Effect of a male-targeted digital decision support application aimed at increasing linkage to HIV care among men: Findings from the HITS cluster randomized clinical trial in rural South Africa

Introduction

Linkage to HIV care remains suboptimal among men. We investigated the effectiveness of a male-targeted HIV-specific decision support app, Empowering People through Informed Choices for HIV (EPIC-HIV), on increasing linkage to HIV care among men in rural South Africa.

Methods

Home-Based Intervention to Test and Start (HITS) was a multi-component cluster-randomized controlled trial among 45 communities in uMkhanyakude, KwaZulu-Natal. The development of EPIC-HIV was guided by self-determination theory and human-centered intervention design to increase intrinsic motivation to seek HIV testing and care among men. EPIC-HIV was offered in two stages: EPIC-HIV 1 at the time of home-based HIV counseling and testing (HBHCT), and EPIC-HIV 2 at 1 month after positive HIV diagnosis. Sixteen communities were randomly assigned to the arms to receive EPIC-HIV, and 29 communities to the arms without EPIC-HIV. Among all eligible men, we compared linkage to care (initiation or resumption of antiretroviral therapy after >3 months of care interruption) at local clinics within 1 year of a home visit, which was ascertained from individual clinical records. Intention-to-treat analysis was performed using modified Poisson regression with adjustment for receiving another intervention (i.e., financial incentives) and clustering at the community level. We also conducted a satisfaction survey for EPIC-HIV 2.

Results

Among all 13,894 eligible men (i.e., ≥15 years and resident in the 45 communities), 20.7% received HBHCT, resulting in 122 HIV-positive tests. Among these, 54 men linked to care within 1 year after HBHCT. Additionally, of the 13,765 eligible participants who did not receive HBHCT or received HIV-negative results, 301 men linked to care within 1 year. Overall, only 13 men received EPIC-HIV 2. The proportion of linkage to care did not differ in the arms assigned to EPIC-HIV compared to those without EPIC-HIV (adjusted risk ratio=1.05; 95% CI:0.86-1.29). All 13 men who used EPIC-HIV 2 reported the app was acceptable, user-friendly, and useful for getting information on HIV testing and treatment.

Conclusion

Reach was low although acceptability and usability of the app was very high among those who engaged with it. Enhanced digital support applications could form part of interventions to increase knowledge of HIV treatment for men. Clinical Trial Number: ClinicalTrials.gov # NCT03757104.

The impact of a conditional financial incentive on linkage to HIV care: Findings from the HITS cluster randomized clinical trial in rural South Africa

Introduction

HIV elimination requires innovative approaches to ensure testing and immediate treatment provision. We investigated the effectiveness of conditional financial incentives on increasing linkage to HIV care in a 2×2 factorial cluster randomized controlled trial-Home-Based Intervention to Test and Start (HITS) - in rural South Africa.

Methods

Of 45 communities in uMkhanyakude, KwaZulu-Natal, 16 communities were randomly assigned to the arms to receive financial incentives for home-based HIV counseling and testing (HBHCT) and linkage to care within 6 weeks (R50 [US$3] food voucher each) and 29 communities to the arms without financial incentives. We examined linkage to care (i.e., initiation or resumption of antiretroviral therapy after >3 months of care interruption) at local clinics within 6 weeks of a home visit, the eligibility period to receive the second financial incentive. Linkage to care was ascertained from individual clinical records. Intention-to-treat analysis (ITT) was performed using modified Poisson regression with adjustment for receiving another intervention (i.e., male-targeted HIV-specific decision support app) and clustering of standard errors at the community level.

Results

Among 13,894 eligible men (i.e., ≥15 years and resident in the 45 communities), 20.7% received HBHCT, which resulted in 122 HIV-positive tests. Of these, 27 linked to care within 6 weeks of HBHCT. Additionally, of eligible men who did not receive HBHCT, 66 linked to care. In the ITT analysis, the proportion of linkage to care among men did not differ in the arms which received financial incentives and those without financial incentives (adjusted Risk Ratio [aRR]=0.78, 95% CI: 0.51-1.21). Among 19,884 eligible women, 29.1% received HBHCT, which resulted in 375 HIV-positive tests. Of these, 75 linked to care. Among eligible women who did not receive HBHCT, 121 linked to care within 6 weeks. Women in the financial incentive arms had a significantly higher probability of linkage to care, compared to those in the arms without financial incentives (aRR=1.50; 95% CI: 1.03-2.21).

Conclusion

While a small once-off financial incentive did not increase linkage to care among men during the eligibility period of 6 weeks, it significantly improved linkage to care among women over the same period. Clinical Trial Number: ClinicalTrials.gov # NCT03757104.

Age Differences in Core Symptoms and Symptom Relationships in Patients With Irritable Bowel Syndrome: A Network Analysis

INTRODUCTION

Irritable bowel syndrome (IBS) is a common disorder of gut-brain interaction, characterized by symptoms of abdominal pain and changes in bowel habits. It often co-occurs with extraintestinal somatic and psychological symptoms. However, the nature of the interrelationships among these symptoms is unclear. Although previous studies have noted age differences in IBS prevalence and specific symptom severity, it remains unknown whether specific symptoms and symptom relationships may differ by age.

