Mirjam Renovanz1, Marlene Hechtner2, Karoline Kohlmann1, Mareile Janko1, Minou Nadji-Ohl3, Susanne Singer2, Florian Ringel1, Jan Coburger4, Anne-Katrin Hickmann3,5. 1. Department of Neurosurgery, University Medical Center, Johannes-Gutenberg-University Mainz, Mainz Germany. 2. Division of Epidemiology and Health Services Research, Institute of Medical Biostatistics, Epidemiology and Informatics, University Medical Center, Johannes-Gutenberg-University Mainz, Mainz Germany. 3. Department of Neurosurgery Klinikum Stuttgart, Katharinenhospital, Stuttgart Germany. 4. Department of Neurosurgery, University Medical Center Ulm/Günzburg, Günzburg Germany. 5. Department of Neurosurgery Hirslanden Klinikum, Luzern Switzerland.
Abstract
BACKGROUND: Patient-reported outcomes are of high importance in clinical neuro-oncology. However, assessment is still suboptimal. We aimed at exploring factors associated with the probability for a) drop out of study and b) death during follow-up. METHODS: Patients were assessed twice during follow-up visits scheduled within 3 to 5 months of each other by using 3 validated patient-reported outcome measures (t1: first assessment, t2: second assessment). As "death" was seen as a competing risk for drop out, univariate competing risk Cox regression models were applied to explore factors associated with dropping out (age, gender, WHO grade, living situation, recurrent surgery, Karnofsky Performance Status, time since diagnosis, and patient-reported outcomes assessed by Distress Thermometer, EORTC-QLQ-C30, EORTC-QLQ-BN20, and SCNS-SF-34G). RESULTS: Two hundred forty-six patients were eligible, 173 (70%) participated. Patients declining participation were diagnosed with glioblastomas more often than with other gliomas (56% vs 39%). At t2, 32 (18%) patients dropped out, n = 14 death-related, n = 18 for other reasons. Motor dysfunction (EORTC-QLQ-BN20) was associated with higher risk for non-death-related drop out (HR: 1.02; 95% CI, 1.00-1.03; P = .03). Death-related drop out was associated with age (HR: 1.09; 95% CI, 1.03-1.14; P = .002), Karnofsky Performance Status (HR: 0.92; 95% CI, 0.88-0.96; P < .001), lower physical functioning (EORTC-QLQ-C30; HR: 0.98; 95% CI, 0.96-1.00; P = .04) and lower motor functioning (EORTC-QLQ-BN20; HR: 1.020; 95% CI, 1.00-1.04; P = .02). CONCLUSION: Patients with motor dysfunction and poorer clinical condition seem to be more likely to drop out of studies applying patient-reported outcome measures. This should be taken into account when planning studies assessing glioma patients and for interpretation of results of patient-reported outcome assessments in clinical routine.
BACKGROUND: Patient-reported outcomes are of high importance in clinical neuro-oncology. However, assessment is still suboptimal. We aimed at exploring factors associated with the probability for a) drop out of study and b) death during follow-up. METHODS: Patients were assessed twice during follow-up visits scheduled within 3 to 5 months of each other by using 3 validated patient-reported outcome measures (t1: first assessment, t2: second assessment). As "death" was seen as a competing risk for drop out, univariate competing risk Cox regression models were applied to explore factors associated with dropping out (age, gender, WHO grade, living situation, recurrent surgery, Karnofsky Performance Status, time since diagnosis, and patient-reported outcomes assessed by Distress Thermometer, EORTC-QLQ-C30, EORTC-QLQ-BN20, and SCNS-SF-34G). RESULTS: Two hundred forty-six patients were eligible, 173 (70%) participated. Patients declining participation were diagnosed with glioblastomas more often than with other gliomas (56% vs 39%). At t2, 32 (18%) patients dropped out, n = 14 death-related, n = 18 for other reasons. Motor dysfunction (EORTC-QLQ-BN20) was associated with higher risk for non-death-related drop out (HR: 1.02; 95% CI, 1.00-1.03; P = .03). Death-related drop out was associated with age (HR: 1.09; 95% CI, 1.03-1.14; P = .002), Karnofsky Performance Status (HR: 0.92; 95% CI, 0.88-0.96; P < .001), lower physical functioning (EORTC-QLQ-C30; HR: 0.98; 95% CI, 0.96-1.00; P = .04) and lower motor functioning (EORTC-QLQ-BN20; HR: 1.020; 95% CI, 1.00-1.04; P = .02). CONCLUSION: Patients with motor dysfunction and poorer clinical condition seem to be more likely to drop out of studies applying patient-reported outcome measures. This should be taken into account when planning studies assessing glioma patients and for interpretation of results of patient-reported outcome assessments in clinical routine.
Entities:
Keywords:
glioma; neuro-oncology; nonparticipation; study drop out; supportive care
Authors: Martin J B Taphoorn; Lily Claassens; Neil K Aaronson; Corneel Coens; Murielle Mauer; David Osoba; Roger Stupp; René O Mirimanoff; Martin J van den Bent; Andrew Bottomley Journal: Eur J Cancer Date: 2010-02-22 Impact factor: 9.162
Authors: Christoph Ostgathe; Jan Gaertner; Maren Kotterba; Sebastian Klein; Gabriele Lindena; Friedemann Nauck; Lukas Radbruch; Raymond Voltz Journal: Support Care Cancer Date: 2009-09-08 Impact factor: 3.603
Authors: Stephanie L Pugh; Joseph P Rodgers; Jennifer Moughan; Roseann Bonanni; Jaskaran Boparai; Ronald C Chen; James J Dignam; Deborah W Bruner Journal: Qual Life Res Date: 2020-09-07 Impact factor: 4.147
Authors: Linda Dirven; Ralf Luerding; Dagmar Beier; Elisabeth Bumes; Christiane Reinert; Clemens Seidel; Matteo Mario Bonsanto; Michael Bremer; Stefan Rieken; Stephanie E Combs; Ulrich Herrlinger; Corinna Seliger; Holger Kuntze; Regine Mayer-Steinacker; Annette Dieing; Claudius Bartels; Oliver Schnell; Astrid Weyerbrock; Sabine Seidel; Oliver Grauer; Minou Nadji-Ohl; Frank Paulsen; Michael Weller; Wolfgang Wick; Peter Hau Journal: J Neurooncol Date: 2020-05-04 Impact factor: 4.130
Authors: Mirjam Renovanz; Anne-Katrin Hickmann; Minou Nadji-Ohl; Naureen Keric; Elke Weimann; Christian Rainer Wirtz; Susanne Singer; Florian Ringel; Jan Coburger Journal: Support Care Cancer Date: 2020-02-14 Impact factor: 3.603