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Background: Incomplete observation units may contain important information about the population being studied, analysis conducted with the complete portion of the dataset, done in most standard statistical software, may produce biased or low statistical power results. In this paper we investigate the behavior of imputation methods for a linkage to HIV care study dataset with more than 60% incomplete cases.Methods: Missing data imputation algorithms amelia, missForest, mice and hmisc were considered. Two sets of simulations were conducted: first with the subset of data containing only complete observations and second with the whole dataset. Imputation accuracy and general behavior for each imputation algorithm were accessed in the first set. Random forest models were fit to evaluate overall prediction accuracy and sensitivity in both sets of simulations. Results: The imputed values by missForest, a single imputation method, were more accurate for all incomplete variables and scenarios. Median overall prediction accuracy of HIV status, a three levels outcome, was slightly higher after imputations with missForest and amelia (approximately 52%, 61% and 65% for samples of 350, 700 and 1050 units respectively). In general, different missing percentages (20%, 40% and 60%) did not result in large changes in prediction or imputation accuracy and larger sample sizes performance improved for imputation and overall prediction accuracy but mixed results were observed with sensitivity. For the second set of simulations, missForest and amelia produced better overall prediction accuracy with larger samples (1200 versus 350 units). For new HIV positive HIV class, hmisc and mice presented better sensitivity, with median sensitivity 65% versus 50% and approximately 90% versus 20% for samples with 350 and 1200 units respectively, compared to incomplete samples. Conclusions: Imputation with mice and hmisc may be used for imputation when the main interest is to increase sensitivity in predicting new HIV positive. Furthermore, it is interesting to investigate which method gives more advantage for other performance measures of interest. Trial registration: NCT02545673

BACKGROUND Cardiotoxicity after cancer treatment is a potentially preventable life-threatening complication among women with breast cancer. There is no algorithm to identify women with breast cancer at risk of cardiotoxicity. OBJECTIVES We quantified signs and symptoms as well as selected laboratory values among women with breast cancer who developed cardiotoxicity. METHODS The clinical characteristics (n = 15) were collected from electronic health records. Spearman correlation coefficients and a nonparametric statistical test were used to analyze data. RESULTS Significant statistical differences were detected in the laboratory values comparing the first and second half of 6 months before cardiotoxicity including alanine aminotransferase (U/L) (30.67 ± 26.27 and 42.31 ± 35.65, respectively; P = .03, Cohen's d = 0.37). A negative correlation was found between estimated glomerular filtration rate and new onset of more than 1 sign or symptom (Spearman's ρ = -0.5, P = .06). CONCLUSIONS Investigating clinical characteristics before cardiotoxicity may determine the mechanism(s) and identify high-risk patients.

To increase power or reduce the number of patients needed for a parallel groups design, the crossover design has been often used to study treatments for noncurable chronic diseases. However, in the presence of carry-over effect caused by treatments, the commonly-used estimator which ignores the carry-over effect leads to a biased estimator for estimating the treatment effect difference. A two-stage test approach aimed to address carry-over effect proposed was found to be potentially misleading. In this paper, we propose a weighted average of the commonly-used estimator and an unbiased estimator that uses only the first period of the data. We derive an optimal weight that minimizes the mean squared error (MSE) and its modified estimator. We apply Monte Carlo simulation to evaluate the performance of the proposed estimators in a variety of situations. In the simulations, we examine the estimated MSE (EMSE), percentile interval length, and coverage probability calculated from the percentile intervals among considered estimators. Simulation results show that our proposed weighted average estimator and its modified estimator lead to smaller EMSEs on average comparing to the two commonly used estimators. The coverage probabilities using our proposed estimators are reasonably close to the nominal confidence level and the interval lengths are shorter comparing to the use of the unbiased estimator that uses only the first period of the data. We apply an example that was to evaluate the efficacy of two type of bronchodilators for asthma treatment to demonstrate the use of the proposed estimators.

