Applying two approaches to detect unmeasured confounding due to time-varying variables in a self-controlled risk interval design evaluating COVID-19 vaccine safety signals, using myocarditis as a case example.

We test the robustness of the self-controlled risk interval (SCRI) design in a setting where time between doses may introduce time-varying confounding, using both negative control outcomes (NCOs) and quantitative bias analysis (QBA). All vaccinated cases identified from 5 European databases between 1 September 2020 and end of data availability were included. Exposures were doses 1-3 of the Pfizer, Moderna, AstraZeneca, and Janssen COVID-19 vaccines; outcomes were myocarditis and otitis externa (NCO). The SCRI used a 60-day control window and dose-specific 28-day risk windows, stratified by vaccine brand and adjusted for calendar time. The QBA included two scenarios: (i) baseline probability of the confounder was higher in the control window and (ii) vice versa. The NCO was not associated with any of the COVID-19 vaccine types or doses except Moderna dose 1 (IRR = 1.09, 95%CI 1.01-1.09). The QBA suggested even the strongest literature-reported confounder (COVID-19; RRmyocarditis = 18.3) could only explain away part of the observed effect from IRR = 3 to IRR = 1.40. The SCRI seems robust to unmeasured confounding in the COVID-19 setting, although a strong unmeasured confounder could bias the observed effect upward. Replication of our findings for other safety signals would strengthen this conclusion.

The mixed model for the analysis of a repeated-measurement multivariate count data.

Clustered overdispersed multivariate count data are challenging to model due to the presence of correlation within and between samples. Typically, the first source of correlation needs to be addressed but its quantification is of less interest. Here, we focus on the correlation between time points. In addition, the effects of covariates on the multivariate counts distribution need to be assessed. To fulfill these requirements, a regression model based on the Dirichlet-multinomial distribution for association between covariates and the categorical counts is extended by using random effects to deal with the additional clustering. This model is the Dirichlet-multinomial mixed regression model. Alternatively, a negative binomial regression mixed model can be deployed where the corresponding likelihood is conditioned on the total count. It appears that these two approaches are equivalent when the total count is fixed and independent of the random effects. We consider both subject-specific and categorical-specific random effects. However, the latter has a larger computational burden when the number of categories increases. Our work is motivated by microbiome data sets obtained by sequencing of the amplicon of the bacterial 16S rRNA gene. These data have a compositional structure and are typically overdispersed. The microbiome data set is from an epidemiological study carried out in a helminth-endemic area in Indonesia. The conclusions are as follows: time has no statistically significant effect on microbiome composition, the correlation between subjects is statistically significant, and treatment has a significant effect on the microbiome composition only in infected subjects who remained infected.

Effect of Anthelmintic Treatment on Insulin Resistance: A Cluster-Randomized, Placebo-Controlled Trial in Indonesia.

Background: Emerging evidence suggests that helminth infections are associated with lower insulin resistance (IR). Current deworming programs might remove this helminth-associated protective effect. Therefore, we evaluated the anthelmintic treatment effect on changes in IR. Methods: We conducted a double-blind, household-cluster-randomized, placebo-controlled clinical trial on Flores island, Indonesia, an area endemic for soil-transmitted helminths (STHs). All subjects received 4 rounds of albendazole or matching placebo with 3-month intervals, for 3 consecutive days. The primary outcome was the change in homeostatic model assessment of IR in those aged >16 years. An intention-to-treat analysis was performed involving all subjects and ad hoc in the helminth-infected subjects. Results: We examined 797 (in 329 households) and 872 (in 353 households) subjects, who were assigned randomly into the albendazole and placebo arms, respectively. Albendazole was associated with a significant reduction in STH prevalence, total immunoglobulin E (IgE), and eosinophil count. Whereas albendazole had no effect on IR (estimated treatment effect, 0.006 [95% confidence interval, -.010 to .021]; P = .48) at the community level, it was associated with a significant increase in IR (estimated treatment effect, 0.031 [95% confidence interval, .004 to .059]; P = .04) (P value for interaction = .01) among helminth-infected subjects as detected by microscopy. Pathway analysis suggested that this might in part be due to an increased body mass index or a reduced eosinophil count. Conclusions: Anthelmintic treatment reduces STH prevalence, total IgE, and eosinophil count but has no effect on IR at the community level. In helminth-infected subjects, treatment significantly increases IR, highlighting the need for metabolic health monitoring with ongoing deworming programs. Clinical Trials Registration: ISRCTN 75636394.

