Predictability of the Survival using Prognostic Index (PI) of Patients with Epithelial Ovarian Cancer.
- Author:
Sam Hyun CHO
;
Seung Ryong KIM
;
Hyang MOON
;
Jai Auk LEE
;
Youn Yeoung HWANG
;
Young Jin MOON
;
Joong Sik SHIN
;
Kyung Tal KIM
;
Chang Young CHUNG
- Publication Type:Original Article ; Clinical Trial
- Keywords:
Ovarian cancer;
Prognostic factors;
Survival;
Prognostic index(PI)
- MeSH:
Ascites;
Blood Platelets;
Drug Resistance;
Drug Therapy, Combination;
Gynecology;
Humans;
Neoplasm Metastasis;
Neoplasm, Residual;
Obstetrics;
Ovarian Neoplasms*;
P-Glycoprotein;
Plasminogen;
Plasminogen Activator Inhibitor 1;
Prognosis;
Proportional Hazards Models;
Survival Rate
- From:Korean Journal of Gynecologic Oncology and Colposcopy
1999;10(2):173-182
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
OBJECTIVES: To predict of the survival of patients with epithelial ovarian cancer, multivariable analysis was done to identify variables with independent prognostic factors. Based on materials from 191 clinical trials performed by Department of Obstetrics and Gynecology, Hanyang University Hospital, we constructed a prognostic index (Pp with considerable predictive power for long-term survival of patients with epithelial ovatian cancer treated with cis-platin based combination chemotherapy, METHODS: On identifying variables with independent prognostic value, statistical analysis were performed with clinicopathologic variables including age, FIGO stage, histologic subtype, histologic grade, residual tumor, presence of ascites, pretreatment levels of hemoglobin, platelet, and tumor markers(CA 125, CA 19-9). We also analyzed biological variables using immunohistochemical staining for GST-pie (glutathione-s-transferase-pie), p-glycoprotein, and MT (metallothinein) as a drug resistance and uPA (urokinase type plasminogen activator), PAI-1 (plasminogen activator inhibitor-l), nm23 (nonmetastatic gene 23) as a tumor invasion and metastasis. In addition, univariable analysis was performed followed by multivariable analysis using Coxs proportional hazards model to identify variables predictive of poor prognosis. Prognostic index (PI) was calculated based on sum of individual beta-coefficient of the most important independent prognostic value. RESULTS: With univariable analysis, age, FIGO stage, histologic grade, histologic subtype, presence of ascites, residual tumor, initial value of CA 125, MT, uPA, and PAI-1 were found to predict of patients survival. In the multivariable analysis and proportional hazard model, the pretreatment characteristics needed for the calculation of the PI are the age, the site of metastases expressed as stage, the histologic subtype, the size of residual tumor, the histological grade, and the presence of ascites. In the subgroup comprising the 10% of the patients with the best prognosis, 5-year survival rate was 78.9%, whereas in the subgmup comprising the 10% with the poorest prognosis, 5-year survival rate was 7.1%, which illustrates the large variability of the prognosis among patients. CONCLUSIONS: The PI was found to retain its value after response was achieved. The information provided by the PI can be expected to be useful in treatment planning and the proper stratification of patients in clinical trials.
