Elizabeth G. Hill

Characteristics of Symptomatic Reflux Episodes on Acid Suppressive Therapy

BACKGROUND:Persistent symptoms on acid suppressive therapy are due to either acid or nonacid gastroesophageal reflux (GER) episodes or are not related to reflux.AIM:To compare physical and chemical characteristics of GER episodes associated with symptoms in patients on acid suppressive therapy.METHODS:Patients with persistent symptoms on acid suppressive therapy underwent combined impedance-pH monitoring. Reflux episodes were classified as acid if nadir pH was <4.0, and nonacid if it remained at ≥4.0, separated into liquid-only or mixed (liquid-gas), and considered to reach the proximal esophagus if liquid was present 15 cm above the lower esophageal sphincter (LES). Reflux episodes were considered symptomatic if patients recorded a symptom within 5 min after the reflux episode. Risk factors of symptomatic reflux episodes were identified using multivariable generalized estimating equations (GEEs).RESULTS:One hundred twenty patients (85 women, median age 54 yr, range 18–85 yr) recorded 3,547 reflux episodes (84.3% nonacid, 50.6% mixed), of which 468 (13.2%) were symptomatic. Based on multivariable GEE analysis with episode-level symptom status (symptomatic vs nonsymptomatic) as the outcome variable, reflux episode acidity was not significantly associated with symptoms (P = 0.40). Mixed reflux episodes were significantly associated with symptoms relative to liquid-only episodes (odds ratio [OR] 1.49, 95% confidence interval [CI] 1.19–1.87, P = 0.0005), as were reflux episodes reaching the proximal esophagus compared with those reaching the distal esophagus only (OR 1.28, 95% CI 1.06–1.55, P = 0.012).CONCLUSION:The majority of reflux episodes on acid suppressive therapy are asymptomatic. Reflux episodes extending proximally and having a mixed (liquid-gas) composition are significantly associated with symptoms, irrespective of whether pH is acid (<4) or nonacid (≥4).

Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA

Statistical tools enable unified analysis of data from multiple global proteomic experiments, producing unbiased estimates of normalization terms despite the missing data problem inherent in these studies. The modeling approach, implementation, and useful visualization tools are demonstrated via a case study of complex biological samples assessed using the iTRAQ relative labeling protocol.

Use of Biomarkers to Guide Decisions on Systemic Therapy for Women With Metastatic Breast Cancer: American Society of Clinical Oncology Clinical Practice Guideline

PURPOSE To provide recommendations on the appropriate use of breast tumor biomarker assay results to guide decisions on systemic therapy for metastatic breast cancer. METHODS A literature search and prospectively defined study selection identified systematic reviews, meta-analyses, randomized controlled trials (RCTs), prospective-retrospective studies, and prospective comparative observational studies published from 2006 through September 2014. RESULTS The literature search revealed 17 articles that met criteria for further review: 11 studies reporting discordances between primary tumors and metastases in expression of hormone receptors or human epidermal growth factor receptor 2 (HER2), one RCT that addressed the use of a biomarker to decide whether to change or continue a treatment regimen, and five prospective-retrospective studies that evaluated the clinical utility of biomarkers. RECOMMENDATIONS In patients with accessible metastases, biopsy for confirmation of disease process and retesting of estrogen receptor, progesterone receptor, and HER2 status should be offered, but evidence is lacking to determine whether changing anticancer treatment on the basis of change in receptor status affects clinical outcomes. With discordance of results between primary and metastatic tissues, the Panel consensus is to use preferentially the estrogen receptor, progesterone receptor, and HER2 status of the metastasis to direct therapy if supported by the clinical scenario and patients goals for care. Carcinoembryonic antigen, cancer antigen 15-3, and cancer antigen 27-29 may be used as adjunctive assessments, but not alone, to contribute to decisions regarding therapy. Recommendations for tumor rebiopsy and use of circulating tumor markers are based on clinical experience and Panel informal consensus in the absence of studies designed to evaluate the clinical utility of the markers. As such, it is also reasonable for clinicians to not use these markers as adjunctive assessments.

