Surgically defined prognostic parameters in patients with early cervical carcinoma: A multivariate survival tree analysis

BACKGROUND: This study was performed to identify a statistical combination of independent pathologic and clinical features that best predict 5-year disease free survival (DFS) in patients with early stage cervical carcinoma treated by radical hysterectomy. The main goal of the study was to identify subsets of patients based on risk factors with maximal differences in DFS. METHODS: Three hundred and seventy patients were found for whom complete clinical and pathologic material, including cone and cervical biopsies, were available for analysis. Variables studied included age, weight, race, marital status, economic status, tumor size (TS), depth of invasion (DI), lymph-vascular space involvement (LVSI), cell type, tumor grade, lymph node metastasis (LNM), and number of lymph nodes removed. Patients with LNM, parametrial involvement, and positive or close surgical margins were offered postoperative radiation. After excluding patients with microinvasive and small cell carcinoma, data from the remaining 301 patients were submitted to univariate and multivariate analyses to define those variables that best predict DFS. RESULTS: Univariate analysis showed that, ranked by degree of significance, DI, TS, LVSI, LNM, tumor volume (TV) and clinical stage were significant in predicting survival. Significant (P 2 cm), LVSI, age (> or = 40 yrs), and LNM were found to be the best combination of risk factors to define prognosis. CONCLUSIONS: The multivariate survival tree analysis maximally separates patients with early stage invasive carcinoma of the cervix into 3 subgroups with 5-year DFS of 91%, 68%, and 43%, respectively. The authors excluded patients with microinvasive carcinoma (SGO, Society of Gynecologic Oncologists), who have an excellent DFS of 100%, and patients with small carcinoma, who have a poor DFS of 36.4% based on cell type alone, to define independent risk factors that maximally separate the remaining patients by DSF. The survival tree prognostic scoring system is easy to apply, and only requires DI (mm), LVSI (+, -), LNM, and age to assign an individual patient to one of three risk groups.