The prognostic significance of tumor location and bowel obstruction in Dukes B and C colorectal cancer. Findings from the NSABP clinical trials
- PMID: 6357118
- PMCID: PMC1353224
- DOI: 10.1097/00000658-198312000-00013
The prognostic significance of tumor location and bowel obstruction in Dukes B and C colorectal cancer. Findings from the NSABP clinical trials
Abstract
The present study examines the prognostic significance of tumor location and bowel obstruction in Dukes B and C colorectal cancer. Data were obtained from 1021 patients entered into two randomized prospective clinical trials of the NSABP. Tumor location proved to be a strong prognostic discriminant. Lesions located in the left colon demonstrated the most favorable prognosis. Tumors of the rectosigmoid and rectum had the worst prognosis with the relative risk of treatment failure for the latter being over three fold that of the left colon. When the relative risks associated with tumor location were adjusted for nodal imbalances, the left colon continued to demonstrate the most favorable prognosis. The presence of bowel obstruction also strongly influenced the prognostic outcome. Examination of the data without considering tumor location disclosed that patients with bowel obstruction were at greater risk for treatment failure than those without obstruction. The effect of bowel obstruction was influenced by the location of the tumor. The occurrence of bowel obstruction in the right colon was associated with a significantly diminished disease-free survival, whereas obstruction in the left colon demonstrated no such effect. This phenomenon was independent of nodal status and tumor encirclement, the latter two factors proving to be of prognostic significance independent of tumor obstruction. A multivariate analysis in which the covariate effects of sex, age, nodal status, tumor obstruction, encirclement, and tumor location were adjusted underscored the role of tumor location and obstruction as prognostic discriminants. The results indicate that the definition of prognostic factors can identify patient subsets with unique characteristics.
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