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Am J Med. Author manuscript; available in PMC 2017 September 01. Published in final edited form as: Am J Med. 2016 September ; 129(9): 1000.e15–1000.e25. doi:10.1016/j.amjmed.2016.02.030.
Direct Medical Costs Attributable to Cancer-Associated Venous Thromboembolism: A Population-based Longitudinal Study
Author Manuscript
Kevin P. Cohoon, D.O., M.Sc., Jeanine E. Ransom, B.A., Cynthia L. Leibson, Ph.D., Aneel A. Ashrani, M.D., M.S., Tanya M. Petterson, M.S., Kirsten Hall Long, Ph.D., Kent R. Bailey, Ph.D., and John A. Heit, M.D. Divisions of Cardiovascular Diseases and Gonda Vascular Center (KPC, JAH) and Hematology (AAA, JAH), Department of Internal Medicine; and the Divisions of Epidemiology (CLL, JAH) and Biomedical Statistics and Informatics (JER, TMP, KRB), Department of Health Sciences Research; Mayo Clinic, Rochester, MN, USA. KHL is affiliated with K Long Health Economics Consulting LLC, St. Paul, MN, USA
Abstract Purpose—To estimate medical costs attributable to venous thromboembolism among patients with active cancer.
Author Manuscript
Methods—In a population-based cohort study, we used Rochester Epidemiology Project (REP) resources to identify all Olmsted County, MN residents with incident venous thromboembolism and active cancer over the 18-year period, 1988–2005 (n=374). One Olmsted County resident with active cancer without venous thromboembolism was matched to each case on age, sex, cancer diagnosis date, and duration of prior medical history. Subjects were followed forward in REP provider-linked billing data for standardized, inflation-adjusted direct medical costs from 1 year before index (venous thromboembolism event date or control matched date) to the earliest of death, emigration from Olmsted County, or December 31, 2011, with censoring on the shortest follow-up to ensure a similar follow-up duration for each case-control pair. We used generalized linear modeling to predict costs for cases and controls and bootstrapping methods to assess uncertainty and significance of mean adjusted cost differences. Outpatient drug costs were not included in our estimates.
Author Manuscript
Results—Adjusted mean predicted costs were 1.9-fold higher for cases ($49,351) than for controls ($26,529) (P=
Am J Med. Author manuscript; available in PMC 2017 September 01. Published in final edited form as: Am J Med. 2016 September ; 129(9): 1000.e15–1000.e25. doi:10.1016/j.amjmed.2016.02.030.
Direct Medical Costs Attributable to Cancer-Associated Venous Thromboembolism: A Population-based Longitudinal Study
Author Manuscript
Kevin P. Cohoon, D.O., M.Sc., Jeanine E. Ransom, B.A., Cynthia L. Leibson, Ph.D., Aneel A. Ashrani, M.D., M.S., Tanya M. Petterson, M.S., Kirsten Hall Long, Ph.D., Kent R. Bailey, Ph.D., and John A. Heit, M.D. Divisions of Cardiovascular Diseases and Gonda Vascular Center (KPC, JAH) and Hematology (AAA, JAH), Department of Internal Medicine; and the Divisions of Epidemiology (CLL, JAH) and Biomedical Statistics and Informatics (JER, TMP, KRB), Department of Health Sciences Research; Mayo Clinic, Rochester, MN, USA. KHL is affiliated with K Long Health Economics Consulting LLC, St. Paul, MN, USA
Abstract Purpose—To estimate medical costs attributable to venous thromboembolism among patients with active cancer.
Author Manuscript
Methods—In a population-based cohort study, we used Rochester Epidemiology Project (REP) resources to identify all Olmsted County, MN residents with incident venous thromboembolism and active cancer over the 18-year period, 1988–2005 (n=374). One Olmsted County resident with active cancer without venous thromboembolism was matched to each case on age, sex, cancer diagnosis date, and duration of prior medical history. Subjects were followed forward in REP provider-linked billing data for standardized, inflation-adjusted direct medical costs from 1 year before index (venous thromboembolism event date or control matched date) to the earliest of death, emigration from Olmsted County, or December 31, 2011, with censoring on the shortest follow-up to ensure a similar follow-up duration for each case-control pair. We used generalized linear modeling to predict costs for cases and controls and bootstrapping methods to assess uncertainty and significance of mean adjusted cost differences. Outpatient drug costs were not included in our estimates.
Author Manuscript
Results—Adjusted mean predicted costs were 1.9-fold higher for cases ($49,351) than for controls ($26,529) (P=
