Accuracy of frozen section diagnosis and factors associated with final pathological diagnosis upgrade of mucinous ovarian tumors

23Citations
Citations of this article
30Readers
Mendeley users who have this article in their library.

Abstract

Objective: To determine the accuracy of frozen section diagnosis and factors associated with final pathological diagnosis upgrade in patients with mucinous ovarian tumors. Methods: This study included 1,032 patients with mucinous ovarian tumors who underwent frozen section diagnosis during surgery. Sensitivity, specificity, and diagnostic accuracy of frozen section diagnosis was calculated. Univariate and multivariate regression analyses were performed to determine factors associated with diagnosis upgrade in the final pathology report. Results: The sensitivity and specificity of frozen section diagnosis were 99.1% (95% confidence interval [CI]=98%–99.6%) and 82.2% (95% CI=77.9%–85.7%), respectively, for benign mucinous tumors; 74.6% (95% CI=69.1%–79.4%) and 96.7% (95% CI=95.2%–97.8%), respectively, for mucinous borderline ovarian tumors; and 72.5% (95% CI=62.9%–80.3%) and 98.8% (95% CI=97.9%–99.3%), respectively, for invasive mucinous carcinomas. The multivariate analysis revealed that mixed tumor histology (odds ratio [OR]=2.8; 95% CI=1.3–6.3; p=0.012), tumor size >12 cm (OR=2.5; 95% CI=1.5–4.3; p=0.001), multilocular tumor (OR=2.9; 95% CI=1.4–6.0; p=0.006), and presence of a solid component in the tumor (OR=3.1; 95% CI=1.8–5.1; p<0.001) were independent risk factors for final pathological diagnosis upgrade. Conclusions: Mixed tumor histology, tumor size >12 cm, multilocular tumor, and presence of a solid component in the tumor were independent risk factors for final pathological diagnosis upgrade based on frozen section diagnosis.

Cite

CITATION STYLE

APA

Park, J. Y., Lee, S. H., Kim, K. R., Kim, Y. T., & Nam, J. H. (2019). Accuracy of frozen section diagnosis and factors associated with final pathological diagnosis upgrade of mucinous ovarian tumors. Journal of Gynecologic Oncology, 30(6). https://doi.org/10.3802/jgo.2019.30.e95

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free