British Journal of Cancer · 2023 · 39 citations · 25 references
MedicineBiostatisticsOncologyCancer EpidemiologyEpidemiologySurvival AnalysisCancer Burden AssessmentCancer Early DetectionCancer MortalityCancer Survival AnalysisEarly Cancer DetectionPopulation ScreeningCancer Burden MappingCancer Mortality By Stage At DiagnosisCancer Screening EpidemiologyCancer Screening StrategiesFalse Positive Rate ReductionMulti-cancer Early DetectionPopulation Survival ModelingPopulation-based Cancer Registration
BACKGROUND: Screening programmes utilising blood-based multi-cancer early detection (MCED) tests, which can detect a shared cancer signal from any site in the body with a single, low false-positive rate, could reduce cancer burden through early diagnosis. METHODS: A natural history ('interception') model of cancer was previously used to characterise potential benefits of MCED screening (based on published performance of an MCED test). We built upon this using a two-population survival model to account for an increased risk of death from cfDNA-detectable cancers relative to cfDNA-non-detectable cancers. We developed another model allowing some cancers to metastasise directly from stage I, bypassing intermediate tumour stages. We used incidence and survival-by-stage data from the National Cancer Registration and Analysis Service in England to estimate longer-term benefits to a cohort screened between ages 50-79 years. RESULTS: Estimated late-stage and mortality reductions were robust to a range of assumptions. With the least favourable dwell (sojourn) time and cfDNA status hazard ratio assumptions, we estimated, among 100,000 screened individuals, 67 (17%) fewer cancer deaths per year corresponding to 2029 fewer deaths in those screened between ages 50-79 years. CONCLUSION: Realising the potential benefits of MCED tests could substantially reduce late-stage cancer diagnoses and mortality.
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Phylogenetic ctDNA analysis depicts early-stage lung cancer evolution
Christopher Abbosh, Nicolai J. Birkbak, Gareth A. Wilson et al. · Nature · 2017 · 1.9K citations · Full text