Comparing symptom reporting by prostate cancer patients and healthcare professionals in the international multicentre REQUITE study
Year: 2022
Type: article
Abstract: INTRODUCTION: Previous studies showed that healthcare professionals and patients had only moderate to low agreement on their assessment of treatment-related symptoms. We aimed to determine the levels of agreement in a large cohort of prostate cancer patients. METHODS: Analyses were made of data from 1,756 prostate cancer patients treated with external beam radiotherapy (RT) and/or brachytherapy in Europe and the USA and recruited into the prospective multicentre observational REQUITE study. Eleven pelvic symptoms at the end of RT were compared after translating patient-reported outcomes (PROs) into CTCAE-based healthcare professional ratings. Gwet's AC2 agreement coefficient and 95% confidence intervals were calculated for each symptom. To compare severity of grading between patients and healthcare professionals, percent agreement and deviations for each symptom were graphically depicted. Stratified and sensitivity analyses were conducted to identify potential influencing factors and to assess heterogeneity and robustness of results. RESULTS: The agreement for the 11 pelvic symptoms varied from very good (AC2 > 0.8: haematuria, rectal bleeding, management of sphincter control) to poor agreement (AC2 ≤ 0.2: proctitis and urinary urgency). Fatigue had a negative impact on the agreement. Patients tended to grade symptoms more severely than healthcare professionals. Information on sexual dysfunction was missing more frequently in healthcare professional assessment than PROs. CONCLUSION: Agreement was better for observable than subjective symptoms, with patients usually grading symptoms more severely than healthcare professionals. Our findings emphasize that PROs should complement symptom assessment by healthcare professionals and be taken into consideration for clinical decision-making to incorporate the patient perspective.
Source: Radiotherapy and Oncology
Authors: Philipp Heumann, Miguel E. Aguado-Barrera, Barbara Avuzzi, David Azria, Erik Briers, Renée Bultijnck, Ananya Choudhury, Dirk De Ruysscher, Marie-Pierre Farcy-Jacquet, Valérie Fonteyne, Antonio Gómez Caamaño, Irmgard Helmbold, Kerstie Johnson, Sarah L. Kerns, Maarten Lambrecht, Zoe Lingard, Tiziana Rancati, Barry S. Rosenstein, Elena Sperk, R. Paul Symonds, Christopher Talbot, Riccardo Valdagni, Ana Vega, Liv Veldeman, Tim Ward, Adam Webb, Catharine M. West, Jenny Chang-Claude, Petra Seibold
Institutions: German Cancer Research Center, Fundación Pública Galega de Medicina Xenómica, Instituto de Investigación Sanitaria de Santiago, Fondazione IRCCS Istituto Nazionale dei Tumori, Inserm, Institut de Recherche en Cancérologie de Montpellier, Institut Regional du Cancer de Montpellier, Ghent University Hospital, Ghent University, University of Manchester, The Christie Hospital, Maastro Clinic, Centre Hospitalier Universitaire de Nîmes, Complejo Hospitalario Universitario de Santiago, Servicio Gallego de Salud, University of Leicester, Medical College of Wisconsin, KU Leuven, Icahn School of Medicine at Mount Sinai, Heidelberg University, University Medical Centre Mannheim, Medizinische Fakultät Mannheim, University of Milan, Centre for Biomedical Network Research on Rare Diseases, Universität Hamburg, University Medical Center Hamburg-Eppendorf, University Cancer Center Hamburg
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $3,250
Funders: Deutsches Krebsforschungszentrum, Cancer Research UK, European Commission, Agence Nationale de la Recherche, Bundesministerium für Bildung und Forschung, Universitair Ziekenhuis Gent, KU Leuven, Universiteit Gent, Universitätsmedizin Mannheim, Fondazione Regionale per la Ricerca Biomedica, Instituto de Salud Carlos III
Awards: G1081616003, G1260474188, Radiogenómica: identificación de biomarcadores a través de métodos basados en transcriptómica, epigenómica e integración de multiómicas, G1914110030, G4536765799, G478156557, G5021406052, G5179103260, Validating predictive models of radiotherapy toxicity to improve quality-of-life and reduce side-effects in cancer survivors, G5752270261, G6566571199, G6681240295, G704912930, G7769187891, G924880562, G988107449
OpenAlex ID: W4310064228