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Introduction: The European Organisation for Research and Treatment of Cancer Quality of Life Core Questionnaire (EORTC QLQ-C30) measures 15 health-related quality of life (HRQoL) scales relevant to the disease and treatment of patients with cancer. A study by Martinelli (2011) demonstrated that these scales could be grouped into three main clusters: physical, psychological and gastrointestinal. This study aims to validate Martinelli's findings in an independent dataset and evaluate whether these clusters are consistent across cancer types and patient characteristics. Methods: Pre-defined criteria for successful validation were three main clusters should emerge with a minimum R-squared value of 0.51 using pooled baseline-data. A cluster analysis was performed on the 15 QLQ-C30 HRQoL-scales in the overall dataset, as well as by cancer type and selected patient characteristics to examine the robustness of the results. Results: The dataset consisted of 20,066 patients pooled across 17 cancer types. Overall, three main clusters were identified (R-2 = 0.61); physical-cluster included role-functioning, physical functioning, social-functioning, fatigue, pain, and global-health status; psychological-cluster included emotional-functioning, cognitive-functioning, and insomnia; gastro-intestinal-cluster included nausea/vomiting and appetite loss. The results were consistent across different levels of disease severity, socio-demographic and clinical characteristics with minor variations by cancer type. Global-health status was found to be strongly linked to the scales included in the physical-functioning-related cluster. Conclusion: This study successfully validated prior findings by Martinelli (2011): the QLQC30 scales are interrelated and can be grouped into three main clusters. Knowing how these multidimensional HRQoL scales are related to each other can help clinicians and patients with cancer in managing symptom burden, guide policymakers in defining social-support plans and inform selection of HRQoL scales in future clinical trials. (C)2022 Elsevier Ltd. All rights reserved.

Background Maintenance of functioning and well-being during the progression-free survival (PFS) period is important for glioma patients. This study aimed to determine whether health-related quality of life (HRQoL) can be maintained during progression-free time, and factors associated with HRQoL deterioration in this period. Methods We included longitudinal HRQoL data from previously published clinical trials in glioma. The percentage of patients with stable HRQoL until progression was determined per scale and at the individual patient level (i.e. considering all scales simultaneously). We assessed time to a clinically relevant deterioration in HRQoL, expressed in deterioration-free survival and time-to-deterioration (the first including progression as an event). We also determined the association between sociodemographic and clinical factors and HRQoL deterioration in the progression-free period. Results Five thousand five hundred and thirty-nine patients with at least baseline HRQoL scores had a median time from randomization to progression of 7.6 months. Between 9–29% of the patients deteriorated before disease progression on the evaluated HRQoL scales. When considering all scales simultaneously, 47% of patients deteriorated on ≥1 scale. Median deterioration-free survival period ranged between 3.8–5.4 months, and median time-to-deterioration between 8.2–11.9 months. For most scales, only poor performance status was independently associated with clinically relevant HRQoL deterioration in the progression-free period. Conclusions HRQoL was maintained in only 53% of patients in their progression-free period, and treatment was not independently associated with this deterioration in HRQoL. Routine monitoring of the patients’ functioning and well-being during the entire disease course is therefore important, so that interventions can be initiated when problems are signaled.

Objectives: To provide reference values for the European Organisation for Treatment and Research of Cancer (EORTC) Quality of Life Questionnaire (QLQ-C30) in advanced-stage Hodgkin lymphoma (HL) patients and 5-year HL survivors. The QLQ-C30 is the most widely used cancer-specific questionnaire to assess Health-Related Quality of Life (HRQoL).Methods: The EORTC database was searched to identify HL RCTs in which patients’ and survivors’ HRQoL was assessed by the QLQ-C30. HRQoL mean scores were calculated and stratified by age and gender. Minimal important differences were used to assess the clinical relevance of the findings. Data from one RCT with HRQoL scores available at baseline (n = 343) and four RCTs with HRQoL scores available at follow-up (n = 1665) were analyzed.Results: Patients reported worse HRQoL scores than survivors across most functioning scales and symptoms’ scales. These scores varied as a function of gender but not age. Survivors’ HRQoL reports were comparable to the ones of the generalpopulation.Conclusions: These values provide an assessment framework for the comparison and interpretation of QLQ-C30 scores in advanced-stage HL. Our findings suggest that although HL patients’ HRQoL scores are worse than the general population, HRQoL scores may normalize over long-term survival