Helminth infections and type 2 diabetes: a cluster-randomized placebo controlled SUGARSPIN trial in Nangapanda, Flores, Indonesia.

BACKGROUND: Insulin resistance is a strong predictor of the development of type 2 diabetes mellitus. Chronic helminth infections might protect against insulin resistance via a caloric restriction state and indirectly via T-helper-2 polarization of the immune system. Therefore the elimination of helminths might remove this beneficial effect on insulin resistance. METHODS/DESIGN: To determine whether soil-transmitted helminth infections are associated with a better whole-body insulin sensitivity and whether this protection is reversible by anthelmintic treatment, a household-based cluster-randomized, double blind, placebo-controlled trial was conducted in the area of Nangapanda on Flores Island, Indonesia, an area endemic for soil-transmitted helminth infections. The trial incorporates three monthly treatment with albendazole or matching placebo for one year, whereby each treatment round consists of three consecutive days of supervised drug intake. The presence of soil-transmitted helminths will be evaluated in faeces using microscopy and/or PCR. The primary outcome of the study will be changes in insulin resistance as assessed by HOMA-IR, while the secondary outcomes will be changes in body mass index, waist circumference, fasting blood glucose, 2 h-glucose levels after oral glucose tolerance test, HbA1c, serum lipid levels, immunological parameters, and efficacy of anthelmintic treatment. DISCUSSION: The study will provide data on the effect of helminth infections on insulin resistance. It will assess the relationship between helminth infection status and immune responses as well as metabolic parameters, allowing the establishment of a link between inflammation and whole-body metabolic homeostasis. In addition, it will give information on anthelmintic treatment efficacy and effectiveness. TRIAL REGISTRATION: This study has been approved by the ethical committee of Faculty of Medicine Universitas Indonesia (ref: 549/H2.F1/ETIK/2013), and has been filed by the ethics committee of Leiden University Medical Center, clinical trial number: ISRCTN75636394. The study is reported in accordance with the CONSORT guidelines for cluster-randomised trials.

A comparison of four self-controlled study designs in an analysis of COVID-19 vaccines and myocarditis using five European databases.

INTRODUCTION: The aim of this study was to assess the possible extent of bias due to violation of a core assumption (event-dependent exposures) when using self-controlled designs to analyse the association between COVID-19 vaccines and myocarditis. METHODS: We used data from five European databases (Spain: BIFAP, FISABIO VID, and SIDIAP; Italy: ARS-Tuscany; England: CPRD Aurum) converted to the ConcePTION Common Data Model. Individuals who experienced both myocarditis and were vaccinated against COVID-19 between 1 September 2020 and the end of data availability in each country were included. We compared a self-controlled risk interval study (SCRI) using a pre-vaccination control window, an SCRI using a post-vaccination control window, a standard SCCS and an extension of the SCCS designed to handle violations of the assumption of event-dependent exposures. RESULTS: We included 1,757 cases of myocarditis. For analyses of the first dose of the Pfizer vaccine, to which all databases contributed information, we found results consistent with a null effect in both of the SCRI and extended SCCS, but some indication of a harmful effect in a standard SCCS. For the second dose, we found evidence of a harmful association for all study designs, with relatively similar effect sizes (SCRI pre = 1.99, 1.40 - 2.82; SCRI post 2.13, 95 %CI - 1.43, 3.18; standard SCCS 1.79, 95 %CI 1.31 - 2.44, extended SCCS 1.52, 95 %CI = 1.08 - 2.15). Adjustment for calendar time did not change these conclusions. Findings using all designs were also consistent with a harmful effect following a second dose of the Moderna vaccine. CONCLUSIONS: In the context of the known association between COVID-19 vaccines and myocarditis, we have demonstrated that two forms of SCRI and two forms of SCCS led to largely comparable results, possibly because of limited violation of the assumption of event-dependent exposures.

HPV and DNA Methylation Testing in Urine for Cervical Intraepithelial Neoplasia and Cervical Cancer Detection.

