Dynamic and concordance-assisted learning for risk stratification with application to Alzheimer's disease.

Dynamic prediction models capable of retaining accuracy by evolving over time could play a significant role for monitoring disease progression in clinical practice. In biomedical studies with long-term follow up, participants are often monitored through periodic clinical visits with repeat measurements until an occurrence of the event of interest (e.g. disease onset) or the study end. Acknowledging the dynamic nature of disease risk and clinical information contained in the longitudinal markers, we propose an innovative concordance-assisted learning algorithm to derive a real-time risk stratification score. The proposed approach bypasses the need to fit regression models, such as joint models of the longitudinal markers and time-to-event outcome, and hence enjoys the desirable property of model robustness. Simulation studies confirmed that the proposed method has satisfactory performance in dynamically monitoring the risk of developing disease and differentiating high-risk and low-risk population over time. We apply the proposed method to the Alzheimer's Disease Neuroimaging Initiative data and develop a dynamic risk score of Alzheimer's Disease for patients with mild cognitive impairment using multiple longitudinal markers and baseline prognostic factors.

Congenital Heart Defects and Concurrent Diagnoses in Influenza Hospitalization in the Pediatric Health Information System Study, 2004-2019.

Influenza is associated with adverse outcomes in children, although modification by additional medical conditions is not well-documented. We aimed to compare outcomes in children with versus without congenital heart defects (CHDs) who were hospitalized for influenza. We retrospectively evaluated patients 1-18y hospitalized for influenza in the Pediatric Health Information (PHIS) database from 2004 to 2019. Outcomes were compared by CHD presence and then by CHD severity (minor biventricular, major biventricular, and single ventricle disease) using log-binomial regression adjusted for propensity scores accounting for age at admission, sex, and history of asthma. Outcomes included inpatient mortality, intensive care unit (ICU) admission, mechanical ventilation, and length of stay (LOS) > 12 days. To evaluate for effect modification by genetic diagnoses, analyses were repeated stratified by CHD and genetic diagnosis. Among 55,161 children hospitalized for influenza, 2369 (4.3%) had CHDs, including 963 with minor biventricular, 938 with major biventricular, and 468 with single ventricle CHDs. Adjusting for propensity scores, children with CHDs had higher mortality (4.1% versus 0.9%) compared to those without CHDs (risk ratio [RR] 2.5, 95% confidence interval [CI] 1.9-3.4). Children with CHDs were at higher risk of mechanical ventilation (RR 1.6, 95% CI 1.6-1.7), ICU admission (RR 1.9, 95% CI 1.8-2.1), and LOS > 12 days (RR 2.2, 95% CI 2.0-2.3). Compared to those with neither CHD nor genetic condition, children with both had significantly higher risk of all outcomes, with the largest difference for LOS > 12 days (RR 2.3, 95% CI 2.0-2.7). Children with CHDs hospitalized for influenza are particularly susceptible to adverse outcomes compared to those without CHDs. Future studies are needed to corroborate findings in light of influenza vaccination.

Short-term associations between precipitation and gastrointestinal illness-related hospital admissions: A multi-city study in Texas.

The ongoing climate change crisis presents challenges to the global public health system. The risk of gastrointestinal illness (GI) related hospitalization increases following extreme weather events but is largely under-reported and under-investigated. This study assessed the association between precipitation and GI-related hospital admissions in four major cities in Texas. Daily data on GI-related hospital admissions and precipitation from 2004 to 2014 were captured from the Texas Department of State Health Services and the National Climate Data Center. Distributed lagged nonlinear modeling approaches were employed to examine the association between precipitation and GI-related hospital admissions. Results showed that the cumulative risk ratios (RRs) of GI-related hospital admissions were elevated in the 2 weeks following precipitation events; however, there were differences observed across study locations. The cumulative RR of GI-related hospitalizations was significantly higher when the amount of daily precipitation ranged from 3.3 mm to 13.5 mm in Dallas and from 6.0 mm to 24.5 mm in Houston. Yet, substantial increases in the cumulative RRs of GI-related hospitalizations were not observed in Austin or San Antonio. Age-specific and cause-specific GI-related hospitalizations were also found to be associated with precipitation events following the same pattern. Among them, Houston depicted the largest RR for overall GI and subgroup GI by age and cause, particularly for the overall GI among children aged 6 and under (RR = 1.35; 95 % CI = 1.11, 1.63), diarrhea-caused GI among children aged 6 and under (RR = 1.38, 95 % CI = 1.13, 1.69), and other-caused GI among children age 6 and under (RR = 1.46; 95 % CI = 1.12, 1.80). The findings underscore the need for public health interventions and adaptation strategies to address climate change-related health outcomes such as GI illness associated with extreme precipitation events.