METHODS

Symptom data were collected in 355 adults with IBS (mean age 41.4 years, 86.2% female). Network analysis was used to examine the interrelationships among 28 symptoms and to identify the core symptoms driving the symptom structure between young (≤45 years) vs older (>45 years) adults with IBS. We evaluated 3 network properties between the 2 age groups: network structure, edge (connection) strength, and global strength.

RESULTS

In both age groups, fatigue was the top core symptom. Anxiety was a second core symptom in the younger age group, but not the older age group. Intestinal gas and/or bloating symptoms also exerted considerable influences in both age groups. The overall symptom structure and connectivity were found to be similar regardless of age.

DISCUSSION

Network analysis suggests fatigue is a critical target for symptom management in adults with IBS, regardless of age. Comorbid anxiety is likely an important treatment focus for young adults with IBS. Rome V criteria update could consider the importance of intestinal gas and bloating symptoms. Additional replication with larger diverse IBS cohorts is warranted to verify our results.

Association of Perceived Neighborhood Environments With Cognitive Function in Older Adults

The current study examined the associations between perceptions of the social and physical neighborhood environments and cognitive function in older adults. This cross-sectional study analyzed 821 adults aged ≥65 years from the Adult Changes in Thought study. Perceived neighborhood attributes were measured by the Physical Activity Neighborhood Environment Scale. Cognitive function was assessed using the Cognitive Ability Screening Instrument. The associations were tested using multivariate linear regression. One point greater perceived access to public transit was associated with 0.56 points greater cognitive function score (95% confidence interval [CI] [0.25, 0.88]), and an additional one point of perceived sidewalk coverage was related to 0.22 points higher cognitive function score (95% CI [0.00, 0.45]) after controlling for sociodemographic factors. The perception of neighborhood attributes alongside physical infrastructure may play an important role in supporting older adults' cognitive function. [Journal of Gerontological Nursing, 49(8), 35-41.].

Mediating role of walking between perceived and objective walkability and cognitive function in older adults

The aim of this study was to examine the role of walking in explaining associations between perceived and objective measures of walkability and cognitive function among older adults. The study employed a cross-sectional design analyzing existing data. Data were obtained from the Adult Changes in Thought Activity Monitor study. Cognitive function and perceived walkability were measured by a survey. Objective walkability was measured using geographic information systems (GIS). Walking was measured using an accelerometer. We tested the mediating relationship based on 1,000 bootstrapped samples. Perceived walkability was associated with a 0.04 point higher cognitive function score through walking (p = 0.006). The mediating relationship accounted for 34% of the total relationship between perceived walkability and cognitive function. Walking did not have a significant indirect relationship on the association between objective walkability and cognitive function. Perceived walkability may be more relevant to walking behavior than objective walkability among older adults. Greater levels of perceived walkability may encourage older adults to undertake more walking, and more walking may in turn improve cognitive function in older adults.

Can a conditional financial incentive (CFI) reduce socio-demographic inequalities in home-based HIV testing uptake? A secondary analysis of the HITS clinical trial intervention in rural South Africa

In sub-Saharan Africa, home-based HIV testing interventions are designed to reach sub-populations with low access to HIV testing such as men, younger or less educated people. Combining these interventions with conditional financial incentives (CFI) has been shown to be effective to increase testing uptake. CFI are effective for one-off health behaviour change but whether they operate differentially on different socio-demographic groups is less clear. Using data from the HITS trial in South Africa, we investigated whether a CFI was able to reduce existing home-based HIV testing uptake inequalities observed by socio-demographic groups. Residents aged ≥15 years in the study area were assigned to an intervention arm (16 clusters) or a control arm (29 clusters). In the intervention arm, individuals received a food voucher (∼3.5 US dollars) if they accepted to take a home-based HIV test. Testing uptake differences were considered for socio-demographic (sex, age, education, employment status, marital status, household asset index) and geographical (urban/rural living area, distance from clinic) characteristics. Among the 37,028 residents, 24,793 (9290 men, 15,503 women) were included in the analysis. CFI increased significantly testing uptake among men (39.2% vs 25.2%, p < 0.001) and women (45.9% vs 32.0%, p < 0.001) with similar absolute increase between men and women. Uptake was higher amongst the youngest or least educated individuals, and amongst single (vs in union) or unemployed men. Absolute uptake increase was also significantly higher amongst these groups resulting in increasing socio-demographic differentials for home-based HIV testing uptake. However, because these groups are known to have less access to other public HIV testing services, CFI could reduce inequalities for HIV testing access in our specific context. Although CFI significantly increased home-based HIV testing uptake, it did not do so differentially by socio-demographic group. Future interventions using CFI should make sure that the intervention alone does not increase existing health inequities.

Home-Based Intervention to Test and Start (HITS): a community-randomized controlled trial to increase HIV testing uptake among men in rural South Africa

Introduction

The uptake of HIV testing and linkage to care remains low among men, contributing to high HIV incidence in women in South Africa. We conducted the “Home‐Based Intervention to Test and Start” (HITS) in a 2x2 factorial cluster randomized controlled trial in one of the World’s largest ongoing HIV cohorts in rural South Africa aimed at enhancing both intrinsic and extrinsic motivations for HIV testing.

