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

backgroundDuring 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, organized screening programmes were 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 diagnostic delays on health outcomes and costs, stratified by molecular subtype.

methodsA 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.

resultsOver five years, diagnostic delays were projected to cause a deterministic total loss of 21 QALYs and €3.2 M in additional healthcare costs across all subtypes, resulting in six additional deaths. This corresponded to an average loss of 0.002 QALYs and €315 additional costs per patient. The burden was disproportionately carried by aggressive subtypes. TNBC accounted for the largest health loss (− 9.5 QALYs) and highest incremental costs (€1.6 M), followed by HER2+ cancer (− 2.5 QALYs; €0.5 M). Probabilistic sensitivity analysis revealed considerable uncertainty in these estimates, particularly influenced by assumed input parameters.

conclusionThe impact of diagnostic delays during Belgium’s first COVID-19 wave was less severe than expected, likely reflecting rapid recovery measures that limited sustained stage shifts. While overall effects were modest, they may conceal a higher burden among faster-progressing subtypes such as TNBC and HER2+. Substantial model uncertainty highlights the need for routine registration of molecular subtypes to support future research on more tailored screening and diagnostic approaches during health system disruptions.