TY - JOUR
AU - Brunelli,, Alessandro
AB - Abstract OBJECTIVES Open in new tabDownload slide Open in new tabDownload slide The aim of this study was to assess whether quality of life (QoL) scales are associated with postoperative length of stay (LoS) following video-assisted thoracoscopic surgery (VATS) lobectomy for lung cancer. METHODS This is a single-centre retrospective analysis on 250 consecutive patients submitted to VATS lobectomies (233) or segmentectomies (17) over a period of 3 years. QoL was assessed in all patients by the self-administration of the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C30 questionnaire. The individual QoL scales were tested for possible association with LoS along with other objective baseline and surgical parameters using univariable and multivariable analyses. RESULTS Thirty-day cardiopulmonary and mortality rates were 22% and 2.4%. The median LoS was 4 days [interquartile range (IQR) 3–7]. Fifty-one (20%) patients remained in hospital longer than 7 days after surgery (upper quartile). General health [global health score (GHS)] (P = 0.019), physical function (P = 0.014) and role functioning (P = 0.016) scales were significantly worse in patients with prolonged stay. They were highly correlated between each other and tested separately in different logistic regression analyses. The best model resulted the one containing GHS (P = 0.032) along with age, low force expiratory volume in 1 s and carbon monoxide lung diffusion capacity and history of cerebrovascular disease. Fifty-nine patients had GHS <58 (lower interquartile value). Thirty-one percent of them experienced prolonged hospital stay (vs 17% of those with higher GHS, P = 0.027). CONCLUSIONS Preoperative patient-reported QoL was associated with prolonged postoperative hospital stay. Baseline QoL status should be taken into consideration to implement psychosocial supportive programmes in the context of enhanced recovery after surgery. Quality of life, Lung cancer surgery, Lobectomy, Segmentectomy, Patient-reported outcomes, Enhanced recovery after surgery INTRODUCTION The use of patient-reported quality of life (QoL) measures has increased in frequency over the past decade and are increasingly recognized as emerging postoperative outcome indicators in thoracic oncologic surgery. The World Health Organization produced a definition of QoL and governments are following suit, considering its implementation into perioperative guidelines [1]. As a part of the patient-reported outcomes sphere, the self-assessment of an individual’s QoL has been found not only to affect surgical outcomes but also to be associated with long-term survival and play a crucial role in risk-assessment and decision-making [2, 3]. Further progress in the domain of perioperative care has been the activation of enhanced recovery after surgery programmes designed to maximize the surgical patient’s recovery and address barriers to patient recovery with an holistic, evidence-based approach [2, 3]. QoL is affected by surgery, to an extensive degree in pneumonectomy and less so following minimally invasive lobectomy. Dyspnoea, advanced age and lower performance scores are the leading factors identified to be collated to postoperative QoL [4]. However, only objective metrics are considered in the literature when designing and evaluating enhanced recovery after surgery pathways after lung cancer recovery [5, 6]. There is a clear lack of data about preoperative patient-reported components. How social and personal factors impact the postoperative period remains to be investigated thoroughly. The objective of this research is to assess whether QoL scales, surveyed in the preoperative setting, are associated with postoperative length of stay (LoS) following video-assisted thoracoscopic surgery (VATS) lobectomy for lung cancer. METHODS This is a single-centre retrospective analysis including 250 consecutive patients (157 males, 93 females) operated on at a tertiary referral centre for general thoracic surgery between September 2014 and March 2016. All patients referred with histologically proven (or highly suspicious) lung cancer candidate for surgery were included in the study. Patients underwent lobectomy or segmentectomy using multi-portal VATS access. This has surmounted traditional open techniques and excelled regarding surgical outcomes as demonstrated in the literature [7, 8]. Patient care was optimized in the postoperative period by following a local enhanced recovery after surgery pathway based on the European Society of Thoracic Surgeons approved scheme [4]. This includes early mobilization, chest physiotherapy, rehabilitation and early oral intake. Analgesia was achieved