PURPOSE: Biomarker detection in urine offers a potential solution to increase effectiveness of cervical cancer screening programs by attracting nonresponders. In this prospective study, the presence of high-risk human papillomavirus (hrHPV) DNA and the performance of DNA methylation analysis was determined for the detection of cervical cancer and high-grade cervical intraepithelial neoplasia (CIN2/3) in urine, and compared with paired cervicovaginal self-samples and clinician-taken cervical scrapes. EXPERIMENTAL DESIGN: A total of 587 samples were included from 113 women with cervical cancer, 92 women with CIN2/3, and 64 controls. Samples were tested for hrHPV DNA and five methylation markers. Univariate and multivariate logistic regression and leave-one-out cross-validation were used to determine the methylation marker performance for CIN3 and cervical cancer (CIN3+) detection in urine. Agreement between samples was determined using Cohen kappa statistics and the Spearman correlation coefficients. RESULTS: HrHPV presence was high in all sample types, 79% to 92%. Methylation levels of all markers in urine significantly increased with increasing severity of disease. The optimal marker panel (ASCL1/LHX8) resulted in an AUC of 0.84 for CIN3+ detection in urine, corresponding to an 86% sensitivity at a 70% predefined specificity. At this threshold 96% (109/113) of cervical cancers, 68% (46/64) of CIN3, and 58% (14/24) of CIN2 were detected. Between paired samples, a strong agreement for HPV16/18 genotyping and a fair to strong correlation for methylation was found. CONCLUSIONS: HrHPV DNA and DNA methylation testing in urine offers a promising solution to detect cervical cancer and CIN2/3 lesions, especially for women currently unreached by conventional screening methods.

Myocarditis and pericarditis associated with SARS-CoV-2 vaccines: A population-based descriptive cohort and a nested self-controlled risk interval study using electronic health care data from four European countries.

Background: Estimates of the association between COVID-19 vaccines and myo-/pericarditis risk vary widely across studies due to scarcity of events, especially in age- and sex-stratified analyses. Methods: Population-based cohort study with nested self-controlled risk interval (SCRI) using healthcare data from five European databases. Individuals were followed from 01/01/2020 until end of data availability (31/12/2021 latest). Outcome was first myo-/pericarditis diagnosis. Exposures were first and second dose of Pfizer, AstraZeneca, Moderna, and Janssen COVID-19 vaccines. Baseline incidence rates (IRs), and vaccine- and dose-specific IRs and rate differences were calculated from the cohort The SCRI calculated calendar time-adjusted IR ratios (IRR), using a 60-day pre-vaccination control period and dose-specific 28-day risk windows. IRRs were pooled using random effects meta-analysis. Findings: Over 35 million individuals (49·2% women, median age 39-49 years) were included, of which 57·4% received at least one COVID-19 vaccine dose. Baseline incidence of myocarditis was low. Myocarditis IRRs were elevated after vaccination in those aged < 30 years, after both Pfizer vaccine doses (IRR = 3·3, 95%CI 1·2-9.4; 7·8, 95%CI 2·6-23·5, respectively) and Moderna vaccine dose 2 (IRR = 6·1, 95%CI 1·1-33·5). An effect of AstraZeneca vaccine dose 2 could not be excluded (IRR = 2·42, 95%CI 0·96-6·07). Pericarditis was not associated with vaccination. Interpretation: mRNA-based COVID-19 vaccines and potentially AstraZeneca are associated with increased myocarditis risk in younger individuals, although absolute incidence remains low. More data on children (≤ 11 years) are needed.

DNA methylation markers have universal prognostic value for anal cancer risk in HIV-negative and HIV-positive individuals.

Anal cancer has increasing incidence and is preceded by high-grade anal intraepithelial neoplasia (HGAIN; AIN2-3). Previously, we identified and validated several methylation markers for accurate detection of anal cancer and HGAIN with cancer risk in HIV-positive (HIV+) men who have sex with men (MSM). This study aimed to evaluate these markers in HIV-negative risk groups. A cross-sectional series of 176 tissue samples of anal cancer, AIN3, AIN2, AIN1 and control biopsies obtained in HIV-negative women and men was tested for six methylation markers (ASCL1, LHX8, SST, WDR17, ZIC1 and ZNF582). Accuracy for detection of AIN3 and cancer (AIN3+) was determined by univariable and multivariable mixed-effect ordinal logistic regression. Methylation levels of all markers increased with increasing severity of disease (P < 0.0001) and were comparable to results in HIV+ MSM. All markers showed high accuracy for AIN3+ detection [area under the curve (AUC): 0.83-0.86]. The optimal marker panel (ASCL1 and ZIC1; AUC = 0.85 for AIN3+) detected 98% of cancers at 79% specificity. In conclusion, DNA methylation markers show a high diagnostic performance for AIN3+ detection in HIV+ and HIV-negative risk groups, justifying broad application of methylation analysis for anal cancer prevention programmes.

