DOI 10.1016/j.ygyno.2024.06.007
Uterine perivascular epithelioid cell tumors (PEComa) and the accuracy of proposed classification systems in predicting the malignant versus non-malignant behavior.
Аннотация
OBJECTIVE
To compare the accuracy of available classification systems (Folpe, modified Folpe, Bennet, and Schoolmester) in predicting the behavior of uterine Perivascular Epithelioid Cell tumors (PEComas).
METHODS
We reviewed the pathology registry to identify all uterine PEComas treated at our center. We conducted a systematic literature review searching electronic databases from inception to November 2023. We included all references reporting at least one case of uterine PEComa; cases associated with tuberous sclerosis complex were excluded. Patient-level data were extracted by identified records. Survival analysis was used to assess the accuracy of all proposed classification systems to classify uterine PEComas as malignant versus non-malignant.
RESULTS
Six uterine PEComas were treated at our center. The literature search identified 101 uterine PEComas from 32 studies. Eighty-five out of 107 PEComas (28 studies and our series) reported enough follow-up data and details to apply all four classifications. The modified Folpe classification demonstrated the highest hazard ratio (HR) for relapse (HR:8.63; 95% confidence interval [CI] 2.06-36.1) and death due to PEComa (HR:6.8, 95%CI:0.89-51.6) for malignant versus non-malignant PEComas. Changing the cut-off of PEComa size to ≥8 cm and mitotic figures per 50 high power fields to ≥5, the HR for recurrence lowered (HR:6.26; 95% CI 2.20-17.80), but HR for death increased (HR:10.3; 95% CI 1.35-77.80).
CONCLUSIONS
The modified Folpe classification was the most accurate in predicting the PEComa behavior. Changing the cut-off of PEComa size and number of mitotic figures may improve the accuracy in predicting death due to disease.
Предметные рубрики MeSH
Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Ошибки и ограничения
История · было → стало
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