Subtype-specific health and economic impact of delayed breast cancer diagnosis during the early COVID-19 pandemic in Belgium: A Markov model analysis

Background: During the first COVID-19 wave, breast cancer diagnoses declined sharply worldwide due to suspended screening programmes and delayed care-seeking driven by fear of infection. In Belgium, the national programme was halted from March to June 2020, leaving 135 invasive breast cancers undiagnosed. Although no stage shifts were observed in 2020, these undiagnosed cases risk later detection at more advanced stages, with worse prognosis, higher healthcare costs, and reduced health-related quality of life. Evidence indicates that such delays disproportionately affect aggressive subtypes (e.g., triple-negative (TNBC)) compared with slower-growing luminal-like cancers. This study projected the five-year impact of these diagnostic delays on health outcomes and costs, stratified by molecular subtype. Methods: A Markov cohort model compared two cohorts of 10,147 Belgian women with breast cancer: a “disrupted-care” cohort (2020 data, including 135 undiagnosed cases) and a “non-disrupted” cohort (2017–2019 trends). Outcomes over five years were estimated from the healthcare payer perspective, including incremental QALYs, direct medical costs, and mortality. Data sources included the Belgian Cancer Registry, literature, and national cost databases. Sensitivity and scenario analyses assessed uncertainty. Results: Over five years, the diagnostic delays were projected to cause a total loss of 21 QALYs and €3.2M in additional healthcare costs across all subtypes, resulting in an estimated six additional deaths. This corresponds to a modest average impact of 0.002 QALYs and €315 per patient. The burden was disproportionately carried by aggressive subtypes. TNBC accounted for the largest health loss (-9.5 QALYs) and highest incremental costs (€1.6M), followed by HER2+ cancer (-2.5 QALYs; €0.5M). Probabilistic sensitivity analysis revealed considerable uncertainty in these estimates, particularly influenced by assumed input parameters. Conclusion: The impact of diagnostic delays during Belgium’s first COVID-19 wave was less severe than expected, likely because rapid recovery measures prevented a sustained stage shift. However, the overall modest results may mask a greater burden among faster-progressing subtypes such as TNBC and HER2+. The high uncertainty in the model underscores the need for better subtype-specific data. Ensuring diagnostic continuity, particularly for high-risk cancers, will be essential to mitigate the impact of future health system disruptions.