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Aims Over the last decades, Health-related Quality of Life (HRQoL) end-points have become an important outcome of the randomised controlled trials (RCTs). HRQoL methodology in RCTs has improved following international consensus recommendations. However, no international recommendations exist concerning the statistical analysis of such data. The aim of our study was to identify and characterise the quality of the statistical methods commonly used for analysing HRQoL data in cancer RCTs. Methods Building on our recently published systematic review, we analysed a total of 33 published RCTs studying the HRQoL methods reported in RCTs since 1991. We focussed on the ability of the methods to deal with the three major problems commonly encountered when analysing HRQoL data: their multidimensional and longitudinal structure and the commonly high rate of missing data. Results All studies reported HRQoL being assessed repeatedly over time for a period ranging from 2 to 36 months. Missing data were common, with compliance rates ranging from 45% to 90%. From the 33 studies considered, 12 different statistical methods were identified. Twenty-nine studies analysed each of the questionnaire sub-dimensions without type I error adjustment. Thirteen studies repeated the HRQoL analysis at each assessment time again without type I error adjustment. Only 8 studies used methods suitable for repeated measurements. Conclusion Our findings show a lack of consistency in statistical methods for analysing HRQoL data. Problems related to multiple comparisons were rarely considered leading to a high risk of false positive results. It is therefore critical that international recommendations for improving such statistical practices are developed.

Purpose Clinical trials in glioma patients with neurocognitive deficits face challenges due to lacking or unreliable patient self-reports on their health-related quality of life (HRQOL). Patient–proxy data could help solve this issue. We determined whether patient–proxy concordance levels were affected by patients’ neurocognitive functioning. Methods Patient and patient-by-proxy HRQOL ratings were assessed via SF-36 and EORTC QLQ-BN20, respectively, in 246 patients. Data on neurocognitive functioning were collected on a subgroup of 195 patients. Patient–proxy agreement was measured using the Bland–Altman limit of agreement, the mean difference, the concordance correlation coefficient (CCC), and the percentage difference (PD, ±0, 5, or 10 points). We defined patients to be cognitively impaired (n = 66) or cognitively intact (n = 129) based on their neurocognitive performance. Results Patients rated their physical function and general health to be better than their proxies did, while at the same time, patients reported more visual disorders, communication deficits, itchy skin, and problems with bladder control. The cognitively impaired subgroup reported poorer physical functioning, more visual disorders, headaches, itchy skin, and issues with bladder control. In the cognitively intact group, no statistical significant differences were observed between patients and proxies. Not surprisingly, Bland–Altman plots revealed a high agreement between the patient and patient-by-proxy rating in all HRQOL domains ranging from 95 to 99 %. The CCC was fairly high in all HRQOL domains (0.37–0.80), and the percentage of perfect agreement (PD ± 0) ranged from 8.5 to 76.8 %. In the cognitively impaired patients, the mean difference between patients and proxies was overall larger, and accordingly, agreement based on Bland–Altman plots was lower. Conclusions The level of agreement between patient and patient-by-proxy ratings of low-grade glioma patients’ HRQOL is generally high. However, patient–proxy agreement is lower in patients with neurocognitive deficits than in patients without neurocognitive deficits. Electronic supplementary material The online version of this article (doi:10.1007/s11136-016-1426-z) contains supplementary material, which is available to authorized users.

