACT-An Total score and all subscales (Table 3). Role-emotional domains on the SF-36 as well as the Table 3 Internal Consistency and Test-retest Reliability of the SF-36 and the FACT-An Subscales a b a b SF-36 domain/Component Summary N Cronbach’s N Test-retest FACT-An total/subscale N Cronbach’s N Test-retest score alpha (ICC) alpha (ICC) Physical functioning 188 0.90 77 0.83 Anemia subscale 190 0.92 76 0.83 Role-physical 193 0.93 76 0.69 Fatigue subscale 196 0.93 76 0.80 Vitality 193 0.82 75 0.64 Total FACT-An score 131 0.95 76 0.88 Role-Emotional 193 0.93 77 0.74 FACT-G score 133 0.91 76 0.86 Mental Health 193 0.81 77 0.75 Functional Well-Being 196 0.87 76 0.83 Social Functioning 194 0.76 77 0.69 Physical Well-Being 196 0.84 76 0.83 subscale Bodily Pain 194 0.88 77 0.74 Social Well-Being 137 0.80 76 0.76 General Health 192 0.69 77 0.75 Emotional Well-Being 193 0.79 76 0.72 Physical Component Summary score – 0.92 76 0.81 Mental Component Summary score – 0.90 76 0.75 Abbreviations: ICC intraclass correlation coefficient, FACT-An Functional Assessment of Cancer Therapy-Anemia, FACT-G Functional Assessment of Cancer Therapy-General, SF-36 Medical Outcomes Survey Short Form-36 a. Number of subjects at Baseline b. Number of subjects with average weekly Hb change within +/− 0.5 g/dL between Week 9 and Week 13/17 (study FGCL-4592-053/study FGCL-4592-041) and who have not received rescue therapy Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 7 of 13 Anemia and Fatigue subscales on the FACT-An. Table 5 Convergent Validity—Correlations of FACT-An and SF- 36 Scales with Hb Level at Baseline, Week 9 and Week 13/17 Test-retest reliability was demonstrated for all domains and both summary scores, using > 0.6 as an acceptable Hb level cut-off [50]. Baseline Week 9 Week 13/17 FACT-An Total/Subscale Convergent and known-groups validity Total FACT-An score 0.20* 0.22* 0.33** As expected, the SF-36 Vitality domain showed strong Total FACT-G score 0.22* 0.20* 0.34*** correlations with the FACT-An Fatigue and Anemia sub- Physical well-being subscale 0.21* 0.17* 0.32** scales (r= 0.76 and r= 0.77, respectively; Table 4). The Functional well-being subscale 0.22* 0.21* 0.29** correlations between the SF-36 and the FACT-An Anemia and Fatigue subscales generally were high. Social/family well-being subscale 0.18* 0.09 0.22* The correlations with Hb level were modest, particu- Emotional well-being subscale 0.16* 0.20* 0.30** larly at baseline where the Hb range was limited by trial Anemia subscale 0.14 0.22* 0.28* inclusion criteria (Table 4). The correlations with Hb Fatigue subscale 0.11 0.26** 0.30** level at Week 9 and 13/17 were similar: SF-36 Vitality Trial outcome index 0.19* 0.22* 0.32** correlated with Hb r= 0.28 (p< 0.001) and Role Physical SF-36v2 Domain/Component score, r= 0.25 (p< 0.01), whilst the FACT-An Total had a correlation of r= 0.33 (p< 0.001), Anemia r= 0.28 (p Physical Functioning 0.07 0.13 0.12 < 0.001), and Fatigue r= 0.30 (p< 0.001). Role-physical 0.24** 0.23* 0.25* For the assessment of known groups validity, a me- Role-emotional 0.12 0.13 0.25* dian split of the predefined SF-36 and FACT An Vitality 0.18* 0.23* 0.28** scores were used, as described earlier in the methods Mental Health 0.23* 0.22* 0.27* section. Highly significant differences were found for Social Functioning 0.10 0.12 0.31** all the key FACT-An and SF-36 domains: the FACT-An scores split by the SF-36 Physical Function- Bodily Pain 0.00 0.10 0.25* ing domain were: FACT-Anemia subscale score (mean General Health 0.17* 0.22* 0.26* 46.4, [SD 13.9]) vs 61.6(12.2), the FACT Fatigue sub- Mental Component Summary 0.20* 0.18* 0.30** scale 28.9(10.8) vs. 39.7(9.5), and the Total FACT-An Physical Component Summary 0.10 0.19* 0.22* score 118.3(28.8) vs 145.0(25.0), all p < 0.0001. Simi- a. Spearman’s rank order correlation. *p < 0.05; **p < 0.001; ***p < 0.001 larly, the corresponding median split using the SF-36 b. Week 13 for NCT00671657; Week 17 for NCT01244763 Vitality scoreand theSF-36 PCS scoreswereall highly significant for all the FACT-An domains by the median FACT-An score showed large and sig- FACT-Anemia., FACT Fatigue subscale and the nificant differences (p < 0.0001) for Physical Function- FACT-An Total scores p < 0.0001. The SF-36 results ing 32.3(9.5) vs 43.8(9.4); and Vitality 39.5(13.5) vs. showed the same pattern, i.e., the SF-36 scores split 55.5(8.3). A split by FACT-Anemia and the FACT-An Table 4 Convergent Validity – Correlations Between SF-36 and Fatigue scales showed the same pattern for the SF-36 the FACT-An Fatigue and Anemia Subscales Physical Functioning and Vitality domains and were SF-36 domain/Component FACT-An subscale all highly significant (p < 0.001). Summary score Anemia Fatigue For the SF-36, using a median split of Hb level to Physical functioning 0.63*** 0.60*** define the group, a significant difference was found for the Vitality domain score at baseline, p< 0.05 Role-Physical 0.64*** 0.61*** (Table 5). The FACT-An Total score, discriminated Vitality 0.77*** 0.76*** between groups based on a median split of Hb level. Role-Emotional 0.53*** 0.52*** When comparing groups with an Hb level of < 11 Mental Health 0.54*** 0.52*** vs ≥ 11 g/DL at Week 9, the FACT-An Total Score, Social Functioning 0.66*** 0.67*** and Anemia and Fatigue subscale produced signifi- Bodily Pain 0.53*** 0.53*** cantly different scores (p < 0.05, p < 0.01, P <0.01, respectively). General Health 0.64*** 0.61*** Mental Component Summary score 0.62*** 0.62*** Ability to detect change Physical Component Summary score 0.69*** 0.66*** Both the SF-36 and Fact-An demonstrated the ability to Spearman’s rank order correlation. *** p< 0.001 detect change. Small improvements (relative to baseline) Abbreviations: FACT-An Functional Assessment of Cancer Therapy-Anemia, SF-36 Medical Outcomes Survey Short Form-36 were observed in all SF-36 domain and Component Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 8 of 13 Summary scores. Despite a high baseline Vitality score Using Hb level to define responders, only the Fa- in both trials, sizeable gains in Vitality were observed in tigue subscale produced significant differences at both trials. Larger gains were observed in the dialysis Week 9 between responders and non-responders group, with a greater than three-point increase by Week based on Hb level/change (p< 0.05),whilstatWeeks 13 for the Physical Component Summary score, and the 11–13/15–17, significant differences were identified Physical functioning, Role-emotional, Role-physical, and for the FACT-An Total score, the and Physical Vitality domains. Only the Vitality change score achieved Well-Being subscales (p< 0.05). Significant differences this cut-off in the non-dialysis group by Week 9 or were also identified in the Fatigue, subscale at Week Week 17. Large improvements in FACT-An Total and 13/17 (p< 0.05); however, the non-responder sample all FACT-An subscale scores (except for the Social size was particularly low (n =19–30) in these analyses Well-Being) were shown at Week 9, and were relatively at the later time points. stable by Week 13/17. When separating by trial, baseline mean scores were higher in the non-dialysis group for the FACT-An Total score and all subscale scores com- Important change scores pared with the dialysis group, and gains were generally Table 6 shows the important change scores produced by larger in dialysis group. each method for each SF-36 domain/Component Sum- For FACT-An Anemia subscale-defined responders, mary scores. The anchor-based methods were produced significant differences between responders and using relatively small sample sizes (n =21–26). The esti- non-responders were identified for all SF-36 domains mates produced by linking were similar to the other and Component Summary change scores at both time anchor-based methods, and typically smaller than the points assessed. Similarly, significant differences were distribution-based estimates. A central principle is that observed between responders and non-responders using confidence in the estimate increases when the domains FACT-An Fatigue-defined responders at Week 9 for all are more highly correlated with the anchor [41, 51, 52]. SF-36 scores, and for all except Physical functioning, Of the anchors used, the FACT-An Anemia subscale General Health and PCS at Week 13/17. had the strongest correlations with the target domains/ Using SF-36 Vitality-defined responders, significant Component Summary scores. For the Physical function- differences were identified for the FACT-An Total ing, Vitality, and Physical Component Summary do- change score,, Anemia and Fatigue subscale change mains, the following important change score estimates scores (p< 0.001) at Week 9 and Week 13/17 (p are recommended: Physical functioning: 2–3 points; Vi- < 0.01). A similar pattern of results was identified tality: 2–4 points; Physical Component Summary: 2–4 using SF-36 Physical functioning-defined and Physical points. Component Summary-defined responders where sig- For the FACT-An scores, distribution-based estimates nificant differences were found for FACT-An Total, were typically larger than anchor-based estimates, with Anemia, and Fatigue subscale scores relative to base- 0.5 SD estimates larger than one SEM estimates for all line (p< 0.01). scores except the Social Well-Being subscale (Table 7). Table 6 SF-36: Important Change Score Estimates Using Distribution-based, Anchor-based, and Linking Methods SF-36 Domain/Component 1 0.5 Anemia 4–7, Anemia 4–7, Fatigue 3–5, Fatigue 3–5, Linking FACT- Linking Linking Summary score SEM SD Week 9 Week 13/17 Week 9 Week 13/17 An total anemia fatigue Physical functioning 4.6 5.5 2.6 2.9 1.5 2.3 2.59 2.96 2.90 Role-Physical 6.2 5.6 1.7 2.4 1.0 0.7 Vitality 7.2 6.0 5.7 3.1 3.9 1.0 2.80 3.20 3.13 Role-Emotional 7.0 6.9 2.9 −1.3 3.7 −2.4 Mental Health 5.8 5.7 3.4 −0.2 3.2 0.9 Social Functioning 6.4 5.8 1.4 1.0 0.5 −1.5 Bodily Pain 5.7 5.6 2.1 −1.4 −0.2 −3.0 General Health 4.8 4.8 3.1 −2.2 − 1.5 − 2.2 Physical Component 4.2 4.7 2.0 1.5 −0.8 0.0 2.19 2.51 2.45 Summary score Mental Component 5.7 5.8 3.6 −0.5 3.8 −1.3 Summary score Abbreviations: FACT-An Functional Assessment of Cancer Therapy-Anemia, SD standard deviation, SEM standard error of measurement, SF-36 Medical Outcomes Survey Short Form-36 Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 9 of 13 Table 7 FACT-An: Important Change Score Estimates Using Distribution-based, anchor-based, and Linking Methods FACT-An 1 0.5 Vitality 3– Vitality 3–4, Physical Physical functioning PCS 2– PCS 2–4, Linking Linking Linking total/ SEM SD 4, Week 9 Week 13/17 functioning 2.8– 2.8–4.2, Week 13/17 4, Week Week 13/ vitality physical PCS subscale 4.2, Week 9 9 17 functioning Total 10.4 15.0 8.7 7.8 4.8 9.1 4.4 7.1 7.50 8.11 6.38 Anemia 6.2 7.5 5.2 4.2 1.3 5.5 2.5 4.7 3.75 4.05 3.19 subscale Fatigue 5.2 5.7 4.0 3.2 2.1 3.9 2.1 3.6 2.88 3.11 2.45 subscale General 6.4 8.5 3.6 3.6 3.5 3.6 1.9 2.4 Physical 2.3 2.7 0.7 1.5 −0.4 1.3 0.3 1.3 Well-Being Functional 2.7 3.3 0.6 0.4 1.7 2.4 0.0 −0.4 Well-Being Social Well- 2.8 2.9 0.9 0.7 0.5 −0.5 0.9 1.7 Being Emotional 2.5 2.4 1.2 1.0 1.7 0.3 0.7 −0.2 Well-Being Abbreviations: FACT-An Functional Assessment of Cancer Therapy-Anemia, PCS Physical Component Summary, SD standard deviation, SEM standard error of measurement One flaw of the anchor-based approach is frequent re- CKD anemia population for capturing the main patient liance on small sample sizes, as was the case in this health issues related to anemia; the strong correlations study (n =14–29), with the anchor range increased to between the SF-36 and FACT-An domains scores further 2.8 to 4.2 for the SF-36 Physical Component Summary support the validity of these measures when used in a change score (as no participants achieved a score change CKD population with anemia. The FACT-An Total score between these values at either time point). The linking also captures these impacts and combines them with a estimates were similar to the other anchor-based general measure of HRQoL (FACT-G); thus, the methods. FACT-An Total score is useful as an overall summary of HRQoL that can capture impairment to well-being Discussion resulting from anemia to describe the full impact of Despite the relatively common use of the SF-36 in CKD with anemia. patients with anemia associated with CKD in clinical When separated by trial, baseline mean scores were studies and clinical trials [6, 16–18, 20–23, 53, 54], similar for the Fatigue and Anemia domains but slightly the psychometric measurement properties of SF-36 higher in the non-dialysis group for the FACT-An Total