by paravertebral infusions of local anaesthetic and patient-controlled analgesia devices. Venous thromboembolism prophylaxis was administered mechanically and pharmacologically. Patient progress was objectively assessed during their recovery, again at 30 days and once further at 90 days. This process was designed as a service evaluation with no formal funding. The conduct of this research was reliant on the voluntary contributions of clinical staff. The study was reviewed by the Research and Innovation Department of the hospital, which classified it as service evaluation and therefore did not need formal National Health Service (NHS) Research Ethics Committee review. Quality of life assessment QoL was assessed through the European Organization for Research and Treatment of Cancer (EORTC) Quality of Life Questionnaire-C30 Version 3 before surgery. This is a core questionnaire that is designed to evaluate the QoL in a wide range of patients with cancer, with the first sample testing patients with lung cancer. It is internationally validated and is considered to be of high reliability and sensitivity [9, 10]. The content of the questionnaire is composed of 9 multi-item and 6 single-item scales. The 9 multi-item scales are: physical functioning (PF), role functioning (RF), cognitive functioning (CF), emotional functioning (EF) and social functioning (SF), nausea/vomiting (NV), pain (PA), fatigue (FA) and a global health score (GHS). The 6 single-item scales are: dyspnoea (DY), insomnia (SL), appetite loss (AP), financial difficulties (FI), diarrhoea (Di) and constipation (CO). The scores range from 0 to 100 after linear transformation of the raw scores. A high score for a functional scale represents a high level of functioning (healthier), whereas a high score for a symptom scale represents a high level of symptoms/problems. Statistical analysis Baseline patient characteristics and surgical parameters tested for a possible association with outcome were age, gender, body mass index, force expiratory volume in 1 s (FEV1), carbon monoxide lung diffusion capacity (DLCO), history of coronary artery disease, cerebrovascular disease [defined as history of stroke or transient ischaemic attack (TIA)] and diabetes. Complications were defined according to the joint Society of Thoracic Surgeons and European Society of Thoracic Surgeons standardized definitions [11] and included respiratory failure requiring mechanical ventilation for longer than 24 h, pneumonia, pulmonary oedema, pulmonary embolisms, atelectasis requiring bronchoscopy, myocardial ischaemia, stroke, atrial fibrillation requiring medical or electric cardioversion and acute kidney injury. For the purpose of this investigation, prolonged length of stay was considered an inpatient hospital admission longer than 7 days, corresponding to the upper interquartile of the median LoS of the whole population. Continuous variables were compared using unpaired t-test in case of normal distribution and Wilcoxon rank-sum test in case of non-normal distribution. Normality of distribution of numeric variables was tested using Shapiro–Wilk normality test. Categorical variables were compared using χ2 test or Fisher’s exact test (when the number of observations was lower than 10 in at least 1 cell). Variables were initially screened using the univariable analysis. No correction for multiple testing was performed in this context as univariable analysis was only used to select variables for multivariable regression analysis. Those variable with a P-value of <0.1 were used as independent predictors in a stepwise logistic regression analysis with backward elimination (P for retention in the final model <0.1). Baseline and surgical variables were entered in the regression model along with those QoL scales resulting with a P-value of <0.1 at univariable analysis. As QoL scales showed a correlation coefficient of >0.5, they could not be tested simultaneously in the regression model to prevent multicollinearity problems. The QoL scales selected at univariable analysis were therefore tested separately running individual logistic regression analyses adjusting for other baseline and surgical factors. Receiver operating characteristic (ROC) analysis was performed to identify the model with the highest discrimination ability. RESULTS The characteristics of the 270 patients included in the study are shown in Table 1. Table 1: Patient demographic characteristics Variables . Total population (n = 250) . Age (years) 68.4 (9.6) Male gender 102 (40.8) BMI (kg/m2) 26.9 (5.1) FEV1% 90.1 (22.6) DLCO% 73.2 (19.1) CAD 16 (6.8) CVD 16 (6.4) Segmentectomies 17 (6.8) Cardiopulmonary complications 54 (21.6) Variables . Total population (n = 250) . Age (years) 68.4 (9.6) Male gender 102 (40.8) BMI (kg/m2) 26.9 (5.1) FEV1% 90.1 (22.6) DLCO% 73.2 (19.1) CAD 16 (6.8) CVD 16 (6.4) Segmentectomies 17 (6.8) Cardiopulmonary complications 54 (21.6) Results are expressed as means and standard deviations for numeric variables and as number of cases and percentages of total for categorical variables. BMI: body mass index; CAD: coronary artery disease; CVD: cerebrovascular disease; DLCO: carbon monoxide lung diffusion capacity; FEV1: forced expiratory volume in 1 s. Open in new tab Table 1: Patient demographic characteristics Variables . Total population (n = 250) . Age (years) 68.4 (9.6) Male gender 102 (40.8) BMI (kg/m2) 26.9 (5.1) FEV1% 90.1 (22.6) DLCO% 73.2 (19.1) CAD 16 (6.8) CVD 16 (6.4) Segmentectomies 17 (6.8) Cardiopulmonary complications 54 (21.6) Variables . Total population (n = 250) . Age (years) 68.4 (9.6) Male gender 102 (40.8) BMI (kg/m2) 26.9 (5.1) FEV1% 90.1 (22.6) DLCO% 73.2 (19.1) CAD 16 (6.8) CVD 16 (6.4) Segmentectomies 17 (6.8) Cardiopulmonary complications 54 (21.6) Results are expressed as means and standard deviations for numeric variables and as number of cases and percentages of total for categorical variables. BMI: body mass index; CAD: coronary artery disease; CVD: cerebrovascular disease; DLCO: carbon monoxide lung diffusion capacity; FEV1: forced expiratory volume in 1 s. Open in new tab The median postoperative LoS was 4 days (IQR 3–7). Fifty-one patients (19%) remained in hospital longer than 7 days after surgery. Four patients received neoadjuvant chemotherapy and none of them experienced a prolonged length of stay. Patient characteristics and individual QoL scales used preoperatively in patients with and without prolonged stay are found in Tables 2 and 3. Cardiopulmonary complications within 30 days or during hospitalization occurred in 54 patients (22%) and 30-day mortality occurred in 6 patients (2.4%). Ninety-day mortality occurred in 8 patients (3.2%). Table 2: Comparison of baseline characteristics between patients with and without prolonged hospital stay (POS) . No POS (199) . POS (51) . P-value . Age (years) 67.7 (9.5) 71.2 (9.3) 0.029 Male gender 77 (39) 25 (49) 0.18 BMI (kg/m2) 27.3 (5.0) 25.8 (5.3) 0.098 FEV1% 91.8 (21.7) 83.3 (24.8) 0.030 DLCO% 75.3 (19.2) 64.7 (16.6) <0.001 CAD 12 (6.0) 5 (9.8) 0.35 CVD 7 (3.5) 9 (18) 0.001 Diabetes 19 (9.5) 9 (18) 0.13 . No POS (199) . POS (51) . P-value . Age (years) 67.7 (9.5) 71.2 (9.3) 0.029 Male gender 77 (39) 25 (49) 0.18 BMI (kg/m2) 27.3 (5.0) 25.8 (5.3) 0.098 FEV1% 91.8 (21.7) 83.3 (24.8) 0.030 DLCO% 75.3 (19.2) 64.7 (16.6) <0.001 CAD 12 (6.0) 5 (9.8) 0.35 CVD 7 (3.5) 9 (18) 0.001 Diabetes 19 (9.5) 9 (18) 0.13 Results are expressed as mean and standard deviation for numerical variables and as numbers and percentages for categorical variables. BMI: body mass index; CAD: coronary artery disease; CVD: cerebrovascular disease; DLCO: carbon monoxide lung diffusion capacity; FEV1: forced expiratory volume in 1 s; POS: prolonged length of stay. Open in new tab Table 2: Comparison of baseline characteristics between patients with and without prolonged hospital stay (POS) . No POS (199) . POS (51) . P-value . Age (years) 67.7 (9.5) 71.2 (9.3) 0.029 Male gender 77 (39) 25 (49) 0.18 BMI (kg/m2) 27.3 (5.0) 25.8 (5.3) 0.098 FEV1% 91.8 (21.7) 83.3 (24.8) 0.030 DLCO% 75.3 (19.2) 64.7 (16.6) <0.001 CAD 12 (6.0) 5 (9.8) 0.35 CVD 7 (3.5) 9 (18) 0.001 Diabetes 19 (9.5) 9 (18) 0.13 . No POS (199) . POS (51) . P-value . Age (years) 67.7 (9.5) 71.2 (9.3) 0.029 Male gender 77 (39) 25 (49) 0.18 BMI (kg/m2) 27.3 (5.0) 25.8 (5.3) 0.098 FEV1% 91.8 (21.7) 83.3 (24.8) 0.030 DLCO% 75.3 (19.2) 64.7 (16.6) <0.001 CAD 12 (6.0) 5 (9.8) 0.35 CVD 7 (3.5) 9 (18) 0.001 Diabetes 19 (9.5) 9 (18) 0.13 Results are expressed as mean and standard deviation for numerical variables and as numbers and percentages for categorical variables. BMI: body mass index; CAD: coronary artery disease; CVD: cerebrovascular disease; DLCO: carbon monoxide lung diffusion capacity; FEV1: forced expiratory volume in 1 s; POS: prolonged length of stay. Open in new tab Table 3: Comparison of baseline quality of life scales between patients with and without prolonged hospital stay (POS) . No POS (199) . POS (51) . P-value . GHS 69.8 (20.2) 59.2 (28.7) 0.019 PF 86.3 (16.6) 79.6 (19.9) 0.014 RF 87.4 (22.6) 78.4 (29.1) 0.016 EF 74.0 (25.3) 77.3 (30.8) 0.28 CF 87.4 (19.3) 83.7 (23.0) 0.24 SF 89.2 (22.5) 86.6 (27.5) 0.67 FA 18.9 (20.3) 28.1 (31.3) 0.11 NV 2.4 (8.8) 1.6 (15.4) 0.43 PA 13.1 (24.6) 19.9 (30.9) 0.11 DY 22.1 (25.1) 23.5 (29.3) 0.73 SL 31.7 (32.6) 25.5 (36.9) 0.14 AP 11.6 (23.3) 16.3 (31.5) 0.46 Co 8.0 (19.9) 7.8 (25.5) 0.67 Di 5.7 (17.4) 4.6 (17.7) 0.86 Fi 8.7 (22.5) 8.5 (26.5) 0.75 . No POS (199) . POS (51) . P-value . GHS 69.8 (20.2) 59.2 (28.7) 0.019 PF 86.3 (16.6) 79.6 (19.9) 0.014 RF 87.4 (22.6) 78.4 (29.1) 0.016 EF 74.0 (25.3) 77.3 (30.8) 0.28 CF 87.4 (19.3) 83.7 (23.0) 0.24 SF 89.2 (22.5) 86.6 (27.5) 0.67 FA 18.9 (20.3) 28.1 (31.3) 0.11 NV 2.4 (8.8) 1.6 (15.4) 0.43 PA 13.1 (24.6) 19.9 (30.9) 0.11 DY 22.1 (25.1) 23.5 (29.3) 0.73 SL 31.7 (32.6) 25.5 (36.9) 0.14 AP 11.6 (23.3) 16.3 (31.5) 0.46 Co 8.0 (19.9) 7.8 (25.5) 0.67 Di 5.7 (17.4) 4.6 (17.7) 0.86 Fi 8.7 (22.5) 8.5 (26.5) 0.75 Results are expressed as means and standard deviations. AP: appetite loss; CF: cognitive functioning; Co: constipation; Di: diarrhoea; DY: dyspnoea; EF: emotional functioning; FA: fatigue; Fi: financial impact; GHS: global health scale; NV: nausea and vomiting; PA: pain; PF: physical functioning; POS: prolonged length of stay; RF: role functioning; SF: social functioning; SL: insomnia. Open in new tab Table 3: Comparison of baseline quality of life scales between patients with and without prolonged hospital stay (POS) . No POS (199) . POS (51) . P-value . GHS 69.8 (20.2) 59.2 (28.7) 0.019 PF 86.3 (16.6) 79.6 (19.9) 0.014 RF 87.4 (22.6) 78.4 (29.1) 0.016 EF 74.0 (25.3) 77.3 (30.8) 0.28 CF 87.4 (19.3) 83.7 (23.0) 0.24 SF 89.2 (22.5) 86.6 (27.5) 0.67 FA 18.9 (20.3) 28.1 (31.3) 0.11 NV 2.4 (8.8) 1.6 (15.4) 0.43 PA 13.1 (24.6) 19.9 (30.9) 0.11 DY 22.1 (25.1) 23.5 (29.3) 0.73 SL 31.7 (32.6) 25.5 (36.9) 0.14 AP 11.6 (23.3) 16.3 (31.5) 0.46 Co 8.0 (19.9) 7.8 (25.5) 0.67 Di 5.7 (17.4) 4.6 (17.7) 0.86 Fi 8.7 (22.5) 8.5 (26.5) 0.75 . No POS (199) . POS (51) . P-value . GHS 69.8 (20.2) 59.2 (28.7) 0.019 PF 86.3 (16.6) 79.6 (19.9) 0.014 RF 87.4 (22.6) 78.4 (29.1) 0.016 EF 74.0 (25.3) 77.3 (30.8) 0.28 CF 87.4 (19.3) 83.7 (23.0) 0.24 SF 89.2 (22.5) 86.6 (27.5) 0.67 FA 18.9 (20.3) 28.1 (31.3) 0.11 NV 2.4 (8.8) 1.6 (15.4) 0.43 PA 13.1 (24.6) 19.9 (30.9) 0.11 DY 22.1 (25.1) 23.5 (29.3) 0.73 SL 31.7 (32.6) 25.5 (36.9) 0.14 AP 11.6 (23.3) 16.3 (31.5) 0.46 Co 8.0 (19.9) 7.8 (25.5) 0.67 Di 5.7 (17.4) 4.6 (17.7) 0.86 Fi 8.7 (22.5) 8.5 (26.5) 0.75 Results are expressed as means and standard deviations. AP: appetite loss; CF: cognitive functioning; Co: constipation; Di: diarrhoea; DY: dyspnoea; EF: emotional functioning; FA: fatigue; Fi: financial impact; GHS: global health scale; NV: nausea and vomiting; PA: pain; PF: physical functioning; POS: prolonged length of stay; RF: role functioning; SF: social functioning; SL: insomnia. Open in new tab General health (GHS) (P = 0.019), physical function (PF) (P = 0.014) and RF (P = 0.016) were significantly worse in patients with prolonged stay (Fig. 1). Three independent stepwise logistic regression analyses were performed by including the different significant QoL scales separately to avoid the problems of multicollinearity. Figure 1: Open in new tabDownload slide Bar chart comparing mean response values to itemized EORTC QoL scales between patients who did not endure POS and those who had a prolonged admission. Asterisks indicate statistical significance. AP: appetite loss; CF: cognitive functioning; Co: constipation; Di: diarrhoea; DY: dyspnoea; EF: emotional functioning; EORTC: European Organization for Research and Treatment of Cancer; FA: fatigue; Fi: financial impact; GHS: global health scale; NV: nausea and vomiting; PA: pain; PF: physical functioning; POS: prolonged length of stay; QoL: quality of life; RF: role functioning; SF: social functioning; SL: insomnia. Figure 1: Open in new tabDownload slide Bar chart comparing mean response values to itemized EORTC QoL scales between patients who did not endure POS and those who had a prolonged admission. Asterisks indicate statistical significance. AP: appetite loss; CF: cognitive functioning; Co: constipation; Di: diarrhoea; DY: dyspnoea; EF: emotional functioning; EORTC: European Organization for Research and Treatment of Cancer; FA: fatigue; Fi: financial impact; GHS: global health scale; NV: nausea and vomiting; PA: pain; PF: physical functioning; POS: prolonged length of stay; QoL: quality of life; RF: role functioning; SF: social functioning; SL: insomnia. All 3 QoL scales were retained in the final models: PF (P = 0.097), RF (P = 0.029) and GHS (P = 0.032). Among the 3 different models, the one with the highest area under curve (AUC) and R-squared resulted in that which includes GHS (AUC 0.762, R-squared 0.14). Other factors resulting independently associated with prolonged stay in all models were age, low FEV1 and DLCO and history of cerebrovascular disease. The GHS, PF and RF lower interquartiles in this population were 58, 80 and 67, respectively. We categorized the patients in 2 groups according to these