Bayesian Hierarchical Logistic Regression Model Research Articles

Association of glycemic gap with stroke recurrence in patients with ischemic stroke.

Glycemic gap, as a novel index of acute glycemic excursion, is associated with poor prognosis of different diseases. This study aimed to explore the association of the glycemic gap with long-term stroke recurrence in patients with ischemic stroke. This study included patients with ischemic stroke from the Nanjing Stroke Registry Program. The glycemic gap was calculated by subtracting the estimated average blood glucose from the blood glucose at admission. Multivariable Cox proportional hazards regression analysis was performed to explore the association between the glycemic gap and the risk of stroke recurrence. The Bayesian hierarchical logistic regression model was used to estimate the effects of the glycemic gap on stroke recurrence stratified by diabetes mellitus and atrial fibrillation. Among 2734 enrolled patients, 381 (13.9%) patients experienced stroke recurrence during a median follow-up of 3.02 years. In multivariate analysis, glycemic gap (high group vs. median group) was associated with significantly increased risk for stroke recurrence (adjusted hazard ratio, 1.488; 95% confidence interval, 1.140-1.942; p = .003) and had varying effects on stroke recurrence depending on atrial fibrillation. The restricted cubic spline curve showed a U-shaped relationship between the glycemic gap and stroke recurrence (p = .046 for nonlinearity). Our study found that the glycemic gap was significantly associated with stroke recurrence in patients with ischemic stroke. The glycemic gap was consistently associated with stroke recurrence across subgroups and had varying effects depending on atrial fibrillation.

High monkeypox vaccine acceptance among male users of smartphone-based online gay-dating apps in Europe, 30 July to 12 August 2022.

We assess monkeypox vaccination acceptance among male adults in the European Region. We conducted an online survey through two dating apps targeting men who have sex with men, from 30 July to 12 August 2022. We developed Bayesian hierarchical logistic regression models to investigate monkeypox vaccination acceptance. Overall crude vaccination acceptance was 82% and higher in north-western compared to south-eastern European regions. Acceptance strongly rose with perception of increased disease severity and transmission risk, and in individuals linked to healthcare.

Brief Report: Active HIV Case Finding in the City of Kigali, Rwanda: Assessment of Voluntary Assisted Partner Notification Modalities to Detect Undiagnosed HIV Infections.

Voluntary assisted partner notification (VAPN) services that use contract, provider, or dual referral modalities may be efficient to identify individuals with undiagnosed HIV infection. We aimed to assess the relative effectiveness of VAPN modalities in identifying undiagnosed HIV infections. VAPN was piloted in 23 health facilities in Kigali, Rwanda. We identified individuals with a new HIV diagnosis before antiretroviral therapy initiation or individuals on antiretroviral therapy (index cases), who reported having had sexual partners with unknown HIV status, to assess the association between referral modalities and the odds of identifying HIV-positive partners using a Bayesian hierarchical logistic regression model. We adjusted our model for important factors identified through a Bayesian variable selection. Between October 2018 and December 2019, 6336 index cases were recruited, leading to the testing of 7690 partners. HIV positivity rate was 7.1% (546/7690). We found no association between the different referral modalities and the odds of identifying HIV-positive partners. Notified partners of male individuals (adjusted odds ratio 1.84; 95% credible interval: 1.50 to 2.28) and index cases with a new HIV diagnosis (adjusted odds ratio 1.82; 95% credible interval: 1.45 to 2.30) were more likely to be infected with HIV. All 3 VAPN modalities were comparable in identifying partners with HIV. Male individuals and newly diagnosed index cases were more likely to have partners with HIV. HIV-positive yield from index testing was higher than the national average and should be scaled up to reach the first UNAIDS-95 target by 2030.

Abstract LBA038: KontRASt: A Phase Ib/II, open-label, multi-center, dose-escalation study of JDQ443 in patients with advanced solid tumors harboring the KRAS G12C mutation

