Analysis Of Peripheral T-Cell Lymphoma (PTCL) Subtype By Race and Geography Using The Comprehensive Oncology Measures For Peripheral T-Cell Lymphoma Treatment (COMPLETE) Dataset

Abstract

Background COMPLETE is a national registry of PTCL patients designed to describe patient characteristics, treatments and outcomes in a ‘real world’ setting. Previous work has suggested that there may be geographic and/or racial differences in the incidence of PTCL subtypes. Using the COMPLETE dataset, we explored the influence of race and geography in the United States on the incidence of PTCL subtypes and examined for interactions between these two variables. Methods We identified patients with locked baseline records and performed univariate analyses comparing disease subtype, stratified by race and geography. A multivariable, multinomial response regression model was used to predict the classification of PTCL subtype based upon race and geographic region. An interaction term for race and region was assessed via a likelihood ratio test and found to be not significant (p = 0.43), thus was removed from the model. Results A total of 247 patients had locked baseline records. Given the small numbers of Asian (7 patients, 3%) and other/race unknown patients (6, 3%), only Black (43, 17%) and White (191, 77%) patients were included in the analyses. Results of the univariate analyses can be found in [Table 1][1]. PTCL-not otherwise specified (NOS) accounted for the largest histologic subtype (35% of patients), consistent with SEER (31%) and other data sources. A trend was noted in distribution of subtype by race and significant differences were seen in histologic distribution by region, with a higher proportion of angioimmunoblastic T-cell lymphoma (AITL) patients diagnosed in the West and a smaller proportion in the South. A higher proportion of patients diagnosed with PTCL-NOS were in the South compared to other regions while a higher proportion of patients in the Northeast were diagnosed with other histologic subtypes. The multinomial regression model suggests there was a relatively high likelihood of being diagnosed with PTCL-NOS for both races in the Midwest, South and West and a relatively high likelihood of being diagnosed with other subtypes of PTCL for patients in the Northeast. White patients in the West have the highest likelihood of being diagnosed with AITL. View this table: Table 1 Results of Univariate Analyses of PTCL Subtype by Race and Region Conclusions These results suggest there is a modest, independent influence of both race and region in the United States on histologic subtype of PTCL. Whether geographic differences are due to patient selection bias or potentially due to environmental factors cannot be determined in this study. As the sample size grows, further analyses are warranted to examine if the effect of race and region is enhanced or diminished while controlling for factors not measured in the current model. Disclosures: Carson: Allos: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau. Foss: merck: Research Funding; spectrum: Research Funding; eisai: Membership on an entity’s Board of Directors or advisory committees; millenium: Honoraria, Membership on an entity’s Board of Directors or advisory committees; celgene: Honoraria, Research Funding; seattle genetics: Research Funding. Pinter-Brown: Allos: Consultancy, Membership on an entity’s Board of Directors or advisory committees. Horwitz: Spectrum (Allos): Consultancy, Research Funding. Rosen: Allos: Consultancy, Honoraria. Gisselbrecht: Allos: Consultancy, Membership on an entity’s Board of Directors or advisory committees. Hsi: Allos: Research Funding; Seattle Genetics: Speakers Bureau; Eli Lilly: Research Funding; Abbott: Research Funding; Cellerant Therapeutics: Research Funding; BD Biosciences: Research Funding; Millennium: Research Funding. [1]: #T1