have not previously been reported in this patient score and the other subscale scores. Moreover, these re- population. This study provides evidence of the reli- sults highlight a somewhat greater impact on those pa- ability, validity, and responsiveness of the SF-36 meas- tients with CKD receiving dialysis (i.e., those at a more ure, and the results support the use of the SF-36 to severe stage of kidney failure), especially across social, assess treatment efficacy in clinical trials in this pa- functional, and emotional domains. tient population. For patients with anemia associated The link between anemia and fatigue, and the impact with CKD, tiredness, fatigue, and poor physical func- of CKD anemia on physical functioning, are each tioning each have a significant impact on HRQoL. highlighted by baseline scores that were comparable Therefore, the Physical functioning and Vitality do- with those found in patients with cancer [55]. These mains may prove particularly useful in assessing the links are underlined by the observation that the correl- major impacts of the treatment of anemia in these ation with the Hb level grew stronger over the duration patients. For a more general assessment of physical of the treatment period. Similar correlations between Hb impact, the Physical Component Summary can also level and fatigue have been reported in patients with be used. cancer [57]. Whereas the SF-36 was developed to measure overall The baseline PRO scores generally indicated a some- HRQoL, the FACT-An Anemia subscale was developed what greater impact on patients with CKD receiving dia- specifically to capture the impact of anemia on HRQoL, lysis compared with the non-dialysis group, across with the shorter Fatigue and Anemia subscales capturing social, functional, emotional domains and FACT-Anemia a major impact often noted in anemia. These subscales and Fatigue subscale scores. The improvement in these show particular promise for use as endpoints in the scores was also generally larger in the dialysis Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 10 of 13 population. However, such a pattern was not shown for circumstances where objective clinical markers do not ex- the SF-36 scores. clusively identify the treatment benefit, inclusion of vali- Reliability, assessed by internal consistency and dated PRO measures as additional measures of efficacy is test-retest correlation coefficients, was demonstrated for important [15]. The low correlations with Hb level also in- the SF-36 domain and summary scores (Cronbach’s dicate that in this study sample more factors influence alpha = 0.69–0.93; ICC = 0.64–0.83), and the FACT-An quality of life than Hb alone. The important change score Total and all subscale scores (Cronbach’s alpha = 0.79– estimates were similar irrespective of whether 0.95; ICC = 0.72–0.88). As expected, high convergent anchor-based or linking-based approaches were used, validity was demonstrated for domains measuring simi- which supports their validity [51]. The FACT-An and lar concepts. SF-36 estimates were also consistent with previously sug- The strong correlation between the Vitality domain gested values for these instruments [40, 41]. with each of the FACT-An subscales was encouraging. For use as an endpoint in clinical trials, a PRO instru- As the Vitality domain had the strongest relationship ment needs to be sensitive to changes in a patient’s con- with the FACT-An Total score and Anemia and Fatigue dition. Although mixed results were identified using Hb subscales, extra consideration was given to the use of level to define responders/non-responders in HRQoL this anchor in determining an important change score. measures, responsiveness was demonstrated using Consequently, the following important change score es- SF-36-defined responders/non-responders for all timates are recommended: FACT-An Total: 6–9 points; FACT-An scores. Coupled with a change in mean scores Anemia: 3–5 points; Fatigue: 2–4 points. from baseline to Week 13/17 in both the SF-36 and The relatively high Vitality score in the present study FACT-An, these findings support the use of the SF-36 is surprising given that a substantial degree of impair- domains, Physical functioning and vitality, and the ment was reported in previous studies of CKD patients FACT-An scores for measuring efficacy from the patient with anemia [6, 7]. perspective. Known-groups validity was demonstrated for the se- Our analysis has several limitations, including use of lected key domains Physical Functioning, and Vitality trial designs were similar, but not identical; however, the with significant differences between groups defined purpose of our research was to evaluate of the SF-36 using the FACT-An Total, Fatigue, and Anemia subscale and FACT-An questionnaires in patients with ESRD, scores. Similarly, the key FACT-An scores, i.e., the which was unlikely to be affected by differences in trial FACT-An Total, and Fatigue and Anemia subscale duration or time of questionnaire administration. Both scores differed significantly when split by SF-36 scores. questionnaires were administered according to instruc- Correlations with Hb level were typically smaller, par- tions provided. Prior research has suggested timing dur- ticularly at baseline, where the Hb level was constrained ing a trial has no significant effect on responses [60]. by the inclusion criteria. Hb level-defined groups pro- The analyses were limited by the unavailability of clinical duced mixed results, which is consistent with published anchors that were not included in the trial, such as pa- data reporting that a modest relationship between PRO tient and clinician overall assessment of changes that measures and Hb level has previously been shown, with would be useful in assessing the measurement perform- fatigue and physical functioning measures demonstrating ance, and in particular responsiveness to change of the additional benefit beyond or in the absence of Hb level two instruments. Although pooling the data of the two change [56–58]. trials both increased the sample size and the range of se- In patients with cancer, the correlation between Hb level verity, the trial samples differed in several sociodemo- and measure of fatigue is moderate, albeit sufficiently high graphic (age, gender, and ethnicity) and clinical (CKD to support the use of Hb as a clinical anchor for validation history and comorbid conditions) characteristics. How- purposes [41, 59]. Notably, Holzner et al. [58] identified ever, even smaller sample sizes would be observed for differences in the Multi-dimensional Fatigue Inventory the anchor-based important change score analyses had scores between patients with cancer and healthy subjects, the data not been pooled. Whilst the results provide despite both groups having a normal Hb range. Further- good evidence of the measurement properties of the more, patients with lung cancer grouped by FACT-Fatigue SF-36 and the FACT-An, additional evidence of validity scale score (in tertiles) had no significant differences in and responsiveness, in a larger sample, and using other Hb level but significant differences in physical functioning variables in the analyses, is desirable. Increasing the and psychological distress [56]. These findings highlight sample size would provide more confidence in the esti- the importance of measures that capture concepts beyond mation of anchor-based important change scores, as Hb level change, as Hb is not the only indicator of disease small sample sizes (such as in this study) are more vul- burden in these patients (especially in light of improve- nerable to individual extreme values distorting the mean. ment in PRO scores in the two trials). Specifically, in Hence, the MID estimates should be regarded as Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 11 of 13 provisional with need for further corroboration in future Authors’ contributions All authors were involved in the design and interpretation of the analyses. trials. Using data derived in a clinical trial for validation All authors contributed to the drafting of the manuscript. All authors read purposes makes it possible to get an estimate of the and approved the final manuscript. magnitude of change observed. This is important for the Ethics approval and consent to participate assessment of responsiveness to change. By deriving The two trials from which data were derived for this analysis, were registered additional data on the measurement properties in future at Clinicaltrials.gov (NCT00761657, NCT01244763), approved by all trials further evidence can be provided. Despite its limi- appropriate institutional review boards, conducted in accordance with the Declaration of Helsinki, and subjects provided written informed consent. tations, this study has demonstrated that the Physical functioning domain of the SF 36 in particular and the Competing interests FACT-An Fatigue and Anemia subscales are useful mea- FvN is a former employee at Astellas Pharma. IW is employed by Evidera, sures for capturing important aspects of HRQoL in pa- and DT was employed by Evidera when this study was conducted. DC and FOF received payment from Astellas for their contribution to the design and tients with CKD associated with suffering from anemia. interpretation of the analyses. The results of this study provide further evidence of the reliability, validity and responsiveness of the SF-36 Publisher’sNote and FACT-An in patients with CKD receiving and not Springer Nature remains neutral with regard to jurisdictional claims in receiving dialysis. Both measures have already been in- published maps and institutional affiliations. cluded as endpoints in clinical trials for anemia associ- Author details ated with CKD [6, 16, 33]. 1 2 Yale University, New Haven, CT, USA. Formerly with Astellas Pharma BV, Sylviusweg 62, 2333, BE, Leiden, The Netherlands. Evidera, Metro Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK. Formerly with Evidera, Metro Conclusions Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK. Department of When evaluating the impact of anemia on patients with Medical Social Sciences, Northwestern University, Evanston, IL, USA. CKD, the SF-36 domains Vitality and Physical function- Received: 6 March 2017 Accepted: 13 May 2018 ing scores, and the FACT-An Total, Fatigue, and Anemia domain subscales show good evidence of reliability, val- idity, and responsiveness. The modest relationship ob- References served between Hb level and HRQoL highlights the 1. Stauffer ME, Fan T. Prevalence of anemia in chronic kidney disease in the United States. PLoS One. 2014;9(1):e84943. importance of capturing HRQoL data, given patients 2. Minutolo R, Locatelli F, Gallieni M, Bonofiglio R, Fuiano G, Oldrizzi L, with CKD treated for anemia experienced an improve- ConteG,DeNicolaL,MangioneF,EspositoP,Dal CA. Anaemia ment in FACT-An and SF-36 scores. Thus, the SF-36 Management in non-dialysis Chronic Kidney Disease (CKD) patients. A Multicentre Prospective Study in Renal Clinics. Nephrol Dial Transplant. and FACT-An questionnaires may be suitable for asses- 2013;28(12):3035–45. sing the benefit of treatment beyond changes in Hb level 3. McFarlane SI, Chen SC, Whaley-Connell AT, Sowers JR, Vassalotti JA, Salifu in patients with anemia associated with CKD. MO, et al. Prevalence and associations of anemia of CKD: kidney early evaluation program (KEEP) and National Health and nutrition examination survey (NHANES) 1999–2004. Am J Kidney Dis. 2008;51(4 Suppl 2):S46–55. Abbreviations 4. Alexander M, Kewalramani R, Agodoa I, Globe D. Association of anemia ANCOVA: Analysis of covariance; CKD: Chronic kidney disease; correction with health related quality of life in patients not on dialysis. Curr ESA: Erythropoiesis-stimulating agents; ESRD: End-stage renal disease; FACT- Med Res Opin. 2007;23(12):2997–3008. An: Functional assessment of cancer therapy-anemia; FACT-G: Functional 5. Weisbord SD, Fried LF, Mor MK, Resnick AL, Unruh ML, Palevsky PM, et al. assessment of cancer therapy-general; Hb: Hemoglobin; HIF: Hypoxia- Renal provider recognition of symptoms in patients on maintenance inducing factor; HIF-PH: Hypoxia-inducing factor- prolyl hydroxylase; hemodialysis. Clin J Am Soc Nephrol. 2007;2(5):960–7. HRQoL: Health-related quality of life; ICC: Intraclass correlation coefficient; 6. Johansen KL, Finkelstein FO, Revicki DA, Evans C, Wan S, Gitlin M, Agodoa IV: Intravenous; MCS: Mental component summary; MID: Minimally important IL. Systematic review of the impact of erythropoiesis–stimulating agents on difference; PCS: Physical component summary; PRO: Patient-reported fatigue in dialysis patients. Nephrol Dial Transplant. 