Methods

Between February and December 2018, in the uMkhanyakude district of KwaZulu‐Natal, we randomly assigned 45 communities (clusters) (n = 13,838 residents) to one of the four arms: (i) financial incentives for home‐based HIV testing and linkage to care (R50 [$3] food voucher each); (ii) male‐targeted HIV‐specific decision support application, called EPIC‐HIV; (iii) both financial incentives and male‐targeted HIV‐specific decision support application and (iv) standard of care (SoC). EPIC‐HIV was developed to encourage and serve as an intrinsic motivator for HIV testing and linkage to care, and individually offered to men via a tablet device. Financial incentives were offered to both men and women. Here we report the effect of the interventions on uptake of home‐based HIV testing among men. Intention‐to‐treat (ITT) analysis was performed using modified Poisson regression with adjustment for clustering of standard errors at the cluster levels.

Results

Among all 13,838 men ≥ 15 years living in the 45 communities, the overall population coverage during a single round of home‐based HIV testing was 20.7%. The uptake of HIV testing was 27.5% (683/2481) in the financial incentives arm, 17.1% (433/2534) in the EPIC‐HIV arm, 26.8% (568/2120) in the arm receiving both interventions and 17.8% in the SoC arm. The probability of HIV testing increased substantially by 55% in the financial incentives arm (risk ratio (RR)=1.55, 95% CI: 1.31 to 1.82, p < 0.001) and 51% in the arm receiving both interventions (RR = 1.51, 95% CI: 1.21 to 1.87 p < 0.001), compared to men in the SoC arm. The probability of HIV testing did not significantly differ in the EPIC‐HIV arm (RR = 0.96, 95% CI: 0.76 to 1.20, p = 0.70).

Conclusions

The provision of a small financial incentive acted as a powerful extrinsic motivator substantially increasing the uptake of home‐based HIV testing among men in rural South Africa. In contrast, the counselling and testing application which was designed to encourage and serve as an intrinsic motivator to test for HIV did not increase the uptake of home‐based testing.

HIV incidence declines in a rural South African population: a G-imputation approach for inference

BACKGROUND

Ad hoc assumptions about the unobserved infection event, which is known only to occur between the latest-negative and earliest-positive test dates, can lead to biased HIV incidence rate estimates. Using a G-imputation approach, we infer the infection dates from covariate data to estimate the HIV incidence rate in a hyper-endemic South African setting.

METHODS

A large demographic surveillance system has annually tested a cohort of HIV-uninfected participants living in the KwaZulu-Natal province. Using this data, we estimated a cumulative baseline hazard function and the effects of time-dependent covariates on the interval censored infection dates. For each HIV-positive participant in the cohort, we derived a cumulative distribution function and sampled multiple infection dates conditional on the unique covariate values. We right censored the data at the imputed dates, calculated the annual HIV incidence rate per 100 person-years, and used Rubin's rules to obtain the 95% confidence intervals.

RESULTS

A total of 20,011 uninfected individuals with a repeat HIV test participated in the incidence cohort between 2005 and 2018. We observed 2,603 infections per 58,769 person-years of follow-up among women and 845 infections per 41,178 person-years of follow-up among men. Conditional on age and circumcision status (men only), the female HIV incidence rate declined by 25%, from 5.0 to 3.7 infections per 100 person-years between 2014 and 2018. During this period, the HIV incidence rate among men declined from 2.1 to 1.1 infections per 100 person-years-a reduction of 49%. We observed similar reductions in male and female HIV incidence conditional on condom-use, marital status, urban residential status, migration history, and the HIV prevalence in the surrounding community.

CONCLUSION

We have followed participants in one of the world's largest and longest running HIV cohorts to estimate long-term trends in the population-wide incidence of infection. Using a G-imputation approach, we present further evidence for HIV incidence rate declines in this hyper-endemic South African setting.

Migration and first-year maternal mortality among HIV-positive postpartum women: A population-based longitudinal study in rural South Africa

BACKGROUND

In South Africa, within-country migration is common. Mobility affects many of the factors in the pathway for entry to or retention in care among people living with HIV. We characterized the patterns of migration (i.e., change in residency) among peripartum women from rural South Africa and their association with first-year postpartum mortality.

METHODS AND FINDINGS

All pregnant women aged ≥15 years were followed-up during pregnancy and the first year postpartum in a population-based longitudinal demographic and HIV surveillance program in KwaZulu-Natal, South Africa, from 2000 to 2016. During the household surveys (every 4-6 months), each household head was interviewed to record demographic components of the household, including composition, migration, and mortality. External migration was defined as moving (i.e., change in residency) into or out of the study area. For women of reproductive age, detailed information on new pregnancy and birth was recorded. Maternal death was ascertained via verbal autopsy and HIV status at delivery via annual HIV surveys. We fitted mixed-effects Cox regression models adjusting for multiple pregnancies per individual. Overall, 19,334 women had 30,291 pregnancies: 3,339 were HIV-positive, 10,958 were HIV-negative, and 15,994 had unknown HIV status at delivery. The median age was 24 (interquartile range: 20-30) years. During pregnancy and the first year postpartum, 64% (n = 19,344) and 13% (n = 3,994) did not migrate and resided within and outside the surveillance area, respectively. Of the 23% who had externally migrated at least once, 39% delivered outside the surveillance area. Overall, the mortality rate was 5.8 per 1,000 person-years (or 831 deaths per 100,000 live births) in the first year postpartum. The major causes of deaths were AIDS- or tuberculosis-related conditions both within 42 days of delivery (53%) and during the first year postpartum (62%). In this study, we observed that HIV-positive peripartum women who externally migrated and delivered outside the surveillance area had a hazard of mortality more than two times greater (hazard ratio = 2.74; 95% confidence interval 1.01-7.40, p-value = 0.047)-after adjusting for age, time period (before or after 2010), and sociodemographic status-compared to that of HIV-positive women who continuously resided within the surveillance area. Study limitations include lack of data on access to antiretroviral therapy (ART) care and social or clinical context at the destinations among mobile participants, which could lead to unmeasured confounding. Further information on how mobile postpartum women access and remain in care would be instructive.

