Interim recruitment prediction for multi-center clinical trials.
Biostatistics
; 23(2): 485-506, 2022 04 13.
Article
en En
| MEDLINE
| ID: mdl-32978616
ABSTRACT
We introduce a general framework for monitoring, modeling, and predicting the recruitment to multi-center clinical trials. The work is motivated by overly optimistic and narrow prediction intervals produced by existing time-homogeneous recruitment models for multi-center recruitment. We first present two tests for detection of decay in recruitment rates, together with a power study. We then introduce a model based on the inhomogeneous Poisson process with monotonically decaying intensity, motivated by recruitment trends observed in oncology trials. The general form of the model permits adaptation to any parametric curve-shape. A general method for constructing sensible parameter priors is provided and Bayesian model averaging is used for making predictions which account for the uncertainty in both the parameters and the model. The validity of the method and its robustness to misspecification are tested using simulated datasets. The new methodology is then applied to oncology trial data, where we make interim accrual predictions, comparing them to those obtained by existing methods, and indicate where unexpected changes in the accrual pattern occur.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Banco de datos:
MEDLINE
Asunto principal:
Modelos Estadísticos
/
Selección de Paciente
Tipo de estudio:
Clinical_trials
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Biostatistics
Año:
2022
Tipo del documento:
Article
País de afiliación:
Reino Unido