In PLCO data and simulations, the pattern mixture model (PMM) gives higher time-dependent AUC for ovarian cancer early detection than the risk of ovarian cancer algorithm (ROCA), except when biomarker measurements are very frequent and ROCA's changepoint assumptions hold.
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Statistical approaches using longitudinal biomarkers for disease early detection: A comparison of methodologies
In PLCO data and simulations, the pattern mixture model (PMM) gives higher time-dependent AUC for ovarian cancer early detection than the risk of ovarian cancer algorithm (ROCA), except when biomarker measurements are very frequent and ROCA's changepoint assumptions hold.