TY - JOUR
AU - Mulloy, Laura, L.
AB - Purpose. Factors associated with adherence to immunosuppressant therapy (IST) in renal transplant recipients were studied. Methods. The Immunosuppressant Therapy Adherence Scale (ITAS) was completed by adult renal transplant recipients in Georgia. Those completing the ITAS were classified as adherent to IST if their ITAS score were 12 and nonadherent if their score was less than 12. The relationship between the dichotomized ITAS scores and patient variables that are readily available to clinicians, such as sex, age, kidney donor type, income, marital status, race or ethnicity, and time since transplantation, was assessed. The relationship of ITAS scores to patients’ clinical and pharmacy data (e.g., graft rejection, serum IST concentrations, serum creatinine [SCr] concentrations, and pharmacy refill-based adherence rates) was also assessed. Results. One hundred thirty-seven patients completed the ITAS. Eighty-nine patients (65%) were adherent to IST, and the remaining 48 (35%) were nonadherent. Patient sex was unrelated to adherence. Compared with nonadherent patients, adherent patients tended to be younger, to take cyclosporine, to have lower incomes, to have received their transplant more recently, to have targeted immunosuppressant concentrations, to have greater refill-based adherence rates, and to be less likely to exhibit an increase in SCr concentration (p < 0.05). There was no significant difference in the number of rejections between adherent and nonadherent patients. Conclusion. Patient age, income, time since transplantation, and the immunosuppressant agent prescribed were associated with IST adherence. Age, Blood levels, Compliance, Cyclosporine, Graft rejection, Immunosuppressive agents, Patients, Sex, Sociology, Transplantation Many solid-organ-transplant recipients do not take their immunosuppressant therapy (IST) as prescribed. Nonadherence to IST after transplantation is one of the leading causes of allograft rejection, graft loss, and death.1,2 Despite the devastating consequences of IST nonadherence, which include decreased quality of life, increased health care costs, need for dialysis, morbidity, and mortality, reported nonadherence rates range from 5% to 68%.3,4 Therefore, adherence, defined as the extent to which a person’s behavior conforms to medical or health advice,5 is a critical issue in transplant medicine.6 As more potent and effective immunosuppressants become available to decrease acute-rejection episodes, immunosuppressant adherence emerges as an important factor determining outcomes of solid-organ transplantation.7 Medication compliance (adherence) is measured by a variety of methods, with no one method of adherence being superior in all aspects to another.8,–10 Although direct questioning of patients (self-reports) as a method of measuring adherence is desirable, since it is not invasive or expensive, self-reports depend on patient accuracy, and most scales used to measure adherence have not been tested for reliability and validity.8 Nonetheless, many studies have used patient self-reports to measure IST adherence and to relate IST adherence to patient-specific factors. Studies have found IST nonadherence to be more common in African Americans, Hispanics, younger adults, single adults, and those who have had their transplants for a longer time than in Caucasians, older adults, married adults, and recent transplantees.2,3,11,–15 Patients with low social economic status have also been found to be more nonadherent than those in higher socioeconomic groups,11,16,17 although those with college educations were found to be less adherent than those without postsecondary education.15 In these studies, the method of defining and confirming recipients’ socioeconomic status was not detailed.11,16,17 To target IST adherence interventions at those who are at highest risk for IST nonadherence, it is beneficial to determine a profile of those who are more likely to be nonadherent. In March 2004, the journal Transplantation featured several articles highlighting the significance of IST adherence.6,7,10,18,–20 Our study serves as a supplement to these articles, since it examined patient data (which are easily accessible to practitioners) and the association of the data (patient-specific factors) with IST adherence. Our purpose was to determine the prevalence of IST nonadherence in a statewide sample of Georgia renal transplant recipients (referred to as patients) and to assess relationships between self-reported IST adherence and patient sex, age, kidney donor type (deceased [cadaveric] or living), income, marital status, race or ethnicity, time since transplantation, rejection episode, serum creatinine (SCr) concentrations, adherence rate according to immunosuppressant refill records, and serum immunosuppressant concentrations. Methods In fall 2003, the Immunosuppressant Therapy Adherence Scale (ITAS) was mailed to 146 renal transplant patients in Georgia. The ITAS is a four-item, valid, reliable self-report measure that was developed to assess transplant recipients’ IST adherence by asking them to indicate how often they were nonadherent to IST, given a particular circumstance.21 Items ask respondents how often they (1) forgot to take their IST medications, (2) were careless about taking their IST medications, (3) stopped taking their IST medications because they felt worse, and (4) missed taking their IST medications for any reason. Response options are 0% of the time, 1–20%, 21–50%, and greater than 50%. The ITAS has been found to have positive correlations with immunosuppressant-refill-based adherence rates and targeted serum immunosuppressant concentrations (p < 0.01). ITAS item scores were negatively related to rejection occurrence and increased SCr level (p < 0.05). The ITAS has acceptable reliability (Cronbach’s α of 0.81) and has construct, convergence, and nomologic validity among solid-organ-transplant recipients.21 To be included in the study, renal transplant recipients had to be members of the Medication Access Program (a statewide program whose mission is to increase medication access among transplant recipients who reside in Georgia), to have a functioning graft, to be taking cyclosporine or tacrolimus, and to be at least 18 years of age. Sixty-eight of the 146 patients surveyed were from the Medical College of Georgia (MCG); the remaining 78 received their posttransplant care from other transplant centers in Georgia. In addition to the data collected for the entire sample, data collected from the MCG subgroup included immunosuppressant refill records, blood (serum) immunosuppressant concentrations, and occurrence of a rejection episode (biopsy proven). Since all participating patients received their medications from the MCG pharmacy and received post-transplant care from the MCG renal transplant clinic, their refill data and serum cyclosporine and tacrolimus levels were used as objective measures of IST adherence. Cyclosporine and tacrolimus were the only immunosuppressant agents examined, because (1) they are commonly used (most renal transplant recipients are prescribed either cyclosporine or tacrolimus as their base IST), and (2) blood concentrations of these agents are routinely measured in practice, thereby providing data to support adherence. Furthermore, cyclosporine and tacrolimus are not used in the same regimen, since they are both calcineurin inhibitors and inhibit the calcineurin pathway. Each patient’s date of birth, sex, race or ethnicity, 2002 income (all patients enrolled in the Medication Access Program during 2003 provided their 2002 income tax forms and Social Security benefit forms), transplant donor type (living or cadaveric), and date of transplantation were also collected. Immunosuppressant refill records, serum immunosuppressant concentrations, SCr concentrations, and occurrence of rejection for each recipient were collected for the period from mid-August through mid-November 2003. A period of three months was selected, because patients’ recall of adherence is limited and decreases over time, statements on the ITAS refer to a three-month period, and three months is often adequate for observing patterns of adherence to long-term medications.8 The study was approved by the human assurance committee (institutional review board) at MCG. Refill records. Each patient’s MCG pharmacy refill records for cyclosporine and tacrolimus were collected between mid-August and mid-November 2003 by using the pharmacy’s prescription computer system. Medical and monthly refill records were used to obtain the details of the cyclosporine or tacrolimus regimen and to calculate the next expected refill. Adherence was estimated by comparing patients’ monthly refill records with the prescribed regimen documented in the medical records. Adherence rates were calculated from the number of days between refills. If the