Introduction: Benign and precancerous endometrial hyperplasias (EH) are differentiated according to two alternative histomorphologic classifications: World Health Organization (WHO) or endometrial intraepithelial neoplasia (EIN) system. The 2017 European Society of Gynaecological Oncology guidelines recommend paired box 2 protein (PAX2) immunohistochemistry to identify precancerous EH. However, methods for interpreting immunostaining and diagnostic accuracy are not defined, and the role of PAX2 in endometrial carcinogenesis is unclear. We aimed to assess: (a) PAX2 expression throughout endometrial carcinogenesis, from normal endometrium to benign EH, precancerous EH, and endometrial cancer (EC); (b) the diagnostic accuracy of PAX2 immunohistochemistry in diagnosing precancerous EH, defining criteria for its use.

Material And Methods: Electronic databases were searched for from their inception to July 2018. All studies evaluating PAX2 immunohistochemistry in normal endometrium, EH, and EC were included. Univariate comparisons of PAX2 expression were performed with Fisher's exact test (significant P < .05). Sensitivity, specificity, positive and negative likelihood ratio, diagnostic odds ratio (DOR), and area under the curve on summary receiver operating characteristic curves were calculated. Subgroup analyses were based on expression thresholds (decrease vs complete loss) and classifications used (WHO vs EIN).

Results: Six studies with 266 normal endometrium, 586 EH, and 114 EC were included. Both decrease and complete loss of PAX2 expression were significantly more common in EC and precancerous EH than benign EH. Diagnostic accuracy was moderate for both PAX2 complete loss and decrease (areas under the curve 0.829 and 0.876, respectively). PAX2 complete loss with EIN system showed the best results (sensitivity = 0.72; specificity = 0.95; DOR = 43.13).

Conclusions: PAX2 seems to behave as a tumor suppressor in endometrial carcinogenesis. PAX2 is an accurate marker of precancerous EH; complete loss of PAX2 and EIN classification appear as the optimal diagnostic criteria.

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http://dx.doi.org/10.1111/aogs.13512DOI Listing

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