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. 2014 Aug;38(4):448-54.
doi: 10.1016/j.canep.2014.04.004. Epub 2014 May 17.

Patterns of metachronous metastases after curative treatment of colorectal cancer

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Patterns of metachronous metastases after curative treatment of colorectal cancer

Yvette R B M van Gestel et al. Cancer Epidemiol. 2014 Aug.

Abstract

Background: This study aimed to provide information on timing, anatomical location, and predictors for metachronous metastases of colorectal cancer based on a large consecutive series of non-selected patients.

Methods: All patients operated on with curative intent for colorectal cancer (TanyNanyM0) between 2003 and 2008 in the Dutch Eindhoven Cancer Registry were included (N=5671). By means of active follow-up by the Cancer Registry staff within ten hospitals, data on development of metastatic disease were collected. Median follow-up was 5.0 years.

Results: Of the 5671 colorectal cancer patients, 1042 (18%) were diagnosed with metachronous metastases. Most common affected sites were the liver (60%), lungs (39%), extra-regional lymph nodes (22%), and peritoneum (19%). 86% of all metastases was diagnosed within three years and the median time to diagnosis was 17 months (interquartile range 10-29 months). Male gender (HR=1.2, 95%CI 1.03-1.32), an advanced primary T-stage (T4 vs. T3 HR=1.6, 95%CI 1.32-1.90) and N-stage (N1 vs. N0 HR=2.8, 95%CI 2.42-3.30 and N2 vs. N0 HR=4.5, 95%CI 3.72-5.42), high-grade tumour differentiation (HR=1.4, 95%CI 1.17-1.62), and a positive (HR=2.1, 95%CI 1.68-2.71) and unknown (HR=1.7, 95%CI 1.34-2.22) resection margin were predictors for metachronous metastases.

Conclusions: Different patterns of metastatic spread were observed for colon and rectal cancer patients and differences in time to diagnosis were found. Knowledge on these patterns and predictors for metachronous metastases may enhance tailor-made follow-up schemes leading to earlier detection of metastasized disease and increased curative treatment options.

Keywords: Colorectal cancer; Metachronous metastases; Population-based; Predictors.

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