Background: The European Organisation for Research and Treatment of Cancer (EORTC) 1325-MG/KEYNOTE-054 trial in patients with resected, high-risk stage III melanoma demonstrated improved recurrence-free survival with adjuvant pembrolizumab compared with placebo (hazard ratio 0·57 [98·4% CI 0·43-0·74]; pMethods: This double-blind, randomised, controlled, phase 3 trial was done at 123 academic centres and community hospitals across 23 countries. Patients aged 18 years or older with previously untreated histologically confirmed stage IIIA, IIIB, or IIIC resected cutaneous melanoma, and an Eastern Cooperative Oncology Group performance status score of 1 or 0 were eligible. Patients were randomly assigned (1:1) using a central interactive voice-response system on the basis of a minimisation technique stratified for stage and geographic region to receive intravenously 200 mg pembrolizumab or placebo. Treatment was administered every 3 weeks for 1 year, or until disease recurrence, unacceptable toxicity, or death. The primary endpoint of the trial was recurrence-free survival (reported elsewhere). HRQOL was a prespecified exploratory endpoint, with global health/quality of life (GHQ) over 2 years measured by the EORTC QLQ-C30 as the primary analysis. Analyses were done in the intention-to-treat population. This study is registered with ClinicalTrials.gov, NCT02362594, and EudraCT, 2014-004944-37, and long-term follow-up is ongoing.Findings: Between Aug 26, 2015, and Nov 14, 2016, 1019 patients were assigned to pembrolizumab (n=514) or placebo (n=505). Median follow-up was 15·1 months (IQR 12·8-16·9) at the time of this analysis. HRQOL compliance was greater than 90% at baseline, greater than 70% during the first year, and greater than 60% thereafter for both groups. Because of low absolute compliance numbers at later follow-up, the analysis was truncated to week 84. Baseline GHQ scores were similar between groups (77·55 [SD 18·20] in the pembrolizumab group and 76·54 [17·81] in the placebo group) and remained stable over time. The difference in average GHQ score between the two groups over the 2 years was -2·2 points (95% CI -4·3 to -0·2). The difference in average score during treatment was -1·1 points (95% CI -3·2 to 0·9) and the difference in average score after treatment was -2·2 points (-4·8 to 0·4). These differences are within the 5-point clinical relevance threshold for the QLQ-C30 and are therefore clinically non-significant.Interpretation: Pembrolizumab does not result in a clinically significant decrease in HRQOL compared with placebo when given as adjuvant therapy for patients with resected, high-risk stage III melanoma. These results support the use of adjuvant pembrolizumab in this setting. placebo when given as adjuvant therapy for patients with resected, high-risk stage III melanoma. These results support the use of adjuvant pembrolizumab in this setting. placebo when given as adjuvant therapy for patients with resected, high-risk stage III melanoma. These results support the use of adjuvant pembrolizumab in this setting.

Background Different analytical methods may lead to different conclusions about the impact of treatment on health-related quality of life (HRQoL). This study aimed to examine 3 different methods to evaluate change in HRQoL and to study whether these methods result in different conclusions. Methods HRQoL data from 15 randomized clinical trials were combined (CODAGLIO project). Change in HRQoL scores, measured with the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 and BN20 questionnaires, was analyzed in 3 ways: (1) at the group level, comparing mean changes in scale/item scores between treatment arms, (2) at the patient level per scale/item, calculating the percentage of patients that deteriorated, improved, or remained stable per scale/item, and (3) at the individual patient level, combining all scales/items. Results Baseline and first follow-up HRQoL data were available for 3727 patients. At the group scale/item level, only the item “hair loss” showed a significant and clinically relevant change (ie, ≥10 points) over time, whereas change scores on the other scales/items were statistically significant only (all P Conclusions Different analytical methods of changes in HRQoL result in distinct conclusions of treatment effects, all of which may be relevant for informing clinical decision making.