Summary Background Stigma is a formidable social structural barrier to HIV testing, and yet the effect of stigma on HIV testing is rarely examined at the community level. We aimed to examine the geospatial relationships of perceived HIV stigma and HIV testing among men and women living in rural Uganda. Methods Women and men (aged ≥18 years or emancipated minor) residing in rural areas of Uganda who self-identified as HIV negative completed interviews that included measures of HIV testing history and how participants perceived HIV stigma. We used geospatial cluster analyses to identify areas of higher perceived stigma and lower perceived stigma and the geographical dispersion of these areas. We used Poisson regression models stratified by gender to test individual-level and community-level perceived stigma in relation to frequency of HIV testing in the previous 2 years. Findings Between Nov 25, 2015, and May 26, 2017, we interviewed 9740 participants (4359 [45%] men and 5381 [55%] women]), among whom 940 (9%) had never been tested for HIV, and among those who had been tested, 1131 (12%) had not been tested in the previous 2 years. Men (3134 [72%] of 4359) were less likely to have been tested in the past 2 years than women (4535 [84%] of 5381) were (p Interpretation Our results suggest that perceived HIV stigma at the community level exerts a differential influence on testing for women and men. HIV testing campaigns that are targeted to men and women in rural Uganda will require gender tailoring to fit local contexts. Funding US National Institute of Mental Health.

A multicenter trial is often applied to facilitate recruiting patients into a trial and enhance the generalizability of results to a population. Under a distribution-free random effects log...

ObjectivesThe present study aimed to identify the prevalence and correlates of depressive symptoms and potential intervention points among women and men from a population-based sample in rural central Uganda.DesignA cross-sectional study.SettingFour districts in rural Uganda.ParticipantsWomen and men aged 15–59 residing in four districts in rural Uganda accepting home-based HIV testing who completed a baseline survey at the time of testing.Primary outcome measuresDepressive symptoms measured by the 10-item Center for Epidemiological Studies Depression Scale using a cut-off score of 13 for significant depressive symptoms.ResultsAmong a sample of 9609 women and 6059 men, 1415 (14.7%) women and 727 (12.0%) men met criteria for significant depressive symptoms. Having ever received mental health services was associated with lower odds of significant depressive symptoms (women: adjusted OR (adjOR)=0.32, 95% CI=0.22 to 0.47; men: adjOR=0.36, 95% CI=0.18 to 0.62). Having received outpatient (women: adjOR=3.64, 95% CI=3.14 to 4.22; men: adjOR=3.37, 95% CI=2.78 to 4.07) or inpatient (women: adjOR=5.44, 95% CI=4.24 to 6.97; men: adjOR=3.42, 95% CI=2.21 to 5.28) care in the prior 6 months was associated with greater odds of significant depressive symptoms. For women only, known HIV positive status (adjOR=1.37, 95% CI=1.05 to 1.77), and for men only, alcohol misuse (adjOR=1.38, 95% CI=1.12 to 1.70), were associated with increased odds of significant depressive symptoms.ConclusionOur findings suggest that depression screening within outpatient and inpatient settings may help to identify people in need of mental health services. Routine screening in outpatient or inpatient clinics along with the implementation of evidence-based interventions could ultimately help close the mental health gap for depression in this and similar settings.

This study analyzed spatiotemporal spread patterns of COVID-19 confirmed cases at the zip code level in the County of San Diego and compared them to neighborhood social and economic factors. We used correlation analysis, regression models, and geographic weighted regression to identify important factors and spatial patterns. We broke down the temporal confirmed case patterns into four stages from 1 April 2020 to 31 December 2020. The COVID-19 outbreak hotspots in San Diego County are South Bay, El Cajon, Escondido, and rural areas. The spatial patterns among different stages may represent fundamental health disparity issues in neighborhoods. We also identified important variables with strong positive or negative correlations in these categories: ethnic groups, languages, economics, and education. The highest association variables were Pop5andOlderSpanish (Spanish-speaking) in Stage 4 (0.79) and Pop25OlderLess9grade (Less than 9thgrade education) in Stage 4 (0.79). We also observed a clear pattern that regions with more well-educated people have negative associations with COVID-19. Additionally, our OLS regression models suggested that more affluent populations have a negative relationship with COVID-19 cases. Therefore, the COVID-19 outbreak is not only a medical disease but a social inequality and health disparity problem.