2012;27(6):2418–25. outcome; SD: Standard deviation; SEM: Standard error of measurement; SF- https://doi.org/10.1093/ndt/gfr697. Epub 2011 Dec 20 36: Medical outcomes survey short form-36; US: United States 7. Bonner A, Wellard S, Caltabiano M. The impact of fatigue on daily activity in people with chronic kidney disease. J Clin Nurs. 2010;19(21–22):3006–15. Acknowledgements 8. Schatell D, Ellstrom-Calder A, Alt PS, Garland JS. Survey of CKD patients The authors thank Wen-Hung Chen, PhD (an employee at Evidera, Bethesda, reveals significant GAPS in knowledge about kidney disease. Part 1. Nephrol MD at the time of contribution) for his contribution to planning the statis- News Issues. 2003;17(5):23–6. tical analyses, and Ren Yu, MA (Evidera, Bethesda, MD) for her assistance in 9. Delano BG. Improvements in quality of life following treatment with r-HuEPO conducting the analyses. The data were provided from two clinical trials in anemic hemodialysis patients. Am J Kidney Dis. 1989;14(2 Suppl 1):14–8. (Clinicaltrials.gov Identifier: NCT01244763 & NCT01414075) conducted by 10. Dharmarajan TS, Norkus EP. Mild anemia and the risk of falls in older adults FibroGen in partnership with Astellas. from nursing homes and the community. J Am Med Dir Assoc. 2004;5(6): 395–400. Funding 11. Finkelstein FO, Story K, Firanek C, Mendelssohn D, Barre P, Takano T, et al. The study was conducted by Evidera, a consultancy company paid by Health-related quality of life and hemoglobin levels in chronic kidney Astellas. disease patients. Clin J Am Soc Nephrol. 2009;4(1):33–8. 12. Kamenetz Y, Beloosesky Y, Zeltzer C, Gotlieb D, Magazanik A, Fishman Availability of data and materials P, et al. Relationship between routine hematological parameters, The datasets generated during and/or analysed during the current study are serum IL-3, IL-6 and erythropoietin and mild anemia and degree of available from the corresponding author on reasonable request. function in the elderly. Aging (Milano). 1998;10(1):32–8. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 12 of 13 13. Lefebvre P, Vekeman F, Sarokhan B, Enny C, Provenzano R, Cremieux PY. Intermediate-1-risk myelodysplastic syndromes with a chromosome 5q deletion: Relationship between hemoglobin level and quality of life in anemic results from a randomized clinical trial. Leuk Res. 2013;37(3):259–65. patients with chronic kidney disease receiving epoetin alfa. Curr Med Res 33. Roger SD, Jassal SV, Woodward MC, Soroka S, McMahon LP. A randomised Opin. 2006;22(10):1929–37. single-blind study to improve health-related quality of life by treating 14. Covic A, Seica A, Gusbeth-Tatomir P, Goldsmith D. Hemoglobin anaemia of chronic kidney disease with Aranesp(R) (darbepoetin alfa) in normalization trials in chronic kidney disease: what should we learn about older people: STIMULATE. Int Urol Nephrol. 2014;46(2):469–75. quality of life as an end point? J Nephrol. 2008;21(4):478–84. 34. European Medicines Agency (EMA). Reflection Paper on the Regulatory 15. Dinan MA, Compton KL, Dhillon JK, Hammill BG, Dewitt EM, Weinfurt KP, et Guidance for the Use of Health-related Quality of Life (HRQL) Measures in al. Use of patient-reported outcomes in randomized, double-blind, placebo- the Evaluation of Medicinal Products. 2005. controlled clinical trials. Med Care. 2011;49(4):415–9. 35. Food and Drug Administration (FDA). Guidance for industry on patient- 16. Gandra SR,Finkelstein FO,Bennett AV,Lewis EF,BrazgT,MartinML.Impact of reported outcome measures: use in medical product development to erythropoiesis–stimulating agents on energy and physical function in nondialysis support labelling claims. Fed Reg. 2009;74FR 65132:65132–3. CKD patients with anemia: a systematic review. Am J Kidney Dis. 2010;55(3):519–34. 36. Besarab A, Provenzano R, Hertel J, Zabaneh R, Klau SJ, Lee T, Leong R, 17. Besarab A, Bolton WK, Browne JK, Egrie JC, Nissenson AR, Okamoto DM, et Hemmerich S, Peony Yu K-HP, Neff TB. Randomized placebo-controlled dose- al. The effects of normal as compared with low hematocrit values in ranging and pharmacodynamics study of roxadustat (FG-4592) to treat anemia patients with cardiac disease who are receiving hemodialysis and epoetin. in nondialysis-dependent chronic kidney disease (NDD-CKD) patients. Nephrol N Engl J Med. 1998;339(9):584–90. Dial Transplant. 2015;30:1665–73. https://doi.org/10.1093/ndt/gfv302. 18. Drueke TB, Locatelli F, Clyne N, Eckardt KU, Macdougall IC, Tsakiris D, et al. 37. Provenzano R, Besarab A, Sun CH, Diamond SA, Durham JH, Cangiano JL, et Normalization of hemoglobin level in patients with chronic kidney disease al. Oral hypoxia-inducible factor prolyl hydroxylase inhibitor Roxadustat (FG- and anemia. N Engl J Med. 2006;355(20):2071–84. 4592) for the treatment of Anemia in patients with CKD. Clin J Am Soc 19. Foley RN, Parfrey PS, Morgan J, Barre PE, Campbell P, Cartier P, et al. Effect Nephrol. 2016;11(6):982–91. of hemoglobin levels in hemodialysis patients with asymptomatic 38. Provenzano R, Besarab A, Wright S, Dua S, Zeig S, Nguyen P, et al. cardiomyopathy. Kidney Int. 2000;58(3):1325–35. Roxadustat (FG-4592) versus Epoetin alfa for Anemia in patients receiving 20. Levin A, Djurdjev O, Thompson C, Barrett B, Ethier J, Carlisle E, et al. maintenance hemodialysis: a phase 2, randomized, 6- to 19-week, open- Canadian randomized trial of hemoglobin maintenance to prevent or label, active-comparator, dose-ranging, safety and exploratory efficacy study. delay left ventricular mass growth in patients with CKD. Am J Kidney Am J Kidney Dis. 2016;67(6):912–24. Dis. 2005;46(5):799–811. 39. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health 21. Parfrey PS, Foley RN, Wittreich BH, Sullivan DJ, Zagari MJ, Frei D. Double- survey (SF-36). I. Conceptual framework and item selection. Med Care. blind comparison of full and partial anemia correction in incident 1992;30(6):473–83. hemodialysis patients without symptomatic heart disease. J Am Soc 40. Maruish ME. User's manual for the SF-36v2 Health Survey (3rd ed.). Lincoln, Nephrol. 2005;16(7):2180–9. RI: QualityMetric Incorporated; 2011. 22. Ritz E, Laville M, Bilous RW, O'Donoghue D, Scherhag A, Burger U, et al. 41. Cella D, Eton DT, Lai JS, Peterman AH, Merkel DE. Combining anchor and Target level for hemoglobin correction in patients with diabetes and CKD: distribution-based methods to derive minimal clinically important primary results of the Anemia correction in diabetes (ACORD) study. Am J differences on the functional assessment of Cancer therapy (FACT) anemia Kidney Dis. 2007;49(2):194–207. and fatigue scales. J Pain Symptom Manag. 2002;24(6):547–61. 23. Roger SD, McMahon LP, Clarkson A, Disney A, Harris D, Hawley C, et al. 42. Pfeffer MA, Burdmann EA, Chen CY, Cooper ME, de Zeeuw D, Eckardt KU, et Effects of early and late intervention with epoetin alpha on left al. A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. ventricular mass among patients with chronic kidney disease (stage 3 N Engl J Med. 2009;361(21):2019–32. or 4): results of a randomized clinical trial. J Am Soc Nephrol. 2004; 43. Leidy NK, Revicki DA, Geneste B. Recommendations for evaluating the 15(1):148–56. validity of quality of life claims for labeling and promotion. Value 24. Rossert J, Levin A, Roger SD, Horl WH, Fouqueray B, Gassmann-Mayer C, et Health. 1999;2(2):113–27. al. Effect of early correction of anemia on the progression of CKD. Am J 44. Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York, NY: Kidney Dis. 2006;47(5):738–50. McGraw-Hill; 1994. 25. Singh AK, Szczech L, Tang KL, Barnhart H, Sapp S, Wolfson M, et al. 45. Cronbach LJ. Coefficient alpha and the internal structure of test. Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Psychometrika. 1951;16(3):297–334. Med. 2006;355(20):2085–98. 46. Hays RD, Revicki DA. Reliability and validity, including responsiveness. In: Fayers 26. Martin ML, Patrick DL, Gandra SR, Bennett AV, Leidy NK, Nissenson AR, PM, Hays RD, editors. Assessing quality of life in clinical trials. 2nd ed. New York, et al. Content validation of two SF-36 subscales for use in type 2 NY: Oxford University Press; 2005. p. 25–39. diabetes and non-dialysis chronic kidney disease-related anemia. Qual 47. Cohen J. Statistical power analysis for the behavioral sciences. Second ed. Life Res. 2011;20(6):889–901. Hillsdale, NJ: Lawrence Erlbaum; 1988. 27. Korevaar JC, Merkus MP, Jansen MAM, Dekker FW, Boeschoten EW, Krediet 48. Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Norman GR. Clinical significance RT for the NECOSAD-study group. Validation of the KDQOL-SFTM: A dialysis- consensus meeting G. Methods to explain the clinical significance of health targeted health measure. Quality of Life Res. 2002;11:437–47. status measures. Mayo Clin Proc. 2002;77(4):371–83. 28. Cella D. The functional assessment of Cancer therapy-Anemia (FACT-an) 49. Coon CD, Cappelleri JC. Interpreting change in scores on patient- scale: a new tool for the assessment of outcomes in cancer anemia and reported outcome instruments. Therapeutic Innovation & Regulatory fatigue. Semin Hematol. 1997;34(3 Suppl 2):13–9. Science. 2016;50(1):22–9. 29. Yellen SB, Cella DF, Webster K, Blendowski C, Kaplan E. Measuring 50. Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed fatigue and other anemia-related symptoms with the functional and standardized assessment instruments in psychology. Psychol Assess. assessment of Cancer therapy (FACT) measurement system. J Pain 1994;6(4):284–90. Symptom Manag. 1997;13(2):63–74. 51. Revicki D, Hays RD, Cella D, Sloan J. Recommended methods for determining responsiveness and minimally important differences for 30. Cruciani RA, Dvorkin E, Homel P, Culliney B, Malamud S, Lapin J, et al. L- patient-reported outcomes. J Clin Epidemiol. 2008;61(2):102–9. carnitine supplementation in patients with advanced cancer and carnitine deficiency: a double-blind, placebo-controlled study. J Pain Symptom 52. Fayers PM, Hays RD. Don't middle your MIDs: regression to the mean Manag. 2009;37(4):622–31. shrinks estimates of minimally important differences. Qual Life Res. 31. Milroy R, Bajetta E, van den Berg P, O'Brien ER, Perez-Manga G. Effects of 2014;23(1):1–4. epoetin alfa on anemia and patient-reported outcomes in patients with 53. Locatelli F, Del Vecchio L, Pozzoni P. Anemia and cardiovascular risk: the non-small cell lung cancer receiving chemotherapy: results of a European, lesson of the CREATE trial. J Am Soc Nephrol. 2006;17(12 Suppl 3):S262–6. multicenter, randomized, controlled study. European Journal of Clinical & 54. Clement FM, Klarenbach S, Tonelli M, Johnson JA, Manns BJ. The impact of Medical Oncology. 2011;3(2):59–6. selecting a high hemoglobin target level on health-related quality of life for 32. Revicki DA, Brandenburg NA, Muus P, Yu R, Knight R, Fenaux P. Health-related quality patients with chronic kidney disease: a systematic review and meta-analysis. of life outcomes of lenalidomide in transfusion-dependent patients with low- or Arch Intern Med. 2009;169(12):1104–12. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 13 of 13 55. Suzuki Y, Tokuda Y, Fujiwara Y, Minami H, Ohashi Y, Saijo N. Weekly epoetin beta maintains haemoglobin levels and improves quality of life in patients with non-myeloid malignancies receiving chemotherapy. Jpn J Clin Oncol. 2008;38(3):214–21. 56. Brown DJ, McMillan DC, Milroy R. The correlation between fatigue, physical function, the systemic inflammatory response, and psychological distress in patients with advanced lung cancer. Cancer. 2005;103(2):377–82. 57. Crawford J, Cella D, Cleeland CS, Cremieux PY, Demetri GD, Sarokhan BJ, et al. Relationship between changes in hemoglobin level and quality of life during chemotherapy in anemic cancer patients receiving epoetin alfa therapy. Cancer. 2002;95(4):888–95. 58. Holzner B, Kemmler G, Greil R, Kopp M, Zeimet A, Raderer M, et al. The impact of hemoglobin levels on fatigue and quality of life in cancer patients. Ann Oncol. 2002;13(6):965–73. 59. Cella D, Kallich J, McDermott A, Xu X. The longitudinal relationship of hemoglobin, fatigue and quality of life in anemic cancer patients: results from five randomized clinical trials. Ann Oncol. 2004;15(6):979–86. 60. Lai J-S, Cook K, Stone A, Beaumont J, Cella D. Classical testing theory and item response theory/Rasch model to assess difference between patient- reported fatigue using seven-day and four-week recall periods. J Clin Epidemiol. 2009;62(9):991–7. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Health and Quality of Life Outcomes Springer Journals