CONCLUSIONS

In this study, we found that a substantial portion of peripartum women moved within the country around the time of delivery and experienced a significantly higher risk of mortality. Despite the scale-up of universal ART and declining trends in maternal mortality, there is an urgent need to derive a greater understanding of the mechanisms underlying this finding and to develop targeted interventions for mobile HIV-positive peripartum women.

A statistical framework for measuring the temporal stability of human mobility patterns

Despite the growing popularity of human mobility studies that collect GPS location data, the problem of determining the minimum required length of GPS monitoring has not been addressed in the current statistical literature. In this paper, we tackle this problem by laying out a theoretical framework for assessing the temporal stability of human mobility based on GPS location data. We define several measures of the temporal dynamics of human spatiotemporal trajectories based on the average velocity process, and on activity distributions in a spatial observation window. We demonstrate the use of our methods with data that comprise the GPS locations of 185 individuals over the course of 18 months. Our empirical results suggest that GPS monitoring should be performed over periods of time that are significantly longer than what has been previously suggested. Furthermore, we argue that GPS study designs should take into account demographic groups.

Home-based intervention to test and start (HITS) protocol: a cluster-randomized controlled trial to reduce HIV-related mortality in men and HIV incidence in women through increased coverage of HIV treatment

BACKGROUND

To realize the full benefits of treatment as prevention in many hyperendemic African contexts, there is an urgent need to increase uptake of HIV testing and HIV treatment among men to reduce the rate of HIV transmission to (particularly young) women. This trial aims to evaluate the effect of two interventions - micro-incentives and a tablet-based male-targeted HIV decision support application - on increasing home-based HIV testing and linkage to HIV care among men with the ultimate aim of reducing HIV-related mortality in men and HIV incidence in young women.

METHODS/DESIGN

This is a cluster randomized trial of 45 communities (clusters) in a rural area in the uMkhanyakude district of KwaZulu Natal, South Africa (2018-2021). The study is built upon the Africa Health Research Institute (AHRI)'s HIV testing platform, which offers annual home-based rapid HIV testing to individuals aged 15 years and above. In a 2 × 2 factorial design, individuals aged ≥15 years living in the 45 clusters are randomly assigned to one of four arms: i) a financial micro-incentive (food voucher) (n = 8); ii) male-targeted HIV specific decision support (EPIC-HIV) (n = 8); iii) both the micro incentives and male-targeted decision support (n = 8); and iv) standard of care (n = 21). The EPIC-HIV application is developed and delivered via a tablet to encourage HIV testing and linkage to care among men. A mixed method approach is adopted to supplement the randomized control trial and meet the study aims.

DISCUSSION

The findings of this trial will provide evidence on the feasibility and causal impact of two interventions - micro-incentives and a male-targeted HIV specific decision support - on uptake of home-based HIV testing, linkage to care, as well as population health outcomes including population viral load, HIV related mortality in men, and HIV incidence in young women (15-30 years of age).

TRIAL REGISTRATION

This trial was registered on 28 November 2018 on, identifier https://clinicaltrials.gov/ .

A method for statistical analysis of repeated residential movements to link human mobility and HIV acquisition

We propose a method for analyzing repeated residential movements based on graphical loglinear models. This method allows an explicit representation of residential presence and absence patterns from several areas without defining mobility measures. We make use of our method to analyze data from one of the most comprehensive demographic surveillance sites in Africa that is characterized by high adult HIV prevalence, high levels of poverty and unemployment and frequent residential changes. Between 2004 and 2016, residential changes were recorded for 8,857 men over 35,500.01 person-years, and for 12,158 women over 57,945.35 person-years. These individuals were HIV negative at baseline. Over the study duration, there were a total of 806 HIV seroconversions in men, and 2,458 HIV seroconversions in women. Our method indicates that establishing a residence outside the rural study area is a strong predictor of HIV seroconversion in men (OR = 2.003, 95% CI = [1.718,2.332]), but not in women. Residing inside the rural study area in a single or in multiple locations is a less significant risk factor for HIV acquisition in both men and women compared to moving outside the rural study area.

Effects of Osteoarthritis Pain and Concurrent Insomnia and Depression on Health Care Use in a Primary Care Population of Older Adults

OBJECTIVE

To examine independent and combined effects of pain with concurrent insomnia and depression symptoms on the use of health care services in older adults with osteoarthritis (OA).

