AN INVESTIGATION OF THE RELIABILITY AND VALIDITY OF THE CENTER FOR EPIDEMIOLOGIC STUDIES DEPRESSION SCALE IN THREE ETHNIC GROUPS

Epidemiologic studies of mental disorder have called attention to the need for identifying untreated cases and to the inadequacies of the instruments available for this purpose. Accurate case ascertainment devices are the basis of sound epidemiology. Without these, neither case classification nor analytic studies of risk factors is possible.^ The purpose of this research was to examine the reliability and validity of an instrument designed to measure depressive symptoms in community populations--the Center for Epidemiologic Studies Depression Scale (CES-D Scale). Two particular foci of the study were whether or not the scale had the same statistical structure across three ethnic groups and whether or not the magnitude and pattern of rates of symptoms for these groups were affected by one source of response error, that due to response tendencies. The effects of age and education on the pattern and magnitude of rates also were examined. In addition, the reliability and validity of the measures of response tendencies were assessed.^ The study population consisted of residents of Alameda County, California. A stratified sample of approximately 700 whites, blacks and Mexican-Americans was interviewed in the summer and fall of 1978.^ The results of the analysis indicated that the scale was reliable and measured a similar content domain across the three ethnic groups. The unadjusted sex- and ethnic-specific rates of depressive symptoms showed an ethnic pattern for both sexes: rates for whites were lowest, those for Mexican-Americans were highest, and those for blacks were intermediate. Measures of response tendencies--need for social approval, trait desirability, and acquiescence--affected the magnitude of the rates for most comparisons. Likewise, the pattern of rates changed somewhat from that originally observed. The one fairly consistent observation was that rates for Mexican-American women were higher than those for the other two female subgroups in most of the comparisons. These results must be considered in the context of the reliability and validity assessment of the measures of response tendencies which indicated the tenuousness of these measures.^ Age affected the ethnic pattern of rates for men in an inconsistent way; for women, Mexican-Americans continued to have higher rates than whites or blacks in all age categories. Education affected the magnitude of rates for women but not for men. For both men and women, Mexican-Americans had higher rates in all educational strata. Rates for women showed an inverse association with education while those for men did not. ^

Data quality in trauma transfusion studies and the impact of missing data on predicting massive transfusion

Maximizing data quality may be especially difficult in trauma-related clinical research. Strategies are needed to improve data quality and assess the impact of data quality on clinical predictive models. This study had two objectives. The first was to compare missing data between two multi-center trauma transfusion studies: a retrospective study (RS) using medical chart data with minimal data quality review and the PRospective Observational Multi-center Major Trauma Transfusion (PROMMTT) study with standardized quality assurance. The second objective was to assess the impact of missing data on clinical prediction algorithms by evaluating blood transfusion prediction models using PROMMTT data. RS (2005-06) and PROMMTT (2009-10) investigated trauma patients receiving ≥ 1 unit of red blood cells (RBC) from ten Level I trauma centers. Missing data were compared for 33 variables collected in both studies using mixed effects logistic regression (including random intercepts for study site). Massive transfusion (MT) patients received ≥ 10 RBC units within 24h of admission. Correct classification percentages for three MT prediction models were evaluated using complete case analysis and multiple imputation based on the multivariate normal distribution. A sensitivity analysis for missing data was conducted to estimate the upper and lower bounds of correct classification using assumptions about missing data under best and worst case scenarios. Most variables (17/33=52%) had <1% missing data in RS and PROMMTT. Of the remaining variables, 50% demonstrated less missingness in PROMMTT, 25% had less missingness in RS, and 25% were similar between studies. Missing percentages for MT prediction variables in PROMMTT ranged from 2.2% (heart rate) to 45% (respiratory rate). For variables missing >1%, study site was associated with missingness (all p≤0.021). Survival time predicted missingness for 50% of RS and 60% of PROMMTT variables. MT models complete case proportions ranged from 41% to 88%. Complete case analysis and multiple imputation demonstrated similar correct classification results. Sensitivity analysis upper-lower bound ranges for the three MT models were 59-63%, 36-46%, and 46-58%. Prospective collection of ten-fold more variables with data quality assurance reduced overall missing data. Study site and patient survival were associated with missingness, suggesting that data were not missing completely at random, and complete case analysis may lead to biased results. Evaluating clinical prediction model accuracy may be misleading in the presence of missing data, especially with many predictor variables. The proposed sensitivity analysis estimating correct classification under upper (best case scenario)/lower (worst case scenario) bounds may be more informative than multiple imputation, which provided results similar to complete case analysis.^

