Effect of M1a and M1b Category in Metastatic Colorectal Cancer

Background. In 2009, the American Joint Committee on Cancer version 7 staging system introduced the M1 sub-classifications M1a (single metastatic site) and M1b (peritoneal or multiple metastatic sites). The study objectives were to evaluate the prognostic effect of site of metastasis and M1a/b category among patients with newly diagnosed colorectal cancer and synchronous metastasis. Patients and Methods. Patients with newly diagnosed pathologic or clinical category M1 colorectal cancer referred to the British Columbia Cancer Agency between 1999 and 2007 were included. Demographic, tumor, treatment, and outcome data were prospectively collected, and prognostic factors were identified. Univariate Cox models were used to assess the prognostic impact of individual sites of metastasis and to determine the effect of M1a/b category on overall survival (OS). Results. Among 2,049 eligible patients, 70% had M1a and 30% M1b category disease. The most common sites of common single sites of metastasis included liver (56%), lung (5.3%), and peritoneum (3.6%). Metastasis to a single organ or site, including peritoneum, was associated with improved OS compared with multiple sites of metastasis. In multivariate analysis, M1b category conferred inferior survival and hazard ratio (HR) 1.38 (95% confidence interval [CI]: 1.22, 1.55), along with age >70 and Eastern Cooperative Oncology Group performance status of 3-4. Resection of primary tumor was associated with improved survival, HR0.46(95% CI: 0.41, 0.52). Results were similar in subgroup analysis of patients undergoing resection of their primary tumor when histology, tumor, and node category were included. Conclusion. The results lend support to the introduction of M1a/b colorectal cancer categories. Consideration may be given to classifying patients with solitary peritoneal metastasis only as M1a rather than M1b category. Further refinement of category M1a to reflect resectability of metastasis at initial diagnosis may improve prognostication.