Abstract Background Kirsten rat sarcoma virus (KRAS) is a GTPase that regulates cell signaling pathways involved in cell proliferation, survival, and tumorigenesis. Somatic mutations in KRAS resulting in a glycine to cysteine substitution at codon 12 (KRAS G12C) lead to a shift toward active, GTP-bound KRAS and increased oncogenic signaling. KRAS G12C mutations occur in approximately 13% of non-squamous, non-small cell lung cancer (NSCLC) cases, and at lower frequencies in other solid tumor malignancies. JDQ443 (NVP-JDQ443) is a selective, covalent, and orally bioavailable investigational KRASG12C inhibitor that binds under the switch II loop, and irreversibly traps KRASG12C in a GDP-bound, inactive state. In preclinical models, JDQ443 potently inhibited KRASG12C cellular signaling and proliferation in a mutant-selective manner and demonstrated dose-dependent anti-tumor activity. In patients with KRAS G12C-mutated solid tumors, JDQ443 may have clinically significant antitumor activity alone and in combination with TNO155, an investigational, SHP2 inhibitor, and in combination with PD-1 blockade. Methods This is a Phase Ib/II, open-label, dose-escalation study with four arms: (A) JDQ443 monotherapy; (B) JDQ443 + TNO155; (C) JDQ443 + anti–PD-1; and (D) JDQ443 + TNO155 + anti–PD-1. Each arm has a dose-escalation portion followed by dose expansion at the maximum tolerated dose (MTD) and/or recommended dose (RD). The escalations are conducted in adult patients with advanced KRAS G12C-mutated solid tumors who have previously received standard-of-care therapies. Dose escalation is guided by an adaptive Bayesian hierarchical logistic regression model following the escalation with overdose control principle. Expansions are planned for patients with advanced (metastatic or unresectable), KRAS G12C-mutated NSCLC who have received prior immune checkpoint inhibitor therapy and platinum-based chemotherapy, and for patients with advanced, KRAS G12C-mutated colorectal cancer who have received prior fluoropyrimidine-, oxaliplatin-, and irinotecan-based chemotherapy. The primary objectives of dose escalation are to assess the safety and tolerability of JDQ443 alone and in combinations, and to identify the MTD and/or the RD, and regimens for future studies. The primary objective of dose expansion is to evaluate the antitumor activity via overall response rates for JDQ443, both alone and in combinations, in selected populations. Secondary objectives for both escalation and expansion are to evaluate the antitumor activity and characterize the pharmacokinetics of JDQ443 alone and in combinations, and to assess the immunogenicity of anti–PD-1 in combination with JDQ443 or TNO155. Safety and tolerability will also be further assessed during dose expansion. The study is currently enrolling to the dose-escalation portions of Arm A (JDQ443 monotherapy) and Arm B (JDQ443 + TNO155). NCT04699188 Citation Format: Benjamin Solomon, Rebecca S Heist, Daniel SW Tan, Philippe A Cassier, Christophe Dooms, Eric Van Cutsem, Conor E Steuer, Neeltje Steeghs, Martin Schuler, Anas Gazzah, Martin Wermke, Enriqueta Felip, Herbert HF Loong, Maria J De Miguel Luken, Ross A Soo, Ashley Jaeger, Kun Xu, Xueying Chen, Xiaoming Cui, Heather Burks, Anna F Farago, Toshio Shimizu. KontRASt: A Phase Ib/II, open-label, multi-center, dose-escalation study of JDQ443 in patients with advanced solid tumors harboring the KRAS G12C mutation [abstract]. In: Proceedings of the AACR-NCI-EORTC Virtual International Conference on Molecular Targets and Cancer Therapeutics; 2021 Oct 7-10. Philadelphia (PA): AACR; Mol Cancer Ther 2021;20(12 Suppl):Abstract nr LBA038.

Lower Volumes, Higher Speeds: Changes to Crash Type, Timing, and Severity on Urban Roads from COVID-19 Stay-at-Home Policies.

Stay-at-home policies in response to COVID-19 transformed high-volume arterials and highways into lower-volume roads, and reduced congestion during peak travel times. To learn from the effects of this transformation on traffic safety, an analysis of crash data in Ohio's Franklin County, U.S., from February to May 2020 is presented, augmented by speed and network data. Crash characteristics such as type and time of day are analyzed during a period of stay-at-home guidelines, and two models are estimated: (i) a multinomial logistic regression that relates daily volume to crash severity; and (ii) a Bayesian hierarchical logistic regression model that relates increases in average road speeds to increased severity and the likelihood of a crash being fatal. The findings confirm that lower volumes are associated with higher severity. The opportunity of the pandemic response is taken to explore the mechanisms of this effect. It is shown that higher speeds were associated with more severe crashes, a lower proportion of crashes were observed during morning peaks, and there was a reduction in types of crashes that occur in congestion. It is also noted that there was an increase in the proportion of crashes related to intoxication and speeding. The importance of the findings lay in the risk to essential workers who were required to use the road system while others could telework from home. Possibilities of similar shocks to travel demand in the future, and that traffic volumes may not recover to previous levels, are discussed, and policies are recommended that could reduce the risk of incapacitating and fatal crashes for continuing road users.

Effectiveness and safety of treat-to-target strategy in elderly-onset rheumatoid arthritis: a 3-year prospective observational study.

