Continuous EBM education through small-group discussion and learner-centred, problem-based self-practice can be a useful way to improve a medical student's knowledge, attitudes and skills.

Background: An hCG regression curve has been used to predict the natural history and response to chemotherapy in gestational trophoblastic disease. We constructed hCG regression curves in high-risk gestational trophoblastic neoplasia (GTN) treated with EMA/CO and identified an optimal hCG level to detect EMA/CO resistance in GTN. Materials and Methods: Eighty-one women with GTN treated with EMA/CO were classified as primary high-risk GTN (n = 65) and single agent-resistance GTN (n = 16). The hCG levels prior to each course of chemotherapy were plotted in the 10th, 50th, and 90th percentiles to construct the hCG regression curves. Diagnostic performance was evaluated for an optimal cut-off value. Results: The median hCG levels were 264,482 mIU/mL mIU/mL and 495.5 mIU/mL mIU/mL for primary high-risk GTN and single agent-resistance GTN, respectively. The 50th percentile of the hCG level in primary high-risk GTN and single agent-resistance turned to normal before the 4th and the 2nd course of chemotherapy, respectively. The 90th percentile of the hCG level in primary high-risk GTN and single agent-resistance turned to normal before the 9th and the 2nd course of chemotherapy, respectively. The hCG level of ≥ 118.6 mIU/mL mIU/mL at the 5thcourse of EMA/CO predicted the EMA/CO resistance in primary high-risk GTN patients with a sensitivity of 85.7% and a specificity of 100%. Conclusion: EMA/CO resistance in primary high-risk GTN can be predicted by using an hCG regression curve in combination with the cut-off value of 118.6 mIU/mL at the 5thcourse of chemotherapy.

To assess the predictive value of the preoperative modified frailty index (mFI) for postoperative complications in endometrial carcinoma, and to evaluate the risk factors associated with complications, and to compare the predictive properties of mFI with the American Society of Anesthesiologists (ASA) Physical Status classification. MethodsA total of 364 patients with endometrial cancer who underwent primary surgery between January 2009and December 2016 were examined. The prognostic value of mFI in predicting severe postoperative complications, assessed according to the Clavien-Dindo classification, was analyzed and compared with ASA status. The risk factors for adverse outcomes were determined using multivariate analysis. ResultsThe 30-day postoperative surgical-or medical-related complication rate was 26.6%. The rates of postoperative complications were 1.3%, 8.8%, 12.2%, and 60.0% for mFI scores of 0, 1, 2, and ≥3, respectively (P<0.001). The odds ratios for predicting postoperative complications in patients with mFI scores of 1, 2, and ≥3 were 7. 38, 10.59, and 114.75, respectively. In the multivariate analysis, the significant predictive factors for postoperative complications were mFI ≥1, body mass index (BMI) ≥30 kg/m 2 , and non-endometrioid cell type. At cut-off points of mFI ≥1 and ASA ≥2, both tools had similar sensitivities but mFI was more specific (sensitivities 92.9% vs. 100%; specificity 45.5% vs. 19.4%). ConclusionmFI provides a satisfactory predictive value for postoperative complications. Patients with an mFI score ≥1, a BMI ≥30 kg/m 2 , and a non-endometrioid subtype, are at risk of postoperative complications and should receive comprehensive preoperative and postoperative management.

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Mucinous ovarian carcinomas (MOCs) are not uncommon and account for 9.0%-18.5% of all epithelial ovarian carcinomas. [1][2][3] According to the National Comprehensive Cancer Network (NCCN) and International Federation of Gynecology and Obstetrics (FIGO) guidelines, in the past, 4,5 patients diagnosed with MOCs should undergo appendectomy to eliminate possible primary appendiceal tumors, detect occult metastases in apparently early-stage disease, and achieve optimal cytoreduction. 4-6 However, the results from a recent metaanalysis suggest that appendectomy of a grossly normal appendix in