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The importance of using ordinal scores for patient classification based on health-related quality of life trajectories

dc.rights.licenseopenen_US
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorBARBIERI, Antoine
dc.contributor.authorCOUSSON-GELIE, Florence
dc.contributor.authorBAUSSARD, Louise
dc.contributor.authorGOURGOU, Sophie
dc.contributor.authorLAVERGNE, Christian
dc.contributor.authorMOLLEVI, Caroline
dc.date.accessioned2022-04-25T12:31:49Z
dc.date.available2022-04-25T12:31:49Z
dc.date.issued2022-03-15
dc.identifier.issn1539-1612 (Electronic) 1539-1604 (Linking)en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/139924
dc.description.abstractEnChanges in health-related quality of life (HRQoL) over time are not necessarily homogeneous within a population of interest. Our study aim was twofold: to determine homogeneous patient subpopulations distinguished by HRQoL trajectories, and to identify the particular patient profile associated with each subpopulation. To classify patients according to HRQoL dimension scores, we compared mixtures of linear mixed models (LMMs) classically applied to scores defined by the EORTC procedure, and mixtures of random effect cumulative models (CMs) applied to scores treated as ordinal variables. A simulation study showed that the mixture of LMMs overestimated the number of subpopulations and was less able to correctly classify patients than the mixture of CMs. Considering HRQoL scores as ordinal rather than continuous variables is relevant when classifying patients. The mixture of CMs for ordinal scores is able to identify homogeneous subpopulations and their associated trajectories. The application focused on changes over time in HRQoL data (collected using the EORTC QLQ-C30 questionnaire) from 132 breast cancer patients from the Moral study. Once the classification is obtained only from HRQoL scores, class membership was then explained through a logistic regression model, given a large panel of variables collected at baseline. Analysis of data revealed that deterioration over time of role functioning and insomnia was closely related to patient anxiety: anxiety at baseline is a prognostic factor for a poor level and/or a deterioration over time of HRQoL. For functional dimensions, large tumor size and high education level were associated with worse HRQoL scores.
dc.language.isoENen_US
dc.subject.enCancer study
dc.subject.enClassification
dc.subject.enHeterogeneous population
dc.subject.enOrdinal data
dc.subject.enQuality of life trajectories
dc.title.enThe importance of using ordinal scores for patient classification based on health-related quality of life trajectories
dc.typeArticle de revueen_US
dc.identifier.doi10.1002/pst.2205en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed35289497en_US
bordeaux.journalPharmaceutical Statisticsen_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.teamBIOSTAT_BPHen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03651050
hal.version1
hal.date.transferred2022-04-25T12:31:51Z
hal.exporttrue
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Pharmaceutical%20Statistics&rft.date=2022-03-15&rft.eissn=1539-1612%20(Electronic)%201539-1604%20(Linking)&rft.issn=1539-1612%20(Electronic)%201539-1604%20(Linking)&rft.au=BARBIERI,%20Antoine&COUSSON-GELIE,%20Florence&BAUSSARD,%20Louise&GOURGOU,%20Sophie&LAVERGNE,%20Christian&rft.genre=article


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