Background Patterns of medication administration prior to in-hospital cardiac arrest (I-HCA) and the potential impact of these on patient outcomes is not well-established. Accordingly, types of medications administered in the 72 ​h prior to I-HCA were examined in relation to initial rhythms of I-HCA and survival. Methods A retrospective, pilot study was conducted among 96 patients who experienced I-HCA. Clinical characteristics and treatments including medications were extracted from electronic health records. Relative risk (RR) of medications or class of medications associated with the initial rhythms of I-HCA and return of spontaneous circulation (ROSC) were calculated. Results Two distinct sub-groups were identified that did not survive to hospital discharge (n ​= ​31): 1) those who received either vasopressin/ desmopressin (n ​= ​16) and 2) those who received combinations of psychotherapeutic agents with anxiolytics, sedatives, and hypnotics (n ​= ​15) prior to I-HCA. The risk of pulseless electrical activity and asystolic arrest was high in patients who received sympathomimetic agents alone or in combination with β-Adrenergic blocking agents, (RR ​= ​1.40, 1.41, respectively). Vasopressin and a combination of vasopressin and fentanyl were associated with risk of unsuccessful ROSC (RR ​= ​2.50, 2.38, respectively). Conclusions The types of medications administered during inpatient care may serve as a surrogate marker for identifying patients at risk of specific initial rhythms of I-HCA and survival.

IntroductionMen who have sex with men (MSM) are one of the most at-risk group for contracting HIV in the USA. However, the HIV epidemic impacts some groups of MSM disproportionately. Latino MSM comprise 25.1% of new HIV infections among MSM between the ages of 13 and 29 years. The daily medication tenofovir/emtricitabine was approved by the Food and Drug Administration for pre-exposure prophylaxis (PrEP) in 2012 and has demonstrated strong efficacy in reducing HIV acquisition.Methods and analysisThrough extensive formative research, this study uses a pilot randomised controlled trial design and will examine the feasibility and acceptability of a patient navigation intervention designed to address multiple barriers to improve engagement in the PrEP continuum among 60 Latino MSM between the ages of 18 and 29 years. The patient navigation intervention will be compared with usual care plus written information to evaluate the feasibility and acceptability of the intervention and study methods and the intervention’s potential in improving PrEP continuum behaviours. The results will be reviewed for preparation for a future full-scale efficacy trial.Ethics and disseminationThis study was approved by the institutional review board at San Diego State University and is registered at ClinicalTrials.gov. The intervention development process, plan and the results of this study will be shared through peer-reviewed journal publications, conference presentations and healthcare system and community presentations.Registration detailsRegistered under the National Institutes of Health’s ClinicalTrials.gov (NCT04048382) on 7 August 2019 and approved by the San Diego State University (HS-2017–0187) institutional review board. This study began on 5 August 2019 and is estimated to continue through 31 March 2021. The clinical trial is in the pre-results stage.

Background Though home-based human immunodeficiency virus (HIV) counseling and testing (HBHCT) is implemented in many sub-Saharan African countries as part of their HIV programs, linkage to HIV care remains a challenge. The purpose of this study is to test an intervention to enhance linkage to HIV care and improve HIV viral suppression among individuals testing HIV positive during HBHCT in rural Uganda. Methods The PATH (Providing Access To HIV Care)/Ekkubo Study is a cluster-randomized controlled trial which compares the efficacy of an enhanced linkage to HIV care intervention vs. standard-of-care (paper-based referrals) at achieving individual and population-level HIV viral suppression, and intermediate outcomes of linkage to care, receipt of opportunistic infection prophylaxis, and antiretroviral therapy initiation following HBHCT. Approximately 600 men and women aged 18-59 who test HIV positive during district-wide HBHCT in rural Uganda will be enrolled in this study. Villages (clusters) are pair matched by population size and then randomly assigned to the intervention or standard-of-care arm. Study teams visit households and participants complete a baseline questionnaire, receive HIV counseling and testing, and have blood drawn for HIV viral load and CD4 testing. At baseline, standard-of-care arm participants receive referrals to HIV care including a paper-based referral and then receive their CD4 results via home visit 2 weeks later. Intervention arm participants receive an intervention counseling session at baseline, up to three follow-up counseling sessions at home, and a booster session at the HIV clinic if they present for care. These sessions each last approximately 30 min and consist of counseling to help clients: identify and reduce barriers to HIV care engagement, disclose their HIV status, identify a treatment supporter, and overcome HIV-related stigma through links to social support resources in the community. Participants in both arms complete interviewer-administered questionnaires at six and 12 months follow-up, HIV viral load and CD4 testing at 12 months follow-up, and allow access to their medical records. Discussion The findings of this study can inform the integration of a potentially cost-effective approach to improving rates of linkage to care and HIV viral suppression in HBHCT. If effective, this intervention can improve treatment outcomes, reduce mortality, and through its effect on individual and population-level HIV viral load, and decrease HIV incidence. Trial registration NCT02545673

