True Effect Size Research Articles

Effect of antibiotic growth promoters (AGPs) on feed conversion ratio (FCR) of broiler chickens: A meta-analysis

Antibiotics have been used for a long time as growth promoters in the poultry industry for growth and health benefits. However, recent studies reflected little, no, or negative impacts of using antibiotics for growth promotion purposes. This study was designed to examine the overall effect of antibiotic supplementation on the feed conversion ratio (FCR) in broiler chickens as a performance indicator and assess different covariates for explaining heterogeneity in response to the use of antibiotics as growth promoters. In this regard, FCRs obtained from articles that compared diets with and without antibiotics for broiler chickens were extracted from electronic databases (PubMed, Web of Science, and Google Scholar) as per PRISMA guidelines. The database comprised 42 scientific articles containing 74 experiments totaling 19,562 chickens. A basic meta-analysis and subgroup analysis were performed to assess the overall impact of antibiotic growth promoters (AGPs) on FCR of broiler chickens while a meta-regression analysis was used to assess different covariates (breed, antibiotic dose, location, time, presence of anticoccidial in the feed, antibiotic type, and housing type) to explain variations in true effect size of the studies. The basic meta-analysis of these studies revealed an overall improvement in FCR by 2.8 % (p < 0.05) due to addition of AGPs than the control group with the confidence interval range from 1.3 to 4.3 % and the prediction interval ranging between -10 and 16 %. The covariates, including breed, dose and location, provided the optimum model fit and explained 53 % of variations in the FCR across different studies. In summary, an overall marginal improvement has been observed in mean FCR of broiler chickens along with a wide range of variations in response to use of AGPs. The variations in true effects among these studies are subject to several confounding effects, particularly breed, dose and location. Considering the marginal positive effect of antibiotic usage in chicken performance, we recommend against using of AGP.

Quantifying Influence: Propensity Score Matching Unravels the True Effect Sizes of Learning Management Models on Students’ Analytical Thinking

&lt;p style="text-align:justify"&gt;Analytical thinking is crucial for developing problem-solving, decision-making, and higher-order thinking skills. Many researchers have consistently developed learning management models to enhance students' analytical thinking, resulting in extensive knowledge but lacking clear systematic summaries. This study aims to: (a) explore the effect sizes and research characteristics influencing students' analytical thinking, and (b) compare the effect sizes of learning management models after adjusting for propensity score matching. In exploring 131 graduate research papers published between 2002 and 2021, the research utilized forms for recording research characteristics and questionnaires for assessing research quality for data collection. Effect sizes were calculated using Glass's method, while data analysis employed random effects, fixed effects, and regression meta-analysis methods. The findings indicate that (a) research on learning management models significantly impacts students' analytical thinking at a high level (d̅ = 1.428). Seven research characteristics, including year of publication, field of research, level, duration per plan, learning management process, measurement and evaluation, and research quality, statistically influence students' analytical thinking, and (b) after propensity score matching, learning through techniques such as KWL, KWL-plus, Six Thinking Hats, 4MAT, and Mind Mapping had the highest influence on students' analytical thinking. Recommendations for developing students' analytical thinking involve creating a learning management process that fosters understanding, systematic practical training, expanding thinking through collaborative exchanges, and assessments using learning materials and tests to stimulate increased analytical thinking.&lt;/p&gt;

The Effects of Exercise on Symptoms of Chemotherapy-Induced Peripheral Neuropathy in Cancer Survivors: A Systematic Review and Meta-Analysis.

