Sormani, Maria Pia;
Chataway, Jeremy;
Kent, David M;
Marrie, Ruth Ann;
(2023)
Assessing heterogeneity of treatment effect in multiple sclerosis trials.
Multiple Sclerosis Journal
, 29
(9)
pp. 1158-1161.
10.1177/13524585231189673.
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Abstract
Multiple sclerosis (MS) is heterogeneous with respect to outcomes, and evaluating possible heterogeneity of treatment effect (HTE) is of high interest. HTE is non-random variation in the magnitude of a treatment effect on a clinical outcome across levels of a covariate (i.e. a patient attribute or set of attributes). Multiple statistical techniques can evaluate HTE. The simplest but most bias-prone is conventional one variable-at-a-time subgroup analysis. Recently, multivariable predictive approaches have been promoted to provide more patient-centered results, by accounting for multiple relevant attributes simultaneously. We review approaches used to estimate HTE in clinical trials of MS.
| Type: | Article |
|---|---|
| Title: | Assessing heterogeneity of treatment effect in multiple sclerosis trials |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1177/13524585231189673 |
| Publisher version: | https://doi.org/10.1177/13524585231189673 |
| Language: | English |
| Additional information: | This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
| Keywords: | Multiple sclerosis, clinical trial |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10176165 |
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