The Effect of Gut Microbiome Composition on Human Immune Responses: An Exploration of Interference by Helminth Infections.

Background: Soil-transmitted helminths have been shown to have the immune regulatory capacity, which they use to enhance their long term survival within their host. As these parasites reside in the gastrointestinal tract, they might modulate the immune system through altering the gut bacterial composition. Although the relationships between helminth infections or the microbiome with the immune system have been studied separately, their combined interactions are largely unknown. In this study we aim to analyze the relationship between bacterial communities with cytokine response in the presence or absence of helminth infections. Results: For 66 subjects from a randomized placebo-controlled trial, stool and blood samples were available at both baseline and 21 months after starting three-monthly albendazole treatment. The stool samples were used to identify the helminth infection status and fecal microbiota composition, while whole blood samples were cultured to obtain cytokine responses to innate and adaptive stimuli. When subjects were free of helminth infection (helminth-negative), increasing proportions of Bacteroidetes was associated with lower levels of IL-10 response to LPS {estimate [95% confidence interval (CI)] -1.96 (-3.05, -0.87)}. This association was significantly diminished when subjects were helminth-infected (helminth positive) (p-value for the difference between helminth-negative versus helminth-positive was 0.002). Higher diversity was associated with greater IFN-γ responses to PHA in helminth-negative (0.95 (0.15, 1.75); versus helminth-positive [-0.07 (-0.88, 0.73), p-value = 0.056] subjects. Albendazole treatment showed no direct effect in the association between bacterial proportion and cytokine responses, although the Bacteroidetes' effect on IL-10 responses to LPS tended downward in the albendazole-treated group [-1.74 (-4.08, 0.59)] versus placebo [-0.11 (-0.84, 0.62); p-value = 0.193]. Conclusion: We observed differences in the relationship between gut microbiome composition and immune responses, when comparing individuals infected or uninfected with geohelminths. Although these findings are part of a preliminary exploration, the data support the hypothesis that intestinal helminths may modulate immune responses, in unison with the gut microbiota. Trial Registration: ISRCTN, ISRCTN83830814. Registered 27 February 2008 - Retrospectively registered, http://www.isrctn.com/ISRCTN83830814.

Dynamic changes in human-gut microbiome in relation to a placebo-controlled anthelminthic trial in Indonesia.

BACKGROUND: Microbiome studies suggest the presence of an interaction between the human gut microbiome and soil-transmitted helminth. Upon deworming, a complex interaction between the anthelminthic drug, helminths and microbiome composition might occur. To dissect this, we analyse the changes that take place in the gut bacteria profiles in samples from a double blind placebo controlled trial conducted in an area endemic for soil transmitted helminths in Indonesia. METHODS: Either placebo or albendazole were given every three months for a period of one and a half years. Helminth infection was assessed before and at 3 months after the last treatment round. In 150 subjects, the bacteria were profiled using the 454 pyrosequencing. Statistical analysis was performed cross-sectionally at pre-treatment to assess the effect of infection, and at post-treatment to determine the effect of infection and treatment on microbiome composition using the Dirichlet-multinomial regression model. RESULTS: At a phylum level, at pre-treatment, no difference was seen in microbiome composition in terms of relative abundance between helminth-infected and uninfected subjects and at post-treatment, no differences were found in microbiome composition between albendazole and placebo group. However, in subjects who remained infected, there was a significant difference in the microbiome composition of those who had received albendazole and placebo. This difference was largely attributed to alteration of Bacteroidetes. Albendazole was more effective against Ascaris lumbricoides and hookworms but not against Trichuris trichiura, thus in those who remained infected after receiving albendazole, the helminth composition was dominated by T. trichiura. DISCUSSION: We found that overall, albendazole does not affect the microbiome composition. However, there is an interaction between treatment and helminths as in subjects who received albendazole and remained infected there was a significant alteration in Bacteroidetes. This helminth-albendazole interaction needs to be studied further to fully grasp the complexity of the effect of deworming on the microbiome. TRIAL REGISTRATION: ISRCTN Registy, ISRCTN83830814.