Factors affecting the symptom burden in chronic heart failure

Background. Heart failure (HF) is a health problem of epidemic proportions and a clinical syndrome that leads to progressively severe symptoms, which contribute significantly to the burden of the disease. Several factors may affect the symptom burden of patients with HF, including physiological, psychological, and spiritual factors. This study was designed to examine the inter-relationship of physiological, psychological, and spiritual factors affecting symptoms for patients with HF. ^ Objectives. The aims of this study were to examine symptom burden of heart failure patients related to: (1) the physiological factor of brain natriuretic peptide (BNP); (2) the psychological factor of depression; (3) the spiritual factors of self transcendence and purpose in life; and (4) combined effects of physiological, psychological and spiritual factors. One additional aim was to describe symptom intensity related to symptom burden. ^ Methods. A cross-sectional non-experimental correlational design was used to examine factors affecting symptom burden in 105 patients with HF from a southwestern medical center outpatient heart failure clinic. Both men and women were included; average age was 56.6 (SD = 16.86). All measures except BNP were obtained by patient self-report. ^ Results. The mean number of symptoms present was 8.17 (SD = 3.34) with the three most common symptoms being shortness of breath on exertion, fatigue, and weakness. The mean symptom intensity was 365.66 (SD = 199.50) on a summative scale of visual analogue reports for 13 symptoms. The mean BNP level was 292.64 pg/ml (SD = 57 1.11). The prevalence rate for depression was 43.6% with a mean score of 3.48 (SD = 2.75) on the Center for Epidemiological Studies - Depression scale (CES-D 10) scale. In a multivariate analysis, depression was the only significant predictor of symptom burden (r = .474; P < .001), accounting for 18% of the variance. Spirituality had an interaction effect with depression (P ≤ .001), serving as a moderator between depression and symptom burden. ^ Conclusion. HF is a chronic and progressive syndrome characterized by severe symptoms, hospitalizations and disability. Depression is significantly related to symptom burden and this relationship is moderated by spirituality. ^

Prevalence of depressive symptoms among Hispanic women attending a public health clinic

Background. Estimates of perinatal depression have ranged from 5% to more than 25% of women (Gavin et al. 2005). Although Hispanics have one of the highest birthrates, few studies have looked at the prevalence of depression among this population. This study aims to describe the prevalence of depressive symptoms among a sample of Hispanic women. Methods. A convenience sample of 439 Hispanic women were screened for depression using the Center for Epidemiologic Studies Depression Scale. Sociodemographic data relating to pregnancy were also collected. Results. Although bivariate analysis found several variables to be significant, multivariate analysis found only marital and pregnancy status to be significant in predicting depression. Conclusions. While marital and pregnancy status proved to the strongest predictors for depression, future research would benefit from collecting information on timing of pregnancy and postpartum to further explore the role of pregnancy status and depressive symptoms. ^

Evidence of secondary dengue infection and potential for association with clinical depression in a subset of a randomly selected cohort in South Texas

Globally, dengue is an emerging disease resulting in an estimated 50 million new cases and 22, 000 deaths each year. Anecdotally, depression has been reported as a possible sequelae of dengue virus infection. To test the association, we performed a cross-sectional analysis in a selected sub-set of participants from the Cameron County Hispanic Cohort (CCHC) in South Texas. All study subjects in the analysis had Center for Epidemiological Studies Depression scale (CES-D) scores and were tested for dengue antibodies using stored plasma. We found that 5.0% of participants tested either positive or equivocal for anti-dengue IgG antibodies using the capture antibody test, which detects acute secondary infections. Logistic regression identified that evidence of acute secondary dengue infection was not associated with depression (Odds Ratio [OR] = 0.97, 95%Confidence Interval [CI] 0.47-1.98); however, both being female (OR = 1.53, 95%CI 1.09-2.15) and obese body mass index (BMI > 30) (OR = 1.84, 95%CI 1.19-2.84) were associated with depression. ^

The Critical Friends Group: An Innovative Way to Build Intercultural Competence Among Student and Faculty Groups

Introduction Few physicians involved in medical education are likely to have had formal training in teaching. One pedagogical method that can enhance relationships, thus improve teaching and learning is the Critical Friends Group (CFG). The CFG is a collegial support team that offers improved understanding of others. Unconditional high regard for team members frames the interactions in the CFG. These teams could be used to reduce bias and enhance intercultural competence among student CFGs and faculty CFGs. [See PDF for complete abstract]

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Concept, design and implementation of a cardiovascular gene-centric 50 k SNP array for large-scale genomic association studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

Interruptions in Workflow for RNs in a Level One Trauma Center

An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by Emergency Department(ED) nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses (RNs) employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephones, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the healthcare community has not systematically studied interruptions in clinical settings to determine and weigh the necessity of the interruption against their sometimes negative results such as medical errors, decreased efficiency, and increased costs. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, thereby improving both the quality of healthcare and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from earlier studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, to identify the bottlenecks of information flow, and to develop interventions to improve the efficiency of emergency care through the management of interruptions.

