Anita J Kumar1, Jason Nelson2, Angie Mae Rodday2, Andrew M Evens3, Jonathan W Friedberg4, Tanya M Wildes5, Susan K Parsons6. 1. Institute for Clinical Research & Health Policy Studies, Tufts Medical Center, Boston, MA, United States of America; Division of Hematology/Oncology, Tufts Medical Center, Boston, MA, United States of America. Electronic address: Akumar5@tuftsmedicalcenter.org. 2. Institute for Clinical Research & Health Policy Studies, Tufts Medical Center, Boston, MA, United States of America. 3. Rutgers Cancer Institute of New Jersey, New Brunswick, NJ, United States of America. 4. Wilmot Cancer Institute, University of Rochester, Rochester, NY, United States of America. 5. Cancer and Aging Research Group, United States of America. 6. Institute for Clinical Research & Health Policy Studies, Tufts Medical Center, Boston, MA, United States of America; Division of Hematology/Oncology, Tufts Medical Center, Boston, MA, United States of America; Department of Medicine and Pediatrics, Tufts University School of Medicine, Boston, MA, United States of America.
Abstract
BACKGROUND: Older adults with Hodgkin Lymphoma (HL) have poorer outcomes than younger patients. There are little data about which baseline patient and disease factors inform prognosis among older patients. We sought to create a prediction model for 1-year mortality among older patients with new HL who received dose-intense chemotherapy. METHODS: We included adults ≥65 years old with a new diagnosis of classical HL between 2000-2013 from the Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset who received full-regimen chemotherapy. Through a non-random 2:1 split, we created development and validation cohorts. Multiple imputation was used for missing data. Using stepwise selection and logistic regression, we identified predictive variables for 1-year mortality. The model was applied to the validation cohort. A final model was then fit in the full cohort. RESULTS: We included 1315 patients. In the development cohort (n = 813), we identified significant predictors of 1-year mortality including age, Charlson comorbidity index (CCI), B symptoms at diagnosis, and advanced stage at diagnosis. The c-statistic was 0.70. When this model was applied to the validation cohort (n = 502), the c-statistic was 0.65. Predictors of 1-year mortality in the final model were CCI (OR = 1.41), B symptoms (OR = 1.54), advanced stage (OR = 1.44), and older age at diagnosis (OR = 1.33). CONCLUSION: We present a prediction model for use among older adults with HL who receive intensive chemotherapy. We identify risk factors for death within 1 year of diagnosis. Future work will build upon prognostication and shared decision-making after diagnosis for this population.
BACKGROUND: Older adults with Hodgkin Lymphoma (HL) have poorer outcomes than younger patients. There are little data about which baseline patient and disease factors inform prognosis among older patients. We sought to create a prediction model for 1-year mortality among older patients with new HL who received dose-intense chemotherapy. METHODS: We included adults ≥65 years old with a new diagnosis of classical HL between 2000-2013 from the Surveillance, Epidemiology, and End Results (SEER)-Medicare dataset who received full-regimen chemotherapy. Through a non-random 2:1 split, we created development and validation cohorts. Multiple imputation was used for missing data. Using stepwise selection and logistic regression, we identified predictive variables for 1-year mortality. The model was applied to the validation cohort. A final model was then fit in the full cohort. RESULTS: We included 1315 patients. In the development cohort (n = 813), we identified significant predictors of 1-year mortality including age, Charlson comorbidity index (CCI), B symptoms at diagnosis, and advanced stage at diagnosis. The c-statistic was 0.70. When this model was applied to the validation cohort (n = 502), the c-statistic was 0.65. Predictors of 1-year mortality in the final model were CCI (OR = 1.41), B symptoms (OR = 1.54), advanced stage (OR = 1.44), and older age at diagnosis (OR = 1.33). CONCLUSION: We present a prediction model for use among older adults with HL who receive intensive chemotherapy. We identify risk factors for death within 1 year of diagnosis. Future work will build upon prognostication and shared decision-making after diagnosis for this population.
Authors: Andrew M Evens; Irene Helenowski; Erika Ramsdale; Chadi Nabhan; Reem Karmali; Britt Hanson; Benjamin Parsons; Scott Smith; Annette Larsen; June M McKoy; Borko Jovanovic; Stephanie Gregory; Leo I Gordon; Sonali M Smith Journal: Blood Date: 2011-11-23 Impact factor: 22.113
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