Analyzing heterogeneity in biomarker discriminative performance through partial time-dependent receiver operating characteristic curve modeling.

This study investigates the heterogeneity of a biomarker's discriminative performance for predicting subsequent time-to-event outcomes across different patient subgroups. While the area under the curve (AUC) for the time-dependent receiver operating characteristic curve is commonly used to assess biomarker performance, the partial time-dependent AUC (PAUC) provides insights that are often more pertinent for population screening and diagnostic testing. To achieve this objective, we propose a regression model tailored for PAUC and develop two distinct estimation procedures for discrete and continuous covariates, employing a pseudo-partial likelihood method. Simulation studies are conducted to assess the performance of these procedures across various scenarios. We apply our model and inference procedure to the Alzheimer's Disease Neuroimaging Initiative data set to evaluate potential heterogeneities in the discriminative performance of biomarkers for early Alzheimer's disease diagnosis based on patients' characteristics.

Relationship between Food Security, Nutrition Security, and Diabetes: The Role of Supplemental Nutrition Assistance Program Participation.

Background: Inadequate nutrition and poor diet quality are associated with a heightened risk of diabetes. The connection between food insecurity measures and diabetes has been established, with evidence indicating that Supplemental Nutrition Assistance Program (SNAP) participation contributes to reductions in food insecurity. Recently developed nutrition security measures, defined as the ability to acquire healthful foods to prevent diseases, and their association with diabetes and SNAP participation are not yet understood. Objectives: This study aimed to assess the relationship between food security and nutrition security in relation to diabetes overall and by SNAP participation and nutrition security as potential modifiers. Methods: Secondary data analysis of cross-sectional pilot study data collected from adults in 5 US states (N = 517). Logistic regression mixed models included moderation analysis and clustering effects by state to address site-level confounding. Results: Higher nutrition security scores among adults, after adjusting for confounders, were significantly associated with lower odds of diabetes risk (adjusted odds ratio = 0.59; 95% confidence interval: 0.40, 0.87; P value = 0.008). Statistically significant interaction effect of differences according to SNAP participation was observed for nutrition security (Phomogeneity/interaction = 0.021), adjusting for age, gender, race/ethnicity, education, employment, National School Lunch Program, Special Supplemental Nutrition Program for Women, Infants, and Children, food pantry use, household with children, survey mode, and food security. The association between food security and diabetes was not statistically significant overall. However, statistically significant interaction effect of differences according to SNAP participation was observed for food security (Phomogeneity/interaction = 0.047). Further, no interaction effect of differences in nutrition security was found between food security and self-reported diabetes/prediabetes (Phomogeneity/interaction = 0.250). Conclusions: This study sheds light on the early exploration of the intricate relationship between nutrition security and diabetes. The findings suggest that a higher nutrition security score, after adjusting for confounders, was significantly associated with lower odds of diabetes risk. Notably, there were statistically significant interaction effects in these associations based on SNAP participation.

Rates and Predictors of Rapid Eye Movement Sleep Behavior Disorder Symptoms Among Post-9/11 Veterans.