Interruptions in workflow for RNs in a Level One Trauma Center.

An understanding of interruptions in healthcare is important for the design, implementation, and evaluation of health information systems and for the management of clinical workflow and medical errors. The purpose of this study is to identify and classify the types of interruptions experienced by ED nurses working in a Level One Trauma Center. This was an observational field study of Registered Nurses employed in a Level One Trauma Center using the shadowing method. Results of the study indicate that nurses were both recipients and initiators of interruptions. Telephone, pagers, and face-to-face conversations were the most common sources of interruptions. Unlike other industries, the outcomes caused by interruptions resulting in medical errors, decreased efficiency and increased cost have not been systematically studied in healthcare. Our study presented here is an initial step to understand the nature, causes, and effects of interruptions, and to develop interventions to manage interruptions to improve healthcare quality and patient safety. We developed an ethnographic data collection technique and a data coding method for the capturing and analysis of interruptions. The interruption data we collected are systematic, comprehensive, and close to exhaustive. They confirmed the findings from early studies by other researchers that interruptions are frequent events in critical care and other healthcare settings. We are currently using these data to analyze the workflow dynamics of ED clinicians, identify the bottlenecks of information flow, and develop interventions to improve the efficiency of emergency care through the management of interruptions.

Effect of Acute Administration of Angiopoietin-1 in Experimental Traumatic Spinal Cord Injury: Magnetic Resonance Imaging and Neurobehavioral Studies

Spinal cord injury (SCI) is a devastating condition that affects people in the prime of their lives. A myriad of vascular events occur after SCI, each of which contributes to the evolving pathology. The primary trauma causes mechanical damage to blood vessels, resulting in hemorrhage. The blood-spinal cord barrier (BSCB), a neurovascular unit that limits passage of most agents from systemic circulation to the central nervous system, breaks down, resulting in inflammation, scar formation, and other sequelae. Protracted BSCB disruption may exacerbate cellular injury and hinder neurobehavioral recovery in SCI. In these studies, angiopoietin-1 (Ang1), an agent known to reduce vascular permeability, was hypothesized to attenuate the severity of secondary injuries of SCI. Using longitudinal magnetic resonance imaging (MRI) studies (dynamic contrast-enhanced [DCE]-MRI for quantification of BSCB permeability, highresolution anatomical MRI for calculation of lesion size, and diffusion tensor imaging for assessment of axonal integrity), the acute, subacute, and chronic effects of Ang1 administration after SCI were evaluated. Neurobehavioral assessments were also performed. These non-invasive techniques have applicability to the monitoring of therapies in patients with SCI. In the acute phase of injury, Ang1 was found to reduce BSCB permeability and improve neuromotor recovery. Dynamic contrast-enhanced MRI revealed a persistent compromise of the BSCB up to two months post-injury. In the subacute phase of injury, Ang1’s effect on reducing BSCB permeability was maintained and it was found to transiently reduce axonal integrity. The SCI lesion burden was assessed with an objective method that compared favorably with segmentations from human raters. In the chronic phase of injury, Ang1 resulted in maintained reduction in BSCB permeability, a decrease in lesion size, and improved axonal integrity. Finally, longitudinal correlations among data from the MRI modalities and neurobehavioral assays were evaluated. Locomotor recovery was negatively correlated with lesion size in the Ang1 cohort and positively correlated with diffusion measures in the vehicle cohort. In summary, the results demonstrate a possible role for Ang1 in mitigating the secondary pathologies of SCI during the acute and chronic phases of injury.

Phase I clinical trials in 56 patients with thyroid cancer: the M. D. Anderson Cancer Center experience.

INTRODUCTION: Thyroid cancer is the most common endocrine malignancy. The outcomes of patients with relapsed thyroid cancer treated on early-phase clinical trials have not been systematically analyzed. PATIENTS AND METHODS: We reviewed the records of consecutive patients with metastatic thyroid cancer referred to the Phase I Clinical Trials Program from March 2006 to April 2008. Best response was assessed by Response Evaluation Criteria in Solid Tumors. RESULTS: Fifty-six patients were identified. The median age was 55 yr (range 35-79 yr). Of 49 patients evaluable for response, nine (18.4%) had a partial response, and 16 (32.7%) had stable disease for 6 months or longer. The median progression-free survival was 1.12 yr. With a median follow-up of 15.6 months, the 1-yr survival rate was 81%. In univariate analysis, factors predicting shorter survival were anaplastic histology (P = 0.0002) and albumin levels less than 3.5 g/dl (P = 0.05). Among 26 patients with tumor decreases, none died (median follow-up 1.3 yr), whereas 52% of patients with any tumor increase died by 1 yr (P = 0.0001). The median time to failure in our phase I clinical trials was 11.5 months vs. 4.1 months for the previous treatment (P = 0.04). CONCLUSION: Patients with advanced thyroid cancer treated on phase I clinical trials had high rates of partial response and prolonged stable disease. Time to failure was significantly longer on the first phase I trial compared with the prior conventional treatment. Patients with any tumor decrease had significantly longer survival than those with any tumor increase.