In cancer research, outcome measures may co-vary. Treatment and treatment related impairment of health-related quality of life (HRQoL) may affect survival. When these effects are analyzed separately, bias may arise. Therefore, we investigated the combined effect of treatment and longitudinally measured HRQoL on survival. Patients with anaplastic oligodendrogliomas (n = 288) who were randomized (EORTC 26951) to radiotherapy (RT) alone or RT plus procarbazine, lomustine, and vincristine (PCV) chemotherapy were analyzed. HRQoL [appetite loss (AP)] was assessed with the EORTC QLQ-C30. We compared survival results from different analysis strategies: Cox model with treatment only [model 1 (M1)] or with treatment and time-dependent AP score [model 2 (M2)] and the joint model combining longitudinal AP score and survival [model 3 (M3)]. The estimated hazard ratio (HR) for RT plus PCV was 0.76 (95 % CI 0.58-1.00) for M1, 0.72 (0.55-0.96) for M2, and 0.69 (0.52-0.92) for M3. This corresponds to a lower risk of death of 24 % in M1, 28 % in M2, and 31 % in M3, for patients treated with RT plus PCV chemotherapy. AP resulted in an increased risk of death, with estimated HR of 1.06 (1.01-1.12) for M2 and 1.13 (1.03-1.23) for M3: Every 10-point increase of AP resulted in a 13 % increased risk of death in M3 as compared to 6 % in M2. Part of the survival benefit of treatment with RT plus PCV chemotherapy can be masked by the negative effect that this treatment has on patients' HRQoL. In our study, up to 7 % of the theoretical treatment efficacy was lost when AP was not adjusted through joint modeling.

BACKGROUND The objective of this study was to examine the prognostic value of baseline health-related quality of life (HRQOL) for survival with regard to different cancer sites using 1 standardized and validated patient self-assessment tool. METHODS In total, 11 different cancer sites pooled from 30 European Organization for Research and Treatment of Cancer (EORTC) randomized controlled trials were selected for this study. For each cancer site, univariate and multivariate Cox proportional hazards modeling was used to assess the prognostic value (P

BACKGROUND We examined if cancer patients' health-related quality of life (HRQoL) scores on the European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 are affected by the specific time point, before or during treatment, at which the questionnaire is completed, and whether this could bias the overall treatment comparison analyses. PATIENTS AND METHODS A 'completion-time window' variable was created on three closed EORTC randomised control trials in lung (non-small cell lung cancer, NSCLC) and colorectal cancer (CRC) to indicate when the QLQ-30 was completed relative to chemotherapy cycle dates, defined as 'before', 'on' and 'after'. HRQoL mean scores were calculated using a linear mixed model. RESULTS Statistically significant differences (P

Background: Little is known about whether changes in health-related quality of life (HRQoL) scores from baseline during treatment also predict survival, which we aim to investigate in this study. Methods: We analysed data from 391 advanced non-small-cell lung cancer (NSCLC) patients enrolled in the EORTC 08975 study, which compared palliative chemotherapy regimens. HRQoL was assessed at baseline and after each chemotherapy cycle using the EORTC QLQ-C30 and QLQ-LC13. The prognostic significance of HRQoL scores at baseline and their changes over time was assessed with Cox regression, after adjusting for clinical and socio-demographic variables. Results: After controlling for covariates, every 10-point increase in baseline pain and dysphagia was associated with 11% and 12% increased risk of death with hazard ratios (HRs) of 1.11 and 1.12, respectively. Every 10-point improvement of physical function at baseline (HR=0.93) was associated with 7% lower risk of death. Every 10-point increase in pain (HR=1.08) was associated with 8% increased risk of death at cycle 1. Every 10-point increase in social function (HR=0.91) at cycle 2 was associated with 9% lower risk of death. Conclusions: Our findings suggest that changes in HRQoL scores from baseline during treatment, as measured on subscales of the EORTC QLQ-C30 and QLQ-LC13, are significant prognostic factors for survival.

Small-cell lung cancer represents about 15% of all lung cancers; increasingly, randomised controlled trials of this disease measure the health-related quality of life of patients. In this Systematic Review we assess the adequacy of reporting of health-related quality-of-life methods in randomised controlled trials of small-cell lung cancer, and the potential effect of this reporting on clinical decision making. Although overall reporting of health-related quality of life was acceptable, improvements are needed to optimise the use of health-related quality of life in randomised controlled trials.

