2022 World Conference on Lung Cancer (ePosters)-EP16.03-024. Cellworks Singula™ Therapy Response Index (TRI) Identifies Superior OS Outcomes for NSCLC Patients: myCare-203A

EP16.03-024. Cellworks Singula™ Therapy Response Index (TRI) Identifies Superior OS Outcomes for NSCLC Patients: myCare-203A

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A study evaluated the effectiveness of Cellworks Singula TRI in predicting the overall survival outcomes for patients with non-small cell lung cancer (NSCLC). Singula TRI is a score that uses tumor Next-Generation Sequencing (NGS) results and computational omics biology modeling to simulate the impact of therapies on restoring normal signaling in patient-specific cells. The study included 453 NSCLC patients and found that Singula TRI was a significant predictor of overall survival, with patients in the favorable outcome group having a median survival time of 17.9 months and those in the unfavorable group having a median survival time of 11.3 months. Singula TRI provided predictive value beyond physician-prescribed therapy, standard clinical factors, and NCCN-guideline genomic factors. The study validated the Singula TRI algorithm in a retrospective cohort of NSCLC patients. <br /><br />The findings suggest that Singula TRI can guide therapeutic decisions for NSCLC patients by providing a continuous measure for alternative therapeutic options and estimating clinical benefit. The score was strongly predictive of overall survival and provided predictive value beyond other patient characteristics. Kaplan-Meier curves showed a significant difference in survival between the Singula TRI Risk Groups, with the favorable group having higher median survival time than the unfavorable group. <br /><br />In conclusion, Singula TRI has the potential to assist clinicians in making therapeutic decisions for NSCLC patients. It can help identify optimal therapies and estimate improvements in overall survival compared to standard care. The score provides additional predictive value beyond physician-prescribed therapy and other clinical and genomic factors. Further research and validation are needed to confirm the effectiveness of Singula TRI in different patient populations.

Asset Subtitle

Mark Klein

Meta Tag

Speaker Mark Klein

Topic Tumour Biology and Biomarkers - Molecular Profiling and Targeted Therapies

Keywords

Cellworks Singula TRI

predicting overall survival

non-small cell lung cancer

NSCLC

tumor Next-Generation Sequencing

computational omics biology modeling

therapeutic decisions

clinical benefit

Kaplan-Meier curves

therapeutic options