Can the potential benefit of individualizing treatment be assessed using trial summary statistics alone?
Am J Epidemiol
; 193(8): 1161-1167, 2024 Aug 05.
Article
in En
| MEDLINE
| ID: mdl-38679458
ABSTRACT
Individualizing treatment assignment can improve outcomes for diseases with patient-to-patient variability in comparative treatment effects. When a clinical trial demonstrates that some patients improve on treatment while others do not, it is tempting to assume that treatment effect heterogeneity exists. However, if outcome variability is mainly driven by factors other than variability in the treatment effect, investigating the extent to which covariate data can predict differential treatment response is a potential waste of resources. Motivated by recent meta-analyses assessing the potential of individualizing treatment for major depressive disorder using only summary statistics, we provide a method that uses summary statistics widely available in published clinical trial results to bound the benefit of optimally assigning treatment to each patient. We also offer alternate bounds for settings in which trial results are stratified by another covariate. Our upper bounds can be especially informative when they are small, as there is then little benefit to collecting additional covariate data. We demonstrate our approach using summary statistics from a depression treatment trial. Our methods are implemented in the rct2otrbounds R package.
Key words
Full text:
1
Database:
MEDLINE
Main subject:
Depressive Disorder, Major
/
Precision Medicine
Limits:
Humans
Language:
En
Year:
2024
Type:
Article