OBJECTIVE: Posttraumatic stress disorder (PTSD) and traumatic brain injury (TBI), which are prevalent conditions among post-9/11 veterans, increase risks of rapid eye movement (REM) sleep behavior disorder (RBD) and degenerative synucleinopathy. Rates and predictors of RBD symptoms were investigated by screening post-9/11 veterans for RBD with a validated questionnaire. METHODS: In this cross-sectional analysis, consecutive patients in the Houston Translational Research Center for TBI and Stress Disorders (TRACTS) were screened with the English translation of the RBD Questionnaire-Hong Kong (RBDQ-HK). In addition to data from the standard TRACTS battery, systematic chart review was used to identify known sleep disorders mimicking or manifesting RBD. RESULTS: Of the 119 patients with available RBDQ-HK scores, 71 (60%) and 65 (55%) screened positive for RBD, when a total score ≥21 and a factor 2 score ≥8 were used as cutoff scores, respectively. Univariable analyses with both cutoffs showed consistent associations between a positive RBDQ-HK screen and global sleep quality, number of TBI exposures, and PTSD severity. Multivariable logistic regression with total score ≥21 as a cutoff indicated that PTSD severity (odds ratio=1.06, 95% CI=1.02-1.10) and number of TBIs (odds ratio=1.63, 95% CI=1.16-2.41) were independent predictors of a positive screen, whereas global sleep quality was no longer significant. Multivariable logistic regression with factor 2 score ≥8 as a cutoff showed similar results. CONCLUSIONS: Interdisciplinary parasomnia assessment, further validation of RBD screens, and standardized reporting of REM sleep without atonia could provide necessary information on the pathophysiological relationships linking PTSD, TBI, RBD symptoms, and ultimately synucleinopathy risk among post-9/11 veterans.

Interventions to increase follow-up of abnormal cervical cancer screening results: A systematic literature review and meta-analysis.

INTRODUCTION: Ensuring timely follow-up of abnormal screening results is essential for eliminating cervical cancer. OBJECTIVE: The purpose of the study was to review single and multicomponent interventions designed to improve follow-up of women with abnormal cervical cancer screening results. We report on effectiveness across studies, and describe what aspects of these interventions might be more impactful. METHODS: Publications were searched between January 2000 and December 2022. The search included observational, quasi-experimental (pre-post studies) and randomized controlled studies describing at least one intervention to increase follow-up of women with abnormal cervical cancer screening results. Outcomes of studies included completion of any follow-up (i.e., attending a follow-up appointment), timely diagnosis (i.e., colposcopy results within 90 days of screening) and time to diagnostic resolution (i.e., days between screening and final diagnosis). We assessed risk of bias for observational and quasi-experimental studies using the Newcastle-Ottawa Scale (NOS) tool and the Cochrane collaboration tool for randomized studies. We conducted a meta-analysis using studies where data were provided to estimate a summary average effect of the interventions on follow-up of patients and to identify characteristics of studies associated with an increased effectiveness of interventions. We extracted the comparison and intervention proportions of women with follow-up before and after the intervention (control and intervention) and plotted the odds ratios (ORs) of completing follow-up along with the 95% confidence intervals (CIs) using forest plots for the interventions vs. controls when data were available. FINDINGS: From 7,457 identified studies, 28 met the inclusion criteria. Eleven (39%) of the included studies had used a randomized design. Most studies (63%) assessed completion of any follow-up visit as the primary outcome, whereas others measured time to definite diagnosis (15%) or diagnostic resolution (22%). Navigation was used as a type of intervention in 63% of the included studies. Most interventions utilized behavioral approaches to improve outcomes. The overall estimate of the OR for completion of follow-up for all interventions was 1.81 (1.36-2.42). The highest impact was for programs using more than one approach (multicomponent interventions) to improve outcomes with OR = 3.01 (2.03-4.46), compared with studies with single intervention approaches with OR = 1.56 (1.14-2.14). No statistical risks were noted from publication bias or small-study effects in the studies reviewed. CONCLUSION: Our findings revealed large heterogeneity in how follow-up of abnormal cervical cancer screening results was defined. Our results suggest that multicomponent interventions were more effective than single component interventions and should be used to improve follow-up after abnormal cervical cancer screening results. Navigation appears to be an important tool for improving follow-up. We also provide recommendations for future studies and implications for policy in terms of better defining outcomes for these interventions.

Improved mortality prediction for pediatric acute liver failure using dynamic prediction strategy.