METHODS

Patients were Group Health Cooperative (GHC) patients with a primary diagnosis of OA (n = 2,976). We used survey data on pain (Graded Chronic Pain Scale), insomnia (Insomnia Severity Index), and depression (Patient Health Questionnaire-8), and health care use extracted from GHC electronic health records (office visits, length of stay, outpatient and inpatient costs, and hip or knee replacement) for 3 years after the survey. Negative binomial, logistic, and generalized linear models were used to assess predictors of health care use.

RESULTS

Approximately 34% and 29% of patients displayed at least subclinical insomnia and at least subclinical depression symptoms, respectively, in addition to moderate-to-severe pain. Pain had the greatest independent effects on increasing all types of health care use, followed by depression (moderate effects) on increased office visits, length of stay, outpatient and inpatient costs, and insomnia (mild effects) on decreased length of stay. No synergistic effects of the 3 symptoms on use of health care services were observed. The combined effects of pain plus insomnia and pain plus depression were significant for all types of health care use and increased greatly with increasing severity of insomnia and depression, except for hip/knee replacement.

CONCLUSION

Pain is the main driver for health care use in patients with OA. In addition to pain, insomnia plus depression jointly increased diverse types of health care use, and these combined effects increased greatly with increasing severity of insomnia and depression. These findings indicate the important role that concurrent symptomatic conditions may play in increasing use of health care services.

Identifying 'corridors of HIV transmission' in a severely affected rural South African population: a case for a shift toward targeted prevention strategies

Background

In the context of a severe generalized African HIV epidemic, the value of geographically targeted prevention interventions has only recently been given serious consideration. However, to date no study has performed a population-based analysis of the micro-geographical clustering of HIV incident infections, limiting the evidential support for such a strategy.

Methods

We followed 17 984 HIV-uninfected individuals aged 15–54 in a population-based cohort in rural KwaZulu-Natal, South Africa, and observed individual HIV sero-conversions between 2004 and 2014. We geo-located all individuals to an exact homestead of residence (accuracy <2 m). We then employed a two-dimensional Gaussian kernel of radius 3 km to produce robust estimates of HIV incidence which vary across continuous geographical space. We also applied Tango's flexibly shaped spatial scan statistic to identify irregularly shaped clusters of high HIV incidence.

Results

Between 2004 and 2014, we observed a total of 2 311 HIV sero-conversions over 70 534 person-years of observation, at an overall incidence of 3.3 [95% confidence interval (CI), 3.1-3.4] per 100 person-years. Three large irregularly-shaped clusters of new HIV infections (relative risk = 1.6, 1.7 and 2.3) were identified in two adjacent peri-urban communities near the National Road (P = 0.001, 0.015) as well as in a rural node bordering a recent coal mine development (P = 0.020), respectively. Together the clusters had a significantly higher age-sex standardized incidence of 5.1 (95% CI, 4.7-5.6) per 100 person-years compared with a standardized incidence of 3.0 per 100 person-years (95% CI, 2.9-3.2) in the remainder of the study area. Though these clusters comprise just 6.8% of the study area, they account for one out of every four sero-conversions observed over the study period.

Conclusions

Our study has revealed clear ‘corridors of transmission’ in this typical rural, hyper-endemic population. Even in a severely affected rural African population, an approach that seeks to provide preventive interventions to the most vulnerable geographies could be more effective and cost-effective in reducing the overall rate of new HIV infections. There is an urgent need to develop and test such interventions as part of an overall combination prevention approach.

Estimating trends in the incidence rate with interval censored data and time-dependent covariates

We propose a multiple imputation method for estimating the incidence rate with interval censored data and time-dependent (and/or time-independent) covariates. The method has two stages. First, we use a semi-parametric G-transformation model to estimate the cumulative baseline hazard function and the effects of the time-dependent (and/or time-independent covariates) on the interval censored infection times. Second, we derive the participant's unique cumulative distribution function and impute infection times conditional on the covariate values. To assess performance, we simulated infection times from a Cox proportional hazards model and induced interval censoring by varying the testing rate, e.g., participants test 100%, 75%, 50% of the time, etc. We then compared the incidence rate estimates from our G-imputation approach with single random-point and mid-point imputation. By comparison, our G-imputation approach gave more accurate incidence rate estimates and appropriate standard errors for models with time-independent covariates only, time-dependent covariates only, and a mixture of time-dependent and time-independent covariates across various testing rates. We demonstrate, for the first time, a multiple imputation approach for incidence rate estimation with interval censored data and time-dependent (and/or time-independent) covariates.

Effects of Pain, Insomnia, and Depression on Psychoactive Medication Supply in Older Adults With Osteoarthritis

BACKGROUND

Determinants of prescribing psychoactive medications for symptom management in older adults remain underexamined despite known risks and cautions concerning these medications.

OBJECTIVE

To examine independent and combined effects of pain, concurrent insomnia and depression symptoms on psychoactive medications supplied to older adults with osteoarthritis (OA).

RESEARCH DESIGN

Survey data on pain, insomnia, and depression obtained from OA patients screened for a randomized controlled trial were used to identify predictors of psychoactive medication supply [opioids, sedatives, tricyclic antidepressants (TCAs), and non-TCAs] over a 4-year period.

SUBJECTS

Group Health Cooperative patients with a diagnosis of OA (N=2976).