values: Fifty-nine patients had a low GHS (<58). Eighteen of them (31%) experienced a prolonged stay (vs 33, 17% of those with higher values, P = 0.027), representing 35% of all patients with a prolonged hospital stay. Fifty-eight patients had a low PF (<80). Seventeen of them (29%) experienced a prolonged stay (vs 34, 18% of those with higher values, P = 0.055), representing 33% of all patients with a prolonged hospital stay. Sixty-five patients had a low RF (<67). Twenty of them (31%) experienced a prolonged stay (vs 31, 17% of those with higher values, P =0.016), representing 39% of all patients with a prolonged hospital stay. DISCUSSION Patient-reported outcomes (PROMs) are gaining traction in cardiothoracic surgery in the areas of preoperative planning and postoperative recovery [12–14]. When last documented, approximately half of the European Society of Thoracic Surgeons centres were using QoL data [15]. Not only could the patient perspective data be used to measure the impact on outcome but also to stratify the plan for a patient’s admission, including making a prediction for their LoS, level of care and intensity of therapy needed to aid them in recovery postoperatively [16]. QoL assessed through the EORTC Quality of Life Questionnaire-C30 has also been inserted by the International Consortium for Health Outcomes Measurement in the consensus set of the outcomes most essential to track in patients with lung cancer, along with baseline demographic, clinical and tumour characteristics [17]. In the context of this study In these data, hospital stay extended to ∼1 week for 20% of patients. Those who fell into the prolonged length of stay category did so for myriad reasons, but the significant factors that affected a patient’s overall time spent in hospital were closely linked to each other and could be determined preoperatively. On closer inspection, the trend of low general health (GHS) was matched by low PF. Patients saw their general health be negatively impacted by low physical health and their perceived low PF correlated with lengthier hospital admission. Twenty-nine percent of patients with a PF of <80 endured a prolonged hospital stay compared to only 18% of those with higher PF. While it may seem self-evident that unhealthy patients take longer to get better, it is interesting that this self-assessment deduced a similar result to objective markers of physiological function. The extent of individual QoL-marker impact is noteworthy, as it can be seen that low PF was independently significant of prolonged stay. Similarly, to the objective laboratory measurements of DLCO and low FEV1. RF was also linked to prolonged stay and correlated with the GHS and PF. The acute recovery period was impacted by patient perceived societal role, those who adhered more closely to ‘their role’ were found to have longer hospital admissions. For clarity, RF relates to the expectation of patients according to their age, comorbidity and social standing. RF is an important part of a patient’s life, but its assessment is complicated by the wide definition of roles and by fluctuations in role participation between social and cultural groups [18]. So, it can be noted that in our population, patients who have a lower RF score preoperatively should expect longer hospital stays as a result, and counselling this during preoperative clinic would be prudent. Objective surgical outcome markers that also exhibited independent association with increased hospital stay were DLCO and low FEV1. However, chronic conditions grossly impacting neuromuscular or cardiovascular function—as in the cases of patients with a history of stroke and/or respiratory pathology—should stimulate different postoperative targets in relation to therapy and discharge planning because they were significantly correlated to increased LoS. It seems evident that subjective and objective measures of fitness complement each other and identify an increased risk of postoperative adverse events and prolonged stay. Self-reported perceived functional status is not currently included in functional guidelines to evaluate fitness for lung resection. A growing body of evidence in this field may contribute to refine current risk stratification by adding a patient-reported functional level, which would warrant further objective tests if deemed critically impaired. In the wider context of the literature Poignant research into measuring QoL postoperatively already stands in the literature, including the extent to which it is affected and the factors that can potentiate worse outcomes [19–21]. VATS procedures are better tolerated and have improved recovery with less physical insult [7, 22, 23]. Other research