Measurement properties of the Short Form-36 (SF-36) and the Functional Assessment of Cancer Therapy - Anemia (FACT-An) in patients with anemia associated with chronic kidney disease

Free
13 pages

Loading next page...
 
/lp/springer_journal/measurement-properties-of-the-short-form-36-sf-36-and-the-functional-MFXoOwkEHn
Publisher
Springer Journals
Copyright
Copyright © 2018 by The Author(s).
Subject
Medicine & Public Health; Quality of Life Research; Quality of Life Research
eISSN
1477-7525
D.O.I.
10.1186/s12955-018-0933-8
Publisher site
See Article on Publisher Site

Abstract

Background: Anemia is a common and debilitating manifestation of chronic kidney disease (CKD). Data from two clinical trials in patients with anemia of CKD were used to assess the measurement properties of the Medical Outcomes Survey Short Form-36 version 2 (hereafter SF-36) and the Functional Assessment of Cancer Therapy-Anemia (FACT-An). The Vitality and Physical functioning domains of the SF-36 and the FACT-An Total, Fatigue and Anemia subscales were identified as domains relevant to CKD-associated anemia. Methods: A total of 204 patients aged 18–80 years were included in the analyses that included internal consistency (Cronbach’s alpha), test-retest reliability (intraclass correlation coefficients [ICCs]), convergent and known-groups validity, responsiveness, and estimates of important change. Results: Both the SF-36 and the FACT-An had strong psychometric properties with high internal consistency (Cronbach’s alpha: 0.69–0.93 and 0.79–0.95), and test-retest reliability (ICCs: 0.64–0.83 and 0.72–0.88). Convergent validity, measured by correlation coefficients between similar concepts in SF-36 and FACT-An, ranged from 0.52 to 0.77. Correlations with hemoglobin (Hb) levels were modest at baseline; by Week 9, the correlations with Hb were somewhat higher, r= 0.23 (p < 0.05) for SF-36 Vitality, r =0.22 (p < 0.05) for FACT-An Total, r =0.26 (p <0.001) for FACT-Fatigue and r= 0.22 (p < 0.01) for Anemia. Correlations with Hb at Week 13/17 were r =0.28 (p <0. 001) for SF-36 Vitality and r =0.25 (p < 0.05) for Role Physical; FACT-An Total correlation was r =0.33 (p <0. 0001), Anemia was r = 0.28 (p < 0.001), and Fatigue was r =0.30 (p < 0.001). The SF-36 domains and Component Summary scores (p <0.05–p < 0.0001) demonstrated ability to detect change. For the FACT-An, significant differences (p <0.05–p < 0.0001) were observed between responder and non-responder change scores: important change score estimates ranged from 2 to 4 for Vitality and 2–3for Physical functioning. Important change scores were also estimated for the FACT-An Total score (6–9), the Anemia (3–5),and Fatiguesubscale(2–4). Conclusions: Both the SF-36 Vitality and Physical function scales and the FACT-An Total, Fatigue and Anemia scales, are reliable and valid measures for assessing health-related quality of life in anemia associated with CKD. Keywords: Anemia, Chronic kidney disease, Quality of life, Psychometric evaluation, SF-36, FACT-An * Correspondence: fof@comcast.net Yale University, New Haven, CT, USA Full list of author information is available at the end of the article © The Author(s). 2018 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 2 of 13 Background review, and expert input. The Total FACT-An score and Anemia is common among patients with chronic kidney the FACT Anemia and Fatigue score are of particular disease (CKD); the prevalence in US patients is esti- interest for use with anemia associated with CKD. Al- mated to be over 15% [1]. An association between though the tool has been used in many oncology clinical anemia and CKD stage has been identified, with anemia trials, [30–33], data in the CKD population are lacking. increasing in prevalence by disease severity from 8.4% in Both the European Medicines Agency [34]and the Stage 1 to 53.4% in Stage 5. Minutolo et al. [2] reported US Food and Drug Administration [35] require that a 44% prevalence of anemia across all CKD stages in pa- new drugs under consideration for approval be tested tients who were not receiving dialysis, while McFarlane in clinical trials with PRO endpoints that are specific et al. estimated a prevalence of 50 to 70% across all and relevant to the proposed treatment population. stages [3]. Documentation of measurement properties of do- Symptoms of anemia include fatigue, low energy, weak- mains of PRO surveys in the target population is es- ness, dizziness, and dyspnea [4, 5]; symptom severıty var- sential. The purpose of this study is to assess further ies wıth the degree of anemia [6]. Persistent fatigue has the measurement properties of the SF-36 and the been identified as one of the most debilitating symptoms FACT-An with particular focus on domains of vital- both pre-dialysis and in dialysis disease stages [7, 8]. The ity/fatigue, anemia, and physical function, which most impact of fatigue varies widely, from being described as closely relate to CKD anemia. Data from two clinical ‘mild impairment’ to greatly affecting daily functioning in- trials in patients with CKD anemia who were not re- cluding, at times, basic activities of daily living [9]. Dimin- ceiving dialysis or who were newly initiated on dialy- ished aspects of health-related quality of life sis were used to evaluate the validity of SF-36 and (HRQoL), such as functional and ambulatory impair- the FACT-An in this sample. ment, and increased risk of falls, have all been identi- fied as complications of anemia [10–14]. Methods Patient-reported outcome (PRO) measures are fre- Patient sample quently used to assess treatment efficacy in clinical trials Data were derived from two clinical trials that evaluated [15]. Although used in some trials as primary endpoints a hypoxia-inducing factor prolyl hydroxylase (HIF-PH) (eg, a patient report of pain is required in the absence of inhibitor in patients with CKD anemia. The trial designs objective clinical markers), PROs are often used to iden- were similar, but not identical, and allow the evaluation tify additional benefits associated with treatment, includ- of the SF-36 and FACT-An questionnaires in patients ing symptom experience, functioning, and HRQoL. with ESRD. Details of these trials including treatment in- Thus, measurement of HRQoL as a primary outcome of terventions have been published previously [36–38]. treatment interventions in end-stage renal disease Briefly, the first (NCT00761657) was a Phase 2, (ESRD), as well as a tool for clinicians to assess patient open-label, randomized trial in patients with anemia and status, is an increasingly accepted research endpoint. Stage 3 or 4 CKD, who were not on dialysis (non-dialysis While earlier studıes suggested a broad range of group) [36]. The patients were 18–70 years old with an symptom improvement wıth anemia treatment, recent Hb level < 10.5 g/dL and an estimated glomerular filtra- studies indicate that the domains of Vitality and tion rate of > 15 to < 60 mL/min/1.73 m Physical functioning are most beneficially affected by pre-randomization. The second (NCT01244763) was a treatment [6, 16]. Phase 2b, randomized, open-label trial in newly initiated The Medical Outcomes Survey Short Form-36 patients on dialysis (dialysis group) [37, 38]. The patients (SF-36) is a generic, widely validated HRQoL measure were 18–80 years old with a pre-randomization Hb level that has been used in numerous research studies and < 10.0 g/dL. They had received hemodialysis or periton- clinical trials of CKD anemia [11, 17–25] with specific eal dialysis for native kidney ESRD for a minimum of 2 focus on the Vitality and Physical functioning domains weeks and a maximum of 4 months. Patients in both [6, 16, 26]. Measurement properties of SF-36 have studies were not currently and had not previously re- been assessed in patients with CKD, [27] but no corre- ceived an erythropoietin-stimulating agent (ESA) or IV sponding data are available specifically for patients iron within 4 weeks of randomization. with CKD anemia. The Functional Assessment of Cancer Therapy-Anemia Study design (FACT-An) was developed to assess the impact of anemia In the non-dialysis trial, dosing strategies for the on quality of life in patients with cancer-associated anemia HIF-PH inhibitor were employed across six cohorts [28, 29]. Content validity was addressed during the devel- (with 24–25 patients per cohort). Patients attended opment of the FACT-An and was based on interviews weekly study visits during the treatment period (16 weeks with patients with cancer-associated anemia, literature for Cohorts A and B, and 24 weeks for Cohorts C Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 3 of 13 through F). The FACT-An and the SF-36 questionnaires The FACT-An also includes 13 fatigue-specific items were administered at baseline, Week 9, Week 17 (Co- (the Fatigue Subscale) plus an additional 7 items specific horts A–D only for SF-36), and Week 24 (Cohorts C–D to anemia and unrelated to fatigue. Anemia subscales only). such as FACT-An Total and the Fatigue and Anemia In the dialysis trial, approximately 12 patients were en- subscales were of special interest. These last 20 items rolled in each of five HIF-PH inhibitor treatment arms. (13 + 7) combine to form the Anemia subscale. Higher The trial employed a 1:1:1 ratio for the first 36 patients scores indicate better health status. An important to receive no iron supplementation, oral iron supple- change score estimate of 4 points for the Anemia total mentation, and IV iron supplementation. Patients visited score and 3 points for the Fatigue score has previously the clinic weekly during the 12-week treatment period, been reported in patients with cancer [41]. In patients followed by a four-week post-treatment follow-up with CKD, a three-point or greater increase was previ- period. The FACT-An and SF-36 questionnaires were ously identified as a clinically meaningful improvement administered at baseline, Week 9, and Week 13. on the FACT-Fatigue total score [42]. Data used to characterize each patient sample were collected at baseline/during screening for both dialysis Statistical analyses and non-dialysis patients. These included sociodemo- Unless stated otherwise, data from the two clinical trials graphic (date of birth, sex, and race/ethnicity) and clin- were pooled at baseline and at Week 9. Week 17 data ical data (weight and height, pulse rate, blood pressure, from the non-dialysis group were pooled with Week 13 respiratory rate, date of CKD diagnosis, date of anemia data from the dialysis group. Pooling the data from the diagnosis, comorbid conditions, laboratory parameters, two trials provided a sufficiently large sample size and a treatments received, and rescue medication use). Hb greater range of impairment within a CKD patient sam- level was collected at baseline, Week 9, and Week 13/17 ple for more effective testing of the measurement prop- (dialysis/non-dialysis) as well as at other time points. erties of SF-36 and FACT-An. All statistical tests were two-sided and significance level was set at p< 0.05. Patient-reported outcome measures For the SF-36 domain/Component Summary scores The SF-36 is designed to assess health concepts that are and the FACT-An Total and subscale scores, descriptive relevant across age, disease, and treatment groups in statistics (mean, SD, median, and range) were calculated adults [39]. As well as a health transition item, the SF-36 at baseline, Week 9, and Week 13/17. contains eight domains: Physical functioning (10 items), Role-physical (4 items), Bodily Pain (2 items), General Reliability Health (5 items), Vitality (4 items), Social functioning (2 Cronbach’s coefficient alpha was used to assess the in- items), Role-emotional (3 items), and Mental Health (5 ternal consistency of the SF-36 domain scores and Com- items). Two Component Summary scores, the Physical ponent Summary scores and the FACT-An Total and Component Summary (PCS) and the Mental Compo- relevant subscales at baseline. A Cronbach’s alpha ≥0.70 nent Summary (MCS), can also be calculated with all was considered an acceptable minimum value definition scores using the norm-based approach (US population for good reliability [43]. Patterns of item-to-item correla- norm mean score for each domain and summary score tions and item-to-total correlations, and the number of is 50, with a standard deviation [SD] of 10) [40]. items in the subscale, were also considered. Alpha coeffi- Anemia-related domains such as the Vitality and Phys- cients > 0.7 indicated good internal consistency, 0.4–< ical functioning were previously identified to be of spe- 0.69 moderate internal consistency, and < 0.4 low in- cial interest [6, 16]. A four-week recall was used for the ternal consistency reliability [44, 45]. SF-36 in both trials. Suggested important change scores Test-retest reliability was assessed in the subgroup of have been reported by the instrument developers for patients (n = 153) whose Hb level was classified as un- each domain and Component Summary score based on changed (average weekly Hb change within ±0.5 g/dL the 2009 US general population [40]. The suggested between Week 9 and Week 13/17 with no rescue ther- change scores are appropriate for T-scores ranging from apy between these time points). The average weekly 30 to 40. Where the T-score for the population exceeds change in Hb was determined by comparing the weekly this range, increasing the change score is recommended. differences in Hb between Week 9 and every week from The FACT-An is designed to assess aspects of quality Week 10 to Week 13/17. Intraclass correlation coeffi- of life affected by anemia in patients with cancer [28]. cients (ICCs) were calculated to compare the SF-36 do- Using a seven-day recall period, the 27 item main/Component Summary and the FACT-An Total FACT-General (FACT-G) includes four dimensions of and subscale scores at Week 9 and Week 13/17. An well-being: Physical (7 items), Functional (7 items), So- ICC ≥ 0.7 indicated good, 0.4–0.7 moderate, and < 0.4 cial/Family (SWB; 7 items), and Emotional (6 items). poor test-retest reliability [44, 45]. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 4 of 13 Validity Baseline Hb level ≤ 8 g/dL: Hb level > 2.0 g/dL Validity refers to the extent to which an instrument increase at the end of Weeks 7–9 and Weeks 11– measures what it is intended to measure; it is typically 13/15–17 assessed by examining correlations with other indicators b. SF-36 responders of similar/related constructs [46]. Correlations of 0.10 Vitality (SF-36) responders: > 3-point increase in are considered small, correlations between 0.30 and 0.50 SF-36 Vitality score are regarded as moderate, and correlations of 0.50 or Physical functioning (SF-36) responders: > 3-point more are considered large [47]. Spearman’s rank-order increase in SF-36 Physical functioning score correlation coefficients between the SF-36 domain/Com- Physical Component Summary (SF-36) responders ponent Summary scores and the FACT-An Total and -– an increase of two points in SF-36 Physical subscale scores at baseline, Week 9, and Week 13/17 Component Summary score; were used to assess convergent validity. c. FACT-An responders The SF-36 Vitality domain was previously identified as FACT-An Anemia responders: > 4-point increase an important measure of disease impact resulting from in FACT-An Anemia score anemia [6, 16], therefore the FACT-An Fatigue and FACT-An Fatigue responders: > 3-point increase Anemia subscales were expected to correlate more in FACT-An Fatigue subscale score. strongly with Vitality domain than other SF-36 domains. Known-groups validity was assessed to demonstrate the Estimating important change scores ability of the SF-36 and FACT-An instrument domain Methods for interpreting the importance of quality of scores to differentiate between patients with varying life changes in clinical research generally follow two ap- levels of anemia, using Hb levels at baseline. The SF-36 proaches: distribution-based and anchor-based. A and FACT-An domain scores were compared between distribution-based approach is based on statistical char- the scores above and below the median Hb level at base- acteristics of the obtained samples. This approach relies line using analysis of covariance (ANCOVA) with adjust- on the distribution of scores and the related effect size ments for gender and age. Similarly, for assessment of of change scores. An anchor-based approach compares known groups validity, the SF-36 Physical Function and the change in a patient reported outcome, such as pa- Vitality median split domain scores were used to estab- tient judgement of change with a second, external meas- lish the difference in the FACT-AN scores at baseline, ure of change, which serves as the anchor. while the FACT-An, FACT Anemia, and FACT Fatigue Anchor-based assessments offer the advantage of linking subscales median split were used to show that the base- the change in a given score to the patient’s perspective line SF-36 scores differed. Groups were defined by Hb (which is captured by the anchor). Because we had rele- level (< 11 g/dL vs ≥ 11 dg/dL; < median vs ≥ median) or vant clinical anchors, we employed both approaches. relevant SF-36 domain/ score and FACT-An specified A minimally important difference (MID) refers to the domain score (< median vs ≥ median). “smallest difference in score in the domain of interest that patients perceive as important, (either beneficial or Ability to detect change harmful, and which would lead the clinician to consider The focus of this study was to document the ability a change in the patient’s management” [48]. Because de- of each instrument to detect change; thus, all ana- termination of the “minimally” important difference or lyses were conducted using pooled data only, i.e., change can vary by context, and because of some misuse no analyses were performed by treatment or doses. of the concept, this term has fallen out of favor, with Using ANCOVA models, the ability to detect terms such as “important change scores” or “clinically change of the SF-36 domain/Component Summary important differences” increasingly used instead [49]. scores and the FACT-An Total and subscale scores Previously reported important change scores for the was assessed by comparing the mean scores of Hb SF-36 for the general population vary from 2 to 3 [40]. responders and non-responders at baseline to Week Clinically important differences reported for the 9 and baseline to Week 13/17 change scores, con- FACT-An targeted domains have been estimated at 3 trolling for age, gender, and baseline score (FAC- points for the Fatigue subscale, 4 FACT-An points for the T-An and SF-36). Anemia subscale, and 6 points for the Total score [41]. Responders were defined with the same clinical criteria In the present study, the SF-36 Vitality, Physical func- used in the trial protocols: tioning domain, and Physical Component Summary score were used as anchors to estimate important a. Hb responders change scores on the FACT-An. Similarly, FACT-An Baseline Hb level > 8 g/dL: Hb level > 11.0 g/dL scores were used as anchors to estimate important with ≥1.0 g/dL increase change scores on the SF-36. Only patients achieving a Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 5 of 13 pre-defined meaningful change score in these domains caution given the smaller number of patients in the dia- (from baseline to Week 9 or to Week 13/17) were in- lysis group. cluded in the analyses. The mean SF-36 or FACT-An Comorbid conditions and disease history were gener- change scores (from baseline to Week 9 or to Week 13/ ally similar; however, diabetes was more common in the 17) for these patients thereby provided an estimate of an non-dialysis group (61.4% vs 18.6%). A high proportion important change score. The meaningful change score of the non-dialysis group had diabetic (55.9%) or hyper- was defined as 3–4 point increase in the SF-36 Vitality tensive nephropathy (53.1%), whereas in the dialysis score, a 3–4 point increase in the SF-36 Physical func- group, the most common CKD history category was is- tioning score, and a 2–3 point change in the SF-36 Phys- chemic nephropathy (42.4%). Additional details of the ical Component Summary score. two patient groups can be found in respective trial publi- For SF-36 change scores, the first anchor used a 4–7 cations [36, 38]. point increase in the FACT-An Anemia subscale score to define the “minimally improved” category to assess Descriptive statistics the change in the SF-36 domain/Component Summary Low baseline SF-36 domain and Component Summary scores associated with a minimal change in condition. A scores for the total sample were found for Physical func- second anchor used a 3–5 point increase in the tioning, Role-physical, General Health, and Physical Com- FACT-An Fatigue subscale score. ponent Summary score (Table 2). Scores approaching the The SF-36 Vitality domain (important change of 3 2009 general US population mean (50.0) were found for Vi- points) and Physical functioning domain (3 points) and tality, Mental Health, and Mental Component Summary the Physical Component Summary (2 points) were used score. The scores indicate that these patients predominantly to calculate important change score estimates for the experienced physical rather than mental impairments. FACT-An Total score and Fatigue and Anemia sub- Baseline scores were similar for both trial samples for scales. Similarly, the following FACT-An MID anchors Physical functioning, Vitality, and the Physical Component [41] were used for SF-36 linking: FACT-An Total score Summary score, whereas Role-physical, Role-emotional, of 6, FACT-An Anemia subscale score of 4, and a and Mental Health domains, and the Mental Component FACT-An Fatigue subscale score of 3 points. Summary score were all lower in dialysis patients. At baseline, the mean FACT-An Total score was 131.5 Results (SD: 30.0), the mean Fatigue subscale score was 34.2 Patient demographics and clinical characteristics (SD: 11.5), and the mean Anemia subscale score was The mean age of patients was 60.2 years (Table 1). The 53.9 (SD: 15.0). (Table 2) The FACT-An Well-Being sub- gender distribution differed by trial; 63.4% of patients in scales ranged from 17.8 to 21.0. Improvements were the non-dialysis group were female vs 47.5% in the dialy- observed by Week 9 in the FACT-An Total and all sis group. Patients in the non-dialysis group were typic- subscale scores, except for the Social Well-Being ally older than patients in the dialysis group. The where a small decrease was identified. These scores statistically significant differences between the dialysis were relatively stable, with similar mean values re- and non-dialysis groups should be interpreted with ported at Week 13/17. Table 1 Demographic Characteristics for Non-dialysis (NCT00761657) and Dialysis (NCT01244763) Patient Groups and Pooled Total Characteristic NCT00761657 (N = 145) NCT01244763 (N = 59) All Patients (N = 204) Age (years), mean (SD)*** 64.4(11.3) 50.0(15.1) 60.2(14.0) Gender (female), n (%)* 92(63.4%) 28(47.5%) 120(58.8%) Race, n (%)** Asian 6(4.1%) 2(3.4%) 8(3.9%) Black or African-American 42(29.0%) 2(3.4%) 44(21.6%) White 92(63.4%) 54(91.5%) 146(71.6%) Other 5(3.4%) 1(1.7%) 6(2.9%) Ethnicity (N, %)*** Hispanic/Latino 47(32.4%) 1(1.7%) 48(23.5%) Not Hispanic/Latino 98(67.6%) 58(98.3%) 156(76.5%) * < 0.05, ** < 0.001, *** < 0.0001 comparing dialysis and non-dialysis patients a. Subjects with at least one intake of study medication and at least one valid SF-36v2 completion b. Other includes Mexican, mixed, Filipino, Spanish and Latin American SD standard deviation Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 6 of 13 Table 2 Descriptive Statistics for the SF-36 and FACT-An at Baseline Measure N Mean ± SD Range Median Mode Missing N, % SF-36 Physical Functioning 194 38.2 ± 11.1 17.1–57.0 38.1 36.0 0 (0.0%) Role-physical 194 40.1 ± 11.2 17.7–56.9 39.7 37.3 0 (0.0%) Role-emotional 193 41.3 ± 13.7 9.2–55.9 44.2 55.9 1 (0.5%) Vitality 194 47.7 ± 12.0 20.9–70.8 49.0 45.9 0 (0.0%) Mental Health 194 48.4 ± 11.5 19.0–64.1 52.8 52.8 0 (0.0%) Social Functioning 194 45.3 ± 11.5 13.2–56.9 45.9 56.9 0 (0.0%) Bodily Pain 194 47.3 ± 11.2 19.9–62.1 46.1 62.1 0 (0.0%) General Health 194 39.5 ± 9.5 16.2–62.5 38.6 32.9 0 (0.0%) Physical Component Summary 194 40.0 ± 9.4 17.0–64.0 40.7 27.5 0 (0.0%) Mental Component Summary 194 48.0 ± 11.5 14.3–67.3 49.6 32.1 0 (0.0%) FACT-An Total FACT-An score 197 131.5 ± 30.0 44.0–185.0 131.0 122.0 1 (0.5%) Total FACT-G score 197 77.6 ± 17.0 25.0–106.8 78.0 72.0 1 (0.5%) Physical Well Being 198 20.9 ± 5.5 2.0–28.0 22.0 25.0 0 (0.0%) Functional Well Being 197 18.0 ± 6.5 2.0–28.0 18.0 28.0 1 (0.5%) Social Well Being 198 21.0 ± 5.8 2.0–28.0 22.0 28.0 0 (0.0%) Emotional Well Being 197 17.8 ± 4.7 0.0–24.0 19.0 21.0 1 (0.5%) Anemia subscale 198 53.9 ± 15.0 14.0–80.0 54.9 57.0 0 (0.0%) Fatigue subscale 198 34.2 ± 11.5 8.0–52.0 35.5 28.0 0 (0.0%) Trial outcome index 197 92.7 ± 24.6 27.0–136.0 92.0 72.0 1 (0.5%) a. Norm-based score based on 2009 US general population survey Internal consistency and test-retest reliability Overall, Cronbach’s alpha scores were acceptable for Good to excellent reliability coefficients were demon- both measures on all other domains, ranging from 0.76 strated for the SF-36 domain/Component Summary to 0.95. Particularly high Cronbach’s alpha scores were scores except the General Health Domain (0.69) and for observed in the Physical functioning, Role-physical, and the FACT-An Total score and all subscales (Table 3). Role-emotional domains on the SF-36 