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Longitudinal analysis of health-related quality of life in cancer clinical trials: methods and interpretation of results

dc.rights.licenseopenen_US
dc.contributor.authorBASCOUL-MOLLEVI, C.
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorBARBIERI, Antoine
dc.contributor.authorBOURGIER, C.
dc.contributor.authorCONROY, T.
dc.contributor.authorCHAUFFERT, B.
dc.contributor.authorHEBBAR, M.
dc.contributor.authorJACOT, W.
dc.contributor.authorJUZYNA, B.
dc.contributor.authorDE FORGES, H.
dc.contributor.authorGOURGOU, S.
dc.contributor.authorBONNETAIN, F.
dc.contributor.authorTOURAINE, C.
dc.contributor.authorANOTA, A.
dc.date.accessioned2021-03-01T10:18:46Z
dc.date.available2021-03-01T10:18:46Z
dc.date.issued2021-01
dc.identifier.issn1573-2649 (Electronic) 0962-9343 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/26375
dc.description.abstractEnPURPOSE: Health-related quality of life (HRQoL) is assessed by self-administered questionnaires throughout the care process. Classically, two longitudinal statistical approaches were mainly used to study HRQoL: linear mixed models (LMM) or time-to-event models for time to deterioration/time until definitive deterioration (TTD/TUDD). Recently, an alternative strategy based on generalized linear mixed models for categorical data has also been proposed: the longitudinal partial credit model (LPCM). The objective of this article is to evaluate these methods and to propose recommendations to standardize longitudinal analysis of HRQoL data in cancer clinical trials. METHODS: The three methods are first described and compared through statistical, methodological, and practical arguments, then applied on real HRQoL data from clinical cancer trials or published prospective databases. In total, seven French studies from a collaborating group were selected with longitudinal collection of QLQ-C30. Longitudinal analyses were performed with the three approaches using SAS, Stata and R software. RESULTS: We observed concordant results between LMM and LPCM. However, discordant results were observed when we considered the TTD/TUDD approach compared to the two previous methods. According to methodological and practical arguments discussed, the approaches seem to provide additional information and complementary interpretations. LMM and LPCM are the most powerful methods on simulated data, while the TTD/TUDD approach gives more clinically understandable results. Finally, for single-item scales, LPCM is more appropriate. CONCLUSION: These results pledge for the recommendation to use of both the LMM and TTD/TUDD longitudinal methods, except for single-item scales, establishing them as the consensual methods for publications reporting HRQoL.
dc.language.isoENen_US
dc.title.enLongitudinal analysis of health-related quality of life in cancer clinical trials: methods and interpretation of results
dc.title.alternativeQual Life Resen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1007/s11136-020-02605-3en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed32809099en_US
bordeaux.journalQuality of Life Researchen_US
bordeaux.page91-103en_US
bordeaux.volume30en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - U1219en_US
bordeaux.issue1en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.teamBiostatisticsen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03154718
hal.version1
hal.date.transferred2021-03-01T10:20:15Z
hal.exporttrue
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