OBJECTIVES: To develop and validate a prediction tool for pediatric acute liver failure (PALF) mortality risks that captures the rapid and heterogeneous clinical course for accurate and updated prediction. METHODS: Data included 1144 participants with PALF enrolled during three phases of the PALF registry study over 15 years. Using joint modeling, we built a dynamic prediction tool for mortality by combining longitudinal trajectories of multiple laboratory and clinical variables. The predictive performance for 7-day and 21-day mortality was assessed using the area under curve (AUC) through cross-validation and split-by-time validation. RESULTS: We constructed a prognostic joint model that combines the temporal trajectories of international normalized ratio, total bilirubin, hepatic encephalopathy, platelet count, and serum creatinine. Dynamic prediction using updated information improved predictive performance over static prediction using the information at enrollment (Day 0) only. In cross-validation, AUC increased from 0.784 to 0.887 when measurements obtained between Days 1 and 2 were incorporated. AUC remained similar when we used the earlier subset of the sample for training and the later subset for testing. CONCLUSIONS: Serial measurements of five variables in the first few days of PALF capture the dynamic clinical course of the disease and improve risk prediction for mortality. Continuous disease monitoring and updating risk prognosis are beneficial for timely and judicious medical decisions.

Addressing subject heterogeneity in time-dependent discrimination for biomarker evaluation.

Accurate discrimination has been the central goal in identifying biomarkers for monitoring disease progression and early detection. Acknowledging the fact that discrimination accuracy of biomarkers for a time-to-event outcome often changes over time, local measures such as the time-dependent receiver operating characteristic curve and its area under the curve (AUC) are used to assess time-dependent predictive discrimination. However, such measures do not address subject heterogeneity, although the impact of covariates including demographics, disease-related characteristics, and other clinical information on the discriminatory performance of biomarkers needs to be investigated before their clinical use. We propose the covariate-specific time-dependent AUC, a measure for covariate-adjusted discrimination. We develop a regression model on the covariate-specific time-dependent AUC to understand how and in what magnitude the covariates influence biomarker performance. Then we construct a pseudo partial-likelihood for estimation and inference. This is followed by our establishing the asymptotic properties of the proposed estimators and provide variance estimation. The simulation studies and application to the AIDS Clinical Trials Group 175 data demonstrate that the proposed method offers an informative tool for inferring covariate-specific and time-dependent predictive discrimination.

The Time-Dependent Association Between Irritable Bowel Syndrome and All-Cause and Cause-Specific Mortality: A Prospective Cohort Study Within the UK Biobank.

INTRODUCTION: Irritable bowel syndrome (IBS) is one of the most common functional gastrointestinal disorders, but few studies have evaluated mortality risks among individuals with IBS. We explored the association between IBS and all-cause and cause-specific mortality in the UK Biobank. METHODS: We included 502,369 participants from the UK Biobank with mortality data through 2022. IBS was defined using baseline self-report and linkage to primary care or hospital admission data. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific mortality using multivariable Cox proportional hazards regression models within partitioned follow-up time categories (0-5, >5-10, and >10 years). RESULTS: A total of 25,697 participants (5.1%) had a history of IBS at baseline. After a median follow-up of 13.7 years, a total of 44,499 deaths occurred. Having an IBS diagnosis was strongly associated with lower risks of all-cause (HR = 0.70, 95% CI = 0.62-0.78) and all-cancer (HR = 0.69, 95% CI = 0.60-0.79) mortality in the first 5 years of follow-up. These associations were attenuated over follow-up, but even after 10 years of follow-up, associations remained inverse (all-cause: HR = 0.89, 95% CI = 0.84-0.96; all-cancer: HR = 0.87, 95% CI = 0.78-0.97) after full adjustment. Individuals with IBS had decreased risk of mortality from breast, prostate, and colorectal cancers in some of the follow-up time categories. DISCUSSION: We found that earlier during follow-up, having diagnosed IBS was associated with lower mortality risk, and the association attenuated over time. Additional studies to understand whether specific factors, such as lifestyle and healthcare access, explain the inverse association between IBS and mortality are needed.

Telemental Health Use Is Associated With Lower Health Care Spending Among Medicare Beneficiaries With Major Depression.

