Factors predicting survival in peripheral T‐cell lymphoma in the USA: a population‐based analysis of 8802 patients in the modern era. (7th November 2014)

• Record Type: Journal Article
• Authors: Petrich, Adam M.; Helenowski, Irene B.; Bryan, Locke J.; Rozell, Shaina A.; Galamaga, Robert; Nabhan, Chadi
• Is Part Of: British journal of haematology. Volume 168:Number 5(2015:Mar.)
• Page Start: 708
• Page End: 718
• Publication Date: 2014-11-07
• Subjects: Hematology -- Periodicals; Blood -- Diseases -- Periodicals; 616.15
• DOI: 10.1111/bjh.13202
• Languages: English
• ISSNs: 0007-1048

Abstract

<abstract abstract-type="main" id="bjh13202-abs-0001"> <title>Summary</title> <p>Current prognostic models for peripheral T‐cell lymphoma (PTCL) have multiple limitations, and questions exist regarding applicability to current patients. We utilized the Surveillance Epidemiology and End Results (SEER)‐18 database to evaluate factors affecting overall survival (OS) of PTCL in the modern era and identified 8802 patients between 2000–2010. Most subtypes of PTCL increased in incidence during the study period. In univariate analyses, age >55 years, black race, advanced stage, absence of extra‐nodal disease, omission of radiation therapy (RT) and high‐risk histology each predicted inferior OS (<italic>P</italic> < 0·0001). Multivariate analysis (MVA) demonstrated that hepatosplenic, enteropathy‐associated and extra‐nodal Natural Killer/T cell histologies, each had hazard ratios >1·5 (<italic>P</italic> ≤ 0·0001) for death. Further, age ≥55 years, black race and advanced stage maintained their significance in the MVA (<italic>P</italic> < 0·0001 each). Based on the significant factors, a prognostic model was constructed and subsequently validated in an independent cohort. The new model incorporated age, stage, histology and race, with an OS ranging from 9 months (highest risk group) to 120 months (lowest risk group). In summary, this is the largest study of PTCL patients in the modern era that provides risk stratification utilizing a new prognostic model that can be incorporated into future prospective clinical trials.</p> </abstract>