The objective of this study was to examine the prognostic value of baseline health-related quality of life (HRQOL) for survival with regard to different cancer sites using 1 standardized and validated patient self-assessment tool.In total, 11 different cancer sites pooled from 30 European Organization for Research and Treatment of Cancer (EORTC) randomized controlled trials were selected for this study. For each cancer site, univariate and multivariate Cox proportional hazards modeling was used to assess the prognostic value (P .05) of 15 HRQOL parameters using the EORTC Core Quality of Life Questionnaire (QLQ-C30). Models were adjusted for age, sex, and World Health Organization performance status and were stratified by distant metastasis.In total, 7417 patients completed the EORTC QLQ-C30 before randomization. In brain cancer, cognitive functioning was predictive for survival; in breast cancer, physical functioning, emotional functioning, global health status, and nausea and vomiting were predictive for survival; in colorectal cancer, physical functioning, nausea and vomiting, pain, and appetite loss were predictive for survival; in esophageal cancer, physical functioning and social functioning were predictive for survival; in head and neck cancer, emotional functioning, nausea and vomiting, and dyspnea were predictive for survival; in lung cancer, physical functioning and pain were predictive for survival; in melanoma, physical functioning was predictive for survival; in ovarian cancer, nausea and vomiting were predictive for survival; in pancreatic cancer, global health status was predictive for survival; in prostate cancer, role functioning and appetite loss were predictive for survival; and, in testis cancer, role functioning was predictive for survival.The current results demonstrated that, for each cancer site, at least 1 HRQOL domain provided prognostic information that was additive over and above clinical and sociodemographic variables.

10058Background: Over the last decades Quality of Life (QoL) endpoints have become an important outcome of the randomized controlled trials (RCTs). QoL methodology in RCTs has improved following in...

9570 Background: Health-related quality of life (HRQOL) has been an important part of the randomised controlled trials (RCTs) conducted by EORTC since 1980. This review aims to provide an update on...

2034 Background: In cancer clinical trials, several outcome measures may co-vary. Both treatment itself and treatment-related impairment of health-related quality of life (HRQoL) may affect surviva...

© Touch MEdical MEdia 2013 Abstract What is quality of life? clinical trials have long been dominated by clinically based endpoints, but research has proved that health-related quality of life (hRQol) can only be captured accurately by patients themselves using patient reported outcomes (PRos). The united States Food and drug administration defines PRos as the measurement of any aspect of a patient’s health status that comes directly from the patient, that is, a measurement taken without interpretation of the patient’s responses by a physician or anyone else. The EoRTc QlQ-c30 is the most widely cancer specific hRQol questionnaire used for PRos in the world. developed in 1991 by the EoRTc Quality of life Group, it has been translated into more than 60 languages and has over 40 developed or under development cancer specific modules. one of the key challenges faced is pooling data and performing meta-analyses of the results of closed trials. The EoRTc Patient Reported outcomes and Behavioural Evidence (PRoBE) team is dedicated to the meta-analysis of EoRTc randomised clinical trial quality of life results. during the last five years, pooled data have revealed important results, such as prognostic indicators of survival, which have informed clinical practice. This research shows how the patient perspective in palliative and curative EoRTc trials has been considered of major importance. The inclusion of patient perspective in drug development shows that a more comprehensive hRQol assessment has taken place over time as better instruments have become available. as clinicians, regulatory bodies and industry acknowledge the value of the patient perspective, we expect that EoRTc will continue including hRQol endpoints where appropriate.

