Presentation (CTI)

OBJECTIVES: Leptomeningeal metastases (LM) represent a devastating complication of advanced cancer, frequently diagnosed at late stage, associated with poor prognosis, and high healthcare costs. Current diagnostic approaches often delay definitive diagnosis, limiting timely initiation of effective therapies and increasing resource utilization. Cost estimation is further complicated by claims bundling, where LM-related treatment costs are often combined with primary cancer treatment.To estimate the cost of care for patients diagnosed with LM at a late stage and evaluate the potential economic and clinical impact of CNSide—a novel cerebrospinal fluid assay platform enabling earlier, more definitive LM tumor cell detection, quantification, characterization, and real-time monitoring of treatment response.
METHODS: A hypothetical cost-of-care model was developed using published literature, real-world data, and claims databases to estimate direct and indirect medical costs associated with late-stage (stage IV) LM diagnosis. Because LM costs are often indistinguishable from primary cancer expenses, cost ranges were applied. The base‑case assumed a 6‑month life expectancy and incorporated cost‑per‑event estimates across drug therapy, imaging, palliative care and hospitalization-related expenses. Sensitivity analyses evaluated potential cost offsets and clinical benefits achievable with CNSide through earlier diagnosis, optimized treatment pathways, and longitudinal response monitoring.
RESULTS: Late‑stage LM diagnosis incurs substantial costs, including median inpatient admission expenses of $20,000 (IQR $10,000-$30,000) with monthly costs exceeding $100,000 due to repeated imaging, LM-directed therapy, and palliative care. Incorporating advanced cost effectiveness models, CNSide may reduce overall LM-related costs by ~40% (33%-47%), driven by earlier intervention, prolonged life expectancy, improved treatment precision, reduced adverse events and hospitalizations, and QALY gains. Imaging costs may remain stable or increase with enhanced monitoring.
CONCLUSIONS: Earlier LM diagnosis and treatment optimization using CNSide may substantially reduce healthcare costs while improving patient outcomes. These findings underscore the need for integrating advanced diagnostic technologies to address the economic and clinical burden of LM.