has not identified similar findings in terms of PROMs and the area is still in need of contribution [24]. Despite the minimal surgical insult from VATS, it can be deduced from our study that recovery is impacted by other patient factors. If RF lengthens recovery, the effect of this may narrow the perceived benefit of minimally invasive surgery compared to open. Our results show higher QoL values than the EORTC reference ones for lung cancer. However, comparison may be difficult as more aggressive pathologies other than non-small-cell lung cancer may have been include in that study, potentially affecting the scoring [25]. Our group described the link between QoL and complications postoperatively. Specifically, poor GHS before surgery showed association with complications following surgery. This conclusion can be extrapolated to demonstrate prolonged hospital stay in these patients with low GHS, further contributing to the power that preoperative measures can have on predicting postoperative QoL outcomes [2]. The mortality rate in this research is consistent with similar studies at ∼2%. As well as physical therapies, social and psychological support may also be of benefit in the period of time surrounding oncologic surgery, given the intense psychosocial burden on these patients. Reduced physical and mental health in the postoperative time period has been documented to have an increased mortality risk [26]. Optimizing rehabilitation to account for these factors could improve outcomes in this research field; however, more investigation would be worthwhile. Limitations This evaluation concedes that there are limitations within the research. First, being a service evaluation with audit data, the patients were already planned for operations and the distribution of the research questionnaire opportunistic. Calculating a consent rate for participation was unachievable. Although VATS outcomes are well supported, there was no alternative operation technique to contrast findings against in this research. Without a comparative operation, the benefits of VATS may not be fully appreciable, or may be impacted upon by other patient-specific factors. We decided to assess QoL during the preoperative consultation with the surgeon for logistic reasons: we may not exclude that the evaluation at different time point in the preoperative phase may have resulted in different results. The EORTC questionnaire is well substantiated in its use for cancer research; however, it is a generic cancer questionnaire and for specific cancer subtypes there are further add-on questionnaires to better specify the response data. These were not used for this research and this may call for future datasets to include questionnaire subtypes. There are also many other lines of enquiry or assessment metrics available to assess patient characteristics, and using these could bring differing results to the literature. Future research in this area is suggested and could involve auditing accuracy rates of patient LoS in hospital using predictions made at preoperative surgical clinics. Managing patient expectation by offering these preoperative predictions based on objective surgical markers and QoL metrics could improve patient care and prioritize understanding of their own health. A more stratified postoperative programme of therapy drawn from the preoperative QoL measures and completeness of operation could enhance recovery for different patient groups. Finally, we appreciate that evaluating perioperative changes in QoL in this context would help in understanding the impact of postoperative outcomes on the residual well-being of our patients. This was not a specific end point of this study, which focused on the association of baseline subjective and objective risk factors with postoperative outcome. Future ongoing analyses requiring a larger sample will focus on perioperative QoL evolution. CONCLUSION QoL scales are associated with postoperative LoS after VATS lobectomy for lung cancer. Poor GHS corresponds to prolonged hospital stay and bears correlation to other QoL subscales. QoL data should be evaluated and considered at preoperative counselling appointments to communicate realistic expectations to patients. Appropriate recovery and therapy measures need further investigation but have the potential to improve outcomes postoperatively. Conflict of interest: none declared. Author contributions Cecilia Pompili: Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Supervision; Writing—original draft; Writing—review & editing. Finn McLennan Battleday: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—original draft; Writing—review & editing. Wei Ling