MEASURES

Survey data on pain (Graded Chronic Pain Scale), insomnia (Insomnia Severity Index), and depression (Patient Health Questionnaire-8); and medications supply assessed from electronic medical records.

RESULTS

In negative binomial models, pain [incidence rate ratio (IRR), 2.8-3.5; P<0.001], insomnia (IRR, 2.0; P<0.001), and depression (IRR, 1.5; P<0.05) each independently predicted opioid supply. Insomnia (IRR, 3.2; P<0.001) and depression (IRR, 3.0; P<0.001) each independently predicted sedative supply. Pain (IRR, 2.1; P<0.05) and insomnia (IRR, 2.0; P<0.05) independently predicted TCA supply, whereas only depression (IRR, 2.2; P<0.001) independently predicted non-TCA supply. Combined effects of pain and insomnia/depression on these medications were additive and increased the rate of medication supply 1.5-7.5 times. Combined effects increased with insomnia or depression severity.

CONCLUSIONS

Concurrent insomnia and depressive symptoms predicted increased supply of opioids, sedatives, and antidepressants after accounting for pain, indicating the importance of sleep and mood disorders as factors increasing supply of these medications.

Incidence rate estimation, periodic testing and the limitations of the mid-point imputation approach

Background

It is common to use the mid-point between the latest-negative and earliest-positive test dates as the date of the infection event. However, the accuracy of the mid-point method has yet to be systematically quantified for incidence studies once participants start to miss their scheduled test dates.

Methods

We used a simulation-based approach to generate an infectious disease epidemic for an incidence cohort with a high (80-100%), moderate (60-79.9%), low (40-59.9%) and poor (30-39.9%) testing rate. Next, we imputed a mid-point and random-point value between the participant's latest-negative and earliest-positive test dates. We then compared the incidence rate derived from these imputed values with the true incidence rate generated from the simulation model.

Results

The mid-point incidence rate estimates erroneously declined towards the end of the observation period once the testing rate dropped below 80%. This decline was in error of approximately 9%, 27% and 41% for a moderate, low and poor testing rate, respectively. The random-point method did not introduce any systematic bias in the incidence rate estimate, even for testing rates as low as 30%.

Conclusions

The mid-point assumption of the infection date is unjustified and should not be used to calculate the incidence rate once participants start to miss the scheduled test dates. Under these conditions, we show an artefactual decline in the incidence rate towards the end of the observation period. Alternatively, the single random-point method is straightforward to implement and produces estimates very close to the true incidence rate.

A BAYESIAN GRAPHICAL MODEL FOR GENOME-WIDE ASSOCIATION STUDIES (GWAS)

The analysis of GWAS data has long been restricted to simple models that cannot fully capture the genetic architecture of complex human diseases. As a shift from standard approaches, we propose here a general statistical framework for multi-SNP analysis of GWAS data based on a Bayesian graphical model. Our goal is to develop a general approach applicable to a wide range of genetic association problems, including GWAS and fine-mapping studies, and, more specifically, be able to: (1) Assess the joint effect of multiple SNPs that can be linked or unlinked and interact or not; (2) Explore the multi-SNP model space efficiently using the Mode Oriented Stochastic Search (MOSS) algorithm and determine the best models. We illustrate our new methodology with an application to the CGEM breast cancer GWAS data. Our algorithm selected several SNPs embedded in multi-locus models with high posterior probabilities. Most of the SNPs selected have a biological relevance. Interestingly, several of them have never been detected in standard single-SNP analyses. Finally, our approach has been implemented in the open source R package genMOSS.

Glycemic Control in US Immigrant and Nonimmigrant Black Youth with Type 1 Diabetes

Differences in glycemic control based on race have been reported in pediatric populations with type 1 diabetes (T1D). It is unknown if differences exist between pediatric populations within the same race classification. This retrospective study identified all immigrant and nonimmigrant Black youth diagnosed with T1D and treated at Seattle Children's Hospital from 2001 to 2011. Demographic characteristics and hemoglobin A1c (HbA1c) levels at 12, 24, and 36 months post diagnosis were obtained from existing medical records. Immigrant youth had lower mean HbA1c levels at all three time points. The ethnicity effect on mean HbA1c levels approached significance at 36 months. When comparing 12 and 36 months, the time effect was significant; the ethnicity effect approached significance. Clinically important differences may exist in glycemic control between pediatric populations with T1D from the same race classification. Additional work is needed to confirm these findings and determine potential causes.

Restricted Covariance Priors with Applications in Spatial Statistics

We present a Bayesian model for area-level count data that uses Gaussian random effects with a novel type of G-Wishart prior on the inverse variance- covariance matrix. Specifically, we introduce a new distribution called the truncated G-Wishart distribution that has support over precision matrices that lead to positive associations between the random effects of neighboring regions while preserving conditional independence of non-neighboring regions. We describe Markov chain Monte Carlo sampling algorithms for the truncated G-Wishart prior in a disease mapping context and compare our results to Bayesian hierarchical models based on intrinsic autoregression priors. A simulation study illustrates that using the truncated G-Wishart prior improves over the intrinsic autoregressive priors when there are discontinuities in the disease risk surface. The new model is applied to an analysis of cancer incidence data in Washington State.