Patient-reported outcomes (PROs), such as symptoms, function, and other health-related quality-of-life aspects, are increasingly evaluated in cancer randomised controlled trials (RCTs) to provide information about treatment risks, benefits, and tolerability. However, expert opinion and critical review of the literature showed no consensus on optimal methods of PRO analysis in cancer RCTs, hindering interpretation of results. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data Consortium was formed to establish PRO analysis recommendations. Four issues were prioritised: developing a taxonomy of research objectives that can be matched with appropriate statistical methods, identifying appropriate statistical methods for PRO analysis, standardising statistical terminology related to missing data, and determining appropriate ways to manage missing data. This Policy Review presents recommendations for PRO analysis developed through critical literature reviews and a structured collaborative process with diverse international stakeholders, which provides a foundation for endorsement; ongoing developments of these recommendations are also discussed.

The 5th EORTC Quality of Life in Cancer Clinical Trials Conference presented the current state of quality of life and other patient-reported outcomes (PROs) research from the perspectives of researchers, regulators, industry representatives, patients and patient advocates and health care professionals. A major theme was the assessment of the burden of cancer treatments, and this was discussed in terms of regulatory challenges in using PRO assessments in clinical trials, patients’ experiences in cancer clinical trials, innovative methods and standardisation in cancer research, innovative methods across the disease sites or populations and cancer survivorship. Conferees demonstrated that PROs are becoming more accepted and major efforts are ongoing internationally to standardise PROs measurement, analysis and reporting in trials. Regulators are keen to collaborate with all stakeholders to ensure that the right questions are asked and the right answers are communicated. Improved technology and increased flexibility of measurement instruments are making PROs data more robust. Patients are being encouraged to be patient partners. International collaborations are essential, because this work cannot be accomplished on a national level. Previous article in issue

Background There is currently a lack of consensus on how health-related quality of life and other patient-reported outcome measures in cancer randomized clinical trials are analyzed and interpreted. This makes it difficult to compare results across randomized controlled trials (RCTs) synthesize scientific research, and use that evidence to inform product labeling, clinical guidelines, and health policy. The Setting International Standards in Analyzing Patient-Reported Outcomes and Quality of Life Endpoints Data for Cancer Clinical Trials (SISAQOL) Consortium aims to develop guidelines and recommendations to standardize analyses of patient-reported outcome data in cancer RCTs. Methods and Results Members from the SISAQOL Consortium met in January 2017 to discuss relevant issues. Data from systematic reviews of the current state of published research in patient-reported outcomes in cancer RCTs indicated a lack of clear reporting of research hypothesis and analytic strategies, and inconsistency in definitions of terms, including “missing data,”“health-related quality of life,” and “patient-reported outcome.” Based on the meeting proceedings, the Consortium will focus on three key priorities in the coming year: developing a taxonomy of research objectives, identifying appropriate statistical methods to analyze patient-reported outcome data, and determining best practices to evaluate and deal with missing data. Conclusion The quality of the Consortium guidelines and recommendations are informed and enhanced by the broad Consortium membership which includes regulators, patients, clinicians, and academics.

Background Cancer incidence increases exponentially with advancing age, cancer patients live longer than in the past, and many new treatments focus on stabilizing disease and HRQOL. The objective of this study is to examine how cancer affects patients' HRQOL and whether their HRQOL is age-dependent. Methods Data from 25 EORTC randomized controlled trials was pooled. EORTC QLQ-C30 mean scores for the cancer cohort and five general population cohorts were compared to assess the impact of cancer on patients' HRQOL. Within the cancer cohort, multiple linear regressions (two-sided level P-value = 0.05 adjusted for multiple testing.) were used to investigate the association between age and HRQOL, adjusted for gender, WHO performance status (PS), distant metastasis and stratified by cancer site. A difference of 10 points on the 0–100 scale was considered clinically important. Results Cancer patients generally have worse HRQOL compared to the general population, but the specific HRQOL domains impaired vary with age. When comparing the cancer versus the general population, young cancer patients had worse financial problems, social and role functioning, while the older cancer groups had more appetite loss. Within the cancer cohort, HRQOL was worse with increasing age for physical functioning and constipation, and better with increasing age for social functioning, insomnia and financial problems (all p Conclusion HRQOL is impaired in cancer patients compared to the general population, but the impact on specific HRQOL domains varies by age. Within the cancer population, some HRQOL components improve with age while others deteriorate. Optimal care for older cancer patients should target HRQOL domains most relevant to this population.

