Prevalence and prognostic effect of high tumor mutation burden (TMB-H) across multiple less common solid cancers using a real-world dataset Published September 2019 Citation Backenroth D, Shao C, Li G, Huang L,Pruitt SK, Castellanos EH, Frampton GM, Carson KR, Snow T, Singal G, Fabrizio D, Alexander BM, Jin FJ, Zhou W. . ESMO Annual Congress. . https://www.sciencedirect.com/science/article/pii/S0923753419600062 Authors:Backenroth D, Shao C, Li G, Huang L,Pruitt SK, Castellanos EH, Frampton GM, Carson KR, Snow T, Singal G, Fabrizio D, Alexander BM, Jin FJ, Zhou W Sources:ESMO Annual Congress Share Posted inPublicationsDrug discoveryTumor agnostic More publicationsESMO AI & Digital OncologyNovember 2025A pan-tumor and pan-country approach to LLM-based extraction of systemic therapies from the electronic health recordViani N, Groizard L, Harrison K, et al. Publication summaryPublicationsMachine learningTumor agnosticData managementISPORApril 2026Impact of telemedicine encounters on survival outcomes in advanced lung cancer: A time-varying cox analysis using EHR-derived dataParatane D, Adamson B, Zemplenyi APublication summaryPublicationsNon-small cell lung cancerISPORApril 2026Real-world (RW) treatment patterns and outcomes in patients with =2 lines of therapy (LOTS) for recurrent or progressive endometrial cancerBhak R, Iyer NN, Hopkins A, et al.Publication summaryPublicationsTreatment patternsAdvanced endometrial cancer