7607 Background: Over 60 cancer clinical trials have shown that baseline health-related quality of life (HRQoL) scores are prognostic for patient survival. Few studies have investigated the added value of change in HRQoL scores. Our aim was to investigate if change in HRQoL scores from baseline over time is also associated with survival. Methods: We analyzed data from an EORTC 3-arm randomized clinical trial (RCT) in advanced non-small-cell lung cancer (NSCLC) patients, comparing gemcitabine+cisplatin, versus paclitaxel+gemcitabine, versus standard arm paclitaxel+cisplatin. HRQoL was measured in 394 patients using the EORTC QLQ-C30 at baseline and after each chemotherapy cycle. The prognostic significance of sex, age and WHO performance status (0-1 vs. 2) and the 15 QLQ-C30 subscales were assessed with Cox proportional hazard models stratified for treatment (level of significance 0.05). Changes in HRQoL scores from baseline to each chemotherapy cycle assessment were categorized as “improved”, “stable” and “worsened” using a threshold of 10 points difference. Due to expected attrition, the analysis was limited to changes from baseline up to cycle 3. Results: There were 248 patients in cycle 1, 212 in cycle 2 and 196 in cycle 3. We performed analyses separately using data at cycle 1, cycle 2, and cycle 3. In all analyses, HRQoL in various subscales and socio-demographic and clinical variables (physical functioning (hazard ratio [HR] 0.91, 95% CI 0.85-0.98; p=0.0103), pain (1.11, 1.05-1.17; p= 0.0004), age (0.98, 0.97-1.00, p=0.0413) and WHO performance status (1.77, 1.09-2.89; p=0.0218) at cycle 1; pain (1.11, 1.03-1.20; p=0.0016), age (0.98, 0.96-1.00; p=0.0217) and sex (0.63, 0.42-0.95; p=0.0081) at cycle 2; and role functioning (0.93, 0.88-1.00; p=0.0128) and age (0.98, 0.96-1.00; p=0.0081) at cycle 3) predicted survival; however, change in HRQoL was only an independent predictor for improvement at cycle 1. Conclusions: Our findings suggest that change from baseline over time in HRQoL, as measured on subscales of the EORTC QLQ-C30, contains added prognostic value for survival independent of baseline HRQoL scores. Further work is needed to assess the robustness and sensitivity of these findings.

6090 Background: Over the last three decades health-related quality of life (HRQOL) has become an important part of the randomised controlled trials (RCTs) conducted by the European Organisation for Research and Treatment of Cancer (EORTC). This review aims to undertake a descriptive database evaluation of all the HRQOL studies conducted in EORTC since 1980. Methods: The EORTC protocol database (n=785) was reviewed, restricting the search to between 1980 and 2011 (n=735). We investigated the number of HRQOL studies conducted in EORTC trials, the RCTs’ status and the use of HRQOL tools since 1980. Results: 157 protocols with HRQOL assessment were identified involving 70,903 patients. 73 studies ended as defined in the protocol; 27 studies closed early due to poor accrual; 17 are at the final analysis of the primary end point stage; 14 studies are still open to recruitment; 11 are closed to patient entry; and 15 new RCTs are pending activation with HRQOL. The majority of phase III (n=135) and phase II/III (n=9) RCTs have HRQOL as secondary endpoint. EORTC also conducted a number of large scale field studies (n=11), where HRQOL was the primary endpoint. During the early period of 1980 to 1989 HRQOL was assessed in 12 EORTC RCTs by using a small number of HRQOL items, but from 1990 to 2000, HRQOL was assessed in 97 RCTs using more comprehensive HRQOL tools. Between 2001 and 2011 the number of RCTs with HRQOL was 48. The EORTC clinical groups with the most RCTs containing HRQOL were Radiation Oncology (n=22), Genito-Urinary (n=20), Gynaecological (n=16), Breast Cancer (n=16), Lung (n=13), Gastrointestinal, (n=13) and Brain (n=10). The EORTC HRQOL tools were used in 90% of the trials, with other validated tools being used when required. Conclusions: Our review of EORTC RCTs has shown how patient perspective has been constantly considered of major importance in oncology during the last three decades. The inclusion of patient perspective in drug development shows that a more comprehensive HRQOL assessment has taken place over time as better instruments have become available. As the positive value of patient perspective grows to clinicians, regulatory bodies and industry, we expect that EORTC will continue its support by including HRQOL endpoints where appropriate.

6002 Background: The prognostic value for survival of HRQOL data derived from self-report questionnaires, has been well documented in cancer research. The objective of this study was to examine the prognostic value of HRQOL parameters for different cancer sites using one standardized and validated patient self-assessment tool. Methods: A total of 11 different cancer sites, pooled from 30 European Organisation for Research and Treatment of Cancer (EORTC) Randomized Controlled Trials (RCTs), were selected for this study. For each cancer site, univariate and multivariate Cox proportional hazard modeling was used to assess the prognostic value (p