Estimating population-based recurrence rates of colorectal cancer over time in the United States

Natalia Kunst, Fernando Alarid Escudero, Eline Aas, Veerle M.H. Coupé, Deborah Schrag, Karen M. Kuntz

Research output: Contribution to journalArticlepeer-review

Abstract

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 populationbased 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 (US)
Pages (from-to)2710-2718
Number of pages9
JournalCancer Epidemiology Biomarkers and Prevention
Volume29
Issue number12
DOIs
StatePublished - Dec 2020

Bibliographical note

Funding Information:
The authors thank Dr. Christopher Jackson for his comments and discussions about the method application. N. Kunst was funded by the Research Council of Norway and LINK Medical Research (grant numbers 276146 and 304034). N. Kuntz and F. Alarid-Escudero were supported by a grant from the NCI (award U01-CA-199335) as part of the Cancer Intervention and Surveillance Modeling Network (CISNET).

Funding Information:
N. Kunst reports grants from the Research Council of Norway (grant numbers 276146 and 304034) during the conduct of the study, personal fees from Thermo Fisher Scientific outside the submitted work, as well as employment with LINK Medical Research, which together with the Research Council of Norway funds N. Kunst’s PhD position. E. Aas reports funding for a project related to cancer end-of-life care (SAFE) from the Norwegian Cancer Association, and from the NordForsk (Nordic Funded Research) that could use cases from cancer treatment. In addition, Dr. Aas provided a report for the Directorate of Health in Norway on costs and cost-effectiveness of screening for colorectal cancer. D. Schrag reports personal fees from JAMA (editorship) and Pfizer (symposium speaker), and grants from AACR (research funding) outside the submitted work. K.M. Kuntz reports grants from NIH during the conduct of the study. No potential conflicts of interest were disclosed by the other authors.

Publisher Copyright:
© 2020 American Association for Cancer Research.

PubMed: MeSH publication types

  • Journal Article
  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

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