Impact of Diagnostic Delays on Lung Cancer Survival Outcomes: A Population Study of the US SEER-Medicare Database
| Autor: | Perrin E. Romine, Qin Sun, Catherine Fedorenko, Li Li, Mariel Tang, Keith D. Eaton, Bernardo H.L. Goulart, Renato G. Martins |
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| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | JCO Oncol Pract |
| ISSN: | 2688-1535 2688-1527 |
| DOI: | 10.1200/op.21.00485 |
| Popis: | PURPOSE: Time from diagnosis to treatment has been associated with worse survival outcomes in non–small-cell lung cancer (NSCLC). However, little is known about the impact of delay in time to diagnosis. We aimed to evaluate the impact of time from radiographic suspicion to histologic diagnosis on survival outcomes using the US SEER-Medicare population database. METHODS: We identified patients from the SEER-Medicare data set diagnosed with any stage NSCLC between January 1, 2011, and December 31, 2015, who received stage-appropriate treatment and had a computed tomography scan within 1 year of diagnosis. Time to confirmation was determined as the interval between most recent computed tomography imaging and date of histologic diagnosis. Our primary outcome was overall survival (OS). RESULTS: In total, 10,824 eligible patients were identified. The median time to confirmation was 20 (range 0-363) days. Using multivariate Cox regression models, longer time to confirmation was associated with improved OS in all comers driven by stage IV patients after adjustment for age, sex, diagnosis year, histology, and comorbidity index. In a separate landmark analysis excluding patients deceased within 6 months of diagnosis, the association between time to diagnosis and survival was no longer evident. CONCLUSION: Time to confirmation of NSCLC was inversely associated with OS in this US SEER population study. This association was lost when patients deceased within 6 months of diagnosis were excluded, suggesting that retrospective registry-claims databases may not be the optimal data source to study time to diagnosis as a quality metric because of the unaccounted confounding effects of tumor behavior. Prospective evaluations of clinically enriched data sources may better serve this purpose. |
| Databáze: | OpenAIRE |
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