BACKGROUND: Some policymakers are concerned that expanding telehealth coverage may increase Medicare expenditures. However, there is limited evidence on the association of telehealth use with utilization and spending among Medicare beneficiaries with major depression. OBJECTIVE: To examine the differences in spending and utilization among telemental health users and non-telemental health users with major depression. METHODS: We examined 2014-2019 traditional Medicare claims data for beneficiaries aged ≥50 years with major depression in Texas. Multivariable generalized linear models were used to assess the relationships between telemental health use and Medicare spending and utilization while adjusting for patient demographics and programmatic and clinical factors. RESULTS: In each of the years between 2014 and 2019, an average of 4.6% Medicare beneficiaries with major depression had at least 1 telemental health visit. Compared with beneficiaries without a telemental health visit, those who had a telemental health visit were significantly more likely to be enrolled in Medicaid, be Medicare eligible due to a disability, live in a lower income area or in a rural area, and have a higher comorbidity index. Beneficiaries utilizing telemental health services incurred higher unadjusted Medicare spending than those not receiving telemental health services. However, this difference appeared due to beneficiary and programmatic characteristics rather than telemental health use. Adjusting for model covariates, the telemental health group had lower overall per member per year predicted spending, inpatient admissions, and emergency department visits than non-telemental health users. CONCLUSION: Our findings suggest that telemental health care use may improve access to mental health care without increasing Medicare spending among telemental health users in Texas.

Coronary flow capacity and survival prediction after revascularization: physiological basis and clinical implications.

BACKGROUND AND AIMS: Coronary flow capacity (CFC) is associated with an observed 10-year survival probability for individual patients before and after actual revascularization for comparison to virtual hypothetical ideal complete revascularization. METHODS: Stress myocardial perfusion (mL/min/g) and coronary flow reserve (CFR) per pixel were quantified in 6979 coronary artery disease (CAD) subjects using Rb-82 positron emission tomography (PET) for CFC maps of artery-specific size-severity abnormalities expressed as percent left ventricle with prospective follow-up to define survival probability per-decade as fraction of 1.0. RESULTS: Severely reduced CFC in 6979 subjects predicted low survival probability that improved by 42% after revascularization compared with no revascularization for comparable severity (P = .0015). For 283 pre-and-post-procedure PET pairs, severely reduced regional CFC-associated survival probability improved heterogeneously after revascularization (P < .001), more so after bypass surgery than percutaneous coronary interventions (P < .001) but normalized in only 5.7%; non-severe baseline CFC or survival probability did not improve compared with severe CFC (P = .00001). Observed CFC-associated survival probability after actual revascularization was lower than virtual ideal hypothetical complete post-revascularization survival probability due to residual CAD or failed revascularization (P < .001) unrelated to gender or microvascular dysfunction. Severely reduced CFC in 2552 post-revascularization subjects associated with low survival probability also improved after repeat revascularization compared with no repeat procedures (P = .025). CONCLUSIONS: Severely reduced CFC and associated observed survival probability improved after first and repeat revascularization compared with no revascularization for comparable CFC severity. Non-severe CFC showed no benefit. Discordance between observed actual and virtual hypothetical post-revascularization survival probability revealed residual CAD or failed revascularization.

Dynamic risk score modeling for multiple longitudinal risk factors and survival.

Modeling disease risk and survival using longitudinal risk factor trajectories is of interest in various clinical scenarios. The capacity to build a prognostic model using the trajectories of multiple longitudinal risk factors, in the presence of potential dependent censoring, would enable more informed, personalized decision making. A dynamic risk score modeling framework is proposed for multiple longitudinal risk factors and survival in the presence of dependent censoring, where both events depend on participants' post-baseline clinical progression and form a competing risks structure. The model requires relatively few random effects regardless of the number of longitudinal risk factors and can therefore accommodate multiple longitudinal risk factors in a parsimonious manner. The proposed method performed satisfactorily in extensive simulation studies. It is further applied to the motivating registry study on pediatric acute liver failure to model death using the trajectories of multiple clinical and biochemical markers. Once established, the model yields an easily calculable longitudinal risk score that can be used for disease monitoring among future patients.