Chemotherapy-induced peripheral neuropathy (CIPN) can cause treatment delays or discontinuation. Exercise can improve CIPN, but the effects have been inconsistent. 12 databases and 5 websites were searched from database inception to December 22, 2023, for primary studies that were reported in English and examined the effects of exercise on CIPN in cancer survivors. 20 studies (N = 1,308 total participants) were identified and reviewed. Using a random-effects model, exercise slightly improved symptoms of CIPN (Hedges's g = 0.28, Hartung-Knapp adjusted 95% confidence interval [0.12, 0.45], p = 0.002). The 95% prediction interval showed that the true effect size of future studies would likely range from -0.1 to 0.66. Frequency of performing exercise moderated the effect size, further improving symptoms. Nurses can encourage cancer survivors to engage in exercise, such as resistance training, aerobic exercise, balance training, and/or yoga. Nurses can refer cancer survivors to trained exercise specialists or provide information about finding a community exercise program for patients with cancer.

The Influence of Nutrition Intervention on the P1NP and CTX-1 Response to an Acute Exercise Bout: A Systematic Review with Meta-Analysis.

Although nutrition and exercise both influence bone metabolism, little is currently known abouttheir interaction, or whether nutritional intervention can modulate the bone biomarker response to acute exercise. Improved understanding of the relationships between nutrition, exercise and bone metabolism may have substantial potential to inform nutritional interventions to protect the bone health of exercising individuals, and to elucidate mechanisms by which exercise and nutrition influence bone. The aim was to synthesise available evidence related to the influence of nutrition on the response of the bone biomarkers procollagen type 1 N-terminal propeptide (P1NP) and C-terminal telopeptide of type 1 collagen (CTX-1) to acute exercise, using a systematic review and meta-analytic approach. Studies evaluating the influence of nutritional status or intervention on the bone biomarker response to an acute exercise bout were included and separated into four categories: (1) feeding status and energy availability, (2) macronutrients, (3) micronutrients and (4) other. Studies conducted on healthy human populations of any age or training status were included. Meta-analysis was conducted when data from at least five studies with independent datasets were available. In the case of insufficient data to warrant meta-analysis, results from individual studies were narratively synthesised and standardised mean effect sizes visually represented. Twenty-two articles were included. Of these, three investigated feeding status or energy availability, eight macronutrients, eight micronutrients (all calcium) and six other interventions including dairy products or collagen supplementation. Three studies had more than one intervention and were included in all relevant outcomes. The largest and most commonly reported effects were for the bone resorption marker CTX-1. Meta-analysis indicated that calcium intake, whether provided via supplements, diet or infusion, reduced exercise-induced increases in CTX-1 (effect size - 1.1; 95% credible interval [CrI] - 2.2 to - 0.05), with substantially larger effects observed in studies that delivered calcium via direct infusion versus in supplements or foods. Narrative synthesis suggests that carbohydrate supplementation may support bone during acute exercise, via reducing exercise-induced increases in CTX-1. Conversely, a low-carbohydrate/high-fat diet appears to induce the opposite effect, as evidenced by an increased exercise associated CTX-1 response, and reduced P1NP response. Low energy availability may amplify the CTX-1 response to exercise, but it is unclear whether this is directly attributable to energy availability or to the lack of specific nutrients, such as carbohydrate. Nutritional intervention can modulate the acute bone biomarker response to exercise, which primarily manifests as an increase in bone resorption. Ensuring adequate attention to nutritional factors may be important to protect bone health of exercising individuals, with energy, carbohydrate and calcium availability particularly important to consider. Although a wide breadth of data were availablefor this evidence synthesis, there was substantial heterogeneity in relation to design and intervention characteristics. Direct and indirect replication is required to confirm key findings and to generate better estimates of true effect sizes.

Vicarious Dissonance: Pre-Registered Meta-Analysis.

The vicarious cognitive dissonance process predicts that observing an inconsistent act by a member of the ingroup causes uncomfortable arousal in the observer, inducing a motivation to reduce this discomfort. This meta-analysis examined the effect of vicarious cognitive dissonance based on 24 studies (N = 16,769). Our results indicated a small effect for the vicarious cognitive dissonance (g = 0.41 [0.27, 0.54], p <.001) with important variability between the outcomes. Our moderator analysis was limited by the low number of included studies. Publication bias analyses indicate a small true effect size (e.g., 3PSM: g = 0.22, p = .042), that was inflated by small sample sizes (R-index = 14.6%). We discussed theoretical issues concerning the psychological processes underlying vicarious cognitive dissonance, and methodological questions concerning operationalization. We proposed ways of improving the design and procedure to ensure that the effects found in the literature exist and are replicable.