A small molecule inhibitor of Pim protein kinases blocks the growth of precursor T-cell lymphoblastic leukemia/lymphoma

The serine/threonine Pim kinases are up-regulated in specific hematologic neoplasms, and play an important role in key signal transduction pathways, including those regulated by MYC, MYCN, FLT3-ITD, BCR-ABL, HOXA9, and EWS fusions. We demonstrate that SMI-4a, a novel benzylidene-thiazolidine-2, 4-dione small molecule inhibitor of the Pim kinases, kills a wide range of both myeloid and lymphoid cell lines with precursor T-cell lymphoblastic leukemia/lymphoma (pre-T-LBL/T-ALL) being highly sensitive. Incubation of pre-T-LBL cells with SMI-4a induced G1 phase cell-cycle arrest secondary to a dose-dependent induction of p27(Kip1), apoptosis through the mitochondrial pathway, and inhibition of the mammalian target of rapamycin C1 (mTORC1) pathway based on decreases in phospho-p70 S6K and phospho-4E-BP1, 2 substrates of this enzyme. In addition, treatment of these cells with SMI-4a was found to induce phosphorylation of extracellular signal-related kinase1/2 (ERK1/2), and the combination of SMI-4a and a mitogen-activated protein kinase kinase 1/2 (MEK1/2) inhibitor was highly synergistic in killing pre-T-LBL cells. In immunodeficient mice carrying subcutaneous pre-T-LBL tumors, treatment twice daily with SMI-4a caused a significant delay in the tumor growth without any change in the weight, blood counts, or chemistries. Our data suggest that inhibition of the Pim protein kinases may be developed as a therapeutic strategy for the treatment of pre-T-LBL.

Maternal super-obesity (body mass index ≥ 50) and adverse pregnancy outcomes

Objective. To determine if pregnancy complications are increased in super‐obese (a body mass index (BMI) of 50 or more) compared to other, less obese parturients. Design. Cross‐sectional study. Setting and population. All 19,700 eligible women, including 425 (2.2%) super‐obese women with singleton births between 1996 and 2007 delivering at a tertiary referral center, identified using a perinatal research database. Methods. Bivariate and trend analyses were used to assess the relation between super‐obesity and various pregnancy complications compared to other well‐established BMI categories. Adjusted odds ratios (ORs) were calculated using multivariable logistic regression techniques. Main outcome measures. Outcomes for adjusted and unadjusted analyses were small‐for‐gestational age (SGA) birth, large‐for‐gestational age (LGA) birth, preeclampsia, gestational diabetes mellitus (GDM), fetal death, preterm birth, placental abruption, cesarean delivery, and Apgar scores < 7. Results. Compared to all other obese and non‐obese women, super‐obese women had the highest rates of preeclampsia, GDM, LGA, and cesarean delivery (all p < 0.05 for trend test). Super‐obesity was also associated with a 44% reduction in SGA compared to all other women (OR 0.55, 95% confidence interval (CI) 0.40–0.76) and a 25% reduction compared to other, less obese women (OR 0.75, 95% CI 0.54–1.03). Super‐obesity was positively associated with LGA, GDM, preeclampsia, cesarean delivery, and a 5‐minute Apgar score < 7 compared to all other women after controlling for important confounders. Conclusion. Super‐obesity is associated with higher rates of pregnancy complications compared to women of all other BMI classes, including other obese women.

A Statistical Model for iTRAQ Data Analysis

We describe biological and experimental factors that induce variability in reporter ion peak areas obtained from iTRAQ experiments. We demonstrate how these factors can be incorporated into a statistical model for use in evaluating differential protein expression and highlight the benefits of using analysis of variance to quantify fold change. We demonstrate the models utility based on an analysis of iTRAQ data derived from a spike-in study.

Evaluation of 32 urine biomarkers to predict the progression of acute kidney injury after cardiac surgery

Biomarkers for acute kidney injury (AKI) have been used to predict the progression of AKI but a systematic comparison of the prognostic ability of each biomarkers alone or in combination has not been performed. In order to assess this, we measured the concentration of 32 candidate biomarkers in the urine of 95 patients with AKIN stage 1 after cardiac surgery. Urine markers were divided into eight groups based on the putative pathophysiologic mechanism they reflect. We then compared the ability of the markers alone or in combination to predict the primary outcome of worsening AKI or death (23 patients) and the secondary outcome of AKIN stage 3 or death (13 patients). IL-18 was the best predictor of both outcomes (AUC of 0.74 and 0.89). L-FABP (AUC of 0.67 and 0.85), NGAL (AUC of 0.72 and 0.83) and KIM-1 (AUC of 0.73 and 0.81) were also good predictors. Correlation between most of the markers was generally related to their predictive ability but KIM-1 had a relatively weak correlation with other markers. The combination of IL-18 and KIM-1 had a very good predictive value with an AUC of 0.93 to predict AKIN 3 or death. Thus, combination of IL-18 and KIM-1 would result in improved identification of high risk patients for enrollment in clinical trials.