To evaluate 3-year outcomes of following a treat-to-target (T2T) strategy targeting low disease activity for patients with elderly-onset RA (EORA) and to confirm safety profile of T2T. Treatment was adjusted to target low disease activity with conventional synthetic DMARDs, followed by biologic DMARDs (bDMARDs) in 197 MTX-naïve EORA patients (mean age 74.9 years) with moderate-to-high disease activity. Non-implementation of T2T was evaluated at week 12, 24, 36, 52, 76, 104 and 128. To evaluate risks of using MTX, bDMARDs and glucocorticoids, 2122 periods of 3 months each were analysed using Bayesian hierarchical logistic regression models. Of the patients, 84.7% received methotrexate, 34.0% glucocorticoids with DMARDs and 41.6% bDMARDs during the observation period. Sixty-nine of the 197 patients failed to adhere to T2T because of comorbidities or the patient's own decision: 33 failed once, 19 twice, 10 three times and 6 four times or more. Simplified disease activity index (SDAI) remission and HAQ Disability Index (HAQ-DI) ≤0.5 at 3 years were achieved in 57.8% and 70.3% of the 128 patients adhering to T2T, and 34.8% and 43.5% of the 69 patients who did not adhere to T2T, respectively, and these were significantly different. Eighty-nine serious adverse events (SAEs) of any type were reported in 61 patients. MTX, bDMARDs and glucocorticoid were not associated with SAEs when adjusted for mean SDAI during the observation period and comorbidities at baseline. T2T strategy for EORA by using MTX and bDMARDs was effective with an acceptable safety profile. Adhering to T2T led to better outcomes.

Leave no child behind: Using data from 1.7 million children from 67 developing countries to measure inequality within and between groups of births and to identify left behind populations.

Goal 3.2 from the Sustainable Development Goals (SDG) calls for reductions in national averages of Under-5 Mortality. However, it is well known that within countries these reductions can coexist with left behind populations that have mortality rates higher than national averages. To measure inequality in under-5 mortality and to identify left behind populations, mortality rates are often disaggregated by socioeconomic status within countries. While socioeconomic disparities are important, this approach does not quantify within group variability since births from the same socioeconomic group may have different mortality risks. This is the case because mortality risk depends on several risk factors and their interactions and births from the same socioeconomic group may have different risk factor combinations. Therefore mortality risk can be highly variable within socioeconomic groups. We develop a comprehensive approach using information from multiple risk factors simultaneously to measure inequality in mortality and to identify left behind populations. We use Demographic and Health Surveys (DHS) data on 1,691,039 births from 182 different surveys from 67 low and middle income countries, 51 of which had at least two surveys. We estimate mortality risk for each child in the data using a Bayesian hierarchical logistic regression model. We include commonly used risk factors for monitoring inequality in early life mortality for the SDG as well as their interactions. We quantify variability in mortality risk within and between socioeconomic groups and describe the highest risk sub-populations. For all countries there is more variability in mortality within socioeconomic groups than between them. Within countries, socioeconomic membership usually explains less than 20% of the total variation in mortality risk. In contrast, country of birth explains 19% of the total variance in mortality risk. Targeting the 20% highest risk children based on our model better identifies under-5 deaths than targeting the 20% poorest. For all surveys, we report efficiency gains from 26% in Mali to 578% in Guyana. High risk births tend to be births from mothers who are in the lowest socioeconomic group, live in rural areas and/or have already experienced a prior death of a child. While important, differences in under-5 mortality across socioeconomic groups do not explain most of overall inequality in mortality risk because births from the same socioeconomic groups have different mortality risks. Similarly, policy makers can reach the highest risk children by targeting births based on several risk factors (socioeconomic status, residing in rural areas, having a previous death of a child and more) instead of using a single risk factor such as socioeconomic status. We suggest that researchers and policy makers monitor inequality in under-5 mortality using multiple risk factors simultaneously, quantifying inequality as a function of several risk factors to identify left behind populations in need of policy interventions and to help monitor progress toward the SDG.

Phase I dose-finding study of oral ERK1/2 inhibitor LTT462 in patients (pts) with advanced solid tumors harboring MAPK pathway alterations.