Survival after in-hospital cardiac arrest (I-HCA) remains < 30 %. There is very limited literature exploring the electrocardiogram changes prior to I-HCA. The purpose of the study was to determine demographics and electrocardiographic predictors prior to I-HCA. A retrospective study was conducted among 39 cardiovascular subjects who had cardiopulmonary resuscitation from I-HCA with initial rhythms of pulseless electrical activity (PEA) and asystole. Demographics including medical history, ejection fraction, laboratory values, and medications were examined. Electrocardiogram (ECG) parameters from telemetry were studied to identify changes in heart rate, QRS duration and morphology, and time of occurrence and location of ST segment changes prior to I-HCA. Increased age was significantly associated with failure to survive to discharge (p < 0.05). Significant change was observed in heart rate including a downtrend of heart rate within 15 min prior to I-HCA (p < 0.05). There was a significant difference in heart rate and QRS duration during the last hour prior to I-HCA compared to the previous hours (p < 0.05). Inferior ECG leads showed the most significant changes in QRS morphology and ST segments prior to I-HCA (p < 0.05). Subjects with an initial rhythm of asystole demonstrated significantly greater ECG changes including QRS morphology and ST segment changes compared to the subjects with initial rhythms of PEA (p < 0.05). Diagnostic ECG trends can be identified prior to I-HCA due to PEA and asystole and can be further utilized for training a predictive machine learning model for I-HCA.

Background: Factors associated with initial methicillin-resistant Staphylococcus aureus (MRSA) skin and soft-tissue infections (SSTIs) and their recurrence have not been fully elucidated among HIV-infected persons. Methods: We retrospectively evaluated a large cohort of HIV-infected patients from 1993 to 2010 for culture-proven MRSA SSTIs. Separate logistic regression models evaluated factors associated with initial and recurrent infections. Results: Of the 794 patients, 63 (8%) developed an initial infection (19.8 infections/1000 person years [PY]); risk factors included CD4 count 3 and HIV RNA level ≥400 copies/mL ( P < .01), US Centers for Disease Control and Prevention (CDC) stage C versus A/B ( P < .01), and injection drug use (IDU, P < .01). In all, 27% developed recurrence (206 infections/1000 PY); risk factors included hospital admission ( P = .02). Minocycline for treatment of the initial infection was associated with an 80% decreased odds for recurrence ( P = .03). Conclusion: HIV control and avoidance of IDU may be useful in reducing rates of MRSA SSTIs among HIV-infected persons.

This study explored the interplay between quality facilities and school climate, charting the effects of facility conditions on student and teacher attitudes, behaviors, and performance within schools slated for renovations in a large metropolitan school district. The research applied a school leadership–building design model to explore how six characteristics of facility quality—movement, aesthetics, play of light, flexible and responsive classrooms, elbow room, and security—interact with four aspects of school climate: academic press, community engagement, teacher professionalism, and collegial leadership. Because the schools were older and participants in the research perceived them as being in great need of maintenance and repair, the school building characteristics were often described as absent qualities. The survey data revealed moderate to strong relationships between the quality of school facilities and school climate. The interviews further explicated these relationships. Two additional themes—counterbalance and equity—emerged as being significant to occupants’ interactions with their current facilities. This study used a mixed-methods triangulation design–data transformation model. Specifically, school climate surveys, photo interviews with students, walking tours of the school facility, and formal interviews were triangulated to obtain complementary data and a more complete understanding of the educational facility to be renovated and its impact on occupants.