Violence and PTSD in Mexico Gender and regional differences

ObjectiveWe examined the lifetime prevalence of violence in Mexico and how different characteristics of the violent event effect the probability of meeting criteria for lifetime post-traumatic stress disorder (PTSD).MethodWe interviewed a probability sample of 2,509 adults from 4 cities in Mexico (Oaxaca, Guadalajara, Hermosillo, Mérida) using the Composite International Diagnostic Interview (CIDI).ResultsLifetime prevalence of violence was 34%. Men reported more single-experience, recurrent, physical, adolescent, adulthood, and stranger violence; women more sexual, childhood, family, and intimate partner violence. Prevalence was generally higher in Guadalajara, though the impact was greater in Oaxaca compared to other cities. Of those exposed, 11.5% met DSM-IV criteria for PTSD. Probabilities were highest after sexual and intimate partner violence, higher for women than men, and higher in Oaxaca than other cities.ConclusionsIt is important to consider the characteristics and the context of violence in order to develop effective prevention and intervention programs to reduce the exposure to and impact of violence.

Predictors of early mortality after traumatic spinal cord injury: a population-based study.

Study Design. Retrospective cohort study. Objective. To identify predictors of early mortality following traumatic spinal cord injury (TSCI). Summary of Background Data. Limited information is available on factors associated with early mortality following TSCI. Ability to identify high risk individuals can help to appropriately treat them, and reduce mortality. Methods. Early mortality was defined as death occurring during the initial hospital admission. Retrospective analysis of 1995 patients with TSCI, admitted to various hospitals of South Carolina from 1993 to 2003, was performed. There were 251 patients with early mortality. Multivariable logistic regression was used in modeling of early death following TSCI with gender, race, age, Frankel grade, trauma center, level of injury, injury severity score (ISS), traumatic brain injury (TBI), and medical comorbidities as covariates. Results. Increasing age after 20 years (OR: 1.2, P = <0.0001), male gender (OR: 1.6, P = 0.016), severe (ISS ≥15) systemic injuries (OR: 1.9, P = 0.012), TBI (OR: 3.7, P < 0.0001), 1 or more comorbidities (P < 0.0001), poor neurologic status (P = 0.015), and level 1 trauma center (OR: 1.4, P = 0.026) were significantly associated with early mortality, after adjusting for other covariates. Conclusion. Early mortality following TSCI is influenced by multiple factors. Timely recognition of these factors is crucial for improving survival in the acute care setting. Severe systemic injuries, medical comorbidities, and TBI continue to be the main limiting factors affecting the outcome. These findings also suggest the need to allocate resources for trauma prevention, and promote research towards improving the care of acutely injured patients.

iQuantitator: A tool for protein expression inference using iTRAQ

BackgroundIsobaric Tags for Relative and Absolute Quantitation (iTRAQ™) [Applied Biosystems] have seen increased application in differential protein expression analysis. To facilitate the growing need to analyze iTRAQ data, especially for cases involving multiple iTRAQ experiments, we have developed a modeling approach, statistical methods, and tools for estimating the relative changes in protein expression under various treatments and experimental conditions.ResultsThis modeling approach provides a unified analysis of data from multiple iTRAQ experiments and links the observed quantity (reporter ion peak area) to the experiment design and the calculated quantity of interest (treatment-dependent protein and peptide fold change) through an additive model under log transformation. Others have demonstrated, through a case study, this modeling approach and noted the computational challenges of parameter inference in the unbalanced data set typical of multiple iTRAQ experiments. Here we present the development of an inference approach, based on hierarchical regression with batching of regression coefficients and Markov Chain Monte Carlo (MCMC) methods that overcomes some of these challenges. In addition to our discussion of the underlying method, we also present our implementation of the software, simulation results, experimental results, and sample output from the resulting analysis report.ConclusioniQuantitators process-based modeling approach overcomes limitations in current methods and allows for application in a variety of experimental designs. Additionally, hypertext-linked documents produced by the tool aid in the interpretation and exploration of results.