Estimating individualized treatment effects from randomized controlled trials: a simulation study to compare risk-based approaches.
BMC Med Res Methodol
; 23(1): 74, 2023 03 28.
Article
em En
| MEDLINE
| ID: mdl-36977990
ABSTRACT
BACKGROUND:
Baseline outcome risk can be an important determinant of absolute treatment benefit and has been used in guidelines for "personalizing" medical decisions. We compared easily applicable risk-based methods for optimal prediction of individualized treatment effects.METHODS:
We simulated RCT data using diverse assumptions for the average treatment effect, a baseline prognostic index of risk, the shape of its interaction with treatment (none, linear, quadratic or non-monotonic), and the magnitude of treatment-related harms (none or constant independent of the prognostic index). We predicted absolute benefit using models with a constant relative treatment effect; stratification in quarters of the prognostic index; models including a linear interaction of treatment with the prognostic index; models including an interaction of treatment with a restricted cubic spline transformation of the prognostic index; an adaptive approach using Akaike's Information Criterion. We evaluated predictive performance using root mean squared error and measures of discrimination and calibration for benefit.RESULTS:
The linear-interaction model displayed optimal or close-to-optimal performance across many simulation scenarios with moderate sample size (N = 4,250; ~ 785 events). The restricted cubic splines model was optimal for strong non-linear deviations from a constant treatment effect, particularly when sample size was larger (N = 17,000). The adaptive approach also required larger sample sizes. These findings were illustrated in the GUSTO-I trial.CONCLUSIONS:
An interaction between baseline risk and treatment assignment should be considered to improve treatment effect predictions.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Ensaios Clínicos Controlados Aleatórios como Assunto
Tipo de estudo:
Clinical_trials
/
Etiology_studies
/
Guideline
/
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2023
Tipo de documento:
Article