Purpose: To characterize the somatic mutational landscape, investigate associations between genetic alterations and clinical outcomes, and determine the prevalence of pathogenic germline mutations in low-grade serous ovarian carcinomas (LGSCs). Experimental design: Patients with LGSC tumors that underwent panel-based sequencing of up to 505 genes were identified. Data on somatic and germline mutations, copy number alterations, and clinicopathologic features, including age at diagnosis, platinum sensitivity, and overall survival (OS), were collected. Results: Following central pathology re-review, 119 patients with LGSC were identified for analysis. One hundred ten (92%) had advanced-stage disease (stages III/IV). Somatic KRAS (33%), NRAS (11%), EIF1AX (10%), and BRAF (11%) alterations were the most common; mitogen-activated protein kinase (MAPK) pathway alterations were found in 60% (n=71) of LGSCs. KRAS mutations were significantly associated with age at diagnosis >50 years (p=0.02) and platinum-sensitive disease (p=0.03). On multivariate analysis, MAPK pathway alterations (p=0.02) and platinum sensitivity (p=0.005) were significantly associated with improved OS. Seventy-nine patients (66%) underwent germline genetic testing; 7 pathogenic germline mutations, including 1 bi-allelic MUTYH mutation (c.1187G>A (p.Gly396Asp)) and 6 mono-allelic alterations, were identified. Somatic loss of the wildtype allele (loss of heterozygosity) in the tumor at the locus of the germline mutation was only observed in the bi-allelic MUTYH mutation carrier. There were no germline BRCA1/2 mutations. Conclusions: This study showed MAPK pathway alterations in LGSC, including KRAS mutations, are independently associated with platinum sensitivity and prolonged survival. Germline data, which were limited, identified few pathogenic germline mutations in patients with LGSC.

Diabetes heightens the risk of wound healing complications among patients undergoing implant-based reconstruction.

No abstract

No abstract

No abstract

No abstract

Background: The Medicaid Analytic eXtract (MAX) is a health care utilization database from publicly insured individuals that has been used for studies of drug safety in pregnancy. Claims-based algorithms for defining many important maternal and neonatal outcomes have not been validated.Objective: To validate claims-based algorithms for identifying selected pregnancy outcomes in MAX using hospital medical records. Methods:The medical records of mothers who delivered between 2000 and 2010 within a single large healthcare system were linked to their claims in MAX. Claimsbased algorithms for placental abruption, preeclampsia, postpartum hemorrhage, small for gestational age, and noncardiac congenital malformation were defined. Fifty randomly sampled cases for each outcome identified using these algorithms were selected, and their medical records were independently reviewed by two physicians to confirm the presence of the diagnosis of interest; disagreements were resolved by a third physician reviewer. Positive predictive values (PPVs) and 95% confidence intervals (CIs) of the claims-based algorithms were calculated using medical records as the gold standard.Results: The linked cohort included 10,899 live-birth pregnancies. The PPV was 92% (95% CI, 82%-97%) for placental abruption, 82% (95% CI, 70%-91%) for preeclampsia, 74% (95% CI, 61%-85%) for postpartum hemorrhage, 92% (95% CI, 82%-97%) for small for gestational age, and 86% (95% CI, 74%-94%) for noncardiac congenital malformation.Conclusions: Across the perinatal outcomes considered, PPVs ranged between 74% and 92%. These PPVs can inform bias analyses that correct for outcome misclassification. K E Y W O R D S databases, pharmacoepidemiology, pregnancy, validation

No abstract