The association between inflammatory bowel disease and all-cause and cause-specific mortality in the UK Biobank.

PURPOSE: Inflammatory bowel disease (IBD) has a rising global prevalence. However, the understanding of its impact on mortality remains inconsistent so we explored the association between IBD and all-cause and cause-specific mortality. METHODS: This study included 502,369 participants from the UK Biobank, a large, population-based, prospective cohort study with mortality data through 2022. IBD was defined by baseline self-report or from primary care or hospital admission data. We estimated hazard ratios (HRs) and 95% confidence intervals (CIs) for all-cause and cause-specific mortality in multivariable Cox proportional hazards regression models. RESULTS: A total of 5799 (1.2%) participants had a history of IBD at baseline. After a median follow-up of 13.7 years, 44,499 deaths occurred. Having IBD was associated with an increased risk of death from all causes (HR = 1.16, 95% CI = 1.07-1.24) and cancer (HR = 1.16, 95% CI = 1.05-1.30), particularly colorectal cancer (CRC) (HR = 1.56, 95% CI = 1.17-2.09). We observed elevated breast cancer mortality rates for individuals with Crohn's disease, and increased CRC mortality rates for individuals with ulcerative colitis. In stratified analyses of IBD and all-cause mortality, mortality risk differed by individuals' duration of IBD, age at IBD diagnosis, body mass index (BMI) (PHeterogeneity = 0.03) and smoking status (PHeterogeneity = 0.01). Positive associations between IBD and all-cause mortality were detected in individuals diagnosed with IBD for 10 years or longer, those diagnosed before the age of 50, all BMI subgroups except obese individuals, and in never or current, but not former smokers. CONCLUSIONS: We found that having IBD was associated with increased risks of mortality from all causes, all cancers, and CRC. This underscores the importance of enhanced patient management strategies and targeted prevention efforts in individuals with IBD.

Association of Atherosclerotic Cardiovascular Disease, Hypertension, Diabetes, and Hyperlipidemia With Gulf War Illness Among Gulf War Veterans.

BACKGROUND: Approximately 30% of the 700 000 Gulf War veterans report a chronic symptom-based illness of varying severity referred to as Gulf War illness (GWI). Toxic deployment-related exposures have been implicated in the cause of GWI, some of which contribute to metabolic dysregulation and lipid abnormalities. As this cohort ages, the relationship between GWI and atherosclerotic cardiovascular disease (ASCVD) is a growing concern. We evaluated associations between GWI and ASCVD, diabetes, hyperlipidemia, and hypertension in veterans of the Gulf War (1990-1991). METHODS AND RESULTS: Analysis of survey data collected in 2014 to 2016 from a national sample of deployed Gulf War veterans (n=942) and Veterans Health Administration electronic health record data (n=669). Multivariable logistic regression models tested for associations of GWI with self-reported ASCVD, diabetes, hyperlipidemia, and hypertension, controlling for confounding factors. Separate models tested for GWI associations with ASCVD and risk factors documented in the electronic health record. GWI was associated with self-reported hypertension (adjusted odds ratio [aOR], 1.67 [95% CI, 1.18-2.36]), hyperlipidemia (aOR, 1.46 [95% CI, 1.03-2.05]), and ASCVD (aOR, 2.65 [95% CI, 1.56-4.51]). In the subset of veterans with electronic health record data, GWI was associated with documented diabetes (aOR, 2.34 [95% CI, 1.43-3.82]) and hypertension (aOR, 2.84 [95% CI, 1.92-4.20]). Hyperlipidemia and hypertension served as partial mediators of the association between GWI and self-reported ASCVD. CONCLUSIONS: Gulf War veterans with GWI had higher odds of hyperlipidemia, hypertension, diabetes, and ASCVD compared with Gulf War veterans without GWI. Further examination of the mechanisms underlying this association, including a possible shared exposure-related mechanism, is necessary.

Evaluating Dynamic Discrimination Performance of Risk Prediction Models for Survival Outcomes.