Although patient-reported outcomes (PROs), such as health-related quality of life, are important endpoints in randomised controlled trials (RCTs), there is little consensus about the analysis, interpretation, and reporting of these data. We did a systematic review to assess the variability, quality, and standards of PRO data analyses in advanced breast cancer RCTs. We searched PubMed for English language articles published in peer-reviewed journals between Jan 1, 2001, and Oct 30, 2017. Eligible articles were those that reported PRO results from RCTs of adult patients with advanced breast cancer receiving anti-cancer treatments with reported sample sizes of at least 50 patients—66 RCTs met the selection criteria. Only eight (12%) RCTs reported a specific PRO research hypothesis. Heterogeneity in the statistical methods used to assess PRO data was observed, with a mixture of longitudinal and cross-sectional techniques. Not all articles addressed the problem of multiple testing. Fewer than half of RCTs (28 [42%]) reported the clinical significance of their findings. 48 (73%) did not report how missing data were handled. Our systematic review shows a need to improve standards in the analysis, interpretation, and reporting of PRO data in cancer RCTs. Lack of standardisation makes it difficult to draw robust conclusions and compare findings across trials. The Setting International Standards in the Analyzing Patient-Reported Outcomes and Quality of Life Data Consortium was set up to address this need and develop recommendations on the analysis of PRO data in RCTs.

BACKGROUND: The aims of this study were to externally validate an established association between baseline health-related quality of life (HRQOL) scores and survival and to assess the added prognostic value of HRQOL with respect to demographic and clinical indicators. METHODS: Pooled data were analyzed from 17 randomized controlled trials opened by the Canadian Cancer Trials Group between 1991 and 2004; they included survival and baseline HRQOL data from 3606 patients with 8 different cancer sites. The models included sex, age (≤60 vs >60 years), World Health Organization performance status (0 or 1 vs 2-4), distant metastases (no vs yes), and 15 European Organization for Research and Treatment of Cancer (EORTC) Core Quality-of-Life Questionnaire (QLQ-C30) scales. Analyses were conducted with multivariate Cox proportional hazards models and were stratified by cancer site. Harrell's discrimination C-index was used to calculate the predictive accuracy of the model when HRQOL parameters were added to clinical and demographic variables. The added value of adding HRQOL scales to clinical and demographic variables was illustrated with Kaplan-Meier curves. RESULTS: In the stratified, multivariate model, HRQOL parameters—global health status (hazard ratio [HR], 0.97; 95% confidence interval [CI], 0.95-1.00; P

BACKGROUND The impact of treatment on both the quality and the quantity of life, i.e. the ‘net clinical benefit’, should be considered to inform glioma patients and facilitate shared decision making. We applied two methods (i.e. Quality Adjusted Effect Sizes (QASES) and Joint Modelling (JM)) that combine survival and health-related quality of life (HRQoL) data into one outcome, to gain insight in the net clinical benefit of a treatment strategy. In addition, we assessed if both methods result in similar interpretations. MATERIAL AND METHODS We calculated the net clinical benefit in one randomized controlled trial, EORTC 26951 comparing radiotherapy (RT) + PCV chemotherapy versus RT alone, as a proof of concept for other trials. With the QASES method, effect sizes for differences in survival and HRQoL between treatment arms were calculated. Next, the combined effect size can be determined by weighing the emphasis put on survival or HRQoL (e.g. survival more important). JM allows simultaneous modeling of a longitudinal outcome (HRQoL), and a time-to event outcome (survival). HRQoL scales/items that were selected for primary analysis in the main study were also selected for this analysis: fatigue, global health, social functioning, communication deficit, seizures, physical functioning, and nausea/vomiting. RESULTS 288/386 patients completed baseline HRQoL forms and were included in the analysis. Overall survival (OS) was significantly longer with combined treatment (difference of 10.8 months). In contrast, the percentage of patients who experienced a clinically relevant deterioration (≥10 points) in nausea/vomiting, fatigue, social functioning and global health up to one year after treatment compared to baseline was larger in the RT+PCV arm. The QASES corresponded to a reduction in the median OS difference from 10.8 months to 6.8 months when adjusted for the HRQoL scales/items, when given equal weights to OS and HRQoL. JM analyses resulted in a theoretical loss of treatment effect in OS of 2–6% when adjusting for HRQoL. CONCLUSION Both methods showed that adjusting for the impact of treatment on a relevant HRQoL parameter reduced the survival benefit in the experimental treatment arm compared to standard treatment arm. Applying these methods may facilitate communicating the impact of treatment to patients in clinical practice.