Background: Analyzing telemetry electrocardiogram (ECG) data over an extended period is often time-consuming because digital records are not widely available at hospitals. Investigating trends and patterns in the ECG data could lead to establishing predictors that would shorten response time to in-hospital cardiac arrest (I-HCA). This study was conducted to validate a novel method of digitizing paper ECG tracings from telemetry systems in order to facilitate the use of heart rate as a diagnostic feature prior to I-HCA. Methods: This multicenter study used telemetry to investigate full-disclosure ECG papers of 44 cardiovascular patients obtained within 1 hr of I-HCA with initial rhythms of pulseless electrical activity and asystole. Digital ECGs were available for seven of these patients. An algorithm to digitize the full-disclosure ECG papers was developed using the shortest path method. The heart rate was measured manually (averaging R-R intervals) for ECG papers and automatically for digitized and digital ECGs. Results: Significant correlations were found between manual and automated measurements of digitized ECGs ( p < .001) and between digitized and digital ECGs ( p < .001). Bland–Altman methods showed bias = .001 s, SD = .0276 s, lower and upper 95% limits of agreement for digitized and digital ECGs = .055 and −.053 s, and percentage error = 0.22%. Root mean square (rms), percentage rms difference, and signal to noise ratio values were in acceptable ranges. Conclusion: The digitization method was validated. Digitized ECG provides an efficient and accurate way of measuring heart rate over an extended period of time.

Background Dengue is one of the most aggressively expanding mosquito-transmitted viruses. The human burden approaches 400 million infections annually. Complex transmission dynamics pose challenges for predicting location, timing, and magnitude of risk; thus, models are needed to guide prevention strategies and policy development locally and globally. Weather regulates transmission-potential via its effects on vector dynamics. An important gap in understanding risk and roadblock in model development is an empirical perspective clarifying how weather impacts transmission in diverse ecological settings. We sought to determine if location, timing, and potential-intensity of transmission are systematically defined by weather. Methodology/Principal Findings We developed a high-resolution empirical profile of the local weather-disease connection across Peru, a country with considerable ecological diversity. Applying 2-dimensional weather-space that pairs temperature versus humidity, we mapped local transmission-potential in weather-space by week during 1994-2012. A binary classification-tree was developed to test whether weather data could classify 1828 Peruvian districts as positive/negative for transmission and into ranks of transmission-potential with respect to observed disease. We show that transmission-potential is regulated by temperature-humidity coupling, enabling epidemics in a limited area of weather-space. Duration within a specific temperature range defines transmission-potential that is amplified exponentially in higher humidity. Dengue-positive districts were identified by mean temperature >22°C for 7+ weeks and minimum temperature >14°C for 33+ weeks annually with 95% sensitivity and specificity. In elevated-risk locations, seasonal peak-incidence occurred when mean temperature was 26-29°C, coincident with humidity at its local maximum; highest incidence when humidity >80%. We profile transmission-potential in weather-space for temperature-humidity ranging 0-38°C and 5-100% at 1°C x 2% resolution. Conclusions/Significance Local duration in limited areas of temperature-humidity weather-space identifies potential locations, timing, and magnitude of transmission. The weather-space profile of transmission-potential provides needed data that define a systematic and highly-sensitive weather-disease connection, demonstrating separate but coupled roles of temperature and humidity. New insights regarding natural regulation of human-mosquito transmission across diverse ecological settings advance our understanding of risk locally and globally for dengue and other mosquito-borne diseases and support advances in public health policy/operations, providing an evidence-base for modeling, predicting risk, and surveillance-prevention planning., Author Summary Timing and spatial-extent of diseases such as dengue and malaria that result from transmission between humans and mosquitoes are regulated by weather in complicated ways. For Aedes aegypti mosquitoes, the primary vector of dengue, slight changes in different components of weather have important effects on population dynamics, lifespan, biting-frequency, virus incubation period and capacity to transmit the virus, thus inducing changes in transmission probability. These complicated dynamics produce a weather-disease connection that is not well-defined for different ecological settings. Understanding this connection is important to critical elements of policy development and operational control of dengue such as predicting risk, developing human-vector transmission models, and planning surveillance-intervention strategies locally and globally. The empirical profile of the weather-disease connection for dengue developed in this study provides a needed understanding of how temperature and humidity work together in regulating human-mosquito transmission. The observed likelihood of low to epidemic-level transmission was highly sensitive to local seasonal duration in limited areas of this two-dimensional weather-space. Data presented represent a resource for estimating where and when transmission-potential supports epidemics of varying magnitude. This high-resolution weather-disease profile for dengue reveals systematic relationships that are informative for mosquito-borne diseases in general and discussions of consequences of global warming.

