Flexible transition probability model for assessing cost-effectiveness of breast cancer screening

TL;DR

This paper introduces a flexible stage distribution model to evaluate the cost-effectiveness of extending breast cancer screening to new age groups, accommodating incomplete data and various estimation approaches.

Contribution

The paper presents a novel flexible model for assessing screening strategies using incomplete data, adaptable to different estimation methods and applicable to real-world policy decisions.

Findings

Model applied to Finnish data for age extension scenarios

Flexible approach accommodates different data availability

Assists policymakers in evaluating screening expansion costs

Abstract

Breast cancer is the most common cancer among Western women. Fortunately, organized screening has reduced breast cancer mortality and, consequently, the European Union has recommended screening with mammography for 50-69-year-old women. This recommendation is followed well in Europe. Widening the screening target age further is supported by conditional recommendations for 45-49- and 70-74-year-old women. However, before extending screening to new age groups, it's essential to carefully consider the benefits and costs locally as circumstances vary between different regions and/or countries. We propose a new approach to assess cost-effectiveness of breast cancer screening for a long-ongoing program with incomplete historical screening data. The new model is called flexible stage distribution model. It is based on estimating the stage distributions of breast cancer cases under different screening strategies. In the model, an ongoing screening strategy may be used as a baseline and other screening strategies may be incorporated by changes in the incidence rates. The model is flexible, as it enables to apply different approaches for estimating the altered stage distributions. Thus, if randomized data is available, one may rely on that. On the other hand, if randomized data is not available, altered stage distributions may be estimated by extrapolating the stage distributions of the youngest and oldest screened/non-screened age groups. We apply the proposed flexible stage distribution model for assessing incremental cost of extending the current biennial breast cancer screening to younger and older target ages in Finland.