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Evaluates ctDNA dynamics in metastatic breast cancer, suggesting improved real-time patient predictions.
This study applies joint modeling (JM) of longitudinal and time-to-event data to circulating tumor DNA (ctDNA) dynamics measured by liquid biopsy in metastatic breast cancer (mBC), with a focus on dynamic prediction. Unlike traditional prognostic approaches that rely on static biomarkers, JM captures the continuous evolution of a methylation-based tumor fraction (TF) and links these changes to clinical outcomes. Serial liquid biopsies from 49 patients with hormone receptor–positive/HER2-negative mBC treated with endocrine therapy plus a CDK4/6 inhibitor were analyzed using the Guardant Reveal assay. JM combined a flexible longitudinal sub-model to characterize temporal TF trajectories with a Cox proportional hazards model for overall survival (OS) and time to treatment discontinuation (TTD). The most recent TF estimate was strongly associated with both OS and TTD ( p < 0.0001), demonstrating an inverse relationship between TF and prognosis. These findings highlight the value of JM for generating patient-specific, dynamically updated predictions that may support real-time, personalized clinical decision-making in mBC management.
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Pretz et al. (2026) studied this question.
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