The crossover design can be of use to save the number of patients or improve power of a parallel groups design in studying treatments to noncurable chronic diseases. We propose using the generalized odds ratio for paired sample data to measure the relative effects in ordinal data between treatments and between periods. We show that one can apply the commonly used asymptotic and exact test procedures for stratified analysis in epidemiology to test non-equality of treatments in ordinal data, as well as obtain asymptotic and exact interval estimators for the generalized odds ratio under a three-period crossover design. We further show that one can apply procedures for testing the homogeneity of the odds ratio under stratified sampling to examine whether there are treatment-by-period interactions. We use the data taken from a three-period crossover trial studying the effects of low and high doses of an analgesic versus a placebo for the relief of pain in primary dysmenorrhea to illustrate the use of these test procedures and estimators proposed here.

When a new diagnostic procedure is developed, it is important to assess whether the diagnostic accuracy of the new procedure is different from that of the standard procedure. For paired-sample ordinal data, this paper develops two test statistics for testing equality of the diagnostic accuracy between two procedures without assuming any parametric models. One is derived on the basis of the probability of correctly identifying the case for a randomly selected pair of a case and a non-case over all possible cutoff points, and the other is derived on the basis of the sensitivity and specificity directly. To illustrate the practical use of the proposed test procedures, this paper includes an example regarding the use of digitized and plain films for screening breast cancer. This paper also applies Monte Carlo simulation to evaluate the finite sample performance of the two statistics developed here and notes that they can perform well in a variety of situations. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

In a conventional randomized trial, the assignment of a patient to receive a treatment after obtaining the patient’s consent may completely depend on a chance mechanism. Thus, neither the patient nor the physician know exactly which treatment the patient will receive at the time of consent. This can compromise the relationship between the patient and the physician. To alleviate this concern, Zelen proposes use of a double consent randomized design, in which we ask each patient for consent after random assignment of patients to treatments. This paper discusses sample size calculation for the double consent randomized design. Because the variance of the test statistic used to derive the required sample size depends upon the null and alternative hypotheses, this paper derives three approximate sample size formulae. The first two formulae tend to provide a lower and an upper limit of the required sample size, and the third one, a simple average of these two formulae, attempts to provide a better approximation. This paper further employs Monte Carlo simulation to evaluate the performance of these approximate sample size formulae with respect to type I error and power. Finally, to help readers employ the results discussed here, tables that summarize the estimated required sample size in a variety of situations are provided.

It is well known that Cornfield's confidence interval of the odds ratio with the continuity correction can mimic the performance of the exact method. Furthermore, because the calculation procedure of using the former is much simpler than that of using the latter, Cornfield's confidence interval with the continuity correction is highly recommended by many publications. However, all these papers that draw this conclusion are on the basis of examining the coverage probability exclusively. The efficiency of the resulting confidence intervals is completely ignored. This paper calculates and compares the coverage probability and the average length for Woolfs logit interval estimator, Gart's logit interval estimator of adding 0.50, Cornfield's interval estimator with the continuity correction, and Cornfield's interval estimator without the continuity correction in a variety of situations. This paper notes that Cornfield's interval estimator with the continuity correction is too conservative, while Cornfield's method without the continuity correction can improve efficiency without sacrificing the accuracy of the coverage probability. This paper further notes that when the sample size is small (say, 20 or 30 per group) and the probability of exposure in the control group is small (say, 0.10) or large (say, 0.90), using Cornfield's method without the continuity correction is likely preferable to all the other estimators considered here. When the sample size is large (say, 100 per group) or when the probability of exposure in the control group is moderate (say, 0.50), Gart's logit interval estimator is probably the best.

We consider repeated measures designs in which multiple subjects are exposed to different “doses” of a predictor variable and among subject variability is modeled through a random coefficients model. The true “dose” present differs from the target level by some random amount; what is known as the Berkson error model. We examine the consequences of such errors on naive analyses (which ignore measurement error) under commonly used linear and quadratic models, with a focus on both regression coefficients and variance parameters. Our investigation allows the measurement errors to have changing variances over the doses and also allows the errors to be correlated either within or among subjects. For linear regression the naive estimates of the coefficients are unbiased and inferences for the coefficients are at least approximately correct as long as there is no correlation in measurement errors among subjects. The presence of correlated measurement errors among subjects, however, results in naive tests and confidence intervals for the coefficients being incorrect. Biases in the naive estimates in the variance components are given, such biases occurring to some degree for all of the measurement error models. Similar results are given for quadratic regression, with the added complication that the naive estimate of some of the regression coefficients are biased, with the nature of the variance in measurement errors determining which coefficients are biased. Some preliminary discussion is presented concerning correcting for measurement error.