total number of days between refills was less than or equal to the total number of days of supply of the immunosuppressant, the adherence rate was 100%. If the number of days between refills was greater than the number of days of supply, the adherence rate was calculated as follows22: {1 – [(Days between refills – total days’ supply)/days between refills]} × 100%. We assumed that any extra doses accumulated during the study period were used as needed by the recipient to adhere to the prescribed therapy if refills were not obtained on time. For example, if the total number of days between cyclosporine refills was three days more than the number of days of supply for month 3, and the same patient refilled his or her month 2 supply five days early, we assumed that the patient used the extra doses obtained in month 2 to cover the three days of supply needed in month 3. Since refill-based adherence rates of 80% or greater have been found to be well correlated with other markers of IST adherence, such as serum IST concentrations,23 this percentage was used to develop an adherent-versus-nonadherent diagnostic index for immunosuppressant refill records. If the refill-based adherence rate was less than 80%, the patient was characterized as nonadherent, and if the rate was 80% or greater, the patient was considered adherent.23 Serum cyclosporine and tacrolimus concentrations measured between August 2003 through November 2003 were recorded. Serum concentrations were classified as achieving or not achieving targeted minimum concentrations. Targeted blood concentrations of at least 100 ng/mL and at least 5 ng/mL were used for cyclosporine and tacrolimus, respectively.24 The minimum targeted concentrations were used as a conservative method of assessing adherence and to allow for varying posttransplant time (lower concentrations are generally more acceptable as time since transplant surgery passes and among patients who are at lower risk for rejection, whereas higher concentrations are associated with more recent transplant surgery). Statistical analysis. Data were entered into a spreadsheet (Excel 2000, Microsoft Inc., Redmond, WA) and downloaded into SPSS, version 12.0 (SPSS Inc., Chicago, IL). Each ITAS item was coded 3 (0% of the time), 2 (1–20%), 1 (21–50%), and 0 (greater than 50%). A higher composite ITAS score would indicate greater adherence. Thus, the four-item ITAS composite score ranged from a low of 0, indicating very poor adherence, to a high of 12, indicating perfect adherence. Since there is abundant literature indicating that self-report measures of adherence tend to overestimate adherence,25,–27 patients were dichotomized as being adherent by having a perfect adherence score (score of 12) on the ITAS to correct for response bias. Dichotomized ITAS scores of 1, representing adherent (composite ITAS score of 12), and 0, representing nonadherent (composite score of less than 12), were coded in the data set for each patient. Dichotomized refill-based adherence scores of 1, representing adherent (refill record greater than 80%), and 0, representing nonadherent (refill record less than 80%), were coded in the data set for each patient. The relationships between the dichotomized ITAS scores and patient factors were assessed by using chi-square and Student’s t tests where appropriate. The a priori level of significance was 0.05. Results One hundred thirty-seven patients completed and returned the ITAS, for a 94% response rate. The study population had a mean ± S.D. age of 52.52 ± 14.02 years and a mean ± S.D. annual income of $16,691 ± $10,747 (Table 11). Table 1. Demographics of Sample Characteristic All Patients (n= 137) Non-MCGaPatients (n = 72) MCG Patients (n= 65) aMCG = Medical College of Georgia. Sex, no. (%)     Male 88 (64) 38 (53) 50 (77)     Female 49 (36) 34 (47) 15 (23) Race, no. (%)     Caucasian 68 (50) 36 (50) 32 (49)     African American 64 (47) 33 (46) 31 (48)     Hispanic 3 (2) 2 (3) 1 (2)     Other 2 (1) 1 (1) 1 (2) Mean ± S.D. age 52.52 ± 14.02 50.17 ± 13.56 55.12 ± 14.17 Characteristic All Patients (n= 137) Non-MCGaPatients (n = 72) MCG Patients (n= 65) aMCG = Medical College of Georgia. Sex, no. (%)     Male 88 (64) 38 (53) 50 (77)     Female 49 (36) 34 (47) 15 (23) Race, no. (%)     Caucasian 68 (50) 36 (50) 32 (49)     African American 64 (47) 33 (46) 31 (48)     Hispanic 3 (2) 2 (3) 1 (2)     Other 2 (1) 1 (1) 1 (2) Mean ± S.D. age 52.52 ± 14.02 50.17 ± 13.56 55.12 ± 14.17 