3640 Background: LTT462 is an investigational small molecule inhibitor of ERK1/2, which has demonstrated preclinical activity in multiple MAPK activated cancer cells and xenograft models. This first-in-human study was designed to evaluate the safety and tolerability of LTT462 in advanced solid tumors harboring MAPK pathway alterations (NCT02711345). Methods: The dose-escalation part of this Phase I, open-label study, enrolled adult and adolescent pts with advanced solid tumors harboring ≥1 documented MAPK pathway alteration with progressive disease (PD) despite standard therapy, or for whom there is no effective standard treatment. Oral LTT462 was given once daily (QD) at 45–600 mg or twice daily (BID) at 150 mg or 200 mg. Objectives were to determine the maximum tolerated dose (MTD) using a Bayesian hierarchical logistic regression model guided by escalation with overdose control, and characterize safety, pharmacokinetics, pharmacodynamics, and preliminary efficacy of LTT462. Results: Sixty-five pts (median age 60 years) including 1 pt aged 15 were enrolled in the dose-escalation; most pts (22%) had 3 prior therapies. Most common primary sites for cancer were in the colon (n = 21; 32%), ovary (n = 9; 14%), and pancreas (n = 7; 11%). All pts discontinued, the majority due to PD (n = 44; 68%). Eleven pts experienced DLTs; 6 pts experienced Grade 3 eye disorder DLTs (4 pts retinopathy, 2 pts chorioretinopathy). Treatment-related adverse events (TRAEs) were reported for 89% of pts, most commonly ( > 30%) diarrhea (n = 25; 38%) and nausea (n = 22; 34%). Grade 3/4 TRAEs were reported in 29% of pts; most common was retinopathy (n = 4; 6%). MTD of LTT462 was 400 mg QD and 150 mg BID. Overall, 8 pts (12%) had stable disease (SD) and 35 pts (54%) had PD. An unconfirmed partial response was reported in a pt with cholangiocarcinoma with BRAF mutation; best change in sum of target lesions per RECIST 1.1 was -33.9%. LTT462 increased plasma peak drug concentration and drug exposure at increasing doses between 45–450 mg QD. Exposure at LTT462 600 mg QD was lower than anticipated, indicating potential saturation of absorption at this dose. LTT462 inhibited ERK1/2 and reduced DUSP6 expression relative to baseline in most pts evaluated. Conclusions: LTT462 is well tolerated. Limited clinical activity was reported with single agent LTT462; best overall response was SD. An ongoing study is investigating LTT462 in combination with the RAF inhibitor, LXH254, in NSCLC and melanoma. Clinical trial information: NCT02711345 .

Computer Mouse Movements as a Scalable Indicator of Work Stress: A Longitudinal Observational Field Study

Background: Work stress afflicts individual health and well-being. The digital transformation of the economy implies profound changes of working conditions, making it even more important to regularly monitor employees’ stress. This study investigates whether the computer mouse can be used for continuous monitoring and early detection of work stress in the field. Method: We hypothesized that stress is associated with a speed-accuracy tradeoff in computer mouse movements (CMMs). To test this hypothesis, we conducted a longitudinal field study at a large business organization, where CMMs from regular work activities were monitored over seven weeks (70 subjects, n=1,829 observations). A Bayesian hierarchical logistic regression model was used to estimate whether self-reported acute work stress is associated with a speed-accuracy tradeoff in CMMs. Findings: Work stress was reported for slightly more than 10 % of observations (185 out of 1,829 self-reports). There was a negative association between stress and the two-way interaction term of mouse speed and accuracy (mean = −0.36, lower = −0.66, upper = −0.08), which means that stress was associated with a speed-accuracy tradeoff. The estimated effect was not sensitive to different criteria for excluding subjects and their recordings. Further, it remained negative after controlling for the demographics, health, and personality traits of subjects. Interpretation: Self-reported acute stress can be inferred from CMMs, specifically in the form of a speed-accuracy tradeoff. This finding suggests to use regular analysis of CMMs for the early and scalable detection of work stress on the job and thus promises more timely and effective stress management. Funding Statement: The study was funded by the Basic Research Fund at the University of St. Gallen. Declaration of Interests: NB and SF acknowledge funding from the Swiss National Science Foundation outside of this study. GB is a cofounder of Corporate Health Solutions, a university spinoff company that develops and disseminates digital solutions for employee health. This spinoff is not involved in the present study and does not apply computer mouse movements in its solutions. EF and TK are affiliated with the Center for Digital Health Interventions (www.c4dhi.org), a joint initiative of the Department of Management, Technology and Economics at ETH Zurich and the Institute of Technology Management at the University of St. Gallen, which is funded in part by the Swiss health insurer CSS. EF and TK are also cofounders of Pathmate Technologies, a university spinoff company that creates and delivers digital clinical pathways. However, Pathmate Technologies is not involved in the study described in this paper. Ethics Approval Statement: The study protocol was approved by the ethics board of the University of St. Gallen, Switzerland.