The susceptibility of Juniperus communities to prescribed fires can vary greatly throughout the year. The objective of this project was to determine the relationship between the seasonal concentration and composition of volatile oils and plant flammability in two Ashe juniper (Juniperus ashei) populations. Total monoterpenoid concentration was significantly affected by season and by plant population. Mean monoterpenoid concentration of a population from each central Texas was 9.16 mg/g fresh weight of juniper needles while the mean concentration of a west central Texas population was 11.62 mg/g of fresh weight. Monoterpenoid concentrations were typically lowest during the summer and highest during the spring and winter in the western population, but there was no seasonal pattern in the eastern population. The eastern population of trees was slightly (4.8%) more flammable than the western population, and male trees were slightly (3.8%) more flammable than female trees. The concentration of limonene was positively related to plant flammability and could increase flammability by 30% over the range of cencentrations found in this species. Bornyl acetate was negatively related to flammability with each 1 mg/g increase in concentration resulting in a 2% decrease in flammability. Caloric energy content and percent leaf moisture were not significant factors in determining the percentage of the Ashe juniper plant actually burned. Secondary chemicals, usually considered as antiherbivore mechanisms, may also serve an important role in determining the likelihood of a plant being consumed by fire.

To describe the perceptions of training and deployment preparation and combat experiences and exposures of U.S. Army combat medics.Data were from the first year of a 3-year longitudinal study designed to assess the impact of combat on the behavioral health and resilience of 347 combat medics surveyed 3 to 6 months after returning from a 12-month deployment to Operation Enduring Freedom/Operation Iraqi Freedom theatre and assigned to brigade combat teams.Analyses indicated that combat medics may benefit from better preparation in types of shifts required during deployment, type and intensity of combat likely to be seen and experienced, more adequate training in the area of stress and mental health care management, and easier access to behavioral mental health care.The military has shown considerable progress in addressing and understanding the mental health care needs of Soldiers. However, challenges remain. Additional emphasis should be placed on reducing the stigma and barriers related to mental health care both in theatre and garrison and on developing an evidence-based, validated program for medics and other Soldiers to recognize stress and mental health issues on the battlefield. For medics, this should be from two perspectives-that of a combat Soldier and that of a medical provider.

Over the past decade, baseball has entered a period of the mega-deal: multi-year, high-priced contracts that lock in superstar players to a particular team for an extended period of time. General managers and fans alike stress over these long term contracts: will the player continue at a high level of perfor-mance, and hopefully even improve? What will the long term cost be towards putting together a team capable of contending for a championship? Recent disasters have compounded these fears as the following few paragraphs of anecdotal evidence account.

4571 Background: mTOR inhibitors have clinical utility in VEGF-refractory RCC and may be useful in non-clear cell disease. In general, mTOR inhibition is inferior to targeting VEGF in the treatment...

e14037 Background: Colorectal cancer (CRC) is the third leading cause of cancer death in men and women combined in the USA. Colorectal liver metastasis (CLM), the most common metastasis of CRC, accounts for at least two thirds of CRC deaths. The purpose of this study is to identify a gene signature that predicts patient survival in patients with CLM. Methods: We analyzed the gene expression profiles of specimens from 24 CLM patients (M:F = 14:10) who underwent metastatic liver resection and unmatched primary CRC specimens from an independent cohort of 30 patients (M:F = 14:16). The association between gene expression levels and survival outcome was evaluated using Cox proportional hazards regression. Random Forests and risk scores were used to construct a gene expression-based survival classifier. Results: Based on survival classifier of CLM patients, a 14-gene signature was developed. According to leave-one-out cross validation, all 24 CLM patients (median follow-up time of 25 months) were correctly assigned into high-risk or low-risk groups (p=0.001). This 14-gene signature was then validated in an independent cohort of 30 primary CRC patients (median follow-up time of 42.2 months; p= 0.03) and a subset of 11 patients who were diagnosed at presentation or follow-up with liver metastasis (M:F = 5:6; median follow-up time of 27.6 months; p=0.04). Conclusions: We have identified a 14-gene signature that predicts the survival of CLM patients after liver resection, with validation in an independent cohort. Although sample size is small, the significance level achieved with our survival analysis warrants further investigation of this 14-gene signature in a larger sample size.