Risk prediction models for survival outcomes are widely applied in medical research to predict future risk for the occurrence of the event. In many clinical studies, the biomarker data are measured repeatedly over time. To facilitate timely disease prognosis and decision making, many dynamic prediction models have been developed and generate predictions on a real-time basis. As a dynamic prediction model updates an individual's risk prediction over time based on new measurements, it is often important to examine how well the model performs at different measurement times and prediction times. In this article, we propose a two-dimensional area under curve (AUC) measure for dynamic prediction models and develop associated estimation and inference procedures. The estimation procedures are discussed under two types of biomarker measurement schedules: regular visits and irregular visits. The model parameters are estimated effectively by maximizing a pseudo-partial likelihood function. We apply the proposed method to a renal transplantation study to evaluate the discrimination performance of dynamic prediction models based on longitudinal biomarkers for graft failure.

Hormonal changes in veterans with Gulf War Illness.

AIMS: Gulf War Illness (GWI) is a multi-system condition of complex etiology and pathophysiology without specific treatment. There is an overlap between the symptoms of GWI and endocrinopathies. This study aimed to identify hormonal alterations in 1990-91 Gulf War (GW) veterans and the relationship between GWI and hormonal dysregulation. MAIN METHODS: Data from 81 GW veterans (54 with GWI and 27 controls without GWI) was analyzed in a cross-sectional, case-control observational study. Participants completed multiple questionnaires, neuropsychiatric assessments, and a comprehensive set of hormone assays including a glucagon stimulation test (GST) for adult growth hormone deficiency (AGHD) and a high-dose adrenocorticotropic hormone (ACTH) stimulation test for adrenal insufficiency. KEY FINDINGS: The GWI group had lower quality of life and greater severity of all symptoms compared to controls. Pain intensity and pain-related interference with general activity were also higher in the GWI group. AGHD was observed in 18 of 51 veterans with GWI (35.3 %) and 2 of 26 veterans without GWI (7.7 %) (p = 0.012 for interaction). Veterans with GWI also exhibited reduced insulin-like growth factor 1 (IGF-1) levels and IGF-1 Z-scores compared to controls. One participant with GWI met the criteria for adrenal insufficiency. No significant changes were observed in other hormonal axes. SIGNIFICANCE: The frequency of AGHD was significantly higher in veterans with GWI compared to controls. Recombinant human growth hormone replacement therapy (GHRT) may become a breakthrough therapeutic option for this subgroup. A large clinical trial is needed to evaluate the efficacy of GHRT in patients with GWI and AGHD.

Reimbursement for HPV Vaccine Cost in the Private Sector: A Comparison Across Specialties.

The human papillomavirus (HPV) vaccine is the most expensive of all routinely recommended pediatric vaccines. Adequate cost reimbursement by 3rd-party payers is a critical enabling factor for clinicians to continue offering vaccines. This study found that net returns from HPV vaccine cost reimbursements are lowest for family physicians ($0.34/dose) and highest for pediatricians ($5.08/dose). Furthermore, a $1 increment in return was associated with an increase in HPV vaccine doses administered (highest for family physicians; 0.08% per dollar). Reimbursement for HPV vaccine costs by private payers is adequate; however, return margins are small for non-pediatric specialties.

A double-robust test for high-dimensional gene coexpression networks conditioning on clinical information.

It has been increasingly appealing to evaluate whether expression levels of two genes in a gene coexpression network are still dependent given samples' clinical information, in which the conditional independence test plays an essential role. For enhanced robustness regarding model assumptions, we propose a class of double-robust tests for evaluating the dependence of bivariate outcomes after controlling for known clinical information. Although the proposed test relies on the marginal density functions of bivariate outcomes given clinical information, the test remains valid as long as one of the density functions is correctly specified. Because of the closed-form variance formula, the proposed test procedure enjoys computational efficiency without requiring a resampling procedure or tuning parameters. We acknowledge the need to infer the conditional independence network with high-dimensional gene expressions, and further develop a procedure for multiple testing by controlling the false discovery rate. Numerical results show that our method accurately controls both the type-I error and false discovery rate, and it provides certain levels of robustness regarding model misspecification. We apply the method to a gastric cancer study with gene expression data to understand the associations between genes belonging to the transforming growth factor ß signaling pathway given cancer-stage information.