Multivariate analysis of the prognostic factors and outcomes in early cervical cancer patients undergoing radical hysterectomy
Introduction
Early-stage cervical cancer has assumed increased importance for gynecological oncologists because of the rising proportion of early-stage invasive cervical cancer among patients. Although the majority of patients with early-stage cancer are cured with radical hysterectomy and pelvic lymphadenectomy or with radiotherapy, the 20% mortality rate among these patients has not improved during the last two decades [1], [2]. The clinical staging system for cervical cancer promoted by the International Federation of Gynecology and Obstetrics (FIGO) is effective in predicting the outcomes of this disease. However, disparate prognoses have been observed in patients with tumors of the same stage. To clarify this discrepancy, many investigators have tried to identify prognostic factors obtained by surgery. Pelvic lymph node metastases (LNM), tumor size (TS), cervical stromal invasion, the presence of lymphovascular space involvement (LVSI), histological subtype, and direct extension of the tumor to the uterine corpus, vagina, parametrium, or to the surgical margins of resection are reported to have prognostic value [3], [4], [5], [6], [7], [8], [9].
It is clear that many of these risk factors are interrelated. Studies have been designed to statistically identify the best combination of these risk factors using multivariate analysis techniques [5], [6], [7]. Using Cox's proportional hazards regression model, these studies have produced different sets of combined risk factors for surgically treated patients. However, the reported variables of combined risk factors are inconclusive, and the definitions of prognostic groups are complicated in the reports by Delgado et al.[5]], Sevin et al. [6], and Kamura et al. [7]. We used univariate and multivariate analysis with Cox's regression model to statistically identify the best combination of these risk factors to predict prognoses. Finally, we used a prognostic grouping system stratified by different survival curves and grouped similar recurrence-free survival (RFS) rates together to maximally separate patients with early-stage invasive cervical cancer into three subgroups. Although adjuvant radiotherapy and/or chemotherapy have been prescribed for different high-risk groups, the role of postoperative adjuvant therapy is only defined in high-risk patients with early-stage disease. For patients who were assigned to poor prognostic factor groups in our study, we attempted to evaluate the impact of postoperative adjuvant therapy and to see if adjuvant CT + RT could improve RFS compared to radiotherapy alone.
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Materials and methods
From 1990 to 1999, there were 213 patients with stages IB and II cervical carcinoma who underwent type III radical hysterectomy and bilateral pelvic lymphadenectomy as primary treatment at Cathay General Hospital in Taipei, Taiwan. Paraaortic lymph node sampling was performed concurrently if there was any suspicion of metastasis. Pelvic lymphadenectomy was performed as described by Ho et al. [10].
All clinical and pathological variables were retrospectively reviewed, using a predefined data
Results
The 5-year overall survival (OS) and RFS of all 197 patients were 82% and 75%, respectively. Univariate analysis showed that deep stromal invasion (outer one-third vs. inner or middle one third of the tumor, P < 0.001), larger TS (P = 0.005), LVSI (P < 0.001), LNM (P < 0.001), higher clinical stage (II vs. IB, P = 0.022), surgical margin involvement (P < 0.003), and adjuvant RT (P < 0.001) were significant predicts of poor RFS. Patients' characteristics and univariate analysis of factors
Discussion
The prognostic grouping system reflects maximal differences in the power of risk factors based on Cox's regression analyses. For example, the presence of LNM is accepted as high risk for treatment failure. In the model, LNM was a poor prognostic factor only in patients with deeply invasive tumors and LVSI. The incidence of LNM for all groups was 23.4%. The incidence of patients with LNM and without deeply invasive tumors was 5.6% in contrast to 17.8% of those with LNM and deeply invasive
Conclusion
Using Cox's multivariate analysis and a prognostic grouping system, we maximally separated patients with early-stage invasive cervical carcinoma into good, intermediate, and poor prognosis subgroups, with corresponding 5-year RFSs of 89%, 69%, and 43%, respectively. The prognostic grouping system was easy to apply, and only required measurement of three independent risk factors: LVSI (+, −), LNM (+, −), and outer 1/3 invasion (+, −) to assign an individual patient to one of three risk groups.
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