A new and validated clinical prognostic model (EPI) for Enteropathy Associated T-cell Lymphoma
Menée à partir de données portant sur 92 patients atteints d'un lymphome T associé à une entéropathie (âge médian : 62 ans), cette étude évalue la performance d'un modèle mathématique, basé sur des variables du système de score "International Prognostic Index" et sur la présence ou non de symptômes systémiques, pour identifier les patients nécessitant un traitement agressif
Purpose: Enteropathy-Associated T-cell Lymphoma (EATL) is a rare intestinal non-Hodgkin lymphoma with a poor, though variable prognosis. The International Prognostic Index (IPI) and the prognostic index for peripheral T-cell lymphoma (PIT) have limited predictive value for outcome of EATL. The purpose of this study was to develop and validate a prognostic model for EATL, which can identify high risk patients who need more aggressive therapy.
Experimental Design: This retrospective multicenter study was based on 92 patients and included 45 patients diagnosed with EATL between 1999 and 2009 from the Netherlands and 47 patients from England and Scotland, diagnosed with EATL between 1994 and 1998. A new EATL prognostic index (EPI) was constructed using the RPART (recursive partitioning and regression trees) procedure. Validation was performed applying the bootstrap method.
Results : Three risk groups were distinguished (P<0.0001): a high risk group, characterized by the presence of B-symptoms (median overall survival (OS) of 2 months); an intermediate risk group, comprising patients without B-symptoms and an IPI score ≥ 2 (7 months); and a low risk group, representing patients without B-symptoms and an IPI score of 0-1 (34 months). Internal validation showed stability of statistical significance and prognostic discrimination. In contrast to the IPI and PIT, the EPI better classified patients in risk groups according to their clinical outcome.
Conclusions : Our new validated prognostic model EPI accurately predicts survival outcome in EATL and may be used for patient selection for new therapeutic strategies and evaluation of clinical trials.
Clinical Cancer Research , résumé, 2015