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Influence of treatment intensity and medical comorbidities in older adults with peripheral T cell lymphoma

医学 内科学 养生 强的松 四分位间距 蒽环类 长春新碱 比例危险模型 切碎 人口 环磷酰胺 淋巴瘤 胃肠病学 化疗 癌症 乳腺癌 环境卫生
作者
Max J. Gordon,Zhigang Duan,Hui Zhao,Loretta J. Nastoupil,Samuel Y. Ng,Alexey V. Danilov,Swaminathan P. Iyer,Sharon H. Giordano
出处
期刊:Leukemia & Lymphoma [Informa]
卷期号:64 (14): 2258-2268
标识
DOI:10.1080/10428194.2023.2256908
摘要

AbstractWe conducted a population-based study of patients >65 years, diagnosed 2008-2017, with peripheral T-cell lymphoma (PTCL) using SEER-Medicare. Associations between PTCL subtype, treatment regimen, comorbidity, and mortality were assessed using the Kaplan-Meier method and multivariable Cox regression. Amongst the 2,546 patients, the median age was 77 years (interquartile range, 71–83). 5-year overall survival (OS) ranged from 22.2% to 37.3% depending on PTCL subtype. The most common frontline regimen was cyclophosphamide, doxorubicin, vincristine, and prednisone (CHOP). 5-year OS rate was 47.0% for patients treated with etoposide + CHOP (N = 67; CHOEP), 33.7% for those treated with CHOP (N = 732), and 23.8% for patients treated with non-anthracycline-containing regimens (N = 105; p < 0.001). In patients without comorbidities, CHOEP remained independently associated with improved OS (HR 0.52, 95% CI,0.30-0.91). Median OS was 1.2 years from initiation of second-line therapy (N = 228) independent of treatment regimen. Frontline but not second-line treatment regimen is associated with OS in older patients with PTCL.Keywords: Peripheral T-cell lymphoma (PTCL)Geriatric oncologyTargeted therapyStem cell transplantComorbidity AcknowledgementsThis study used the linked SEER-Medicare database. The interpretation and reporting of these data are the sole responsibility of the authors. The authors acknowledge the efforts of the National Cancer Institute; the Office of Research, Development and Information, Center for Medicare and Medicaid Services; Information Management Services, Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database.The collection of cancer incidence data used in this study was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103885; Centers for Disease Control and Prevention’s (CDC) National Program of Cancer Registries, under cooperative agreement 1NU58DP007156; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201800032I awarded to the University of California, San Francisco, contract HHSN261201800015I awarded to the University of Southern California, and contract HHSN261201800009I awarded to the Public Health Institute. The ideas and opinions expressed herein are those of the author(s) and do not necessarily reflect the opinions of the State of California, Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors. We thank Ashli Nguyen-Villarreal and Bryan Tutt, Research Medical Library, The University of Texas MD Anderson Cancer Center, for editing the manuscript.Author contributionsMG, AD, SI and SG conceptualized the study, directed the analysis, and wrote the manuscript. ZD and HZ developed the statistical methodology, performed the analysis, and wrote the manuscript. LN and SN wrote and reviewed the manuscript. SI, AV, and SG supervised the project.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingMJG is supported by a Ruth L. Kirschstein National Research Service Award (T32) training grant (5T32CA009666-27). SG is supported by a Cancer Prevention and Research Institute of Texas grant (RP160674) and a Susan G. Komen grant (SC150061). AVD is a Leukemia and Lymphoma Society Clinical Scholar (#2319-19). Lastly, this research was supported in part by a Cancer Center Support Grant (NCI P30CA016672). Susan G. Komen for the Cure.

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