Time-kill and synergism studies of ceftobiprole against Enterococcus faecalis, including beta-lactamase-producing and vancomycin-resistant isolates.

Ceftobiprole (BAL9141) is an investigational cephalosporin with broad in vitro activity against gram-positive cocci, including enterococci. Ceftobiprole MICs were determined for 93 isolates of Enterococcus faecalis (including 16 beta-lactamase [Bla] producers and 17 vancomycin-resistant isolates) by an agar dilution method following the Clinical and Laboratory Standards Institute recommendations. Ceftobiprole MICs were also determined with a high inoculum concentration (10(7) CFU/ml) for a subset of five Bla producers belonging to different previously characterized clones by a broth dilution method. Time-kill and synergism studies (with either streptomycin or gentamicin) were performed with two beta-lactamase-producing isolates (TX0630 and TX5070) and two vancomycin-resistant isolates (TX2484 [VanB] and TX2784 [VanA]). The MICs of ceftobiprole for 50 and 90% of the isolates tested were 0.25 and 1 microg/ml, respectively. All Bla producers and vancomycin-resistant isolates were inhibited by concentrations of

The Role of Cell Sterilization in Population Based Studies of Radiogenic Second Cancers Following Radiation Therapy

Advances in radiotherapy have generated increased interest in comparative studies of treatment techniques and their effectiveness. In this respect, pediatric patients are of specific interest because of their sensitivity to radiation induced second cancers. However, due to the rarity of childhood cancers and the long latency of second cancers, large sample sizes are unavailable for the epidemiological study of contemporary radiotherapy treatments. Additionally, when specific treatments are considered, such as proton therapy, sample sizes are further reduced due to the rareness of such treatments. We propose a method to improve statistical power in micro clinical trials. Specifically, we use a more biologically relevant quantity, cancer equivalent dose (DCE), to estimate risk instead of mean absorbed dose (DMA). Our objective was to demonstrate that when DCE is used fewer subjects are needed for clinical trials. Thus, we compared the impact of DCE vs. DMA on sample size in a virtual clinical trial that estimated risk for second cancer (SC) in the thyroid following craniospinal irradiation (CSI) of pediatric patients using protons vs. photons. Dose reconstruction, risk models, and statistical analysis were used to evaluate SC risk from therapeutic and stray radiation from CSI for 18 patients. Absorbed dose was calculated in two ways: with (1) traditional DMA and (2) with DCE. DCE and DMA values were used to estimate relative risk of SC incidence (RRCE and RRMA, respectively) after proton vs. photon CSI. Ratios of RR for proton vs. photon CSI (RRRCE and RRRMA) were then used in comparative estimations of sample size to determine the minimal number of patients needed to maintain 80% statistical power when using DCE vs. DMA. For all patients, we found that protons substantially reduced the risk of developing a second thyroid cancer when compared to photon therapy. Mean RRR values were 0.052±0.014 and 0.087±0.021 for RRRMA and RRRCE, respectively. However, we did not find that use of DCE reduced the number of patents needed for acceptable statistical power (i.e, 80%). In fact, when considerations were made for RRR values that met equipoise requirements and the need for descriptive statistics, the minimum number of patients needed for a micro-clinical trial increased from 17 using DMA to 37 using DCE. Subsequent analyses revealed that for our sample, the most influential factor in determining variations in sample size was the experimental standard deviation of estimates for RRR across the patient sample. Additionally, because the relative uncertainty in dose from proton CSI was so much larger (on the order of 2000 times larger) than the other uncertainty terms, it dominated the uncertainty in RRR. Thus, we found that use of corrections for cell sterilization, in the form of DCE, may be an important and underappreciated consideration in the design of clinical trials and radio-epidemiological studies. In addition, the accurate application of cell sterilization to thyroid dose was sensitive to variations in absorbed dose, especially for proton CSI, which may stem from errors in patient positioning, range calculation, and other aspects of treatment planning and delivery.