| Literature DB >> 32007209 |
Corneel Coens1, Madeline Pe2, Amylou C Dueck3, Jeff Sloan4, Ethan Basch5, Melanie Calvert6, Alicyn Campbell7, Charles Cleeland8, Kim Cocks9, Laurence Collette1, Nancy Devlin10, Lien Dorme1, Hans-Henning Flechtner11, Carolyn Gotay12, Ingolf Griebsch13, Mogens Groenvold14, Madeleine King15, Paul G Kluetz16, Michael Koller17, Daniel C Malone18, Francesca Martinelli1, Sandra A Mitchell19, Jammbe Z Musoro1, Daniel O'Connor20, Kathy Oliver21, Elisabeth Piault-Louis22, Martine Piccart23, Chantal Quinten24, Jaap C Reijneveld25, Christoph Schürmann26, Ashley Wilder Smith19, Katherine M Soltys27, Martin J B Taphoorn28, Galina Velikova29, Andrew Bottomley1.
Abstract
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.Entities:
Mesh:
Year: 2020 PMID: 32007209 DOI: 10.1016/S1470-2045(19)30790-9
Source DB: PubMed Journal: Lancet Oncol ISSN: 1470-2045 Impact factor: 41.316