Phase II Study of Midostaurin + Chemotherapy in Pediatric Patients with Untreated, Newly Diagnosed, FLT3-Mutated Acute Myeloid Leukemia (AML)

Background: In pediatric patients with AML, the presence of FLT3-internal tandem duplication (ITD) mutation is indicative of high-risk disease and confers a worse prognosis and a greater chance of relapse. Midostaurin is a multikinase inhibitor with potent activity against both mutated and non-mutated FLT3. In adult patients with FLT3-mutated AML, midostaurin in combination with chemotherapy has demonstrated good safety/tolerability and significantly improved overall survival (OS) and event-free survival (EFS) compared with placebo + chemotherapy. We present here the design of an ongoing phase II study (NCT03591510) evaluating midostaurin combined with standard chemotherapy and as a single-agent post-consolidation therapy in newly diagnosed pediatric patients with FLT3-mutated AML, other than acute promyelocytic leukemia. Study Design and Methods: This open-label, single-arm study is composed of 2 parts. For Part 1, the primary objective is to determine the recommended phase II dose (RP2D) of midostaurin in combination with chemotherapy, as determined by the occurrence of dose-limiting toxicities. For Part 2, in which patients will receive the RP2D of midostaurin, the primary objective is to evaluate the efficacy of midostaurin + chemotherapy as measured by the EFS rate at 24 mo (for regulatory purposes outside the US) or to assess the safety/tolerability of midostaurin + chemotherapy (for regulatory purposes within the US). Secondary objectives include safety/tolerability (outside US) and EFS at 24 mo (within US), other efficacy parameters (including OS, complete remission [CR], CR with incomplete blood count recovery [CRi], cumulative incidence of relapse, and minimal residual disease-negative status), and characterization of the pharmacokinetics of midostaurin. Eligible patients are aged 3 mo to < 18 yr with expected survival of > 12 wk, have a Lansky or Karnofsky performance status of ≥ 60, and have previously untreated de novo AML with FLT3 mutation: ITD and/or mutation in the tyrosine kinase domain, with mutant/wild-type signal ratio cutoff of ≥ 0.05. Exclusion criteria include any concurrent malignancy, Philadelphia chromosome or BCR-ABL1-positive AML, AML associated with Down syndrome, secondary AML, symptomatic leukemic central nervous system involvement, bone marrow failure syndrome, or prior treatment with a FLT3 inhibitor. Patients are to receive 5 treatment blocks: 2 of standard induction (Blocks 1-2) and 3 of consolidation (Blocks 3-5) chemotherapy, each with sequential twice-daily (BID) oral midostaurin. In Part 1 of the study, midostaurin will be given at a starting dose of 30 mg/m2 BID; dose escalation and determination of RP2D will be facilitated by a Bayesian hierarchical logistic regression model guided by escalation with overdose control principle. In Part 2, midostaurin will be administered at the RP2D. Induction therapy will be the local standard chemotherapy regimen with midostaurin starting after 24 hr from identification of FLT3 abnormalities and continuing for 14 d for Block 1, and FLADx (fludarabine + high-dose cytarabine on D1-5, daunorubicin on D2, 4, 6) with sequential midostaurin on D8-21 for Block 2. Patients demonstrating CR or modified CRi will proceed to consolidation with the following chemotherapy regimens, each with sequential midostaurin on D8-21: HAM (high-dose cytarabine on D1-3, mitoxantrone on D3, 4) for Block 3, HA3E (high-dose cytarabine on D1-3, etoposide on D1-5) for Block 4, and HiDAC (high-dose cytarabine on D1-3) for Block 5. Patients must be in continued remission (CR or modified CRi) to receive each block of consolidation therapy. Patients who complete Block 5 and remain in remission will proceed to 12 × 28-d cycles of post-consolidation therapy with single-agent midostaurin. Patients may undergo allogeneic hematopoietic stem cell transplantation at any time at the investigator's discretion. Overall, the aim is to recruit a minimum of 52 patients, including at least 49 at the RP2D dose. This study is currently enrolling patients at 13 centers in 7 countries (as of July 26, 2019), and a total of 37 centers in 14 countries are planned. Disclosures Reinhardt: Novartis: Other: Participation in Advisory Boards; Jazz: Other: Participation in Advisory Boards, Research Funding; CSL Behring: Research Funding; Roche: Research Funding. Zwaan:BMS: Research Funding; Servier: Consultancy; Sanofi: Consultancy; Celgene: Consultancy, Research Funding; Janssen: Consultancy; Pfizer: Research Funding; Novartis: Consultancy; Daiichi Sankyo: Consultancy; Jazz Pharmaceuticals: Other: Travel support; Roche: Consultancy; Incyte: Consultancy. Hoenekopp:Novartis Pharma AG Basel: Employment, Equity Ownership. Niolat:Novartis Pharma: Employment. Ifrah:Novartis: Employment. Noel-Baron:Novartis: Employment, Equity Ownership. Locatelli:Miltenyi: Honoraria; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bellicum: Consultancy, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; BluebirdBio: Consultancy; Novartis: Consultancy, Membership on an entity's Board of Directors or advisory committees. OffLabel Disclosure: Midostaurin is a kinase inhibitor approved in combination with chemotherapy for the treatment of FLT3-mutated AML in adults; the study reported here is in pediatric patients with FLT3-mutated AML.

