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- W2036082100 abstract "The multicenter International Ovarian Tumor Analysis (IOTA) group has developed prediction models to assist clinicians in the preoperative diagnosis of adnexal masses as benign or malignant. These models have been successfully validated on 2757 patients. The aim of this study was to investigate which histologies were difficult to classify using the prediction model LR1. The 2757 validation patients collected at 21 centers were used. These comprised 312 patients from IOTA phase 1 used to test LR1, 507 patients from an intermediate IOTA phase used for an initial temporal validation, and 1938 patients from IOTA phase 2 used for an extensive temporal and external validation. The adnexal masses were divided into 20 histological categories. The performance of LR1 was assessed using the mean predicted risk of malignancy (MPR, in %) and the percentage correctly classified cases (PC) when using the previously suggested threshold of 10% risk of malignancy to predict malignancy. Fibroma was the most difficult histology to characterize correctly (MPR 35%, PC 32%). Rare benign tumors and abscesses were also difficult (MPR 24% and 18%, PC 49% and 50%). The predicted risk of malignancy for the three stage II borderline tumors in our dataset was at most 19.3%. MPR was relatively low for the other borderline tumors as well, but PC was above 80%. For primary invasive tumors, including stage I cancers, PC exceeded 95%. Not all types of adnexal masses are easily classified by prediction models. Fibromas, abscesses, rare benign tumors and stage II borderline tumors are the most difficult groups to assess. Future research should aim to find predictor variables that can help in the correct classification of these masses." @default.
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- W2036082100 date "2010-10-01" @default.
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- W2036082100 title "OC23.04: Which adnexal masses are difficult to classify as benign or malignant with prediction models?" @default.
- W2036082100 doi "https://doi.org/10.1002/uog.7899" @default.
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