Lung cancer is the leading cause of cancer death among both men and women, making up almost 25% of all cancer deaths. Each year, more people die of lung cancer than colon, breast, and prostate cancers combined.
In honor of Lung Cancer Awareness Month this November, Oncology Analytics invites you to a webinar dedicated to the evaluation of selected lung cancer clinical trials, using real-world patient data to illustrate why trial outcomes may not be representative.
Clinical trials are often designed for the most ideal patient, typically with excellent performance status and devoid of serious comorbidities. This has called into question if the benefit seen in randomized clinical trials (RCTs) is “diluted” in real world patients due to lower adherence, reduced tolerability, and increased competing risks of death (comorbidities). Furthermore, RCTs may not capture rare toxicities, long-term sequelae, and practical limitations. Real-world data is better suited to capture these phenomena, which oncologists can then use in discussion with their patients to set more realistic expectations.
Oncology Analytics will provide initial results from an analysis of four trials used in first-line non-small cell lung cancer treatment: KEYNOTE 189, Impower150, KEYNOTE 407, and KEYNOTE 024. Key insights will include a comparison of patient characteristics in the RCTs vs. real-world datasets, including age, performance status, gender, and molecular markers stratified by insurance type (Medicare, Medicaid, and Commercial) with the intent to reveal why real-world outcomes may not always conform to RCT findings.
During this webinar, the following topics will be explored:
- For Health Plans, how to use real-world data to improve your understanding of patient outcomes across the spectrum of lung cancer care.
- For Life Sciences Companies, how to use real-world data to improve your understanding of how different patient populations fare on current lung cancer therapies.