Objective: The need to perform genetic sequencing to diagnose the polymerase epsilon exonuclease (POLE) subtype of endometrial cancer (EC) hinders the adoption of molecular classification. We investigated clinicopathologic and protein markers that distinguish the POLE from the copy number (CN)-low subtype in EC. Methods: Ninety-one samples (15 POLE, 76 CN-low) were selected from The Cancer Genome Atlas EC dataset. Clinicopathologic and normalized reverse phase protein array expression data were analyzed for associations with the subtypes. A logistic model including selected markers was constructed by stepwise selection using area under the curve (AUC) from 5-fold cross-validation (CV). The selected markers were validated using immunohistochemistry (IHC) in a separate cohort. Results: Body mass index (BMI) and tumor grade were significantly associated with the POLE subtype. With BMI and tumor grade as covariates, 5 proteins were associated with the EC subtypes. The stepwise selection method identified BMI, cyclin B1, caspase 8, and X-box binding protein 1 (XBP1) as markers distinguishing the POLE from the CN-low subtype. The mean of CV AUC, sensitivity, specificity, and balanced accuracy of the selected model were 0.97, 0.91, 0.87, and 0.89, respectively. IHC validation showed that cyclin B1 expression was significantly higher in the POLE than in the CN-low subtype and receiver operating characteristic curve of cyclin B1 expression in IHC revealed AUC of 0.683. Conclusion BMI and expression of cyclin B1, caspase 8, and XBP1 are candidate markers distinguishing the POLE from the CN-low subtype. Cyclin B1 IHC may replace POLE sequencing in molecular classification of EC.

Background: A coronavirus disease 2019 (COVID-19) outbreak started in February 2020 and was controlled at the end of March 2020 in Daegu, the epicenter of the coronavirus outbreak in Korea. The aim of this study was to describe the clinical course and outcomes of patients with COVID-19 in Daegu. Methods: In collaboration with Daegu Metropolitan City and Korean Center for Diseases Control, we conducted a retrospective, multicenter cohort study. Demographic, clinical, treatment, and laboratory data, including viral RNA detection, were obtained from the electronic medical records and cohort database and compared between survivors and non-survivors. We used univariate and multi-variable logistic regression methods and Cox regression model and performed Kaplan–Meier analysis to determine the risk factors associated with the 28-day mortality and release from isolation among the patients. Results: In this study, 7,057 laboratory-confirmed patients with COVID-19 (total cohort) who had been diagnosed from February 18 to July 10, 2020 were included. Of the total cohort, 5,467 were asymptomatic to mild patients (77.4%) (asymptomatic 30.6% and mild 46.8%), 985 moderate (14.0%), 380 severe (5.4%), and 225 critical (3.2%). The mortality of the patients was 2.5% (179/7,057). The Cox regression hazard model for the patients with available clinical information (core cohort) (n = 2,254) showed the risk factors for 28-day mortality: age > 70 (hazard ratio [HR], 4.219, P = 0.002), need for O 2 supply at admission (HR, 2.995; P = 0.001), fever (> 37.5°C) (HR, 2.808; P = 0.001), diabetes (HR, 2.119; P = 0.008), cancer (HR, 3.043; P = 0.011), dementia (HR, 5.252; P = 0.008), neurological disease (HR, 2.084; P = 0.039), heart failure (HR, 3.234;P = 0.012), and hypertension (HR, 2.160; P = 0.017). The median duration for release from isolation was 33 days (interquartile range, 24.0–46.0) in survivors. The Cox proportional hazard model for the long duration of isolation included severity, age > 70, and dementia. Conclusion Overall, asymptomatic to mild patients were approximately 77% of the total cohort (asymptomatic, 30.6%). The case fatality rate was 2.5%. Risk factors, including older age, need for O 2 supply, dementia, and neurological disorder at admission, could help clinicians to identify COVID-19 patients with poor prognosis at an early stage.

PURPOSE: Discovery of models predicting the exact prognosis of epithelial ovarian cancer (EOC) is necessary as the first step of implementation of individualized treatment. This study aimed to develop nomograms predicting treatment response and prognosis in EOC. MATERIALS AND METHODS: We comprehensively reviewed medical records of 866 patients diagnosed with and treated for EOC at two tertiary institutional hospitals between 2007 and 2016. Patients’ clinico-pathologic characteristics, details of primary treatment, intra-operative surgical findings, and survival outcomes were collected. To construct predictive nomograms for platinum sensitivity, 3-year progression-free survival (PFS), and 5-year overall survival (OS), we performed stepwise variable selection by measuring the area under the receiver operating characteristic curve (AUC) with leave-one-out cross-validation. For model validation, 10-fold cross-validation was applied. RESULTS: The median length of observation was 42.4 months (interquartile range, 25.7 to 69.9 months), during which 441 patients (50.9%) experienced disease recurrence. The median value of PFS was 32.6 months and 3-year PFS rate was 47.8% while 5-year OS rate was 68.4%. The AUCs of the newly developed nomograms predicting platinum sensitivity, 3-year PFS, and 5-year OS were 0.758, 0.841, and 0.805, respectively. We also developed predictive nomograms confined to the patients who underwent primary debulking surgery. The AUCs for platinum sensitivity, 3-year PFS, and 5-year OS were 0.713, 0.839, and 0.803, respectively. CONCLUSION: We successfully developed nomograms predicting treatment response and prognosis of patients with EOC. These nomograms are expected to be useful in clinical practice and designing clinical trials.
Area Under Curve ; Disease-Free Survival ; Humans ; Medical Records ; Nomograms ; Ovarian Neoplasms ; Platinum ; Prognosis ; Recurrence ; ROC Curve

Objective: To compare survival outcomes between bevacizumab (BEV) and olaparib (OLA) maintenance therapy in BRCA-mutated, platinum-sensitive relapsed (PSR) high-grade serous ovarian carcinoma (HGSOC). Methods: From 10 institutions, we identified HGSOC patients with germline and/or somatic BRCA1/2 mutations, who experienced platinum-sensitive recurrence between 2013 and 2019, and received second-line platinum-based chemotherapy. Patients were divided into BEV (n=29), OLA (n=83), and non-BEVon-OLA users (n=36). The OLA and non-BEVon-OLA users were grouped as the OLA intent group. We conducted 1:2 nearest neighbor-matching between the BEV and OLA intent groups, setting the proportion of OLA users in the OLA intent group from 65% to 100% at 5% intervals, and compared survival outcomes among the matched groups. Results: Overall, OLA users showed significantly better progression-free survival (PFS) than BEV users (median, 23.8 vs. 17.4 months; p=0.004). Before matching, PFS improved in the OLA intent group but marginal statistical significance (p=0.057). After matching, multivariate analyses adjusting confounders identified intention-to-treat OLA as an independent favorable prognostic factor for PFS in the OLA 65P (adjusted hazard ratio [aHR]=0.505; 95% confidence interval [CI]=0.280−0.911; p=0.023) to OLA 100P (aHR=0.348; 95% CI=0.184−0.658; p=0.001) datasets. The aHR of intention-to-treat OLA for recurrence decreased with increasing proportions of OLA users. No differences in overall survival were observed between the BEV and OLA intent groups, and between the BEV and OLA users. Conclusion Compared to BEV, intention-to-treat OLA and actual use of OLA maintenance therapy were significantly associated with decreased disease recurrence risk in patients with BRCA-mutated, PSR HGSOC.