Cost-effectiveness of population-based mammography screening strategies by age range and frequency

Abstract

a b s t r a c tThere is little cost-effectiveness evidence for breast cancer screening with mammography in women under the age of 50 years, or over the age of 70 years, and available estimates vary widely. The Canadian Task Force on Preventive Health Care (CTFPHC) took cost-effectiveness into account in their recent recommendations on breast cancer screening, but no data are available from a Canadian setting. We constructed a microsimulation model using data from the Screening Mammography Program of British Columbia (BC) and the BC Cancer Registry. Eight screening strategies with varying age ranges and frequencies were compared to a reference strategy of no screening. Local screening, diagnostic, and treatment costs, and utility weights from the literature were applied to health states. Cost-effectiveness was expressed as incremental cost-effectiveness ratios (ICER) and cost-effectiveness acceptability curves, using the results of probabilistic sensitivity analysis. The most cost-effective strategies were biennial screening from ages 50 to 69, with an ICER of $28,921/QALY, and biennial screening from 40 to 69, with an ICER of $86,029/QALY. Screening women ages 40-49 was more cost-effective than screening women ages 70-74, which conflicts with the recommendations of the CTFPHC. There was, however, considerable uncertainty around these cost-effectiveness results. Regardless of willingness-to-pay, no single strategy was significantly more likely to be cost effective than the others. There is value in reducing the uncertainty around these cost-effectiveness estimates, to better inform future screening policy.

Cost-effectiveness of mammography from a publicly funded health care system perspective

“…[35][36][37][38] Several studies have evaluated the cost-effectiveness of screening strategies, but most have been conducted from the perspective of the US health care system and/or have considered different risk factors such as early and late age and genetic profile. 4,13,[39][40][41] Gocgun and colleagues 42 constructed a model to estimate the Canadian cost per life saved using data from the Canadian National Breast Cancer Screening Study. 43,44 That model was not validated and was based on study results from the 1980s, when film mammography (now obsolete) was used.…”

Hepatitis C Virus Screening Trends: Serial Cross-Sectional Analysis of the National Health Interview Survey Population, 2013–2015

“…8 Cost-effectiveness analyses demonstrate one-time testing in this birth cohort produces an incremental cost-effectiveness ratio observed in other cancer screenings. 9,10 Despite these recommendations and potential benefits, an analysis of the 2013 National Health Interview Survey (NHIS) showed only 12% of individuals born between1945-1965 reported ever being screened for HCV. 11…”

Leveraging system sciences methods in clinical trial evaluation: An example concerning African American women diagnosed with breast cancer via the Patient Navigation in Medically Underserved Areas study

“…The probability of screening adherence will be taken from data reported in Table 1 for PNMUA participants and network members. Subsequently, these data will be entered in a spreadsheet model that has been based on published evidence-based models [[72], [73], [74], [75], [76]]. Fundamentally, the projections depend on the difference in probability of screening adherence between navigated and non-navigated patients and network members, rates of breast cancer, and projections of quality adjusted life years (QALY) associated with screening rates.…”