A Bayesian hierarchical logistic regression model of multiple informant family health histories

BackgroundFamily health history (FHH) inherently involves collecting proxy reports of health statuses of related family members. Traditionally, such information has been collected from a single informant. More recently, research has suggested that a multiple informant approach to collecting FHH results in improved individual risk assessments. Likewise, recent work has emphasized the importance of incorporating health-related behaviors into FHH-based risk calculations. Integrating both multiple accounts of FHH with behavioral information on family members represents a significant methodological challenge as such FHH data is hierarchical in nature and arises from potentially error-prone processes.MethodsIn this paper, we introduce a statistical model that addresses these challenges using informative priors for background variation in disease prevalence and the effect of other, potentially correlated, variables while accounting for the nested structure of these data. Our empirical example is drawn from previously published data on families with a history of diabetes.ResultsThe results of the comparative model assessment suggest that simply accounting for the structured nature of multiple informant FHH data improves classification accuracy over the baseline and that incorporating family member health-related behavioral information into the model is preferred over alternative specifications.ConclusionsThe proposed modelling framework is a flexible solution to integrate multiple informant FHH for risk prediction purposes.

Prevalence of Avian Influenza A(H5) and A(H9) Viruses in Live Bird Markets, Bangladesh.

We conducted a cross-sectional study in live bird markets (LBMs) in Dhaka and Chittagong, Bangladesh, to estimate the prevalence of avian influenza A(H5) and A(H9) viruses in different types of poultry and environmental areas by using Bayesian hierarchical logistic regression models. We detected these viruses in nearly all LBMs. Prevalence of A(H5) virus was higher in waterfowl than in chickens, whereas prevalence of A(H9) virus was higher in chickens than in waterfowl and, among chicken types, in industrial broilers than in cross-breeds and indigenous breeds. LBMs with >1 wholesaler were more frequently contaminated by A(H5) virus than retail-only LBMs. Prevalence of A(H9) virus in poultry and level of environmental contamination were also higher in LBMs with >1 wholesaler. We found a high level of circulation of both avian influenza viruses in surveyed LBMs. Prevalence was influenced by type of poultry, environmental site, and trading.

Receiver Operating Characteristic Curve–Based Prediction Model for Periodontal Disease Updated With the Calibrated Community Periodontal Index

The accuracy of a prediction model for periodontal disease using the community periodontal index (CPI) has been undertaken by using an area under a receiver operating characteristics (AUROC) curve. How the uncalibrated CPI, as measured by general dentists trained by periodontists in a large epidemiologic study, and affects the performance in a prediction model, has not been researched yet. A two-stage design was conducted by first proposing a validation study to calibrate CPI between a senior periodontal specialist and trained general dentists who measured CPIs in the main study of a nationwide survey. A Bayesian hierarchical logistic regression model was applied to estimate the non-updated and updated clinical weights used for building up risk scores. How the calibrated CPI affected performance of the updated prediction model was quantified by comparing AUROC curves between the original and updated models. Estimates regarding calibration of CPI obtained from the validation study were 66% and 85% for sensitivity and specificity, respectively. After updating, clinical weights of each predictor were inflated, and the risk score for the highest risk category was elevated from 434 to 630. Such an update improved the AUROC performance of the two corresponding prediction models from 62.6% (95% confidence interval [CI]: 61.7% to 63.6%) for the non-updated model to 68.9% (95% CI: 68.0% to 69.6%) for the updated one, reaching a statistically significant difference (P <0.05). An improvement in the updated prediction model was demonstrated for periodontal disease as measured by the calibrated CPI derived from a large epidemiologic survey.

Influenza Virus Detection Following Administration of Live-Attenuated Intranasal Influenza Vaccine in Children With Cystic Fibrosis and Their Healthy Siblings.

