Optimizing Multicancer Early Detection (MCED) Testing Based on Patient Stratification: A Comprehensive Analysis of Economic and Clinical Impact from a US Payer Perspective

Author(s)

Long B, Alhegelan M, Fried M
Alva10, Durham, NC, USA

OBJECTIVES: MCED is an emerging technology to improve outcomes and costs of cancer care. The effectiveness of population-wide utilization is uncertain, and optimization requires use in populations with increasing cancer incidence, younger age (<65), specific risk factors, or outside guidelines-recommended screening. The increasing incidence of obesity-related cancers in younger populations is an example. A dynamic budget impact analysis model was developed to estimate the economic impact of adopting an MCED test from a US payer perspective.

METHODS: Using a hypothetical 1M payer population, standard of care for a one-year patient cohort across 16 cancers was modeled over 5 years for incidence, stage at detection, treatment costs, and mortality based on SEER data and published literature. The future state modeled the effects of MCED test use on cancers detected, stage at detection, and mortality, accounting for costs of treatment, end-of-life care, MCED false positives, and overdiagnosis. The modeled population can be stratified by age, risk factors, and cancer types, producing multiple scenarios for analysis.

RESULTS: In one scenario, testing the population aged 40-64 years for 10 obesity-related cancers resulted in MCED testing in 2.8% of the population, intercepting 22.3% of the 10 cancers and shifting mean stage at diagnosis from 1.9 to 1.6. Cost savings (not including test cost) for the 10 cancers were 3.5% per year, $480 per MCED-tested patient, and $1.12 per-member, per-month.

CONCLUSIONS: Targeted utilization of MCED tests can result in cost savings and improved clinical outcomes. Modeling test use in specific populations ascertains the ranges of economic and clinical utility, identifying the specific ages, risk factors, cancer types, and test performance requirements for the most effective test strategy. Modeling also identifies areas for further research and real-world evidence production for MCED test development and adoption.

Conference/Value in Health Info

2024-05, ISPOR 2024, Atlanta, GA, USA

Value in Health, Volume 27, Issue 6, S1 (June 2024)

Code

EE429

Topic

Economic Evaluation, Medical Technologies, Methodological & Statistical Research

Topic Subcategory

Budget Impact Analysis, Diagnostics & Imaging

Disease

Medical Devices, Oncology

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