The state of prediction models in hematologic disease: a worrisome assessment.

Abstract

Purpose of review: The lack of optimal treatments for haematological disorders has led to the need for prediction models for diagnosis, therapeutic decision-making and life planning. In this review, the worrying current state of predictive models in the field is discussed.

Recent findings: Here, we reviewed 100 studies on prediction models in this field. Our analysis revealed a concerning state of affairs, with a prevalence of suboptimal research methodologies and questionable statistical practices. This includes insufficient sample sizes, inadequate model evaluations, lack of necessary reports of model results, etc. In this regard, we present statistical considerations in the development and validation process of numerous models. This will provide the reader with the statistical knowledge related to prediction model necessary to assess bias in studies, compare other published models and determine the clinical utility of models.

Summary: Awareness among authors, reviewers and editors of the required statistical considerations is crucial. Reinforcing these in all studies involving prediction models is needed. We all should encourage their use in evaluating existing studies and taking them fully into account in future studies.