as well as the Table 3 Internal Consistency and Test-retest Reliability of the SF-36 and the FACT-An Subscales a b a b SF-36 domain/Component Summary N Cronbach’s N Test-retest FACT-An total/subscale N Cronbach’s N Test-retest score alpha (ICC) alpha (ICC) Physical functioning 188 0.90 77 0.83 Anemia subscale 190 0.92 76 0.83 Role-physical 193 0.93 76 0.69 Fatigue subscale 196 0.93 76 0.80 Vitality 193 0.82 75 0.64 Total FACT-An score 131 0.95 76 0.88 Role-Emotional 193 0.93 77 0.74 FACT-G score 133 0.91 76 0.86 Mental Health 193 0.81 77 0.75 Functional Well-Being 196 0.87 76 0.83 Social Functioning 194 0.76 77 0.69 Physical Well-Being 196 0.84 76 0.83 subscale Bodily Pain 194 0.88 77 0.74 Social Well-Being 137 0.80 76 0.76 General Health 192 0.69 77 0.75 Emotional Well-Being 193 0.79 76 0.72 Physical Component Summary score – 0.92 76 0.81 Mental Component Summary score – 0.90 76 0.75 Abbreviations: ICC intraclass correlation coefficient, FACT-An Functional Assessment of Cancer Therapy-Anemia, FACT-G Functional Assessment of Cancer Therapy-General, SF-36 Medical Outcomes Survey Short Form-36 a. Number of subjects at Baseline b. Number of subjects with average weekly Hb change within +/− 0.5 g/dL between Week 9 and Week 13/17 (study FGCL-4592-053/study FGCL-4592-041) and who have not received rescue therapy Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 7 of 13 Anemia and Fatigue subscales on the FACT-An. Table 5 Convergent Validity—Correlations of FACT-An and SF- 36 Scales with Hb Level at Baseline, Week 9 and Week 13/17 Test-retest reliability was demonstrated for all domains and both summary scores, using > 0.6 as an acceptable Hb level cut-off [50]. Baseline Week 9 Week 13/17 FACT-An Total/Subscale Convergent and known-groups validity Total FACT-An score 0.20* 0.22* 0.33** As expected, the SF-36 Vitality domain showed strong Total FACT-G score 0.22* 0.20* 0.34*** correlations with the FACT-An Fatigue and Anemia sub- Physical well-being subscale 0.21* 0.17* 0.32** scales (r= 0.76 and r= 0.77, respectively; Table 4). The Functional well-being subscale 0.22* 0.21* 0.29** correlations between the SF-36 and the FACT-An Anemia and Fatigue subscales generally were high. Social/family well-being subscale 0.18* 0.09 0.22* The correlations with Hb level were modest, particu- Emotional well-being subscale 0.16* 0.20* 0.30** larly at baseline where the Hb range was limited by trial Anemia subscale 0.14 0.22* 0.28* inclusion criteria (Table 4). The correlations with Hb Fatigue subscale 0.11 0.26** 0.30** level at Week 9 and 13/17 were similar: SF-36 Vitality Trial outcome index 0.19* 0.22* 0.32** correlated with Hb r= 0.28 (p< 0.001) and Role Physical SF-36v2 Domain/Component score, r= 0.25 (p< 0.01), whilst the FACT-An Total had a correlation of r= 0.33 (p< 0.001), Anemia r= 0.28 (p Physical Functioning 0.07 0.13 0.12 < 0.001), and Fatigue r= 0.30 (p< 0.001). Role-physical 0.24** 0.23* 0.25* For the assessment of known groups validity, a me- Role-emotional 0.12 0.13 0.25* dian split of the predefined SF-36 and FACT An Vitality 0.18* 0.23* 0.28** scores were used, as described earlier in the methods Mental Health 0.23* 0.22* 0.27* section. Highly significant differences were found for Social Functioning 0.10 0.12 0.31** all the key FACT-An and SF-36 domains: the FACT-An scores split by the SF-36 Physical Function- Bodily Pain 0.00 0.10 0.25* ing domain were: FACT-Anemia subscale score (mean General Health 0.17* 0.22* 0.26* 46.4, [SD 13.9]) vs 61.6(12.2), the FACT Fatigue sub- Mental Component Summary 0.20* 0.18* 0.30** scale 28.9(10.8) vs. 39.7(9.5), and the Total FACT-An Physical Component Summary 0.10 0.19* 0.22* score 118.3(28.8) vs 145.0(25.0), all p < 0.0001. Simi- a. Spearman’s rank order correlation. *p < 0.05; **p < 0.001; ***p < 0.001 larly, the corresponding median split using the SF-36 b. Week 13 for NCT00671657; Week 17 for NCT01244763 Vitality scoreand theSF-36 PCS scoreswereall highly significant for all the FACT-An domains by the median FACT-An score showed large and sig- FACT-Anemia., FACT Fatigue subscale and the nificant differences (p < 0.0001) for Physical Function- FACT-An Total scores p < 0.0001. The SF-36 results ing 32.3(9.5) vs 43.8(9.4); and Vitality 39.5(13.5) vs. showed the same pattern, i.e., the SF-36 scores split 55.5(8.3). A split by FACT-Anemia and the FACT-An Table 4 Convergent Validity – Correlations Between SF-36 and Fatigue scales showed the same pattern for the SF-36 the FACT-An Fatigue and Anemia Subscales Physical Functioning and Vitality domains and were SF-36 domain/Component FACT-An subscale all highly significant (p < 0.001). Summary score Anemia Fatigue For the SF-36, using a median split of Hb level to Physical functioning 0.63*** 0.60*** define the group, a significant difference was found for the Vitality domain score at baseline, p< 0.05 Role-Physical 0.64*** 0.61*** (Table 5). The FACT-An Total score, discriminated Vitality 0.77*** 0.76*** between groups based on a median split of Hb level. Role-Emotional 0.53*** 0.52*** When comparing groups with an Hb level of < 11 Mental Health 0.54*** 0.52*** vs ≥ 11 g/DL at Week 9, the FACT-An Total Score, Social Functioning 0.66*** 0.67*** and Anemia and Fatigue subscale produced signifi- Bodily Pain 0.53*** 0.53*** cantly different scores (p < 0.05, p < 0.01, P <0.01, respectively). General Health 0.64*** 0.61*** Mental Component Summary score 0.62*** 0.62*** Ability to detect change Physical Component Summary score 0.69*** 0.66*** Both the SF-36 and Fact-An demonstrated the ability to Spearman’s rank order correlation. *** p< 0.001 detect change. Small improvements (relative to baseline) Abbreviations: FACT-An Functional Assessment of Cancer Therapy-Anemia, SF-36 Medical Outcomes Survey Short Form-36 were observed in all SF-36 domain and Component Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 8 of 13 Summary scores. Despite a high baseline Vitality score Using Hb level to define responders, only the Fa- in both trials, sizeable gains in Vitality were observed in tigue subscale produced significant differences at both trials. Larger gains were observed in the dialysis Week 9 between responders and non-responders group, with a greater than three-point increase by Week based on Hb level/change (p< 0.05),whilstatWeeks 13 for the Physical Component Summary score, and the 11–13/15–17, significant differences were identified Physical functioning, Role-emotional, Role-physical, and for the FACT-An Total score, the and Physical Vitality domains. Only the Vitality change score achieved Well-Being subscales (p< 0.05). Significant differences this cut-off in the non-dialysis group by Week 9 or were also identified in the Fatigue, subscale at Week Week 17. Large improvements in FACT-An Total and 13/17 (p< 0.05); however, the non-responder sample all FACT-An subscale scores (except for the Social size was particularly low (n =19–30) in these analyses Well-Being) were shown at Week 9, and were relatively at the later time points. stable by Week 13/17. When separating by trial, baseline mean scores were higher in the non-dialysis group for the FACT-An Total score and all subscale scores com- Important change scores pared with the dialysis group, and gains were generally Table 6 shows the important change scores produced by larger in dialysis group. each method for each SF-36 domain/Component Sum- For FACT-An Anemia subscale-defined responders, mary scores. The anchor-based methods were produced significant differences between responders and using relatively small sample sizes (n =21–26). The esti- non-responders were identified for all SF-36 domains mates produced by linking were similar to the other and Component Summary change scores at both time anchor-based methods, and typically smaller than the points assessed. Similarly, significant differences were distribution-based estimates. A central principle is that observed between responders and non-responders using confidence in the estimate increases when the domains FACT-An Fatigue-defined responders at Week 9 for all are more highly correlated with the anchor [41, 51, 52]. SF-36 scores, and for all except Physical functioning, Of the anchors used, the FACT-An Anemia subscale General Health and PCS at Week 13/17. had the strongest correlations with the target domains/ Using SF-36 Vitality-defined responders, significant Component Summary scores. For the Physical function- differences were identified for the FACT-An Total ing, Vitality, and Physical Component Summary do- change score,, Anemia and Fatigue subscale change mains, the following important change score estimates scores (p< 0.001) at Week 9 and Week 13/17 (p are recommended: Physical functioning: 2–3 points; Vi- < 0.01). A similar pattern of results was identified tality: 2–4 points; Physical Component Summary: 2–4 using SF-36 Physical functioning-defined and Physical points. Component Summary-defined responders where sig- For the FACT-An scores, distribution-based estimates nificant differences were found for FACT-An Total, were typically larger than anchor-based estimates, with Anemia, and Fatigue subscale scores relative to base- 0.5 SD estimates larger than one SEM estimates for all line (p< 0.01). scores except the Social Well-Being subscale (Table 7). Table 6 SF-36: Important Change Score Estimates Using Distribution-based, Anchor-based, and Linking Methods SF-36 Domain/Component 1 0.5 Anemia 4–7, Anemia 4–7, Fatigue 3–5, Fatigue 3–5, Linking FACT- Linking Linking Summary score SEM SD Week 9 Week 13/17 Week 9 Week 13/17 An total anemia fatigue Physical functioning 4.6 5.5 2.6 2.9 1.5 2.3 2.59 2.96 2.90 Role-Physical 6.2 5.6 1.7 2.4 1.0 0.7 Vitality 7.2 6.0 5.7 3.1 3.9 1.0 2.80 3.20 3.13 Role-Emotional 7.0 6.9 2.9 −1.3 3.7 −2.4 Mental Health 5.8 5.7 3.4 −0.2 3.2 0.9 Social Functioning 6.4 5.8 1.4 1.0 0.5 −1.5 Bodily Pain 5.7 5.6 2.1 −1.4 −0.2 −3.0 General Health 4.8 4.8 3.1 −2.2 − 1.5 − 2.2 Physical Component 4.2 4.7 2.0 1.5 −0.8 0.0 2.19 2.51 2.45 Summary score Mental Component 5.7 5.8 3.6 −0.5 3.8 −1.3 Summary score Abbreviations: FACT-An Functional Assessment of Cancer Therapy-Anemia, SD standard deviation, SEM standard error of measurement, SF-36 Medical Outcomes Survey Short Form-36 Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 9 of 13 Table 7 FACT-An: Important Change Score Estimates Using Distribution-based, anchor-based, and Linking Methods FACT-An 1 0.5 Vitality 3– Vitality 3–4, Physical Physical functioning PCS 2– PCS 2–4, Linking Linking Linking total/ SEM SD 4, Week 9 Week 13/17 functioning 2.8– 2.8–4.2, Week 13/17 4, Week Week 13/ vitality physical PCS subscale 4.2, Week 9 9 17 functioning Total 10.4 15.0 8.7 7.8 4.8 9.1 4.4 7.1 7.50 8.11 6.38 Anemia 6.2 7.5 5.2 4.2 1.3 5.5 2.5 4.7 3.75 4.05 3.19 subscale Fatigue 5.2 5.7 4.0 3.2 2.1 3.9 2.1 3.6 2.88 3.11 2.45 subscale General 6.4 8.5 3.6 3.6 3.5 3.6 1.9 2.4 Physical 2.3 2.7 0.7 1.5 −0.4 1.3 0.3 1.3 Well-Being Functional 2.7 3.3 0.6 0.4 1.7 2.4 0.0 −0.4 Well-Being Social Well- 2.8 2.9 0.9 0.7 0.5 −0.5 0.9 1.7 Being Emotional 2.5 2.4 1.2 1.0 1.7 0.3 0.7 −0.2 Well-Being Abbreviations: FACT-An Functional Assessment of Cancer Therapy-Anemia, PCS Physical Component Summary, SD standard deviation, SEM standard error of measurement One flaw of the anchor-based approach is frequent re- CKD anemia population for capturing the main patient liance on small sample sizes, as was the case in this health issues related to anemia; the strong correlations study (n =14–29), with the anchor range increased to between the SF-36 and FACT-An domains scores further 2.8 to 4.2 for the SF-36 Physical Component Summary support the validity of these measures when used in a change score (as no participants achieved a score change CKD population with anemia. The FACT-An Total score between these values at either time point). The linking also captures these impacts and combines them with a estimates were similar to the other anchor-based general measure of HRQoL (FACT-G); thus, the methods. FACT-An Total score is useful as an overall summary of HRQoL that can capture impairment to well-being Discussion resulting from anemia to describe the full impact of Despite the relatively common use of the SF-36 in CKD with anemia. patients with anemia associated with CKD in clinical When separated by trial, baseline mean scores were studies and clinical trials [6, 16–18, 20–23, 53, 54], similar for the Fatigue and Anemia domains but slightly the psychometric measurement properties of SF-36 higher in the non-dialysis group for the FACT-An Total have not previously been reported in this patient score and the other subscale scores. Moreover, these re- population. This study provides evidence of the reli- sults highlight a somewhat greater impact on those pa- ability, validity, and responsiveness of the SF-36 