Open in new tab Table 1. Demographics of Sample Characteristic All Patients (n= 137) Non-MCGaPatients (n = 72) MCG Patients (n= 65) aMCG = Medical College of Georgia. Sex, no. (%)     Male 88 (64) 38 (53) 50 (77)     Female 49 (36) 34 (47) 15 (23) Race, no. (%)     Caucasian 68 (50) 36 (50) 32 (49)     African American 64 (47) 33 (46) 31 (48)     Hispanic 3 (2) 2 (3) 1 (2)     Other 2 (1) 1 (1) 1 (2) Mean ± S.D. age 52.52 ± 14.02 50.17 ± 13.56 55.12 ± 14.17 Characteristic All Patients (n= 137) Non-MCGaPatients (n = 72) MCG Patients (n= 65) aMCG = Medical College of Georgia. Sex, no. (%)     Male 88 (64) 38 (53) 50 (77)     Female 49 (36) 34 (47) 15 (23) Race, no. (%)     Caucasian 68 (50) 36 (50) 32 (49)     African American 64 (47) 33 (46) 31 (48)     Hispanic 3 (2) 2 (3) 1 (2)     Other 2 (1) 1 (1) 1 (2) Mean ± S.D. age 52.52 ± 14.02 50.17 ± 13.56 55.12 ± 14.17 Open in new tab Eighty-nine (65%) of the patients had a composite ITAS score of 12 and therefore were considered adherent; the remaining 48 patients (35%) had a composite score of less than 12 and were considered nonadherent. Data for the MCG subsample (n = 65, response rate of 96%) indicated that 50 patients (77%) were adherent by composite ITAS scores and that 15 (23%) were nonadherent. Data for the MCG subsample also indicated that 41 patients (63%) were adherent by refill records and that 24 (37%) were nonadherent. Table 22 summarizes patients’ responses to the ITAS questions. Table 2. Responses on Immunosuppressant Therapy Adherence Scale No. (%) Patients Giving Response Question and Response All Patients (n= 137) Non-MCGa Patients (n = 72) MCG Patients (n= 65) MCG Patients with Rejection (n= 6) aMCG = Medical College of Georgia. In the last 3 months, how often did you forget to take your immunosuppressant medications?     0% of the time 98 (72) 49 (68) 49 (75) 3 (50)     1–20% 37 (27) 22 (31) 15 (23) 2 (33)     21–50% 2 (1) 1 (1) 1 (2) 1 (17)     >50% 0 0 0 0 In the last 3 months, how often were you careless about taking your immunosuppressant medications?     0% of the time 107 (78) 55 (76) 52 (80) 4 (67)     1–20% 29 (21) 16 (22) 13 (20) 2 (33)     21–50% 0 0 0 0     >50% 1 (1) 1 (1) 0 0 In the last 3 months, how often did you stop taking your immunosuppressant medications because you felt worse?     0% of the time 127 (93) 68 (94) 59 (91) 4 (67)     1–20% 10 (7) 4 (6) 6 (9) 2 (33)     21–50% 0 0 0 0     >50% 0 0 0 0 In the last 3 months, how often did you miss taking your immunosuppressant medications for any reason?     0% of the time 89 (65) 40 (56) 49 (75) 3 (50)     1–20% 43 (31) 29 (40) 14 (22) 2 (33)     21–50% 4 (3) 2 (3) 2 (3) 1 (17)     >50% 1 (1) 1 (1) 0 0 No. (%) Patients Giving Response Question and Response All Patients (n= 137) Non-MCGa Patients (n = 72) MCG Patients (n= 65) MCG Patients with Rejection (n= 6) aMCG = Medical College of Georgia. In the last 3 months, how often did you forget to take your immunosuppressant medications?     0% of the time 98 (72) 49 (68) 49 (75) 3 (50)     1–20% 37 (27) 22 (31) 15 (23) 2 (33)     21–50% 2 (1) 1 (1) 1 (2) 1 (17)     >50% 0 0 0 0 In the last 3 months, how often were you careless about taking your immunosuppressant medications?     0% of the time 107 (78) 55 (76) 52 (80) 4 (67)     1–20% 29 (21) 16 (22) 13 (20) 2 (33)     21–50% 0 0 0 0     >50% 1 (1) 1 (1) 0 0 In the last 3 months, how often did you stop taking your immunosuppressant medications because you felt worse?     0% of the time 127 (93) 68 (94) 59 (91) 4 (67)     1–20% 10 (7) 4 (6) 6 (9) 2 (33)     21–50% 0 0 0 0     >50% 0 0 0 0 In the last 3 months, how often did you miss taking your immunosuppressant medications for any reason?     0% of the time 89 (65) 40 (56) 49 (75) 3 (50)     1–20% 43 (31) 29 (40) 14 (22) 2 (33)     21–50% 4 (3) 2 (3) 2 (3) 1 (17)     >50% 1 (1) 1 (1) 0 0 Open in new tab Table 2. Responses on Immunosuppressant Therapy Adherence Scale No. (%) Patients Giving Response Question and Response All Patients (n= 137) Non-MCGa Patients (n = 72) MCG Patients (n= 65) MCG Patients with Rejection (n= 6) aMCG = Medical College of Georgia. In the last 3 months, how often did you forget to take your immunosuppressant medications?     0% of the time 98 (72) 49 (68) 49 (75) 3 (50)     1–20% 37 (27) 22 (31) 15 (23) 2 (33)     21–50% 2 (1) 1 (1) 1 (2) 1 (17)     >50% 0 0 0 0 In the last 3 months, how often were you careless about taking your immunosuppressant medications?     