ESTIMATING REAL-WORLD HEALTHCARE COSTS ATTRIBUTABLE TO ADVERSE EVENTS IN PATIENTS WITH METASTATIC BREAST CANCER OR ACUTE MYELOID LEUKEMIA IN TAIWAN
Author(s)
Po Yang Tu, RPh1, Thi Thuy Dung Nguyen, MS1, Shihchen Kuo, RPh, PhD2, Sin-Syue Li, MD3, Huang-tz Ou, PhD1.
1Institute of Clinical Pharmacy and Pharmaceutical Science, National Cheng Kung University, Tainan, Taiwan, 2Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA, 3Division of Hematology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan, Tainan City, Taiwan.
1Institute of Clinical Pharmacy and Pharmaceutical Science, National Cheng Kung University, Tainan, Taiwan, 2Division of Metabolism, Endocrinology and Diabetes, Department of Internal Medicine, University of Michigan Medical School, Ann Arbor, MI, USA, 3Division of Hematology, Department of Internal Medicine, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan, Tainan City, Taiwan.
OBJECTIVES: To estimate incremental healthcare costs attributable to adverse events (AEs) among patients with metastatic breast cancer (mBC, as the highest incident solid tumor in females) or those with acute myeloid leukemia (AML, as the highest incident leukemia).
METHODS: We linked the Taiwan Cancer Registry Database to the National Health Insurance Research Database to construct longitudinal cohorts of patients newly diagnosed with mBC or AML during 01/01/2013-12/31/2022. Patients were followed from diagnosis until death or 12/31/2022. Clinically relevant and/or prevalent AEs were identified from inpatient, emergency department (ED), and outpatient claims records using ICD-9-CM/ICD-10-CM codes. Separate patient-month-level two-part models were fitted for each cohort with adjustment for time-varying clinical, treatment, disease-course, and healthcare-setting factors and time-invariant demographic, clinical, and baseline-cost covariates. Marginal standardization was used to estimate adjusted AE-attributable monthly costs, with patient-level bootstrap 95% confidence intervals. Sensitivity analyses were restricted to severe AEs identified by inpatient or ED records; scenario analyses were limited to the first-line treatment period.
RESULTS: This study included 9,548 mBC patients and 4,406 AML patients. Model-estimated baseline monthly costs (2024 U.S. dollars) were US$77 and US$106 for mBC and AML, respectively. For most AEs, adjusted AE-attributable monthly costs ranged from US$156 to US$1,400 in mBC and from US$685 to US$4,360 in AML, although several rare severe AEs yielded larger and less precise estimates. The three largest adjusted multipliers for monthly costs were acute respiratory failure (2.23), acute kidney injury (1.59), and sepsis (1.47) in mBC, and venous thromboembolism (2.85), interstitial lung disease (2.54), and pneumonia (1.77) in AML. Findings were broadly consistent in sensitivity and scenario analyses.
CONCLUSIONS: AEs were associated with substantial incremental healthcare costs in both mBC and AML patients. These real-world cost estimates can strengthen economic evaluations and inform reimbursement and resource-allocation decisions for cancer management.
METHODS: We linked the Taiwan Cancer Registry Database to the National Health Insurance Research Database to construct longitudinal cohorts of patients newly diagnosed with mBC or AML during 01/01/2013-12/31/2022. Patients were followed from diagnosis until death or 12/31/2022. Clinically relevant and/or prevalent AEs were identified from inpatient, emergency department (ED), and outpatient claims records using ICD-9-CM/ICD-10-CM codes. Separate patient-month-level two-part models were fitted for each cohort with adjustment for time-varying clinical, treatment, disease-course, and healthcare-setting factors and time-invariant demographic, clinical, and baseline-cost covariates. Marginal standardization was used to estimate adjusted AE-attributable monthly costs, with patient-level bootstrap 95% confidence intervals. Sensitivity analyses were restricted to severe AEs identified by inpatient or ED records; scenario analyses were limited to the first-line treatment period.
RESULTS: This study included 9,548 mBC patients and 4,406 AML patients. Model-estimated baseline monthly costs (2024 U.S. dollars) were US$77 and US$106 for mBC and AML, respectively. For most AEs, adjusted AE-attributable monthly costs ranged from US$156 to US$1,400 in mBC and from US$685 to US$4,360 in AML, although several rare severe AEs yielded larger and less precise estimates. The three largest adjusted multipliers for monthly costs were acute respiratory failure (2.23), acute kidney injury (1.59), and sepsis (1.47) in mBC, and venous thromboembolism (2.85), interstitial lung disease (2.54), and pneumonia (1.77) in AML. Findings were broadly consistent in sensitivity and scenario analyses.
CONCLUSIONS: AEs were associated with substantial incremental healthcare costs in both mBC and AML patients. These real-world cost estimates can strengthen economic evaluations and inform reimbursement and resource-allocation decisions for cancer management.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
EE91
Topic
Economic Evaluation, Study Approaches
Topic Subcategory
Cost/Cost of Illness/Resource Use Studies
Disease
Oncology