ABSTRACT
BACKGROUND: Uterine leiomyomata (fibroids) affect up to 77% of women by menopause and account for $9.4 billion in yearly healthcare costs. Most studies rely on self-reported diagnosis, which may result in misclassification of controls since as many as 50% of cases are asymptomatic and thus undiagnosed. Our objective was to evaluate the performance and accuracy of a fibroid phenotyping algorithm constructed from electronic medical record (EMR) data, limiting to subjects with pelvic imaging. METHODS: Our study population includes women from a clinical population at Vanderbilt University Medical Center (2008-2012). Analyses were restricted to women 18 years and older with at least one fibroid diagnosis confirmed by imaging for cases or at least two separate pelvic imaging procedures without a diagnosis for controls. We randomly reviewed 218 records to evaluate the accuracy of our algorithm and assess the indications for pelvic imaging. Participant characteristics and indications for imaging were compared between cases and controls in unadjusted and adjusted logistic regression analyses. RESULTS: Our algorithm had a positive predictive value of 96% and negative predictive value of 98%. Increasing age (odds ratio=1.05, 95% confidence interval 1.03-1.08) and Black race (odds ratio=2.15, 95% confidence interval 1.18-3.94) were identified as risk factors for fibroids. The most common indications for imaging in both cases and controls were pain, bleeding, and reproductive factors, and the most common imaging modality was a pelvic ultrasound. CONCLUSIONS: These data suggest that using biorepositories linked to EMR data is a feasible way to identify populations of imaged women that facilitate investigations of fibroid risk factors.
Subject(s)
Algorithms , Electronic Health Records , Leiomyoma/diagnosis , Pelvic Pain/diagnostic imaging , Uterine Neoplasms/diagnosis , Adolescent , Adult , Age Factors , Aged , Black People/statistics & numerical data , Case-Control Studies , Female , Humans , Magnetic Resonance Imaging , Middle Aged , Pelvic Pain/etiology , Phenotype , Predictive Value of Tests , Retrospective Studies , Risk Factors , Tomography, X-Ray Computed , UltrasonographyABSTRACT
Because Helicobacter pylori persist for decades in the human stomach, the aim of this study was to examine the long-term course of H. pylori-specific serum immunoglobulin G (IgG) responses with respect to subclass and antigenic target. We studied paired serum samples obtained in 1973 and in 1994 in Vammala, Finland, from 64 healthy H. pylori-positive adults and from other healthy control subjects. H. pylori serum immunoglobulin A, IgG, and IgG subclass responses were determined by antigen-specific enzyme-linked immunosorbent assays. H. pylori-specific IgG1 and IgG4 subtype responses from 47 subjects were similar in 1973 and 1994, but not when compared with unrelated persons. H. pylori-specific IgG1:IgG4 ratios among the participants varied >1000-fold; however, 57 (89.1%) of 64 subjects had an IgG1:IgG4 ratio >1.0, consistent with a predominant IgG1 (Th1) response. Furthermore, ratios in individual hosts were stable over the 21-year period (r = 0.56; P < .001). The immune response to heat shock protein HspA was unchanged in 49 (77%) of the 64 subjects tested; of the 15 whose serostatus changed, all seroconverted and were significantly younger than those whose status did not change. These findings indicate that H. pylori-specific antibody responses are host-specific with IgG1:IgG4 ratios stable over 21 years, IgG1 responses predominating, and HspA seroconversion with aging.