A health-system-scale, episode-resolved multimodal atlas of cancer cachexia.

Longitudinal clinicogenomic data from over 52,000 cancer patients reveal cachectic weight loss episodes cluster near disease progression and are linked to worse outcomes across cancer types.

• Why it matters: Understanding the systemic drivers and consequences of cancer cachexia is crucial due to its significant impact on patient morbidity and mortality, yet remains poorly defined.
• What they did: Researchers analyzed longitudinal clinical and genomic data, linking cachectic episodes to serologic signatures, tumor genotypes, and outcomes, and developed a multivariate model to predict cachexia risk.
• The result: The model accurately predicted impending cachectic weight loss in lung, colorectal, and prostate cancers, validated in an external cohort, demonstrating routine clinicogenomic data as a scalable resource for cachexia discovery.