Type 1 Diabetes Among East African Immigrant and Nonimmigrant Black Youth in the U.S

Type 1 diabetes has not previously been described in East African immigrant youth in the United States. The purpose of this study was to compare East African immigrant and nonimmigrant Black youth with type 1 diabetes. Among other clinical and demographic differences, estimated prevalence of type 1 diabetes was nearly four times higher among East African youth in King County, Washington (6.20/1000, 95% confidence interval (CI) [4.49, 7.91] vs. 1.56/1000, 95% CI [1.03, 2.09]) compared to nonimmigrant Black youth. These observations are lost within the Black/African American race classification and additional work is needed to confirm and further explore these findings.

Transcriptome profiling of human hippocampus dentate gyrus granule cells in mental illness

This study is, to the best of our knowledge, the first application of whole transcriptome sequencing (RNA-seq) to cells isolated from postmortem human brain by laser capture microdissection. We investigated the transcriptome of dentate gyrus (DG) granule cells in postmortem human hippocampus in 79 subjects with mental illness (schizophrenia, bipolar disorder, major depression) and nonpsychiatric controls. We show that the choice of normalization approach for analysis of RNA-seq data had a strong effect on results; under our experimental conditions a nonstandard normalization method gave superior results. We found evidence of disrupted signaling by miR-182 in mental illness. This was confirmed using a novel method of leveraging microRNA genetic variant information to indicate active targeting. In healthy subjects and those with bipolar disorder, carriers of a high- vs those with a low-expressing genotype of miR-182 had different levels of miR-182 target gene expression, indicating an active role of miR-182 in shaping the DG transcriptome for those subject groups. By contrast, comparing the transcriptome between carriers of different genotypes among subjects with major depression and schizophrenia suggested a loss of DG miR-182 signaling in these conditions.

Fatigue-related gene networks identified in CD(14)+ cells isolated from HIV-infected patients: part I: research findings

PURPOSE

Human immunodeficiency virus (HIV)-related fatigue (HRF) is multicausal and potentially related to mitochondrial dysfunction caused by antiretroviral therapy with nucleoside reverse transcriptase inhibitors (NRTIs).

METHODOLOGY

The authors compared gene expression profiles of CD14(+) cells of low versus high fatigued, NRTI-treated HIV patients to healthy controls (n = 5/group). The authors identified 32 genes predictive of low versus high fatigue and 33 genes predictive of healthy versus HIV infection. The authors constructed genetic networks to further elucidate the possible biological pathways in which these genes are involved. RELEVANCE FOR NURSING PRACTICE: Genes including the actin cytoskeletal regulatory proteins Prokineticin 2 and Cofilin 2 along with mitochondrial inner membrane proteins are involved in multiple pathways and were predictors of fatigue status. Previously identified inflammatory and signaling genes were predictive of HIV status, clearly confirming our results and suggesting a possible further connection between mitochondrial function and HIV. Isolated CD14(+) cells are easily accessible cells that could be used for further study of the connection between fatigue and mitochondrial function of HIV patients.

IMPLICATION FOR PRACTICE

The findings from this pilot study take us one step closer to identifying biomarker targets for fatigue status and mitochondrial dysfunction. Specific biomarkers will be pertinent to the development of methodologies to diagnosis, monitor, and treat fatigue and mitochondrial dysfunction.

Bayesian Inference for General Gaussian Graphical Models With Application to Multivariate Lattice Data

We introduce efficient Markov chain Monte Carlo methods for inference and model determination in multivariate and matrix-variate Gaussian graphical models. Our framework is based on the G-Wishart prior for the precision matrix associated with graphs that can be decomposable or non-decomposable. We extend our sampling algorithms to a novel class of conditionally autoregressive models for sparse estimation in multivariate lattice data, with a special emphasis on the analysis of spatial data. These models embed a great deal of flexibility in estimating both the correlation structure across outcomes and the spatial correlation structure, thereby allowing for adaptive smoothing and spatial autocorrelation parameters. Our methods are illustrated using a simulated example and a real-world application which concerns cancer mortality surveillance. Supplementary materials with computer code and the datasets needed to replicate our numerical results together with additional tables of results are available online.

Fatigue-related gene networks identified in CD14+ cells isolated from HIV-infected patients: part II: statistical analysis

PURPOSE

In limited samples of valuable biological tissues, univariate ranking methods of microarray analyses often fail to show significant differences among expression profiles. In order to allow for hypothesis generation, novel statistical modeling systems can be greatly beneficial. The authors applied new statistical approaches to solve the issue of limited experimental data to generate new hypotheses in CD14(+) cells of patients with HIV-related fatigue (HRF) and healthy controls.

METHODOLOGY

We compared gene expression profiles of CD14(+) cells of nucleoside reverse transcriptase inhibitor (NRTI)-treated HIV patients with low versus high fatigue to healthy controls (n = 5 each). With novel Bayesian modeling procedures, the authors identified 32 genes predictive of low versus high fatigue and 33 genes predictive of healthy versus HIV infection. Sparse association and liquid association networks further elucidated the possible biological pathways in which these genes are involved. RELEVANCE FOR NURSING PRACTICE: Genetic networks developed in a comprehensive Bayesian framework from small sample sizes allow nursing researchers to design future research approaches to address such issues as HRF.

