Assess the Application of the E-Value in the Unmeasured Confounder Evaluation of Observational Pharmaceutical Studies

Public health is very important in big cities, and data analysis on public health studies is always a demanding issue that determines the study effectiveness. E-value was proposed as a standard sensitivity analysis tool to assess unmeasured confounders in observational studies, but its value is doubted. To evaluate the usefulness of E-value, in this paper, we collected 368 observational studies on drug effectiveness evaluation published from 1998 to September 2019 (out of 3426 searched studies) and evaluated the features of E-value. We selected the effects of primary outcomes or the largest effects in terms of hazard ratio, risk ratio, or odds ratio. Effects were transformed into estimated effect sizes following a standard E-value computation. In all 368 studies, the disease with the highest percentage was infections and infestations, at 21.7% (80/368). Our results showed that the median relative effect size was 1.89 (Q1-Q3: 1.41–2.95), and the corresponding median E-value was 3.19 with 95% confidence interval lower bound 1.77. Smaller studies yielded larger E-values for the effect size estimate and the relationship was considerably attenuated when considering the E-value for the lower bound of 95% confidence interval on the effect size. Notably, E-values have a monotonic, almost linear relationship with effect estimates. We found that E-value may cause misimpressions on the unmeasured confounder, and the same E-value does not reflect the varying nature of the unmeasured confounders in different studies, and there lacks a guidance on how E-value can be deemed as small or large, all of which limits the capability of E-value as a standard sensitivity analysis tool in real applications.

Addressing the issue of bias in observational studies: Using instrumental variables and a quasi-randomization trial in an ESME research project

Purpose Observational studies using routinely collected data are faced with a number of potential shortcomings that can bias their results. Many methods rely on controlling for measured and unmeasured confounders. In this work, we investigate the use of instrumental variables (IV) and quasi-trial analysis to control for unmeasured confounders in the context of a study based on the retrospective Epidemiological Strategy and Medical Economics (ESME) database, which compared overall survival (OS) with paclitaxel plus bevacizumab or paclitaxel alone as first-line treatment in patients with HER2-negative metastatic breast cancer (MBC). Patients and methods Causal interpretations and estimates can be made from observation data using IV and quasi-trial analysis. Quasi-trial analysis has the same conceptual basis as IV, however, instead of using IV in the analysis, a “superficial” or “pseudo” randomized trial is used in a Cox model. For instance, in a multicenter trial, instead of using the treatment variable, quasi-trial analysis can consider the treatment preference in each center, which can be informative, and then comparisons of results between centers or clinicians can be informative. Results In the original analysis, the OS adjusted for major factors was significantly longer with paclitaxel and bevacizumab than with paclitaxel alone. Using the center-treatment preference as an instrument yielded to concordant results. For the quasi-trial analysis, a Cox model was used, adjusted on all factors initially used. The results consolidate those obtained with a conventional multivariate Cox model. Conclusion Unmeasured confounding is a major concern in observational studies, and IV or quasi-trial analysis can be helpful to complement analysis of studies of this nature.

Eating Problems in Autistic Females and Males: A Co-twin Control Study

This study investigated the association between autism and self-reported eating problems and the influence of gender on the association, in a sample of adolescent and adult twins (N = 192). Autistic traits and autism diagnosis were associated with both total and specific eating problems, including selective eating and sensory sensitivity during mealtimes. Interaction effects indicated a stronger association between autistic traits and total eating problems in females, as well as more difficulties with eating in social contexts among autistic females. In within-pair analyses, where unmeasured confounders including genes and shared environment are implicitly controlled for, the association was lost within monozygotic pairs, which might further indicate a genetic influence on the relationship between autism and eating problems.

Reply to a letter from Robert Colebunders entitled COVID-19: The African Enigma

We thank Dr. Colebunders for his comments regarding our manuscript. Our study was an ecological study prompted by the low frequency of cases and deaths from the SARS-CoV-2 COVID-19 virus in some African countries. We agree with Dr. Colebunders that other factors could explain the observed association between APOC countries and COVID-19 mortality. However, these unmeasured confounders would have to be strongly associated with Covid-19 mortality to explain the observed 28% reduction. In updated information, as of 12-17-20, APOC countries had a 42% lower risk of death than the non-APOC countries, adjusted for confounders. (Not published) Hellwig et al., in addition to reporting similar findings to ours for African and Asian countries, surmised that they may be connected to ivermectin’s ability to inhibit SARS-CoV-2 replication suggesting other pathways must exist to explain the persistence of such an inhibitory effect after serum levels of ivermectin have declined. As mentioned by Mbow et al. “, it is increasingly recognized that the immune system is shaped not only by genetics but also by environmental factors, such as exposure to microorganisms and parasites. This educates the immune system to protect against invading pathogens not only specifically but also nonspecifically through, for example, “trained immunity,” which involves the reprogramming of innate cells that, on secondary encounter with a pathogen, can show a stronger response.” Those infections, such as onchocerciasis, may downregulate immune responses and potentially inactivate the inflammatory signalling pathways that may induce acute respiratory distress syndrome (ARDS), one of the causes of death in COVID-19 infected persons, seems very attractive explanation.

