Dataset Information

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses.

ABSTRACT: INTRODUCTION:We used European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) data from the LUME-Colon 1 study to illustrate different methods of statistical analysis for health-related quality of life (HRQoL), and compared the results. PATIENTS AND METHODS:Patients were randomized 1:1 to receive nintedanib 200 mg twice daily plus best supportive care (n = 386) or matched placebo plus best supportive care (n = 382). Five methods (mean treatment difference averaged over time, using a mixed-effects growth curve model; mixed-effects models for repeated measurements (MMRM); time-to-deterioration (TTD); status change; and responder analysis) were used to analyze EORTC QLQ-C30 global health status (GHS)/QoL and scores from functional scales. RESULTS:Overall, GHS/QoL and physical functioning deteriorated over time. Mean treatment difference slightly favored nintedanib over placebo for physical functioning (adjusted mean, 2.66; 95% confidence interval [CI], 0.97-4.34) and social functioning (adjusted mean, 2.62; 95% CI, 0.66-4.47). GHS/QoL was numerically better with nintedanib versus placebo (adjusted mean, 1.61; 95% CI, -0.004 to 3.27). MMRM analysis had similar results, with better physical functioning in the nintedanib group at all timepoints. There was no significant delay in GHS/QoL deterioration (10%) and physical functioning (16%) with nintedanib versus placebo (TTD analysis). Status change analysis showed a higher proportion of patients with markedly improved GHS/QoL and physical functioning in the nintedanib versus placebo groups. Responder analysis showed a similar, less pronounced pattern. CONCLUSION:Analyses of EORTC QLQ-C30 data showed that HRQoL was not impaired by treatment with nintedanib versus placebo. Analysis and interpretation of HRQoL endpoints should consider symptom type and severity and course of disease.

SUBMITTER: Lenz HJ

PROVIDER: S-EPMC7505163 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses.

Lenz Heinz-Josef HJ Argiles Guillem G Yoshino Takayuki T Lonardi Sara S Falcone Alfredo A Limón María Luisa ML Sobrero Alberto A Hastedt Claudia C Peil Barbara B Voss Florian F Griebsch Ingolf I Van Cutsem Eric E

Clinical colorectal cancer 20190904 4

<h4>Introduction</h4>We used European Organization for Research and Treatment of Cancer Quality of Life Questionnaire (EORTC QLQ-C30) data from the LUME-Colon 1 study to illustrate different methods of statistical analysis for health-related quality of life (HRQoL), and compared the results.<h4>Patients and methods</h4>Patients were randomized 1:1 to receive nintedanib 200 mg twice daily plus best supportive care (n = 386) or matched placebo plus best supportive care (n = 382). Five methods (mea ...[more]

PMID: 31628043

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Project description:In oncology, health-related quality of life (HRQoL) data are often collected using disease-specific patient questionnaires while generic, patient-level utility data required for health economic modeling are often not collected.We developed a mapping algorithm for multiple myeloma that relates HRQoL scores from the European Organization for Research and Treatment of Cancer (EORTC) questionnaires QLQ-C30 and QLQ-MY20 to a utility value from the European QoL-5 Dimensions (EQ-5D) questionnaire. Data were obtained from 154 multiple myeloma patients who had participated in a multicenter cohort study in the UK or Germany. All three questionnaires were administered at a single time point. Scores from all 19 domains of the QLQ-C30 and QLQ-MY20 instruments were univariately tested against EQ-5D values and retained in a multivariate regression model if statistically significant. A 10-fold cross-validation model selection method was also used as an alternative testing means. Two models were developed: one based on QLQ-C30 plus QLQ-MY20 scores and one based on QLQ-C30 scores alone. Adjusted R-squared, correlation coefficients, and plots of observed versus predicted EQ-5D values were presented for both models.Mapping revealed that Global Health Status/QoL, Physical Functioning, Pain, and Insomnia were significant predictors of EQ-5D utility values. Similar results were observed when QLQ-MY20 scores were excluded from the model, except that Emotional Functioning and became a significant predictor and Insomnia was no longer a significant predictor. Adjusted R-squared values were of similar magnitude with or without inclusion of QLQ-MY20 scores (0.70 and 0.69, respectively), suggesting that the EORTC QLQ-MY20 adds little in terms of predicting utility values in multiple myeloma.This algorithm successfully mapped EORTC HRQoL data onto EQ-5D utility in patients with multiple myeloma. Current mapping will aid in the analysis of cost-effectiveness of novel therapies for this indication.

Project description:BACKGROUND:The European Organisation for Research and Treatment of Cancer (EORTC) QLQ-C30 is a widely used cancer-specific questionnaire assessing 15 domains of health-related quality of life (HRQoL). Our aim was to facilitate the interpretation of scores on this questionnaire by providing Austrian normative data based on a general population sample. METHODS:The calculation of normative data was based on the EORTC QLQ-C30 data collected from an Austrian general population sample that was part of an international online panel study on the development of European normative data. Data reported herein were stratified and weighted by age and sex. Normative data were calculated for all 15 HRQoL domains of the EORTC QLQ-C30. For precise predictions of EORTC QLQ-C30 scores, a regression model based on sex, age and the presence of health conditions was built. RESULTS:The Austrian sample comprised 1002 Austrian participants (50.1% female, 51.4% when weighted by age and sex based on United Nation statistics). The mean age was 53.7?years (weighted: 47.7?years) and 53.6% (weighted: 47.4%) reported at least one health condition. Men reported better physical (Cohen's d?=?0.17) and emotional (Cohen's d?=?0.17) functioning as well as less fatigue (Cohen's d?=?0.18) and insomnia (Cohen's d?=?0.25) compared with women. Younger individuals (<?40?years) reported less dyspnea (Cohen's d?=?0.61) and pain (Cohen's d?=?0.51), whereas older individuals (?60?years) reported better emotional functioning (Cohen's d?=?0.55). CONCLUSIONS:We present Austrian normative data for the EORTC QLQ-C30. Differences by age and sex are mostly in line with the findings of other European normative studies. The Austrian population sample shows higher HRQoL and lower morbidity compared with other European countries. The normative data in this study will facilitate the interpretation of EORTC QLQ-C30 scores in oncological practice and research at a national and international level (including cross-cultural comparisons).

Dataset Information

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses.

Publications

Health-related Quality of Life in the Phase III LUME-Colon 1 Study: Comparison and Interpretation of Results From EORTC QLQ-C30 Analyses.

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