PIEPOC: a new prognostic index for advanced epithelial ovarian cancer--Japan Multinational Trial Organization OC01-01.
OBJECTIVE
The purpose of this study was to construct a simple and powerful prognostic index (PI) of epithelial ovarian cancer, the PIEPOC.


METHODS
In a retrospective review, data from 768 women with stage III or IV epithelial ovarian cancer from 24 institutions in Japan were evaluated for clinical features predictive of overall survival. A PI and risk groups to predict overall survival after initial surgery were developed using the proportional hazards regression model.


RESULTS
Of six factors, the four prognostic factors that remained independently significant in the analysis of a training sample (538 randomly selected patients) were age, performance status (PS), histologic cell type, and residual tumor size. From the regression function, we derived a PI = 1 (if age 70 and above) + 1 (if PS 1 or 2) + 2 (if PS 3 or 4) + 1 (if mucinous or clear-cell) + 2 (if residual size 0.1 cm and above). Patients were classified into three risk groups (PIEPOC): low risk (PI 0-2), intermediate risk (PI 3), and high risk (PI 4-6). The PIEPOC was equally predictive in a validation sample (n = 230), identifying three groups (5-year survival: 0.67 in low, 0.43 in intermediate, 0.17 in high risk).


CONCLUSIONS
Our proposed PI, the PIEPOC, was predictive in our patient population and may have utility in clinical practice. Prospective studies would be needed to confirm the prognostic predictive ability of the PIEPOC for patients with advanced epithelial ovarian cancer.
Teramukai
Satoshi
S
Department of Clinical Trial Design and Management, Translational Research Center, Kyoto University Hospital, Kyoto, Japan. steramu@kuhp.kyoto-u.ac.jp
Ochiai
Kazunori
K
Tada
Harue
H
Fukushima
Masanori
M
D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D007564:Japan / Q000453:epidemiology; D008875:Middle Aged; D010051:Ovarian Neoplasms / Q000401:mortality* / Q000473:pathology* / Q000628:therapy; D011237:Predictive Value of Tests; D011379:Prognosis; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012189:Retrospective Studies; D012307:Risk Factors; D016019:Survival Analysis