Background. We aimed to explore the detection profile of influenza viruses following live-attenuated intranasal influenza vaccination (LAIV) in children aged 2–19 years with and without cystic fibrosis (CF). Methods. Before the 2013–2014 influenza season, flocked nasal swabs were obtained before vaccination and 4 times in the week of follow-up from 76 participants (nCF: 57; nhealthy: 19). Influenza was detected by reverse transcription polymerase chain reaction (RT-PCR) assays. A Bayesian hierarchical logistic regression model was used to estimate the effect of CF status and age on influenza detection. Results. Overall, 69% of the study cohort shed influenza RNA during follow-up. The mean duration of RT-PCR detection was 2.09 days (95% credible interval [CrI]: 1.73–2.48). The odds of influenza RNA detection on day 1 following vaccination decreased with age in years (odds ratio [OR]: 0.82 per year; 95% CrI: 0.70–0.95), and subjects with CF had higher odds of influenza RNA detection on day 1 of follow-up (OR: 5.09; 95% CrI: 1.02–29.9). Conclusion. Despite the small sample size, our results indicate that LAIV vaccine strains are detectable during the week after LAIV, mainly in younger individuals and vaccinees with CF. It remains unclear whether recommendations for avoiding contact with severely immunocompromised patients should differ for these groups.

Geographical variation in a fatal outcome of acute myocardial infarction and association with contact to a general practitioner

BackgroundGeographical variation in incidence and mortality of acute myocardial infarction (AMI) is present in Denmark. We aimed at examining the association between contact to a general practitioner (GP) the year before AMI and a fatal outcome of AMI. MethodsRegister-based data and individual-level addresses including 69,608 individuals with AMI in 2006-2011. A Bayesian hierarchical logistic regression model was used to examine the association. ResultsA fatal outcome of AMI was seen among 12.0% (78%) of individuals with (without) contact to a GP the year before AMI. A significant association was estimated. ConclusionsA fatal outcome of AMI was significantly associated with contact to a GP. A high population to GP ratio and long distance to GP could not explain the increased odds of a fatal outcome of AMI for individuals with no contact to a GP.

Geography and social distribution of malaria in Indonesian Papua: a cross-sectional study.

BackgroundDespite being one of the world’s most affected regions, only little is known about the social and spatial distributions of malaria in Indonesian Papua. Existing studies tend to be descriptive in nature; their inferences are prone to confounding and selection biases. At the same time, there remains limited malaria-cartographic activity in the region. Analysing a subset (N = 22,643) of the National Basic Health Research 2007 dataset (N = 987,205), this paper aims to quantify the district-specific risk of malaria in Papua and to understand how socio-demographic/economic factors measured at individual and district levels are associated with individual’s probability of contracting the disease.MethodsWe adopt a Bayesian hierarchical logistic regression model that accommodates not only the nesting of individuals within the island’s 27 administrative units but also the spatial autocorrelation among these locations. Both individual and contextual characteristics are included as predictors in the model; a normal conditional autoregressive prior and an exchangeable one are assigned to the random effects. Robustness is then assessed through sensitivity analyses using alternative hyperpriors.ResultsWe find that rural Papuans as well as those who live in poor, densely forested, lowland districts are at a higher risk of infection than their counterparts. We also find age and gender differentials in malaria prevalence, if only to a small degree. Nine districts are estimated to have higher-than-expected malaria risks; the extent of spatial variation on the island remains notable even after accounting for socio-demographic/economic risk factors.ConclusionsAlthough we show that malaria is geography-dependent in Indonesian Papua, it is also a disease of poverty. This means that malaria eradication requires not only biological (proximal) interventions but also social (distal) ones.

Field evaluation of tolerance toTobacco streak virusin sunflower germplasm, and observations of seasonal disease spread

Strong statistical evidence was found for differences in tolerance to natural infections of Tobacco streak virus (TSV) in sunflower hybrids. Data from 470 plots involving 23 different sunflower hybrids tested in multiple trials over 5 years in Australia were analysed. Using a Bayesian Hierarchical Logistic Regression (BHLR) model for analysis provided: (a) a rigorous method for investigating the relative effects of hybrid, seasonal rainfall and proximity to inoculum source on the incidence of severe TSV disease; (b) a natural method for estimating the probability distributions of disease incidence in different hybrids under historical rainfall conditions; and (c) a method for undertaking all pairwise comparisons of disease incidence between hybrids while controlling the familywise error rate without any drastic reduction in statistical power. The tolerance identified in field trials was effective against the main TSV strain associated with disease outbreaks, TSV-parthenium. Glasshouse tests indicate this tolerance to also be effective against the other TSV strain found in central Queensland, TSV-crownbeard. The use of tolerant germplasm is critical to minimise the risk of TSV epidemics in sunflower in this region. We found strong statistical evidence that rainfall during the early growing months of March and April had a negative effect on the incidence of severe infection with greatly reduced disease incidence in years that had high rainfall during this period.

Finding big shots: small-area mapping and spatial modelling of obesity among Swiss male conscripts.

