Readiness of Healthcare Systems to Generate Real-World Evidence: Reliability of CT Radiographic End Points for Evaluation of First-Line Systemic Treatment. Issue 12 (December 2021) - Ho, Cheryl; Chan, Brandon; Cameron, David; Shokoohi, Aria; Regier, Dean A.; Lim, Howard
Abstract : PURPOSE: Regulatory agencies such as the US Food and Drug Administration and health technology assessment bodies are increasingly using real-world evidence (RWE). The ability of healthcare systems to reliably generate response rate and progression-free survival from real-world data is unknown. We examined the capacity of a single-payer system to provide RWE by evaluating the frequency of computed tomography (CT) imaging during standard first-line metastatic systemic treatment of breast, colorectal, and lung cancer. METHODS: A 1-year cohort of patients with metastatic-at-diagnosis breast, colorectal, and lung cancer treated with first-line systemic therapy (excluding hormone therapy) referred to BC Cancer in 2016 was retrospectively reviewed for first-line treatment and CT imaging. Duration of first-line treatment was calculated from the first to the last dose of therapy. CT imaging was counted from the start of therapy to 8 weeks after the last therapy dose. RESULTS: A cohort of 664 patients was identified from the BC Cancer Registry. Distribution of metastatic disease at diagnosis was breast (n = 82), colorectal (n = 214), and lung (n = 368) cancer. For breast, colorectal, and lung cancer, there was a baseline CT within 4 weeks of treatment initiation in 59%, 51%, and 48% of patients, with median duration of first-line treatment of 14.6, 25.3, and 11.9 weeks and median CT imaging interval of 9.1, 9.0, and 6.1 weeks. CONCLUSION: In our publicly funded healthcare system, availability of baseline CT imaging was 48% to 59% and the frequency of assessment ranged from 6.1 to 9.1 weeks, subject to patterns of practice and resource availability. Our system was not capable of providing RWE for image-based end points. Alternative end points should be considered to capitalize on the wealth of real-world data.