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CHICAGO, May 13, 2025--(BUSINESS WIRE)--Tempus AI, Inc. (NASDAQ: TEM), a technology company leading the adoption of AI to advance precision medicine and patient care, has announced the presentation of six posters, including one oral presentation, at the 2025 annual meeting of the Professional Society for Health Economics and Outcomes Research (ISPOR), taking place May 13-16 in Montreal, Canada. Tempus researchers are showcasing scientific and clinical studies highlighting the impact of AI and real-world data on health economics and outcomes research.
"The research we’re presenting at ISPOR 2025 underscores the powerful potential of integrating clinical, molecular, and claims data to unlock actionable insights that drive more personalized and effective cancer care," said Emilie Scherrer, Senior Director and Head of Outcomes Research, at Tempus. "At Tempus, we share ISPOR’s deep focus on empowering providers and health systems with the real-world data they need to optimize treatment strategies and improve outcomes for their patients."
Research highlights include:
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Date/Time: Thursday, May 15; 10:15 AM - 11:15 AM ET
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Overview: The Coalition to Advance Real-World Evidence through Randomized Controlled Trial (RCT) Emulation (CARE) Initiative seeks to advance understanding of when real-world data (RWD) can generate valid treatment effectiveness estimates by emulating RCTs. This study presents findings from three oncology emulations. The KEYNOTE-189 (metastatic NSCLC) and PALOMA-2 (advanced breast cancer) trials were emulated using electronic health record datasets. Trial entry criteria were applied, and treatment status was based on first-line medications. Inverse probability of treatment weighting controlled for baseline confounding, and Kaplan-Meier and Cox models estimated primary outcomes. In the KEYNOTE-189 emulation, the real-world progression-free survival (rwPFS) hazard ratio (HR) in one dataset was similar to the RCT finding, while the other was closer to the null. PALOMA-2's rwPFS HR was also closer to the null. Real-world overall survival estimates in KEYNOTE-189 also varied across datasets. The researchers conclude that RWD oncology emulation conclusions depend on dataset features, route of administration, and real-world follow-up characteristics.
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Poster Presentation: Impact of Adverse Event Definitions on Real-World Detection of Immune-Related Adverse Events
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Date/Time: Thursday, May 15; 10:30 AM - 1:30 PM ET
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Location: Exhibit Hall 220B-E, Poster #6044
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Overview: Researchers investigated the impact of varying definitions on the identification of immune-related adverse events (irAEs) in real-world data (RWD) from non-small cell lung cancer (NSCLC) patients treated with immune checkpoint blockade (ICB). The research utilized Tempus clinico-genomic data linked to Komodo Health's claims to analyze irAEs within one year of ICB treatment in patients with stage 3C+ NSCLC. Three peer-reviewed irAE definitions—differing in included irAEs, ICD-10 codes, and pre-treatment washout periods—were applied to the cohort of 4,831 patients. The overall prevalence of irAEs varied significantly across definitions: 41.0% (n=1,981) for Study A (9 irAEs), 75.4% (n=3,849) for Study B (10 irAEs), and 5.4% (n=264) for Study C (3 irAEs). This study demonstrates that irAE identification in RWD varies based on the definitions used, which can affect post-market surveillance, clinical practice guidelines, and patient care. The authors emphasize the need for researchers to accurately communicate the definitions used and conduct sensitivity analyses.
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