Special Issue PRO-Analysis of Clinically Meaningful Change on Patient-Reported Outcomes: Renewed Insights About Covariate Adjustment.

analysis of covariance change scores clinical important change clinical outcome assessments covariate adjustment longitudinal analysis mean change method patient-reported outcomes within-patient change

Journal

Journal of biopharmaceutical statistics
ISSN: 1520-5711
Titre abrégé: J Biopharm Stat
Pays: England
ID NLM: 9200436

Informations de publication

Date de publication:
01 Aug 2023
Historique:
medline: 1 8 2023
pubmed: 1 8 2023
entrez: 1 8 2023
Statut: aheadofprint

Résumé

Determining clinically meaningful change (CMC) in a patient-reported (PRO) measure is central to its existence in gauging how patients feel and function, especially for evaluating a treatment effect. Anchor-based approaches are recommended to estimate a CMC threshold on a PRO measure. Determination of CMC involves linking changes or differences in the target PRO measure to that in an external (anchor) measure that is easier to interpret than and appreciably associated with the PRO measure. One type of anchor-based approach for CMC is the "mean change method" where the mean change in score of the target PRO measure within a particular anchor transition level (e.g. one-category improvement) is subtracted from the mean change in score of within an adjacent anchor category (e.g. no change category). In the literature, the mean change method has been applied with and without an adjustment for the baseline scores for the PRO of interest. This article provides the analytic rationale and conceptual justification for keeping the analysis unadjusted and not controlling for baseline PRO scores. Two illustrative examples are highlighted. The current research is essentially a variation of Lord's paradox (where whether to adjust for a baseline variable depends on the research question) placed in a new context. Once the adjustment is made, the resulting CMC estimate reflects an artificial case where the anchor transition levels are forced to have the same average baseline PRO score. The unadjusted estimate acknowledges that the anchor transition levels are naturally occurring (not randomized) groups and thus maintains external validity.

Identifiants

pubmed: 37526447
doi: 10.1080/10543406.2023.2237115
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

1-14

Auteurs

Joseph C Cappelleri (JC)

Statistical Research and Data Science Center, Pfizer Inc, Groton, Connecticut, USA.

Paul R Cislo (PR)

Statistical Research and Data Science Center, Pfizer Inc, Groton, Connecticut, USA.

Classifications MeSH