Associations between individual antipsychotics and the risk of arrests and convictions of violent and other crime: a nationwide within-individual study of 74 925 persons

Background Individuals diagnosed with psychiatric disorders who are prescribed antipsychotics have lower rates of violence and crime but the differential effects of specific antipsychotics are not known. We investigated associations between 10 specific antipsychotic medications and subsequent risks for a range of criminal outcomes. Methods We identified 74 925 individuals who were ever prescribed antipsychotics between 2006 and 2013 using nationwide Swedish registries. We tested for five specific first-generation antipsychotics (levomepromazine, perphenazine, haloperidol, flupentixol, and zuclopenthixol) and five second-generation antipsychotics (clozapine, olanzapine, quetiapine, risperidone, and aripiprazole). The outcomes included violent, drug-related, and any criminal arrests and convictions. We conducted within-individual analyses using fixed-effects Poisson regression models that compared rates of outcomes between periods when each individual was either on or off medication to account for time-stable unmeasured confounders. All models were adjusted for age and concurrent mood stabilizer medications. Results The relative risks of all crime outcomes were substantially reduced [range of adjusted rate ratios (aRRs): 0.50–0.67] during periods when the patients were prescribed antipsychotics v. periods when they were not. We found that clozapine (aRRs: 0.28–0.44), olanzapine (aRRs: 0.46–0.72), and risperidone (aRRs: 0.53–0.64) were associated with lower arrest and conviction risks than other antipsychotics, including quetiapine (aRRs: 0.68–0.84) and haloperidol (aRRs: 0.67–0.77). Long-acting injectables as a combined medication class were associated with lower risks of the outcomes but only risperidone was associated with lower risks of all six outcomes (aRRs: 0.33–0.69). Conclusions There is heterogeneity in the associations between specific antipsychotics and subsequent arrests and convictions for any drug-related and violent crimes.

Use and impact of high intensity treatments in patients with traumatic brain injury across Europe: a CENTER-TBI analysis

Purpose To study variation in, and clinical impact of high Therapy Intensity Level (TIL) treatments for elevated intracranial pressure (ICP) in patients with traumatic brain injury (TBI) across European Intensive Care Units (ICUs). Methods We studied high TIL treatments (metabolic suppression, hypothermia (< 35 °C), intensive hyperventilation (PaCO2 < 4 kPa), and secondary decompressive craniectomy) in patients receiving ICP monitoring in the ICU stratum of the CENTER-TBI study. A random effect logistic regression model was used to determine between-centre variation in their use. A propensity score-matched model was used to study the impact on outcome (6-months Glasgow Outcome Score-extended (GOSE)), whilst adjusting for case-mix severity, signs of brain herniation on imaging, and ICP. Results 313 of 758 patients from 52 European centres (41%) received at least one high TIL treatment with significant variation between centres (median odds ratio = 2.26). Patients often transiently received high TIL therapies without escalation from lower tier treatments. 38% of patients with high TIL treatment had favourable outcomes (GOSE ≥ 5). The use of high TIL treatment was not significantly associated with worse outcome (285 matched pairs, OR 1.4, 95% CI [1.0–2.0]). However, a sensitivity analysis excluding high TIL treatments at day 1 or use of metabolic suppression at any day did reveal a statistically significant association with worse outcome. Conclusion Substantial between-centre variation in use of high TIL treatments for TBI was found and treatment escalation to higher TIL treatments were often not preceded by more conventional lower TIL treatments. The significant association between high TIL treatments after day 1 and worse outcomes may reflect aggressive use or unmeasured confounders or inappropriate escalation strategies. Take home message Substantial variation was found in the use of highly intensive ICP-lowering treatments across European ICUs and a stepwise escalation strategy from lower to higher intensity level therapy is often lacking. Further research is necessary to study the impact of high therapy intensity treatments. Trial registration The core study was registered with ClinicalTrials.gov, number NCT02210221, registered 08/06/2014, https://clinicaltrials.gov/ct2/show/NCT02210221?id=NCT02210221&draw=1&rank=1 and with Resource Identification Portal (RRID: SCR_015582).

Critical appraisal and issues regarding generalisability of comparative effectiveness studies of NOACs in atrial fibrillation and their relation to clinical trial data: a systematic review

ObjectiveTo critically appraise the published comparative effectiveness studies on non-vitamin K antagonist oral anticoagulants (NOACs) in non-valvular atrial fibrillation (NVAF). Results were compared with expectations formulated on the basis of trial results with specific attention to the patient years in each study.MethodsAll studies that compared the effectiveness or safety between at least two NOACs in patients with NVAF were eligible. We performed a systematic literature review in Medline and EMbase to investigate the way comparisons between NOACs were made, search date 23 April 2019. Critical appraisal of the studies was done using among others ISPOR Good Research Practices for comparative effectiveness research.ResultsWe included 39 studies in which direct comparison between at least two NOACs were made. Almost all studies concerned patient registries, pharmacy or prescription databases and/or health insurance database studies using a cohort design. Corrections for differences in patient characteristics was applied in all but two studies. Eighteen studies matched using propensity scores (PS), 8 studies weighted patients based on the inverse probability of treatment, 1 study used PS stratification and 10 studies applied a proportional hazards model. These studies have some important limitations regarding unmeasured confounders and channelling bias, even though the larger part of the studies were well conducted technically. On the basis of trial results, expected differences are small and a naïve analysis suggests trials with between 7200 and 56 500 patients are needed to confirm the observed differences in bleedings and between 51 800 and 7 994 300 to confirm differences in efficacy.DiscussionComparisons regarding effectiveness and safety between NOACs on the basis of observational data, even after correction for baseline characteristics, may not be reliable due to unmeasured confounders, channelling bias and insufficient sample size. These limitations should be kept in mind when results of these studies are used to decide on ranking NOAC treatment options.