Un panorama actualizado de la dispepsia

La dispepsia es un conjunto de síntomas gastrointestinales superiores, como sensación de plenitud, saciedad temprana, náuseas, ardor o malestar abdominal que se presentan por un mínimo de 4 semanas. Se cree que los mecanismos subyacentes implican anomalías en la motilidad gastrointestinal, hipersensibilidad visceral, alteración del microbiota gastrointestinal, factores genéticos, factores psicológicos (estrés, ansiedad), así como factores dietéticos y ambientales. Se clasifica en dispepsia orgánica y funcional; en éstas existe asociación con la infección por Helicobacter pylori, uso crónico de medicamentos (antinflamatorios no esteroideos), consumo de tabaco y el sexo femenino. Los criterios de Roma IV se utilizan para identificar y clasificar la dispepsia funcional en subtipos según los síntomas, serían: Síndrome de distrés posprandial que presenta plenitud posprandial molesta o saciedad posprandial 3 veces a la semana, y el Síndrome de dolor epigástrico que demuestra al menos dolor y/o ardor epigástrico al menos 1 vez a la semana.  (provisto por Infomedic International)

Dyspepsia is a cluster of upper gastrointestinal symptoms, such as fullness, early satiety, nausea, burning or abdominal discomfort that occur for a minimum of 4 weeks. The underlying mechanisms are thought to involve gastrointestinal motility abnormalities, visceral hypersensitivity, altered gastrointestinal microbiota, genetic factors, psychological factors (stress, anxiety), as well as dietary and environmental factors. It is classified into organic and functional dyspepsia; in the latter there is an association with Helicobacter pylori infection, chronic use of medications (non-steroidal anti-inflammatory drugs), tobacco use and female sex. The Rome IV criteria are used to identify and classify functional dyspepsia into subtypes according to symptoms, which are: Postprandial Distress Syndrome presenting with bothersome postprandial fullness or postprandial satiety 3 times a week, and Epigastric Pain Syndrome demonstrating at least epigastric pain and/or burning at least 1 time a week. (provided by Infomedic International)

The Gail model predicts breast cancer in women with suspicious radiographic lesions.

BACKGROUND: We sought to evaluate whether a woman's 5-year Gail risk adds to the predictive value of the Breast Imaging Reporting and Data System (BI-RADS) classification for the detection of breast cancer. METHODS: We performed a retrospective review of the BI-RADS classifications and pathology results for all image-guided needle breast biopsy examinations over a 3-year period at our institution. The 5-year Gail risk was calculated for eligible patients. Chi-square analysis was used to compare rates of malignancy based on Gail and BI-RADS scores. RESULTS: A total of 632 image-guided needle biopsy examinations were performed in 609 women. A total of 414 women had suspicious (BI-RADS 4) lesions and underwent 424 biopsy examinations. For this subset, women with a Gail risk of less than 1.7% had 21% malignant results, whereas those with a Gail risk of 1.7% or greater had 42% malignant results (relative risk, 1.94; 95% confidence interval, 1.45-2.66). CONCLUSIONS: The Gail model can stratify further the risk for breast cancer in women with suspicious breast imaging reports.

Initial Results of Multigene Panel Testing for Hereditary Breast and Ovarian Cancer and Lynch Syndrome.

Multigene panel testing for hereditary cancer risk has recently become commercially available; however, the impact of its use on patient care is undefined. We sought to evaluate results from implementation of panel testing in a multidisciplinary cancer center. We performed a retrospective review of consecutive patients undergoing genetic testing after initiating use of multigene panel testing at Loma Linda University Medical Center. From February 13 to August 25, 2014, 92 patients were referred for genetic testing based on National Comprehensive Cancer Network guidelines. Testing was completed in 90 patients. Overall, nine (10%) pathogenic mutations were identified: five BRCA1/2, and four in non-BRCA loci. Single-site testing identified one BRCA1 and one BRCA2 mutation. The remaining mutations were identified by use of panel testing for hereditary breast and ovarian cancer. There were 40 variants of uncertain significance identified in 34 patients. The use of panel testing more than doubled the identification rate of clinically significant pathogenic mutations that would have been missed with BRCA testing alone. The large number of variants of uncertain significance identified will require long-term follow-up for potential reclassification. Multigene panel testing provides additional information that may improve patient outcomes.

Disparities in BRCA testing: when insurance coverage is not a barrier.

BACKGROUND: Strategies to reduce the risk of developing breast and ovarian cancer in carriers of deleterious BRCA 1 and 2 mutations are readily available. However, many people who are at high risk of having these genetic mutations are reluctant to obtain the test. We sought to identify factors associated with choice of testing. METHODS: We performed a retrospective cohort review of high-risk patients referred to a multidisciplinary breast health center for BRCA testing between January 2001 and March 2008. Demographic variables were compared by using logistic regression between those who completed genetic testing and those who did not. RESULTS: A total of 213 patients were referred for BRCA testing. The mean age was 49.2 years (range, 16-84 y). Five patients were male. The majority of individuals (63.4%) were white, 15% were Hispanic, 6.6% were black, and 4.7% were Asian. Insurance coverage for testing was available in 91.1% of patients, of whom 49.2% had private insurance, 26.7% had managed care insurance, and 24.1% had government-sponsored insurance. A total of 111 patients (52.1%) underwent testing. On multivariate analysis, patients were significantly more likely to complete testing if they had a personal history of breast cancer (73.0% of tested patients) (P = .005) and had at least some college education (61.3%) (P = .03). There were no statistically significant differences in tested versus untested groups by age, race, language, family history, parity, marital status, religion, socioeconomic status, or insurance status. Of patients whose insurance plans offered coverage for genetic testing, 51.4% underwent testing and 48.6% did not (P = not significant [NS]). Of those who had no insurance coverage for testing, 41.2% underwent testing and 58.9% did not (P = NS). CONCLUSIONS: Our data show that half of those patients at risk for carrying a BRCA mutation do not undergo testing. Insurance coverage for genetic testing does not influence the decision to test. Developing counseling instruments that explain the benefits of testing to unaffected high-risk individuals or targeted to those with a high school level education may be a strategy to improve testing rates.