BackgroundIn Switzerland, as in other developed countries, the prevalence of overweight and obesity has increased substantially since the early 1990s. Most of the analyses so far have been based on sporadic surveys or self-reported data and did not offer potential for small-area analyses. The goal of this study was to investigate spatial variation and determinants of obesity among young Swiss men using recent conscription data.MethodsA complete, anonymized dataset of conscription records for the 2010–2012 period were provided by Swiss Armed Forces. We used a series of Bayesian hierarchical logistic regression models to investigate the spatial pattern of obesity across 3,187 postcodes, varying them by type of random effects (spatially unstructured and structured), level of adjustment by individual (age and professional status) and area-based [urbanicity and index of socio-economic position (SEP)] characteristics.ResultsThe analysed dataset consisted of 100,919 conscripts, out of which 5,892 (5.8 %) were obese. Crude obesity prevalence increased with age among conscripts of lower individual and area-based SEP and varied greatly over postcodes. Best model’s estimates of adjusted odds ratios of obesity on postcode level ranged from 0.61 to 1.93 and showed a strong spatial pattern of obesity risk across the country. Odds ratios above 1 concentrated in central and north Switzerland. Smaller pockets of elevated obesity risk also emerged around cities of Geneva, Fribourg and Lausanne. Lower estimates were observed in North-East and East as well as south of the Alps. Importantly, small regional outliers were observed and patterning did not follow administrative boundaries. Similarly as with crude obesity prevalence, the best fitting model confirmed increasing risk of obesity with age and among conscripts of lower professional status. The risk decreased with higher area-based SEP and, to a lesser degree – in rural areas.ConclusionIn Switzerland, there is a substantial spatial variation in obesity risk among young Swiss men. Small-area estimates of obesity risk derived from conscripts records contribute to its understanding and could be used to design further studies and interventions.Electronic supplementary materialThe online version of this article (doi:10.1186/s40608-016-0092-6) contains supplementary material, which is available to authorized users.

Catchment area analysis using bayesian regression modeling.

A catchment area (CA) is the geographic area and population from which a cancer center draws patients. Defining a CA allows a cancer center to describe its primary patient population and assess how well it meets the needs of cancer patients within the CA. A CA definition is required for cancer centers applying for National Cancer Institute (NCI)-designated cancer center status. In this research, we constructed both diagnosis and diagnosis/treatment CAs for the Massey Cancer Center (MCC) at Virginia Commonwealth University. We constructed diagnosis CAs for all cancers based on Virginia state cancer registry data and Bayesian hierarchical logistic regression models. We constructed a diagnosis/treatment CA using billing data from MCC and a Bayesian hierarchical Poisson regression model. To define CAs, we used exceedance probabilities for county random effects to assess unusual spatial clustering of patients diagnosed or treated at MCC after adjusting for important demographic covariates. We used the MCC CAs to compare patient characteristics inside and outside the CAs. Among cancer patients living within the MCC CA, patients diagnosed at MCC were more likely to be minority, female, uninsured, or on Medicaid.

Influenza outbreak control practices and the effectiveness of interventions in long‐term care facilities: a systematic review

BackgroundEvaluation of influenza control measures frequently focuses on the efficacy of chemoprophylaxis and vaccination, while the effectiveness of non-pharmaceutical interventions (NPI) receives less emphasis. While influenza control measures are frequently reported for individual outbreaks, there have been few efforts to characterize the real-world effectiveness of these interventions across outbreaks.ObjectivesTo characterize influenza case and outbreak definitions and control measures reported by long-term care facilities (LTCFs) of elderly adults and estimate the reduction in influenza-like illness (ILI) attack rates due to chemoprophylaxis and NPI.MethodsWe conducted a literature search in PubMed including English-language studies reporting influenza outbreaks among elderly individuals in LTCFs. A Bayesian hierarchical logistic regression model estimated the effects of control measures on ILI attack rates.ResultsOf 654 articles identified in the literature review, 37 articles describing 60 influenza outbreaks met the inclusion criteria. Individuals in facilities where chemoprophylaxis was used were significantly less likely to develop influenza A or B than those in facilities with no interventions [odds ratio (OR) 0·48, 95% CI: 0·28, 0·84]. Considered by drug class, adamantanes significantly reduced infection risk (OR 0·22, 95% CI: 0·12, 0·42), while neuraminidase inhibitors did not show a significant effect. Although NPI showed no significant effect, the results suggest that personal protective equipment may produce modest protective effects.ConclusionsOur results indicate pharmaceutical control measures have the clearest reported protective effect in LTCFs. Non-pharmaceutical approaches may be useful; however, most data were from observational studies and standardized reporting or well-conducted clinical trials of NPI are needed to more precisely measure these effects.