0% of the time 107 (78) 55 (76) 52 (80) 4 (67)     1–20% 29 (21) 16 (22) 13 (20) 2 (33)     21–50% 0 0 0 0     >50% 1 (1) 1 (1) 0 0 In the last 3 months, how often did you stop taking your immunosuppressant medications because you felt worse?     0% of the time 127 (93) 68 (94) 59 (91) 4 (67)     1–20% 10 (7) 4 (6) 6 (9) 2 (33)     21–50% 0 0 0 0     >50% 0 0 0 0 In the last 3 months, how often did you miss taking your immunosuppressant medications for any reason?     0% of the time 89 (65) 40 (56) 49 (75) 3 (50)     1–20% 43 (31) 29 (40) 14 (22) 2 (33)     21–50% 4 (3) 2 (3) 2 (3) 1 (17)     >50% 1 (1) 1 (1) 0 0 No. (%) Patients Giving Response Question and Response All Patients (n= 137) Non-MCGa Patients (n = 72) MCG Patients (n= 65) MCG Patients with Rejection (n= 6) aMCG = Medical College of Georgia. In the last 3 months, how often did you forget to take your immunosuppressant medications?     0% of the time 98 (72) 49 (68) 49 (75) 3 (50)     1–20% 37 (27) 22 (31) 15 (23) 2 (33)     21–50% 2 (1) 1 (1) 1 (2) 1 (17)     >50% 0 0 0 0 In the last 3 months, how often were you careless about taking your immunosuppressant medications?     0% of the time 107 (78) 55 (76) 52 (80) 4 (67)     1–20% 29 (21) 16 (22) 13 (20) 2 (33)     21–50% 0 0 0 0     >50% 1 (1) 1 (1) 0 0 In the last 3 months, how often did you stop taking your immunosuppressant medications because you felt worse?     0% of the time 127 (93) 68 (94) 59 (91) 4 (67)     1–20% 10 (7) 4 (6) 6 (9) 2 (33)     21–50% 0 0 0 0     >50% 0 0 0 0 In the last 3 months, how often did you miss taking your immunosuppressant medications for any reason?     0% of the time 89 (65) 40 (56) 49 (75) 3 (50)     1–20% 43 (31) 29 (40) 14 (22) 2 (33)     21–50% 4 (3) 2 (3) 2 (3) 1 (17)     >50% 1 (1) 1 (1) 0 0 Open in new tab Women were no more likely to be adherent than men (p = 0.237) (Table 33). Compared with nonadherent patients, adherent patients were significantly younger, more often took cyclosporine than tacrolimus, had lower average incomes, were more often within targeted range of immunosuppressant concentrations, had greater refill-record-based adherence rates, and less often exhibited a rise in SCr concentration (to greater than 0.3 mg/dL) (p < 0.01). Adherent patients had received their transplants more recently (p = 0.017). Patients who experienced a graft-rejection episode had a mean ± S.D. ITAS score of 10.00 ± 2.45. There was a nonsignificant tendency (p = 0.100) for nonadherent patients to more often experience a rejection episode. There were no significant differences between the groups in donor type or race. Table 3. Association of Patient Characteristics with Adherence Variable Adherent Patients (ITASa Score, 12) Nonadherent Patients (ITAS Score, <12) p aITAS = Immunosuppressant Therapy Adherence Scale. bBased on entire sample of 137 patients (89 adherent patients and 48 nonadherent patients). cChi-square test. dt test. eBased on the Medical College of Georgia subsample of 65 patients (50 adherent patients and 15 nonadherent patients). fRefill record-based adherence. Adherent was defined as a three-month adherence rate of 80% or greater, and nonadherent was defined as a three-month adherence rate of less than 80%. Sex, no. (%)b 0.237c     Male 54 (61) 34 (71)     Female 35 (40) 14 (29) Mean ± S.D. age, yrb 49.67 ± 11.94 57.79 ± 16.07 0.001d Age, range, yrb 26–74 21–84 Donor type, no. (%)e 0.923c     Living 16 (32) 5 (33)     Cadaveric 34 (68) 10 (67) Immunosuppressant, no. (%)e <0.001c     Cyclosporine 38 (76) 4 (26)     Tacrolimus 12 (24) 11 (73) Mean ± S.D. annual income, $b 14,387 ± 7,644 21,079 ± 14,081 0.001d Serum immunosuppressant concentration, no. (%)e <0.001c     Achieving targeted minimum 41 (82) 3 (20)     Not achieving targeted minimum 9 (18) 12 (80) Race, no. (%)b 0.941c     Caucasian 45 (51) 23 (48)     African American 41 (46) 23 (48)     Other 3 (3) 2 (4) Time since transplantation, no. (%)b 0.017c     ≤2 yr 25 (28) 5 (10)     >2 yr 64 (72) 43 (90) Refill records, no. (%)e,f <0.001c     Adherent 39 (78) 2 (13)     Nonadherent 11 (22) 13 (87) Rejection episode, no. (%)e 0.100c     With rejection 3 (6) 3 (20)     Without rejection 47 (94) 12 (80) Increase in serum creatinine conc. no. (%)e 0.005c     With increase 11 (22) 9 (60)     Without increase 39 (78) 6 (40) Variable Adherent Patients (ITASa Score, 12) Nonadherent Patients (ITAS Score, <12) p aITAS = Immunosuppressant Therapy Adherence Scale. bBased on entire sample of 137 patients (89 adherent