Literature DB >> 31672773

The EORTC QLQ-C30 Summary Score as Prognostic Factor for Survival of Patients with Cancer in the "Real-World": Results from the Population-Based PROFILES Registry.

Olga Husson1,2, Belle H de Rooij3,4, Jacobien Kieffer5, Simone Oerlemans4, Floortje Mols3,4, Neil K Aaronson5, Winette T A van der Graaf6,7, Lonneke V van de Poll-Franse5,3,4.   

Abstract

BACKGROUND: Health-related quality of life (HRQoL) has been shown to be a prognostic factor for cancer survival in randomized clinical trials and observational "real-world" cohort studies; however, it remains unclear which HRQoL domains are the best prognosticators. The primary aims of this population-based, observational study were to (a) investigate the association between the novel European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire-Core30 (QLQ-C30) summary score and all-cause mortality, adjusting for the more traditional sociodemographic and clinical prognostic factors; and (b) compare the prognostic value of the QLQ-C30 summary score with the global quality of life (QoL) and physical functioning scales of the QLQ-C30.
MATERIALS AND METHODS: Between 2008 and 2015, patients with cancer (12 tumor types) were invited to participate in PROFILES disease-specific registry studies (response rate, 69%). In this secondary analysis of 6,895 patients, multivariate Cox proportional hazard regression models were used to investigate the association between the QLQ-C30 scores and all-cause mortality.
RESULTS: In the overall Cox regression model including sociodemographic and clinical variables, the QLQ-C30 summary score was associated significantly with all-cause mortality (hazard ratio [HR], 0.77; 99% confidence interval [CI], 0.71-0.82). In stratified analyses, significant associations between the summary score and all-cause mortality were observed for colon, rectal, and prostate cancer, non-Hodgkin lymphoma, chronic lymphocytic leukemia, and multiple myeloma. The QLQ-C30 summary score had a stronger association with all-cause mortality than the global QoL scale (HR, 0.82; 99% CI, 0.77-0.86) or the physical functioning scale (HR, 0.81; 95% CI, 0.77-0.85).
CONCLUSION: In a real-world setting, the QLQ-C30 summary score has a strong prognostic value for overall survival for a number of populations of patients with cancer above and beyond that provided by clinical and sociodemographic variables. The QLQ-C30 summary score appears to have more prognostic value than the global QoL, physical functioning, or any other scale within the QLQ-C30. IMPLICATIONS FOR PRACTICE: The finding that health-related quality of life provides distinct prognostic information beyond known sociodemographic and clinical measures, not only around cancer diagnosis (baseline) but also at follow-up, has implications for clinical practice. Implementation of cancer survivorship monitoring systems for ongoing surveillance may improve post-treatment rehabilitation that leads to better outcomes.
© 2019 The Authors. The Oncologist published by Wiley Periodicals, Inc. on behalf of AlphaMed Press.

Keywords:  Cancer; Health‐related quality of life; Mortality; Patient‐reported outcome; Survival

Year:  2019        PMID: 31672773     DOI: 10.1634/theoncologist.2019-0348

Source DB:  PubMed          Journal:  Oncologist        ISSN: 1083-7159


  33 in total

Review 1.  Evidence-based guidelines for determination of sample size and interpretation of the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire Core 30.

Authors:  Kim Cocks; Madeleine T King; Galina Velikova; Marrissa Martyn St-James; Peter M Fayers; Julia M Brown
Journal:  J Clin Oncol       Date:  2010-11-22       Impact factor: 44.544

2.  Big data infrastructure for cancer outcomes research: implications for the practicing oncologist.

Authors:  Anne-Marie Meyer; Ethan Basch
Journal:  J Oncol Pract       Date:  2015-04-14       Impact factor: 3.840

Review 3.  Cancer survivorship monitoring systems for the collection of patient-reported outcomes: a systematic narrative review of international approaches.

Authors:  N Corsini; J Fish; I Ramsey; G Sharplin; I Flight; R Damarell; B Wiggins; C Wilson; D Roder; M Eckert
Journal:  J Cancer Surviv       Date:  2017-04-03       Impact factor: 4.442

4.  Methods for Developing Patient-Reported Outcome-Based Performance Measures (PRO-PMs).

Authors:  Ethan Basch; John Spertus; R Adams Dudley; Albert Wu; Cynthia Chuahan; Perry Cohen; Mary Lou Smith; Nick Black; Amaris Crawford; Keri Christensen; Kathleen Blake; Christine Goertz
Journal:  Value Health       Date:  2015-05-21       Impact factor: 5.725

5.  The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology.

Authors:  N K Aaronson; S Ahmedzai; B Bergman; M Bullinger; A Cull; N J Duez; A Filiberti; H Flechtner; S B Fleishman; J C de Haes
Journal:  J Natl Cancer Inst       Date:  1993-03-03       Impact factor: 13.506

Review 6.  The impact of measuring patient-reported outcomes in clinical practice: a systematic review of the literature.

Authors:  J M Valderas; A Kotzeva; M Espallargues; G Guyatt; C E Ferrans; M Y Halyard; D A Revicki; T Symonds; A Parada; J Alonso
Journal:  Qual Life Res       Date:  2008-01-04       Impact factor: 4.147

7.  Measuring quality of life in routine oncology practice improves communication and patient well-being: a randomized controlled trial.

Authors:  Galina Velikova; Laura Booth; Adam B Smith; Paul M Brown; Pamela Lynch; Julia M Brown; Peter J Selby
Journal:  J Clin Oncol       Date:  2004-02-15       Impact factor: 44.544

8.  Guidance for industry: patient-reported outcome measures: use in medical product development to support labeling claims: draft guidance.

Authors: 
Journal:  Health Qual Life Outcomes       Date:  2006-10-11       Impact factor: 3.186

9.  Replication and validation of higher order models demonstrated that a summary score for the EORTC QLQ-C30 is robust.

Authors:  Johannes M Giesinger; Jacobien M Kieffer; Peter M Fayers; Mogens Groenvold; Morten Aa Petersen; Neil W Scott; Mirjam A G Sprangers; Galina Velikova; Neil K Aaronson
Journal:  J Clin Epidemiol       Date:  2015-09-28       Impact factor: 6.437

10.  Cancer survivors not participating in observational patient-reported outcome studies have a lower survival compared to participants: the population-based PROFILES registry.

Authors:  Belle H de Rooij; Nicole P M Ezendam; Floortje Mols; Pauline A J Vissers; Melissa S Y Thong; Carla C P Vlooswijk; Simone Oerlemans; Olga Husson; Nicole J E Horevoorts; Lonneke V van de Poll-Franse
Journal:  Qual Life Res       Date:  2018-08-30       Impact factor: 4.147

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