Details

Autor(en) / Beteiligte

• Bouda, Jiri
• Hes, Ondrej
• Koprivova, Miroslava
• Pesek, Martin
• Svoboda, Tomas
• Boudova, Ludmila

Titel

P27 as a Prognostic Factor of Early Cervical Carcinoma

Ist Teil von

• International journal of gynecological cancer, 2013-01, Vol.23 (1), p.164-169

Ort / Verlag

England: Copyright by IGCS and ESGO

Erscheinungsjahr

2013

Quelle

MEDLINE

Beschreibungen/Notizen

• OBJECTIVEThe aim of this study was to clarify whether the evaluation of cell-cycle regulatory protein p27 can serve as a prognostic factor in patients with International Federation of Gynecology and Obstetrics (FIGO) stage IB cervical carcinoma. PATIENTS AND METHODSA retrospective study was performed on 130 surgically treated patients with FIGO stage IB cervical carcinoma with at least a 5-year follow-up. The expression of p27 was investigated independently by 2 experienced pathologists using immunohistochemistry. The prognostic significance of established prognostic factors and p27 expression were analyzed using univariate and multivariate analyses. RESULTSIn a univariate analysis, lymph node status, tumor diameter, Gynecologic Oncology Group (GOG) score, lymph vascular space invasion, and p27 expression were significant prognostic factors for overall survival (OS). We found a correlation between p27 expression and lymph node status, tumor diameter, invasion, and GOG score. The p27 expression was a statistically significant prognostic factor for OS in a univariate analysis (log-rank test, P = 0.03). In a multivariate analysis, only lymph node status and tumor diameter were statistically significant prognostic factors for OS. CONCLUSIONSThis study demonstrated that a low p27 expression is associated with lymph node metastasis, deep stromal invasion, tumor diameter more than 20 mm, and high GOG score and had a prognostic influence on OS in a univariate analysis in a series of 130 women with FIGO stage IB cervical carcinoma. Lymph node status and the diameter of the tumor were the only statistically significant prognostic factors in multivariate analysis.