Chia: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—review & editing. Nilanjan Chaudhuri: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—review & editing. Emmanuel Kefaloyannis: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—review & editing. Richard Milton: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—review & editing. Kostas Papagiannopoulos: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—review & editing. Peter Tcherveniakov: Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—review & editing. Alessandro Brunelli: Conceptualization; Data curation; Formal analysis; Funding acquisition; Investigation; Methodology; Project administration; Writing—original draft; Writing—review & editing. Reviewer information European Journal of Cardio-Thoracic Surgery thanks Pierre-Emmanuel Falcoz, Nuria M Novoa, Gonzalo Varela and the other, anonymous reviewer(s) for their contribution to the peer review process of this article. Presented at the 27th European Conference on General Thoracic Surgery, Dublin, Ireland, 9–12 June 2019. REFERENCES 1 Lim E , Baldwin D , Beckles M , Duffy J , Entwisle J , Faivre-Finn C et al. Guidelines on the radical management of patients with lung cancer . Thorax 2010 ; 65 : iii1 – 27 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 2 Pompili C , Velikova G , White J , Callister M , Robson J , Dixon S et al. Poor preoperative patient-reported quality of life is associated with complications following pulmonary lobectomy for lung cancer . Eur J Cardiothorac Surg 2017 ; 51 : 526 – 31 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 3 Pompili C , Salati M , Refai M , Berardi R , Onofri A , Mazzanti P et al. Preoperative quality of life predicts survival following pulmonary resection in stage I non-small-cell lung cancer . Eur J Cardiothorac Surg 2013 ; 43 : 905 – 10 . Google Scholar Crossref Search ADS PubMed WorldCat 4 Batchelor TJP , Naidu B , Rasburn NJ , Abdelnour-Berchtold E , Gonzalez M , Brunelli A et al. Guidelines for enhanced recovery after lung surgery: recommendations of the Enhanced Recovery After Surgery (ERAS®) Society and the European Society of Thoracic Surgeons (ESTS) . Eur J Cardiothorac Surg 2019 ; 55 : 91 – 115 . Google Scholar Crossref Search ADS PubMed WorldCat 5 Forster C , Doucet V , Perentes JY , Abdelnour-Berchtold E , Zellweger M , Marcucci C et al. Impact of compliance with components of an ERAS pathway on the outcomes of anatomic VATS pulmonary resections . J Cardiothorac Vasc Anesth 2020 ; 34 : 1858 – 66 . Google Scholar Crossref Search ADS PubMed WorldCat 6 Semenkovich TR , Hudson JL , Subramanian M , Kozower BD. Enhanced recovery after surgery (ERAS) in thoracic surgery . Semin Thorac Cardiovasc Surg 2018 ; 30 : 342 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat 7 Falcoz PE , Puyraveau M , Thomas PA , Decaluwe H , Hurtgen M , Petersen RH et al. Video-assisted thoracoscopic surgery versus open lobectomy for primary non-small-cell lung cancer: a propensity-matched analysis of outcome from the European Society of Thoracic Surgeon database . Eur J Cardiothorac Surg 2016 ; 49 : 602 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat 8 Cao C , Manganas C , Ang SC , Peeceeyen S , Yan TD. Video-assisted thoracic surgery versus open thoracotomy for non-small cell lung cancer: a meta-analysis of propensity score-matched patients . Interact CardioVasc Thorac Surg 2013 ; 16 : 244 – 9 . Google Scholar Crossref Search ADS PubMed WorldCat 9 Aaronson NK , Ahmedzai S , Bergman B , Bullinger M , Cull A , Duez NJ et al. The European Organization for research and treatment of cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology . J Natl Cancer Inst 1993 ; 85 : 365 – 76 . Google Scholar Crossref Search ADS PubMed WorldCat 10 Apolone G , Filiberti A , Cifani S , Ruggiata R , Mosconi P. Evaluation of the EORTC QLQ-C30 questionnaire: a comparison with SF-36 Health Survey in a cohort of Italian long-survival cancer patients . Ann Oncol 1998 ; 9 : 549 – 57 . Google Scholar Crossref Search ADS PubMed WorldCat 11 Fernandez FG , Falcoz PE , Kozower BD , Salati M , Wright CD , Brunelli A. The Society of Thoracic Surgeons and the European Society of Thoracic Surgeons general thoracic surgery databases: joint standardization of variable definitions and terminology . Ann Thorac Surg 2015 ; 99 : 368 – 76 . Google Scholar Crossref Search ADS PubMed WorldCat 12 Basch E , Abernethy AP , Mullins CD , Reeve BB , Smith ML , Coons SJ et al. Recommendations for incorporating patient-reported outcomes into clinical comparative effectiveness research in adult oncology . J Clin Oncol 2012 ; 30 : 4249 – 55 . Google Scholar Crossref Search ADS PubMed WorldCat 13 Handy JJR , Asaph JW , Douville EC , Ott GY , Grunkemeier GL , Wu Y. Does video-assisted thoracoscopic lobectomy for lung cancer provide improved functional outcomes compared with open lobectomy? Eur J Cardiothorac Surg 2009 ; 37 : 451 – 5 . Google Scholar PubMed OpenURL Placeholder Text WorldCat 14 Pompili C , Koller M , Velikova G , Franks K , Absolom K , Callister M et al. EORTC QLQ-C30 summary score reliably detects changes in QoL three months after anatomic lung resection for non-small cell lung cancer (NSCLC) . Lung Cancer 2018 ; 123 : 149 – 54 . Google Scholar Crossref Search ADS PubMed WorldCat 15 Pompili C , Novoa N , Balduyck B. Clinical evaluation of quality of life: a survey among members of European Society of Thoracic Surgeons (ESTS) . Interact CardioVasc Thorac Surg 2015 ; 21 : 415 – 19 . Google Scholar Crossref Search ADS PubMed WorldCat 16 Brunelli A , Salati M , Refai M , Xiume F , Berardi R , Mazzanti P et al. Development of a patient-centered aggregate score to predict survival after lung resection for non-small cell lung cancer . J Thorac Cardiovasc Surg 2013 ; 146 : 385 – 90.e1-2 . Google Scholar Crossref Search ADS PubMed WorldCat 17 Mak KS , van Bommel AC , Stowell C , Abrahm JL , Baker M , Baldotto CS et al. Defining a standard set of patient-centred outcomes for lung cancer . Eur Respir J 2016 ; 48 : 852 – 60 . Google Scholar Crossref Search ADS PubMed WorldCat 18 Anatchkova MD , Bjorner JB. Health and role functioning: the use of focus groups in the development of an item bank. Quality of life research: an international journal of quality of life aspects of treatment . Qual Life Res 2010 ; 19 : 111 – 23 . Google Scholar Crossref Search ADS PubMed WorldCat 19 Fernando HC , Landreneau RJ , Mandrekar SJ , Nichols FC , DiPetrillo TA , Meyers BF et al. Analysis of longitudinal quality-of-life data in high-risk operable patients with lung cancer: results from the ACOSOG Z4032 (Alliance) multicenter randomized trial . J Thorac Cardiovasc Surg 2015 ; 149 : 718 – 26 . Google Scholar Crossref Search ADS PubMed WorldCat 20 Ferguson MK , Parma CM , Celauro AD , Vigneswaran WT. Quality of life and mood in older patients after major lung resection . Ann Thorac Surg 2009 ; 87 : 1007 – 12; discussion 12 – 13 . Google Scholar Crossref Search ADS PubMed WorldCat 21 Pompili C , Brunelli A , Xiume F , Refai M , Salati M , Sabbatini A. Predictors of postoperative decline in quality of life after major lung resections . Eur J Cardiothorac Surg 2011 ; 39 : 732 – 7 . Google Scholar Crossref Search ADS PubMed WorldCat 22 Sandri A , Papagiannopoulos K , Milton R , Chaudhuri N , Kefaloyannis E , Pompili C et al. High-risk patients and postoperative complications following video-assisted thoracic surgery lobectomy: a case-matched comparison with lower-risk counterparts . Interact CardioVasc Thorac Surg 2015 ; 21 : S41 – 5 . Google Scholar Crossref Search ADS WorldCat 23 Bendixen M , Jørgensen OD , Kronborg C , Andersen C , Licht PB. Postoperative pain and quality of life after lobectomy via video-assisted thoracoscopic surgery or anterolateral thoracotomy for early stage lung cancer: a randomised controlled trial . Lancet Oncol 2016 ; 17 : 836 – 44 . Google Scholar Crossref Search ADS PubMed WorldCat 24 Rizk NP , Ghanie A , Hsu M , Bains MS , Downey RJ , Sarkaria IS et al. A prospective trial comparing pain and quality of life measures after anatomic lung resection using thoracoscopy or thoracotomy . Ann Thorac Surg 2014 ; 98 : 1160 – 6 . Google Scholar Crossref Search ADS PubMed WorldCat 25 Scott NW , Fayers PM , Aaronson NK , Bottomley A , de Graeff A , Groenvold M et al. EORTC QLQ-C30 Reference Values Manual , 2nd edn. EORTC Quality of Life Group : Brussels , 2008 . Google Scholar Google Preview OpenURL Placeholder Text WorldCat COPAC 26 Möller A , Sartipy U. Predictors of postoperative quality of life after surgery for lung cancer . J Thorac Oncol 2012 ; 7 : 406 – 11 . Google Scholar Crossref Search ADS PubMed WorldCat Abbreviations DLCO Carbon monoxide lung diffusion capacity EORTC European Organization for Research and Treatment of Cancer FEV1 Force expiratory volume in 1 s GHS Global health score LoS Length of stay PF Physical function QoL Quality of life RF Role functioning VATS Video-assisted thoracoscopic surgery © The Author(s) 2020. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)
TI - Poor preoperative quality of life predicts prolonged hospital stay after VATS lobectomy for lung cancer
JF - European Journal of Cardio-Thoracic Surgery
DO - 10.1093/ejcts/ezaa245
DA - 2021-01-04
UR - https://www.deepdyve.com/lp/oxford-university-press/poor-preoperative-quality-of-life-predicts-prolonged-hospital-stay-KQQ2KZTY43
SP - 116
EP - 121
VL - 59
IS - 1
DP - DeepDyve
ER -