Calingaert, Brian

Abstract Study Objectives Narcolepsy is a chronic condition affecting the sleep/wake cycle that is challenging to diagnose. Epidemiological data from large US-focused studies remain limited, with no validated claims-based case selection definitions for narcolepsy. We estimated the prevalence/incidence of diagnosed narcolepsy (type 1 [NT1], type 2 [NT2], overall) in an insured US population using validated, claims-based narcolepsy case definitions. Materials and Methods This observational study used HealthVerity administrative claims-linked electronic medical records to develop case definitions identifying individuals with NT1, NT2, and overall narcolepsy from diagnosis, medication, and procedure codes. Claims-based case definition performance (NT1, NT2, overall narcolepsy) was assessed using positive predictive values (PPVs). Prevalence (per 100 000 persons, on December 31, 2023) and annual incidence (per 100 000 person-years [PY], 2020 − 2023) were calculated/adjusted using PPVs for each case definition. Results Unadjusted point prevalence among individuals with ≥12 months of continuous enrollment were 15.5/100 000 (NT1), 51.1/100 000 (NT2), and 67.0/100 000 (overall narcolepsy). Unadjusted incidence rates were stable from 2020 − 2023 for NT1 (range, 2.0 − 2.3/100 000 PY) but declined across years for NT2 (9.1 − 7.6/100 000 PY) and overall narcolepsy (11.3 − 9.6/100 000 PY). PPVs (95% confidence interval) of NT1, NT2, and overall narcolepsy were 0.81 (0.72 − 0.88), 0.84 (0.75 − 0.91), and 0.80 (0.71 − 0.87), contributing to epidemiologic estimates being reduced by ~20% after PPV adjustment. Prevalence and incidence were higher in females than males. Individuals with NT1 were ~ 4 years younger versus NT2. Conclusions Validated definitions for narcolepsy can reduce potential misclassification. Our findings highlight a relatively low NT1 prevalence in the US. In contrast, NT2 prevalence estimates were > 3 times higher than NT1.

Abstract The p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r2 = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07–1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01–1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region. [Cancer Res 2009;69(6):2349–57]

AbstractOver 22,000 cases of ovarian cancer were diagnosed in 2007 in the United States, but only a fraction of them can be attributed to mutations in highly penetrant genes such as BRCA1. To determine whether low-penetrance genetic variants contribute to ovarian cancer risk, we genotyped 1,536 single nucleotide polymorphisms (SNP) in several candidate gene pathways in 848 epithelial ovarian cancer cases and 798 controls in the North Carolina Ovarian Cancer Study (NCO) using a customized Illumina array. The inflammation gene interleukin-18 (IL18) showed the strongest evidence for association with epithelial ovarian cancer in a gene-by-gene analysis (P = 0.002) with a <25% chance of being a false-positive finding (q value = 0.240). Using a multivariate model search algorithm over 11 IL18 tagging SNPs, we found that the association was best modeled by rs1834481. Further, this SNP uniquely tagged a significantly associated IL18 haplotype and there was an increased risk of epithelial ovarian cancer per rs1834481 allele (odds ratio, 1.24; 95% confidence interval, 1.06-1.45). In a replication stage, 12 independent studies from the Ovarian Cancer Association Consortium (OCAC) genotyped rs1834481 in an additional 5,877 cases and 7,791 controls. The fixed effects estimate per rs1834481 allele was null (odds ratio, 0.99; 95% confidence interval, 0.94-1.05) when data from the 12 OCAC studies were combined. The effect estimate remained unchanged with the addition of the initial North Carolina Ovarian Cancer Study data. This analysis shows the importance of consortia, like the OCAC, in either confirming or refuting the validity of putative findings in studies with smaller sample sizes. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3567–72)