J Korean Surg Soc.  2001 Aug;61(2):172-177.

Multivariate Analysis of Prognostic Factors in Colorectal Cancers

Affiliations
  • 1Division of Gastroenterology, Department of Surgery, Chonnam University Medical School, Gwangju, Korea. drkhr@chonnam.ac.kr

Abstract

PURPOSE: Colorectal cancer is one of the most common gastrointestinal malignancies in Korea. However, there have been few studies concerning the prognosis of colorectal cancer in Korea. The purpose of this study is to elucidate the prognostic factors of colorectal cancer and identify those independent prognostic factors.
METHODS
A total of 960 cases with colorectal cancer who received surgery at Chonnam University Hospital of Korea between Jan 1, 1980 and Dec 31, 2000 were analyzed retrospectively with respect to several prognostic factors including age, sex, location of tumor, histologic grade, stage, Borrmann type, depth of invasion, invasion of lymph node, tumor size, liver metastasis, peritoneal seeding, preoperative serum CEA level and DNA ploidy. Survival curves were estimated by the Kaplan-Meier method, and differences were analyzed by the Log-rank test. The Cox proportional hazard model was used for multivariate analysis. The data was considered to be significant when the p value was less than 0.05.
RESULTS
The mean age was 57 years and median follow-up was 26.7 months. By univariate analysis, significant prognostic factors were stage by TNM, histologic grade, invasion of lymph node, liver metastasis, peritoneal seeding, depth of invasion, Borrmann type and preoperative serum CEA level. By multivariate analysis, TNM stage was the most obvious independent prognostic factor. Histologic grade and depth of invasion were also significant independent prognostic factors.
CONCLUSION
In this study, TNM stage, histologic grade and depth of invasion were revealed independent prognostic factors.

Keyword

Colorectal cancer; Prognostic factor; Multivariate analysis

MeSH Terms

Colorectal Neoplasms*
DNA
Follow-Up Studies
Jeollanam-do
Korea
Liver
Lymph Nodes
Multivariate Analysis*
Neoplasm Metastasis
Ploidies
Prognosis
Proportional Hazards Models
Retrospective Studies
DNA
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