[Study on the prognostic factors of colorectal cancer and on suggested model for prediction].
OBJECTIVE
To explore the factors related to the prognosis of colorectal cancer (CRC) and to establish a prognostic model for evaluating the prognosis of the patients with CRC.


METHODS
370 cases with CRC were selected in the study and clinical/pathological factors were collected and patients were followed. Kaplan-Meier method was used to calculate survival rate. Log-rank test and proportional-hazards regression model (Cox model) were used for univariate and multivariate analysis. Log cumulative hazards function plot was used to test Cox model proportional-hazards assumption (PH assumption). Prognostic index (P1) was calculated based on the results of multivariate analysis.


RESULTS
(1) One-year, three-year and five-year survival rates were 90.5%, 78.3% and 76.5% respectively. (2) Lymphatic metastasis, Duckes classification and therapeutic measure were independent prognostic factors of CRC and all passed PH assumption. (3) Patients with different PI were classified into 3 groups and there were significant differences noticed in survival rates (P < 0.001). (4) Individual survival rate was evaluated based on the prognostic Cox model and PI.


CONCLUSIONS
Lymphatic metastasis, Duckes classification and therapeutic measure were independent prognostic factors of CRC. To test PH assumption of the factors, selection of Cox model was essential. Cox model and PI seemed to be available in predicting the long term survivrate of patients with CRC.
Liu
Wei
W
Department of Epidemiology and Health Statistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
Nie
Shao-Fa
SF
Chen
Ji-Gui
JG
Huang
Tian
T
He
Jing-Jing
JJ
Liu
Chang
C
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D015179:Colorectal Neoplasms / Q000150:complications / Q000401:mortality / Q000473:pathology*; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D016016:Proportional Hazards Models; D016019:Survival Analysis