Malignancy risk scoring of hydatidiform moles.

Several risk factors leading to malignant transformation of hydatidiform moles have been described previously. Many studies showed that prophylactic chemotherapy for high risk hydatidiform moles could significantly decrease the incidence of malignancy. Thus, it is essential to discover a breakthrough to determine patients with high risk malignancy so that prophylactic chemotherapy can be started as soon as possible.
Development of a scoring system of risk factors as a predictor of hydatidiform mole malignant transformation.
This research is a case control study with hydatidiform mole and choriocarcinoma patients as subjects. Multiple logistic regression was used to analyze the data. Odds ratios (OR), attributable at risk (AR : OR-1) and risk index (ARxβ) were calculated for develoipment of a scoring system of malignancy risk. The optimal cut-off point was determined using receiver operating characteristic (ROC) curve.
This study analyzed 34 choriocarcinoma cases and 68 benign hydatidiform mole cases. Four factors significantly increased the risk of malignancy, namely age≥35 years old (OR:4.41, 95%CI:1.07- 16.09, risk index 5); gestational age≥12 weeks (OR:11.7, 95%CI:1.8-72.4, risk index 26); uterine size greater than the gestational age (OR:10.2, 95%CI:2.8-36.6, risk index 21); and histopathological grade II-III (OR:3.4, 95%CI:1.1-10.6, risk index 3). The lowest and the highest scores for the risk factors were zero and 55, respectively. The best cut-off point to decide high risk malignancy patients was ≥31.
Malignant transformation of hydatidiform moles can be predicted using the risk scoring by analyzing the above four parameters. Score≥31 implies high risk patients so that prophylactic chemotherapy can be promptly administered for prevention.
AuthorsHeru Pradjatmo, Djaswadi Dasuki, Ery Kus Dwianingsih, Ediati Triningsih
JournalAsian Pacific journal of cancer prevention : APJCP (Asian Pac J Cancer Prev) Vol. 16 Issue 6 Pg. 2441-5 ( 2015) ISSN: 1513-7368 [Print] Thailand
PMID25824778 (Publication Type: Journal Article)

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