Abstract

ObjectiveTo model the cost–effectiveness of a risk-based breast cancer screening programme in urban China, launched in 2012, compared with no screening.MethodsWe developed a Markov model to estimate the lifetime costs and effects, in terms of quality-adjusted life years (QALYs), of a breast cancer screening programme for high-risk women aged 40–69 years. We derived or adopted age-specific incidence and transition probability data, assuming a natural history progression between the stages of cancer, from other studies. We obtained lifetime direct and indirect treatment costs in 2014 United States dollars (US$) from surveys of breast cancer patients in 37 Chinese hospitals. To calculate QALYs, we derived utility scores from cross-sectional patient surveys. We evaluated incremental cost–effectiveness ratios for various scenarios for comparison with a willingness-to-pay threshold.FindingsOur baseline model of annual screening yielded an incremental cost–effectiveness ratio of US$ 8253/QALY, lower than the willingness-to-pay threshold of US$ 23 050/QALY. One-way and probabilistic sensitivity analyses demonstrated that the results are robust. In the exploration of various scenarios, screening every 3 years is the most cost–effective with an incremental cost–effectiveness ratio of US$ 6671/QALY. The cost–effectiveness of the screening is reduced if not all diagnosed women seek treatment. Finally, the economic benefit of screening women aged 45–69 years with both ultrasound and mammography, compared with mammography alone, is uncertain.ConclusionHigh-risk population-based breast cancer screening is cost–effective compared with no screening.

Highlights

  • Breast cancer is the most common cancer among women

  • The risk-based breast cancer screening yielded higher quality-adjusted life years (QALYs) compared with no screening (23.0129 QALYs versus 22.9843 QALYs), but was more expensive than no screening (US$ 335.43 versus US$ 99.68)

  • We found the incremental cost–effectiveness ratios to be lower than the threshold at both the upper and lower limits of these variables

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Summary

Introduction

Breast cancer is the most common cancer among women. Globally, 1.67 million women were diagnosed with breast cancer in 2012, contributing to more than 25% of female cancer incident cases.[1]. The Surveillance, Epidemiology, and End Results Programme reported that women diagnosed with breast cancer at an early stage (Stage I or II) have a better prognosis (5-year survival rate, 85–98%) than for advanced breast cancer (5-year survival rate for Stage III or IV, 30–70%).[4] The strong argument for earlier diagnosis with respect to patient outcome has resulted in the initiation of breast cancer screening programmes in many countries. The aims of such programmes are the early diagnosis and treatment of cancer patients to improve disease outcomes and to reduce mortality.[5]

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