patients and 48 nonadherent patients). cChi-square test. dt test. eBased on the Medical College of Georgia subsample of 65 patients (50 adherent patients and 15 nonadherent patients). fRefill record-based adherence. Adherent was defined as a three-month adherence rate of 80% or greater, and nonadherent was defined as a three-month adherence rate of less than 80%. Sex, no. (%)b 0.237c     Male 54 (61) 34 (71)     Female 35 (40) 14 (29) Mean ± S.D. age, yrb 49.67 ± 11.94 57.79 ± 16.07 0.001d Age, range, yrb 26–74 21–84 Donor type, no. (%)e 0.923c     Living 16 (32) 5 (33)     Cadaveric 34 (68) 10 (67) Immunosuppressant, no. (%)e <0.001c     Cyclosporine 38 (76) 4 (26)     Tacrolimus 12 (24) 11 (73) Mean ± S.D. annual income, $b 14,387 ± 7,644 21,079 ± 14,081 0.001d Serum immunosuppressant concentration, no. (%)e <0.001c     Achieving targeted minimum 41 (82) 3 (20)     Not achieving targeted minimum 9 (18) 12 (80) Race, no. (%)b 0.941c     Caucasian 45 (51) 23 (48)     African American 41 (46) 23 (48)     Other 3 (3) 2 (4) Time since transplantation, no. (%)b 0.017c     ≤2 yr 25 (28) 5 (10)     >2 yr 64 (72) 43 (90) Refill records, no. (%)e,f <0.001c     Adherent 39 (78) 2 (13)     Nonadherent 11 (22) 13 (87) Rejection episode, no. (%)e 0.100c     With rejection 3 (6) 3 (20)     Without rejection 47 (94) 12 (80) Increase in serum creatinine conc. no. (%)e 0.005c     With increase 11 (22) 9 (60)     Without increase 39 (78) 6 (40) Open in new tab Table 3. Association of Patient Characteristics with Adherence Variable Adherent Patients (ITASa Score, 12) Nonadherent Patients (ITAS Score, <12) p aITAS = Immunosuppressant Therapy Adherence Scale. bBased on entire sample of 137 patients (89 adherent patients and 48 nonadherent patients). cChi-square test. dt test. eBased on the Medical College of Georgia subsample of 65 patients (50 adherent patients and 15 nonadherent patients). fRefill record-based adherence. Adherent was defined as a three-month adherence rate of 80% or greater, and nonadherent was defined as a three-month adherence rate of less than 80%. Sex, no. (%)b 0.237c     Male 54 (61) 34 (71)     Female 35 (40) 14 (29) Mean ± S.D. age, yrb 49.67 ± 11.94 57.79 ± 16.07 0.001d Age, range, yrb 26–74 21–84 Donor type, no. (%)e 0.923c     Living 16 (32) 5 (33)     Cadaveric 34 (68) 10 (67) Immunosuppressant, no. (%)e <0.001c     Cyclosporine 38 (76) 4 (26)     Tacrolimus 12 (24) 11 (73) Mean ± S.D. annual income, $b 14,387 ± 7,644 21,079 ± 14,081 0.001d Serum immunosuppressant concentration, no. (%)e <0.001c     Achieving targeted minimum 41 (82) 3 (20)     Not achieving targeted minimum 9 (18) 12 (80) Race, no. (%)b 0.941c     Caucasian 45 (51) 23 (48)     African American 41 (46) 23 (48)     Other 3 (3) 2 (4) Time since transplantation, no. (%)b 0.017c     ≤2 yr 25 (28) 5 (10)     >2 yr 64 (72) 43 (90) Refill records, no. (%)e,f <0.001c     Adherent 39 (78) 2 (13)     Nonadherent 11 (22) 13 (87) Rejection episode, no. (%)e 0.100c     With rejection 3 (6) 3 (20)     Without rejection 47 (94) 12 (80) Increase in serum creatinine conc. no. (%)e 0.005c     With increase 11 (22) 9 (60)     Without increase 39 (78) 6 (40) Variable Adherent Patients (ITASa Score, 12) Nonadherent Patients (ITAS Score, <12) p aITAS = Immunosuppressant Therapy Adherence Scale. bBased on entire sample of 137 patients (89 adherent patients and 48 nonadherent patients). cChi-square test. dt test. eBased on the Medical College of Georgia subsample of 65 patients (50 adherent patients and 15 nonadherent patients). fRefill record-based adherence. Adherent was defined as a three-month adherence rate of 80% or greater, and nonadherent was defined as a three-month adherence rate of less than 80%. Sex, no. (%)b 0.237c     Male 54 (61) 34 (71)     Female 35 (40) 14 (29) Mean ± S.D. age, yrb 49.67 ± 11.94 57.79 ± 16.07 0.001d Age, range, yrb 26–74 21–84 Donor type, no. (%)e 0.923c     Living 16 (32) 5 (33)     Cadaveric 34 (68) 10 (67) Immunosuppressant, no. (%)e <0.001c     Cyclosporine 38 (76) 4 (26)     Tacrolimus 12 (24) 11 (73) Mean ± S.D. annual income, $b 14,387 ± 7,644 21,079 ± 14,081 0.001d Serum immunosuppressant concentration, no. (%)e <0.001c     Achieving targeted minimum 41 (82) 3 (20)     Not achieving targeted minimum 9 (18) 12 (80) Race, no. (%)b 0.941c     Caucasian 45 (51) 23 (48)     African American 41 (46) 23 (48)     Other 3 (3) 2 (4) Time since transplantation, no. (%)b 0.017c     ≤2 yr 25 (28) 5 (10)     >2 yr 64 (72) 43 (90) Refill records, no. (%)e,f <0.001c     Adherent 39 (78) 2 (13)     Nonadherent 11 (22) 13 (87) Rejection episode, no. (%)e 0.100c     With rejection 3 (6) 3 (20)     Without rejection 47 (94) 12 (80) Increase in serum creatinine conc. no. (%)e 0.005c     With increase 11 (22) 9 (60)     Without increase 39 (78) 6 (40) Open in new tab Discussion The percentages of patients who were classified as adherent to IST by ITAS composite scores and refill records were 77% (n = 50) and 23% (n = 15), respectively, and the percentages classified as nonadherent were 63% (n = 41) and 37% (n = 24), respectively. Thus, 23–37% of patients were nonadherent, depending on which adherence measure was used. These data support two important points. First, a high rate of IST nonadherence existed among renal transplant recipients, with as many as one patient out of three being nonadherent. Second, although different measures of adherence may yield different adherence scores, adherence behaviors assessed by valid adherence measures should be associated with each other and with clinical outcomes (Table 33). Although a recent study suggests that measures of adherence in current clinical use do not perform well when tested against other adherence measures (e.g., electronic monitoring),6 our study indicates that patients’ refill-based adherence rates, serum immunosuppressant concentrations, and SCr concentrations are associated with each other. Specifically, lower ITAS scores were associated with less IST adherence, as indicated by lower refill-based adherence rates, not achieving targeted serum immunosuppressant concentrations, increased SCr concentrations, and graft rejections.21 Our study is unique in its use of three measures of adherence; the association of all three measures with one another supports their validity. The association of adherence with clinical outcomes is of vital importance in transplant medicine. Rovelli and colleagues16,17 conducted retrospective and prospective studies that assessed nonadherence in organ transplant recipients. Although the mean time since transplant surgery and the duration of the adherence evaluations were unclear, the retrospective study found that 91% of those who were noncompliant with both follow-up (defined as clinic or physician office and laboratory appointments) and therapy experienced a rejection or died, compared with only 18% of compliant patients. In the prospective study, 30% of noncompliant patients (measured by patient self-reports) had a graft rejection or died, whereas only 1% of compliant patients rejected their transplants. Although the objective of our study was to identify patient-specific factors associated with adherence to IST and not to determine if there was a difference in rejection rates between adherent and nonadherent patients, the finding that 20% of nonadherent patients (n = 3) had a rejection episode compared with only 6% of adherent patients (n = 3) is interesting. Future studies involving a larger number of patients may be needed to detect an association between objective measures of adherence (e.g., adherence measured by refill records and blood concentrations) and rejection. What is the clinical relevance of this study? Good tools for predicting which patients may be at risk for nonadherence would allow for better and more targeted interventions.10 Butler et al.18 found that a median of 36% of graft losses were associated with nonadherence; in our study, 50% of the rejections were associated with nonadherence. Patients who have characteristics associated with nonadherence should receive intensive evaluation and intervention. Furthermore, adherence strategies should address the reasons leading to nonadherence. For example, some patients indicated that they missed doses because they forgot to take them; strategies to overcome this may include reminder instruments, such as alarms. To assess the association of adherence with patient-specific factors, it was important for us to select a limited number of factors that were easily accessible to clinicians, believed to influence adherence, and consistent (i.e., not changing dramatically over time). The number of medications that a patient had to take was not examined, because (1) the number of medications taken changes constantly, (2) medication units constituting a dose may differ drastically and may be difficult to accurately assess, and (3) preliminary analysis of the data revealed no