meas- tients with CKD receiving dialysis (i.e., those at a more ure, and the results support the use of the SF-36 to severe stage of kidney failure), especially across social, assess treatment efficacy in clinical trials in this pa- functional, and emotional domains. tient population. For patients with anemia associated The link between anemia and fatigue, and the impact with CKD, tiredness, fatigue, and poor physical func- of CKD anemia on physical functioning, are each tioning each have a significant impact on HRQoL. highlighted by baseline scores that were comparable Therefore, the Physical functioning and Vitality do- with those found in patients with cancer [55]. These mains may prove particularly useful in assessing the links are underlined by the observation that the correl- major impacts of the treatment of anemia in these ation with the Hb level grew stronger over the duration patients. For a more general assessment of physical of the treatment period. Similar correlations between Hb impact, the Physical Component Summary can also level and fatigue have been reported in patients with be used. cancer [57]. Whereas the SF-36 was developed to measure overall The baseline PRO scores generally indicated a some- HRQoL, the FACT-An Anemia subscale was developed what greater impact on patients with CKD receiving dia- specifically to capture the impact of anemia on HRQoL, lysis compared with the non-dialysis group, across with the shorter Fatigue and Anemia subscales capturing social, functional, emotional domains and FACT-Anemia a major impact often noted in anemia. These subscales and Fatigue subscale scores. The improvement in these show particular promise for use as endpoints in the scores was also generally larger in the dialysis Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 10 of 13 population. However, such a pattern was not shown for circumstances where objective clinical markers do not ex- the SF-36 scores. clusively identify the treatment benefit, inclusion of vali- Reliability, assessed by internal consistency and dated PRO measures as additional measures of efficacy is test-retest correlation coefficients, was demonstrated for important [15]. The low correlations with Hb level also in- the SF-36 domain and summary scores (Cronbach’s dicate that in this study sample more factors influence alpha = 0.69–0.93; ICC = 0.64–0.83), and the FACT-An quality of life than Hb alone. The important change score Total and all subscale scores (Cronbach’s alpha = 0.79– estimates were similar irrespective of whether 0.95; ICC = 0.72–0.88). As expected, high convergent anchor-based or linking-based approaches were used, validity was demonstrated for domains measuring simi- which supports their validity [51]. The FACT-An and lar concepts. SF-36 estimates were also consistent with previously sug- The strong correlation between the Vitality domain gested values for these instruments [40, 41]. with each of the FACT-An subscales was encouraging. For use as an endpoint in clinical trials, a PRO instru- As the Vitality domain had the strongest relationship ment needs to be sensitive to changes in a patient’s con- with the FACT-An Total score and Anemia and Fatigue dition. Although mixed results were identified using Hb subscales, extra consideration was given to the use of level to define responders/non-responders in HRQoL this anchor in determining an important change score. measures, responsiveness was demonstrated using Consequently, the following important change score es- SF-36-defined responders/non-responders for all timates are recommended: FACT-An Total: 6–9 points; FACT-An scores. Coupled with a change in mean scores Anemia: 3–5 points; Fatigue: 2–4 points. from baseline to Week 13/17 in both the SF-36 and The relatively high Vitality score in the present study FACT-An, these findings support the use of the SF-36 is surprising given that a substantial degree of impair- domains, Physical functioning and vitality, and the ment was reported in previous studies of CKD patients FACT-An scores for measuring efficacy from the patient with anemia [6, 7]. perspective. Known-groups validity was demonstrated for the se- Our analysis has several limitations, including use of lected key domains Physical Functioning, and Vitality trial designs were similar, but not identical; however, the with significant differences between groups defined purpose of our research was to evaluate of the SF-36 using the FACT-An Total, Fatigue, and Anemia subscale and FACT-An questionnaires in patients with ESRD, scores. Similarly, the key FACT-An scores, i.e., the which was unlikely to be affected by differences in trial FACT-An Total, and Fatigue and Anemia subscale duration or time of questionnaire administration. Both scores differed significantly when split by SF-36 scores. questionnaires were administered according to instruc- Correlations with Hb level were typically smaller, par- tions provided. Prior research has suggested timing dur- ticularly at baseline, where the Hb level was constrained ing a trial has no significant effect on responses [60]. by the inclusion criteria. Hb level-defined groups pro- The analyses were limited by the unavailability of clinical duced mixed results, which is consistent with published anchors that were not included in the trial, such as pa- data reporting that a modest relationship between PRO tient and clinician overall assessment of changes that measures and Hb level has previously been shown, with would be useful in assessing the measurement perform- fatigue and physical functioning measures demonstrating ance, and in particular responsiveness to change of the additional benefit beyond or in the absence of Hb level two instruments. Although pooling the data of the two change [56–58]. trials both increased the sample size and the range of se- In patients with cancer, the correlation between Hb level verity, the trial samples differed in several sociodemo- and measure of fatigue is moderate, albeit sufficiently high graphic (age, gender, and ethnicity) and clinical (CKD to support the use of Hb as a clinical anchor for validation history and comorbid conditions) characteristics. How- purposes [41, 59]. Notably, Holzner et al. [58] identified ever, even smaller sample sizes would be observed for differences in the Multi-dimensional Fatigue Inventory the anchor-based important change score analyses had scores between patients with cancer and healthy subjects, the data not been pooled. Whilst the results provide despite both groups having a normal Hb range. Further- good evidence of the measurement properties of the more, patients with lung cancer grouped by FACT-Fatigue SF-36 and the FACT-An, additional evidence of validity scale score (in tertiles) had no significant differences in and responsiveness, in a larger sample, and using other Hb level but significant differences in physical functioning variables in the analyses, is desirable. Increasing the and psychological distress [56]. These findings highlight sample size would provide more confidence in the esti- the importance of measures that capture concepts beyond mation of anchor-based important change scores, as Hb level change, as Hb is not the only indicator of disease small sample sizes (such as in this study) are more vul- burden in these patients (especially in light of improve- nerable to individual extreme values distorting the mean. ment in PRO scores in the two trials). Specifically, in Hence, the MID estimates should be regarded as Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 11 of 13 provisional with need for further corroboration in future Authors’ contributions All authors were involved in the design and interpretation of the analyses. trials. Using data derived in a clinical trial for validation All authors contributed to the drafting of the manuscript. All authors read purposes makes it possible to get an estimate of the and approved the final manuscript. magnitude of change observed. This is important for the Ethics approval and consent to participate assessment of responsiveness to change. By deriving The two trials from which data were derived for this analysis, were registered additional data on the measurement properties in future at Clinicaltrials.gov (NCT00761657, NCT01244763), approved by all trials further evidence can be provided. Despite its limi- appropriate institutional review boards, conducted in accordance with the Declaration of Helsinki, and subjects provided written informed consent. tations, this study has demonstrated that the Physical functioning domain of the SF 36 in particular and the Competing interests FACT-An Fatigue and Anemia subscales are useful mea- FvN is a former employee at Astellas Pharma. IW is employed by Evidera, sures for capturing important aspects of HRQoL in pa- and DT was employed by Evidera when this study was conducted. DC and FOF received payment from Astellas for their contribution to the design and tients with CKD associated with suffering from anemia. interpretation of the analyses. The results of this study provide further evidence of the reliability, validity and responsiveness of the SF-36 Publisher’sNote and FACT-An in patients with CKD receiving and not Springer Nature remains neutral with regard to jurisdictional claims in receiving dialysis. Both measures have already been in- published maps and institutional affiliations. cluded as endpoints in clinical trials for anemia associ- Author details ated with CKD [6, 16, 33]. 1 2 Yale University, New Haven, CT, USA. Formerly with Astellas Pharma BV, Sylviusweg 62, 2333, BE, Leiden, The Netherlands. Evidera, Metro Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK. Formerly with Evidera, Metro Conclusions Building, 6th Floor, 1 Butterwick, London, W6 8DL, UK. Department of When evaluating the impact of anemia on patients with Medical Social Sciences, Northwestern University, Evanston, IL, USA. CKD, the SF-36 domains Vitality and Physical function- Received: 6 March 2017 Accepted: 13 May 2018 ing scores, and the FACT-An Total, Fatigue, and Anemia domain subscales show good evidence of reliability, val- idity, and responsiveness. The modest relationship ob- References served between Hb level and HRQoL highlights the 1. Stauffer ME, Fan T. Prevalence of anemia in chronic kidney disease in the United States. PLoS One. 2014;9(1):e84943. importance of capturing HRQoL data, given patients 2. Minutolo R, Locatelli F, Gallieni M, Bonofiglio R, Fuiano G, Oldrizzi L, with CKD treated for anemia experienced an improve- ConteG,DeNicolaL,MangioneF,EspositoP,Dal CA. Anaemia ment in FACT-An and SF-36 scores. Thus, the SF-36 Management in non-dialysis Chronic Kidney Disease (CKD) patients. A Multicentre Prospective Study in Renal Clinics. Nephrol Dial Transplant. and FACT-An questionnaires may be suitable for asses- 2013;28(12):3035–45. sing the benefit of treatment beyond changes in Hb level 3. McFarlane SI, Chen SC, Whaley-Connell AT, Sowers JR, Vassalotti JA, Salifu in patients with anemia associated with CKD. MO, et al. Prevalence and associations of anemia of CKD: kidney early evaluation program (KEEP) and National Health and nutrition examination survey (NHANES) 1999–2004. Am J Kidney Dis. 2008;51(4 Suppl 2):S46–55. Abbreviations 4. Alexander M, Kewalramani R, Agodoa I, Globe D. Association of anemia ANCOVA: Analysis of covariance; CKD: Chronic kidney disease; correction with health related quality of life in patients not on dialysis. Curr ESA: Erythropoiesis-stimulating agents; ESRD: End-stage renal disease; FACT- Med Res Opin. 2007;23(12):2997–3008. An: Functional assessment of cancer therapy-anemia; FACT-G: Functional 5. Weisbord SD, Fried LF, Mor MK, Resnick AL, Unruh ML, Palevsky PM, et al. assessment of cancer therapy-general; Hb: Hemoglobin; HIF: Hypoxia- Renal provider recognition of symptoms in patients on maintenance inducing factor; HIF-PH: Hypoxia-inducing factor- prolyl hydroxylase; hemodialysis. Clin J Am Soc Nephrol. 2007;2(5):960–7. HRQoL: Health-related quality of life; ICC: Intraclass correlation coefficient; 6. Johansen KL, Finkelstein FO, Revicki DA, Evans C, Wan S, Gitlin M, Agodoa IV: Intravenous; MCS: Mental component summary; MID: Minimally important IL. Systematic review of the impact of erythropoiesis–stimulating agents on difference; PCS: Physical component summary; PRO: Patient-reported fatigue in dialysis patients. Nephrol Dial Transplant. 2012;27(6):2418–25. outcome; SD: Standard deviation; SEM: Standard error of measurement; SF- https://doi.org/10.1093/ndt/gfr697. Epub 2011 Dec 20 36: Medical outcomes survey short form-36; US: United States 7. Bonner A, Wellard S, Caltabiano M. The impact of fatigue on daily activity in people with chronic kidney disease. J Clin Nurs. 2010;19(21–22):3006–15. Acknowledgements 8. Schatell D, Ellstrom-Calder A, Alt PS, Garland JS. Survey of CKD patients The authors thank Wen-Hung Chen, PhD (an employee at Evidera, Bethesda, reveals significant GAPS in knowledge about kidney disease. Part 1. Nephrol MD at the time of contribution) for his contribution to planning the statis- News Issues. 