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  • Title: Is frozen section analysis of pelvic lymph nodes accurate in locally advanced cervical cancer patients administered preoperative chemoradiation?
    Author: Ferrandina G, Fanfani F, Ludovisi M, Fagotti A, Carbone A, Zannoni G, Guerriero M, Petrillo M, Scambia G.
    Journal: Gynecol Oncol; 2008 Jan; 108(1):220-5. PubMed ID: 17976708.
    Abstract:
    OBJECTIVE: No thorough investigation of the diagnostic performance of frozen section analysis in predicting the final status of lymph nodes after exposure to concomitant chemoradiation (CT/RT) has been performed until now. The aim of the study was to analyze the accuracy of pelvic lymph node frozen section examination in a large, consecutive series of locally advanced cervical cancer (LACC) patients undergoing preoperative CT/RT. METHODS: A total of 123 consecutive LACC patients underwent preoperative CT/RT followed by radical hysterectomy according to Piver classification, with bilateral systematic pelvic lymphadenectomy. If pelvic nodes were intraoperatively defined as positive for tumor metastasis, para-aortic lymphadenectomy up to inferior mesenteric artery was carried out. The diagnostic performance of frozen section examination of pelvic lymph nodes was assessed by calculating the negative predictive value (NPV), the positive predictive value (PPV), specificity, sensitivity, and overall accuracy. RESULTS: A total of 1647 and 4345 pelvic lymph nodes were analyzed by frozen section examination and at final diagnosis, respectively. Lymph node metastases were found in 11 cases (8.9%) at frozen section examination, and in 14 cases (11.4%) at definitive histological diagnosis. We found 7 incorrect diagnoses at frozen section examination, represented by 5 false negative and 2 false positive cases. Specificity, sensitivity, overall accuracy, NPV, and PPV were 98.2%, 64.3%, 94.3%, 95.5% and 81.8%, respectively. CONCLUSIONS: Preoperative chemoradiation does not impair the role of frozen section analysis in predicting the pelvic lymph node involvement in LACC patients.
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