François-Clément Bidard: AI-Driven Digital Pathology Identifies Low-Risk Subgroup in ER+ Early Breast Cancer
François-Clément Bidard, Head of Center for Clinical Investigation, Inserm CIC-1428 at Inserm, shared on LinkedIn:
“Back to school: our newest Journal of Clinical Oncology paper on eBC.
Here, the whole idea is simple – to identify a subgroup of patients with clinically high-risk ER+ early BC but with excellent long-term outcomes after standard adjuvant chemotherapy and endocrine therapy – suggesting they may not require further escalation. The technical approach was rooted in AI tools from Thomas Walter’s lab and successfully implemented by Spotlight Medical, a digital pathology-focused spin-off from Institut Curie.
Results: this digital pathology assay on H&E slides identified ~20% of clinically high-risk patients with >95% 9-year freedom from distant recurrence across two independent trials from Unicancer.
Given this excellent survival rate, the absolute benefit of intensive surveillance (e.g., ctDNA monitoring) or adding further treatment (e.g., SERDs or CDK4/6i) for this patient population is likely close to zero for this subgroup (~20%), while increased for the rest of the high risk population (~80%).
This foundational work highlights the power of collaboration involving the two French oncology-focused University Hospital Institutes Institute of Women’s Cancers (Institut Curie) and PRISM (Gustave Roussy), with many key external US and French experts involved.”
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