2003;17(5):23–6. tical analyses, and Ren Yu, MA (Evidera, Bethesda, MD) for her assistance in 9. Delano BG. Improvements in quality of life following treatment with r-HuEPO conducting the analyses. The data were provided from two clinical trials in anemic hemodialysis patients. Am J Kidney Dis. 1989;14(2 Suppl 1):14–8. (Clinicaltrials.gov Identifier: NCT01244763 & NCT01414075) conducted by 10. Dharmarajan TS, Norkus EP. Mild anemia and the risk of falls in older adults FibroGen in partnership with Astellas. from nursing homes and the community. J Am Med Dir Assoc. 2004;5(6): 395–400. Funding 11. Finkelstein FO, Story K, Firanek C, Mendelssohn D, Barre P, Takano T, et al. The study was conducted by Evidera, a consultancy company paid by Health-related quality of life and hemoglobin levels in chronic kidney Astellas. disease patients. Clin J Am Soc Nephrol. 2009;4(1):33–8. 12. Kamenetz Y, Beloosesky Y, Zeltzer C, Gotlieb D, Magazanik A, Fishman Availability of data and materials P, et al. Relationship between routine hematological parameters, The datasets generated during and/or analysed during the current study are serum IL-3, IL-6 and erythropoietin and mild anemia and degree of available from the corresponding author on reasonable request. function in the elderly. Aging (Milano). 1998;10(1):32–8. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 12 of 13 13. Lefebvre P, Vekeman F, Sarokhan B, Enny C, Provenzano R, Cremieux PY. Intermediate-1-risk myelodysplastic syndromes with a chromosome 5q deletion: Relationship between hemoglobin level and quality of life in anemic results from a randomized clinical trial. Leuk Res. 2013;37(3):259–65. patients with chronic kidney disease receiving epoetin alfa. Curr Med Res 33. Roger SD, Jassal SV, Woodward MC, Soroka S, McMahon LP. A randomised Opin. 2006;22(10):1929–37. single-blind study to improve health-related quality of life by treating 14. Covic A, Seica A, Gusbeth-Tatomir P, Goldsmith D. Hemoglobin anaemia of chronic kidney disease with Aranesp(R) (darbepoetin alfa) in normalization trials in chronic kidney disease: what should we learn about older people: STIMULATE. Int Urol Nephrol. 2014;46(2):469–75. quality of life as an end point? J Nephrol. 2008;21(4):478–84. 34. European Medicines Agency (EMA). Reflection Paper on the Regulatory 15. Dinan MA, Compton KL, Dhillon JK, Hammill BG, Dewitt EM, Weinfurt KP, et Guidance for the Use of Health-related Quality of Life (HRQL) Measures in al. Use of patient-reported outcomes in randomized, double-blind, placebo- the Evaluation of Medicinal Products. 2005. controlled clinical trials. Med Care. 2011;49(4):415–9. 35. Food and Drug Administration (FDA). Guidance for industry on patient- 16. Gandra SR,Finkelstein FO,Bennett AV,Lewis EF,BrazgT,MartinML.Impact of reported outcome measures: use in medical product development to erythropoiesis–stimulating agents on energy and physical function in nondialysis support labelling claims. Fed Reg. 2009;74FR 65132:65132–3. CKD patients with anemia: a systematic review. Am J Kidney Dis. 2010;55(3):519–34. 36. Besarab A, Provenzano R, Hertel J, Zabaneh R, Klau SJ, Lee T, Leong R, 17. Besarab A, Bolton WK, Browne JK, Egrie JC, Nissenson AR, Okamoto DM, et Hemmerich S, Peony Yu K-HP, Neff TB. Randomized placebo-controlled dose- al. The effects of normal as compared with low hematocrit values in ranging and pharmacodynamics study of roxadustat (FG-4592) to treat anemia patients with cardiac disease who are receiving hemodialysis and epoetin. in nondialysis-dependent chronic kidney disease (NDD-CKD) patients. Nephrol N Engl J Med. 1998;339(9):584–90. Dial Transplant. 2015;30:1665–73. https://doi.org/10.1093/ndt/gfv302. 18. Drueke TB, Locatelli F, Clyne N, Eckardt KU, Macdougall IC, Tsakiris D, et al. 37. Provenzano R, Besarab A, Sun CH, Diamond SA, Durham JH, Cangiano JL, et Normalization of hemoglobin level in patients with chronic kidney disease al. Oral hypoxia-inducible factor prolyl hydroxylase inhibitor Roxadustat (FG- and anemia. N Engl J Med. 2006;355(20):2071–84. 4592) for the treatment of Anemia in patients with CKD. Clin J Am Soc 19. Foley RN, Parfrey PS, Morgan J, Barre PE, Campbell P, Cartier P, et al. Effect Nephrol. 2016;11(6):982–91. of hemoglobin levels in hemodialysis patients with asymptomatic 38. Provenzano R, Besarab A, Wright S, Dua S, Zeig S, Nguyen P, et al. cardiomyopathy. Kidney Int. 2000;58(3):1325–35. Roxadustat (FG-4592) versus Epoetin alfa for Anemia in patients receiving 20. Levin A, Djurdjev O, Thompson C, Barrett B, Ethier J, Carlisle E, et al. maintenance hemodialysis: a phase 2, randomized, 6- to 19-week, open- Canadian randomized trial of hemoglobin maintenance to prevent or label, active-comparator, dose-ranging, safety and exploratory efficacy study. delay left ventricular mass growth in patients with CKD. Am J Kidney Am J Kidney Dis. 2016;67(6):912–24. Dis. 2005;46(5):799–811. 39. Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health 21. Parfrey PS, Foley RN, Wittreich BH, Sullivan DJ, Zagari MJ, Frei D. Double- survey (SF-36). I. Conceptual framework and item selection. Med Care. blind comparison of full and partial anemia correction in incident 1992;30(6):473–83. hemodialysis patients without symptomatic heart disease. J Am Soc 40. Maruish ME. User's manual for the SF-36v2 Health Survey (3rd ed.). Lincoln, Nephrol. 2005;16(7):2180–9. RI: QualityMetric Incorporated; 2011. 22. Ritz E, Laville M, Bilous RW, O'Donoghue D, Scherhag A, Burger U, et al. 41. Cella D, Eton DT, Lai JS, Peterman AH, Merkel DE. Combining anchor and Target level for hemoglobin correction in patients with diabetes and CKD: distribution-based methods to derive minimal clinically important primary results of the Anemia correction in diabetes (ACORD) study. Am J differences on the functional assessment of Cancer therapy (FACT) anemia Kidney Dis. 2007;49(2):194–207. and fatigue scales. J Pain Symptom Manag. 2002;24(6):547–61. 23. Roger SD, McMahon LP, Clarkson A, Disney A, Harris D, Hawley C, et al. 42. Pfeffer MA, Burdmann EA, Chen CY, Cooper ME, de Zeeuw D, Eckardt KU, et Effects of early and late intervention with epoetin alpha on left al. A trial of darbepoetin alfa in type 2 diabetes and chronic kidney disease. ventricular mass among patients with chronic kidney disease (stage 3 N Engl J Med. 2009;361(21):2019–32. or 4): results of a randomized clinical trial. J Am Soc Nephrol. 2004; 43. Leidy NK, Revicki DA, Geneste B. Recommendations for evaluating the 15(1):148–56. validity of quality of life claims for labeling and promotion. Value 24. Rossert J, Levin A, Roger SD, Horl WH, Fouqueray B, Gassmann-Mayer C, et Health. 1999;2(2):113–27. al. Effect of early correction of anemia on the progression of CKD. Am J 44. Nunnally JC, Bernstein IH. Psychometric theory. 3rd ed. New York, NY: Kidney Dis. 2006;47(5):738–50. McGraw-Hill; 1994. 25. Singh AK, Szczech L, Tang KL, Barnhart H, Sapp S, Wolfson M, et al. 45. Cronbach LJ. Coefficient alpha and the internal structure of test. Correction of anemia with epoetin alfa in chronic kidney disease. N Engl J Psychometrika. 1951;16(3):297–334. Med. 2006;355(20):2085–98. 46. Hays RD, Revicki DA. Reliability and validity, including responsiveness. In: Fayers 26. Martin ML, Patrick DL, Gandra SR, Bennett AV, Leidy NK, Nissenson AR, PM, Hays RD, editors. Assessing quality of life in clinical trials. 2nd ed. New York, et al. Content validation of two SF-36 subscales for use in type 2 NY: Oxford University Press; 2005. p. 25–39. diabetes and non-dialysis chronic kidney disease-related anemia. Qual 47. Cohen J. Statistical power analysis for the behavioral sciences. Second ed. Life Res. 2011;20(6):889–901. Hillsdale, NJ: Lawrence Erlbaum; 1988. 27. Korevaar JC, Merkus MP, Jansen MAM, Dekker FW, Boeschoten EW, Krediet 48. Guyatt GH, Osoba D, Wu AW, Wyrwich KW, Norman GR. Clinical significance RT for the NECOSAD-study group. Validation of the KDQOL-SFTM: A dialysis- consensus meeting G. Methods to explain the clinical significance of health targeted health measure. Quality of Life Res. 2002;11:437–47. status measures. Mayo Clin Proc. 2002;77(4):371–83. 28. Cella D. The functional assessment of Cancer therapy-Anemia (FACT-an) 49. Coon CD, Cappelleri JC. Interpreting change in scores on patient- scale: a new tool for the assessment of outcomes in cancer anemia and reported outcome instruments. Therapeutic Innovation & Regulatory fatigue. Semin Hematol. 1997;34(3 Suppl 2):13–9. Science. 2016;50(1):22–9. 29. Yellen SB, Cella DF, Webster K, Blendowski C, Kaplan E. Measuring 50. Cicchetti DV. Guidelines, criteria, and rules of thumb for evaluating normed fatigue and other anemia-related symptoms with the functional and standardized assessment instruments in psychology. Psychol Assess. assessment of Cancer therapy (FACT) measurement system. J Pain 1994;6(4):284–90. Symptom Manag. 1997;13(2):63–74. 51. Revicki D, Hays RD, Cella D, Sloan J. Recommended methods for determining responsiveness and minimally important differences for 30. Cruciani RA, Dvorkin E, Homel P, Culliney B, Malamud S, Lapin J, et al. L- patient-reported outcomes. J Clin Epidemiol. 2008;61(2):102–9. carnitine supplementation in patients with advanced cancer and carnitine deficiency: a double-blind, placebo-controlled study. J Pain Symptom 52. Fayers PM, Hays RD. Don't middle your MIDs: regression to the mean Manag. 2009;37(4):622–31. shrinks estimates of minimally important differences. Qual Life Res. 31. Milroy R, Bajetta E, van den Berg P, O'Brien ER, Perez-Manga G. Effects of 2014;23(1):1–4. epoetin alfa on anemia and patient-reported outcomes in patients with 53. Locatelli F, Del Vecchio L, Pozzoni P. Anemia and cardiovascular risk: the non-small cell lung cancer receiving chemotherapy: results of a European, lesson of the CREATE trial. J Am Soc Nephrol. 2006;17(12 Suppl 3):S262–6. multicenter, randomized, controlled study. European Journal of Clinical & 54. Clement FM, Klarenbach S, Tonelli M, Johnson JA, Manns BJ. The impact of Medical Oncology. 2011;3(2):59–6. selecting a high hemoglobin target level on health-related quality of life for 32. Revicki DA, Brandenburg NA, Muus P, Yu R, Knight R, Fenaux P. Health-related quality patients with chronic kidney disease: a systematic review and meta-analysis. of life outcomes of lenalidomide in transfusion-dependent patients with low- or Arch Intern Med. 2009;169(12):1104–12. Finkelstein et al. Health and Quality of Life Outcomes (2018) 16:111 Page 13 of 13 55. Suzuki Y, Tokuda Y, Fujiwara Y, Minami H, Ohashi Y, Saijo N. Weekly epoetin beta maintains haemoglobin levels and improves quality of life in patients with non-myeloid malignancies receiving chemotherapy. Jpn J Clin Oncol. 2008;38(3):214–21. 56. Brown DJ, McMillan DC, Milroy R. The correlation between fatigue, physical function, the systemic inflammatory response, and psychological distress in patients with advanced lung cancer. Cancer. 2005;103(2):377–82. 57. Crawford J, Cella D, Cleeland CS, Cremieux PY, Demetri GD, Sarokhan BJ, et al. Relationship between changes in hemoglobin level and quality of life during chemotherapy in anemic cancer patients receiving epoetin alfa therapy. Cancer. 2002;95(4):888–95. 58. Holzner B, Kemmler G, Greil R, Kopp M, Zeimet A, Raderer M, et al. The impact of hemoglobin levels on fatigue and quality of life in cancer patients. Ann Oncol. 2002;13(6):965–73. 59. Cella D, Kallich J, McDermott A, Xu X. The longitudinal relationship of hemoglobin, fatigue and quality of life in anemic cancer patients: results from five randomized clinical trials. Ann Oncol. 2004;15(6):979–86. 60. Lai J-S, Cook K, Stone A, Beaumont J, Cella D. Classical testing theory and item response theory/Rasch model to assess difference between patient- reported fatigue using seven-day and four-week recall periods. J Clin Epidemiol. 2009;62(9):991–7.

Journal

Health and Quality of Life OutcomesSpringer Journals

Published: May 31, 2018

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Search

Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly

Organize

Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.

Access

Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve

Freelancer

DeepDyve

Pro

Price

FREE

$49/month
$360/year

Save searches from
Google Scholar,
PubMed

Create lists to
organize your research

Export lists, citations

Read DeepDyve articles

Abstract access only

Unlimited access to over
18 million full-text articles

Print

20 pages / month

PDF Discount

20% off