difference between adherent and nonadherent patients in the number of medications taken. Our study confirms the findings of some IST adherence studies but is in direct conflict with others. Like Siegal and Greenstein14 and Green-stein and Siegal,15 we found recent transplantees to be more adherent than those who had transplants longer. We also found that younger patients were more adherent than older patients, which was not found in some other studies.11,13,–17,28,29 It makes sense that older adults would be less adherent than younger adults, given the probability of older patients having additional challenges, such as forgetfulness, increased impairment due to other conditions, and less access to health care (e.g., limited transportation).8,30 Since we did not find significant differences in adherence between non-Caucasians and Caucasians, our study contradicts studies suggesting that minority populations, such as African Americans, are less adherent to IST.3,11,12,14,31 However, one of the largest studies of adherence in renal transplant patients (involving over 1400 patients) did not find adherence differences between non-Caucasians and Caucasians.15 Patient income was significantly associated with IST adherence. Data concerning the relationship between renal transplant patients’ income and IST adherence have not been published. However, data are available suggesting that those with higher socioeconomic status have better adherence,11,16,17 while other data suggest that white-collar occupations and some college education are more often associated with nonadherence.15 We believe that income may have influenced those taking cyclosporine to be more adherent than patients taking tacrolimus, since supplementary analysis of the data indicated that tacrolimus users more often reported that they skipped doses when they were short of money.32 These findings may have resulted because tacrolimus costs more than cyclosporine (no generic products are available for tacrolimus) and because it is more difficult for patients to qualify to receive free medication from the tacrolimus manufacturer’s assistance program than from the cyclosporine manufacturer’s assistance program. Thus, the higher cost of tacrolimus to the patient may have reduced access to therapy and lowered adherence. Failure to admit to nonadherence is common among patients. Since all adherence measures have limitations,8,9 we confirmed adherence by using the ITAS, prescription refill records, and serum drug concentrations. Using SCr concentration as an outcome measure has limitations. Although increased SCr concentrations can often result from IST non-adherence (e.g., in patients with rejection due to nonadherence), other events can also be responsible (e.g., dehydration, graft rejection due to reasons other than IST nonadherence). Since SCr concentration is a clinical measure frequently used to assess renal function, it was used as such in this study. Another study limitation is that the sample size was too small to detect a significant difference in rejections between adherent and nonadherent patients. Although fewer adherent patients had a rejection episode, the difference was not significant (p = 0.100). Since the study did not have the power to detect a difference in rejection episodes, and since the sample size was small, a Type II error may account for the nonsignificant finding for graft rejection. Studies with multiple, valid, and reliable measures of adherence that involve using larger samples to detect differences in graft rejection are needed. This study should serve as a springboard for such studies, including studies that identify patients who are underadherent (take less medication than prescribed) and overadherent (take more medication than prescribed). Conclusion Patient age, income, time since kidney transplantation, and the immunosuppressant agent prescribed were associated with IST adherence. Footnotes Supported by the Carlos and Marguerite Mason Trust Fund. References 1 Gaston R, Hudson S, War M et al. 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TI - Patient factors associated with adherence to immunosuppressant therapy in renal transplant recipients
JO - American Journal of Health-System Pharmacy
DO - 10.2146/ajhp040541
DA - 2005-09-01
UR - https://www.deepdyve.com/lp/oxford-university-press/patient-factors-associated-with-adherence-to-immunosuppressant-therapy-7E8HdQzPNg
SP - 1775
VL - 62
IS - 17
DP - DeepDyve
ER -