IMPLICATION FOR PRACTICE

The findings from this pilot study may take us one step closer to the development of useful biomarker targets for fatigue status. Specific and reliable tests are needed to diagnosis, monitor and treat fatigue and mitochondrial dysfunction.

Sparse covariance estimation in heterogeneous samples

Standard Gaussian graphical models implicitly assume that the conditional independence among variables is common to all observations in the sample. However, in practice, observations are usually collected from heterogeneous populations where such an assumption is not satisfied, leading in turn to nonlinear relationships among variables. To address such situations we explore mixtures of Gaussian graphical models; in particular, we consider both infinite mixtures and infinite hidden Markov models where the emission distributions correspond to Gaussian graphical models. Such models allow us to divide a heterogeneous population into homogenous groups, with each cluster having its own conditional independence structure. As an illustration, we study the trends in foreign exchange rate fluctuations in the pre-Euro era.

Bayes computation for ecological inference

Ecological data are available at the level of the group, rather than at the level of the individual. The use of ecological data in spatial epidemiological investigations is particularly common. Although the computational methods described are more generally applicable, this paper concentrates on the situation in which the margins of 2 × 2 tables are observed in each of n geographical areas, with a Bayesian approach to inference. We consider auxiliary schemes that impute the missing data, and compare with a previously suggested normal approximation. The analysis of ecological data is subject to ecological bias, with the only reliable means of removing such bias being the addition of auxiliary individual-level information. Various schemes have been suggested for this supplementation, and we illustrate how the computational methods may be applied to the analysis of such enhanced data. The methods are illustrated using simulated data and two examples. In the first example, the ecological data are supplemented with a simple random sample of individual-level data, and in this example the normal approximation fails. In the second example case-control sampling provides the additional information.

Variable selection and dependency networks for genomewide data

We describe a new stochastic search algorithm for linear regression models called the bounded mode stochastic search (BMSS). We make use of BMSS to perform variable selection and classification as well as to construct sparse dependency networks. Furthermore, we show how to determine genetic networks from genomewide data that involve any combination of continuous and discrete variables. We illustrate our methodology with several real-world data sets.

Monte Carlo Algorithms for Hardy-Weinberg Proportions

The Hardy-Weinberg law is among the most important principles in the study of biological systems. Given its importance, many tests have been devised to determine whether a finite population follows Hardy-Weinberg proportions. Because asymptotic tests can fail, Guo and Thompson developed an exact test; unfortunately, the Monte Carlo method they proposed to evaluate their test has a running time that grows linearly in the size of the population N. Here, we propose a new algorithm whose expected running time is linear in the size of the table produced, and completely independent of N. In practice, this new algorithm can be considerably faster than the original method.

Gene Expression Profiling and Genetic Markers in Glioblastoma Survival

Despite the strikingly grave prognosis for older patients with glioblastomas, significant variability in patient outcome is experienced. To explore the potential for developing improved prognostic capabilities based on the elucidation of potential biological relationships, we did analyses of genes commonly mutated, amplified, or deleted in glioblastomas and DNA microarray gene expression data from tumors of glioblastoma patients of age >50 for whom survival is known. No prognostic significance was associated with genetic changes in epidermal growth factor receptor (amplified in 17 of 41 patients), TP53 (mutated in 11 of 41 patients), p16INK4A (deleted in 15 of 33 patients), or phosphatase and tensin homologue (mutated in 15 of 41 patients). Statistical analysis of the gene expression data in connection with survival involved exploration of regression models on small subsets of genes, based on computational search over multiple regression models with cross-validation to assess predictive validity. The analysis generated a set of regression models that, when weighted and combined according to posterior probabilities implied by the statistical analysis, identify patterns in expression of a small subset of genes that are associated with survival and have value in assessing survival risks. The dominant genes across such multiple regression models involve three key genes-SPARC (Osteonectin), Doublecortex, and Semaphorin3B-which play key roles in cellular migration processes. Additional analysis, based on statistical graphical association models constructed using similar computational analysis methods, reveals other genes which support the view that multiple mediators of tumor invasion may be important prognostic factor in glioblastomas in older patients.

DIG--a system for gene annotation and functional discovery

SUMMARY

We describe a database and information discovery system named DIG (Duke Integrated Genomics) designed to facilitate the process of gene annotation and the discovery of functional context. The DIG system collects and organizes gene annotation and functional information, and includes tools that support an understanding of genes in a functional context by providing a framework for integrating and visualizing gene expression, protein interaction and literature-based interaction networks.

Bounds for cell entries in contingency tables given marginal totals and decomposable graphs

Upper and lower bounds on cell counts in cross-classifications of nonnegative counts play important roles in a number of practical problems, including statistical disclosure limitation, computer tomography, mass transportation, cell suppression, and data swapping. Some features of the Frechet bounds are well known, intuitive, and regularly used by those working on disclosure limitation methods, especially those for two-dimensional tables. We previously have described a series of results relating these bounds to theory on loglinear models for cross-classified counts. This paper provides the actual theory and proofs for the special case of decomposable loglinear models and their related independence graphs. It also includes an extension linked to the structure of reducible graphs and a discussion of the relevance of other results linked to nongraphical loglinear models.