Estimating Population-Based Recurrence Rates of Colorectal Cancer over Time in the United States.

Natalia Kunst, Fernando Alarid-Escudero, Eline Aas, VMH Coupé, Deborah Schrag, Karin Kuntz

Research output: Contribution to journalArticleAcademicpeer-review


Background: Population-based metastatic recurrence rates for patients diagnosed with nonmetastatic colorectal cancer cannot be estimated directly from population-based cancer registries because recurrence information is not reported. We derived population-based colorectal cancer recurrence rates using disease-specific survival data based on our understanding of the colorectal cancer recurrence-death process.

Methods: We used a statistical continuous-time multistate survival model to derive population-based annual colorectal cancer recurrence rates from 6 months to 10 years after colorectal cancer diagnosis using relative survival data from the Surveillance, Epidemiology, and End Results Program. The model was based on the assumption that, after 6 months of diagnosis, all colorectal cancer-related deaths occur only in patients who experience a metastatic recurrence first, and that the annual colorectal cancer-specific death rate among patients with recurrence was the same as in those diagnosed with de novo metastatic disease. We allowed recurrence rates to vary by post-diagnosis time, age, stage, and location for two diagnostic time periods.

Results: In patients diagnosed in 1975-1984, annual recurrence rates 6 months to 5 years after diagnosis ranged from 0.054 to 0.060 in stage II colon cancer, 0.094 to 0.105 in stage II rectal cancer, and 0.146 to 0.177 in stage III colorectal cancer, depending on age. We found a statistically significant decrease in colorectal cancer recurrence among patients diagnosed in 1994-2003 compared with those diagnosed in 1975-1984 for 6 months to 5 years after diagnosis (hazard ratios between 0.43 and 0.70).

Conclusions: We derived population-based annual recurrence rates for up to 10 years after diagnosis using relative survival data.

Impact: Our estimates can be used in decision-analytic models to facilitate analyses of colorectal cancer interventions that are more generalizable.
Original languageEnglish
Pages (from-to)2710
Number of pages2718
JournalCancer Epidemiology Biomarkers and Prevention
Issue number12
Publication statusPublished - 29 Dec 2020

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