Basic aspects of meta-analysis. Part 2

Meta-analysis combines the results of several scientific studies to obtain a summary quantitative estimation of effect size in order to compare the results of several studies and to identify patterns among them and possible sources of biases. Since the research teams, patients, research protocol, clinical guidelines and time intervals are often different between original scientific studies all these sources of difference can influence the results of each study, causing statistical heterogeneity. Meta-analyses are the highest level of credibility within evidence-based medicine, as they allow us to take into account the influence of many confounding factors and publication biases on the true effect size. Understanding the possible sources of erroneous conclusions in papers will allow researchers to analyze the results of such studies correctly and properly plan their own experiments. In this article the reader will be introduced to methods for identifying and quantifying hidden heterogeneity, such as subgroup analysis and meta-regression. In addition, the reader will learn how to calculate effect size in studies, estimate publication bias mathematically and graphically, and incorporate this estimate into the overall average effect size estimate in meta-analyses.

ZIBGLMM: Zero-Inflated Bivariate Generalized Linear Mixed Model for Meta-Analysis with Double-Zero-Event Studies.

Double-zero-event studies (DZS) pose a challenge for accurately estimating the overall treatment effect in meta-analysis. Current approaches, such as continuity correction or omission of DZS, are commonly employed, yet these ad hoc methods can yield biased conclusions. Although the standard bivariate generalized linear mixed model can accommodate DZS, it fails to address the potential systemic differences between DZS and other studies. In this paper, we propose a zero-inflated bivariate generalized linear mixed model (ZIBGLMM) to tackle this issue. This two-component finite mixture model includes zero-inflation for a subpopulation with negligible or extremely low risk. We develop both frequentist and Bayesian versions of ZIBGLMM and examine its performance in estimating risk ratios (RRs) against the bivariate generalized linear mixed model and conventional two-stage meta-analysis that excludes DZS. Through extensive simulation studies and real-world meta-analysis case studies, we demonstrate that ZIBGLMM outperforms the bivariate generalized linear mixed model and conventional two-stage meta-analysis that excludes DZS in estimating the true effect size with substantially less bias and comparable coverage probability.

A randomized, embedded, pragmatic, Bayesian clinical trial examining clinical decision support for high flow nasal cannula management in children with bronchiolitis: design and statistical analysis plan

BackgroundHigh flow nasal cannula (HFNC) has been increasingly adopted in the past 2 decades as a mode of respiratory support for children hospitalized with bronchiolitis. The growing use of HFNC despite a paucity of high-quality data regarding the therapy’s efficacy has led to concerns about overutilization. We developed an electronic health record (EHR) embedded, quality improvement (QI) oriented clinical trial to determine whether standardized management of HFNC weaning guided by clinical decision support (CDS) results in a reduction in the duration of HFNC compared to usual care for children with bronchiolitis.MethodsThe design and summary of the statistical analysis plan for the REspiratory SupporT for Efficient and cost-Effective Care (REST EEC; “rest easy”) trial are presented. The investigators hypothesize that CDS-coupled, standardized HFNC weaning will reduce the duration of HFNC, the trial’s primary endpoint, for children with bronchiolitis compared to usual care. Data supporting trial design and eventual analyses are collected from the EHR and other real world data sources using existing informatics infrastructure and QI data sources. The trial workflow, including randomization and deployment of the intervention, is embedded within the EHR of a large children’s hospital using existing vendor features. Trial simulations indicate that by assuming a true hazard ratio effect size of 1.27, equivalent to a 6-h reduction in the median duration of HFNC, and enrolling a maximum of 350 children, there will be a > 0.75 probability of declaring superiority (interim analysis posterior probability of intervention effect > 0.99 or final analysis posterior probability of intervention effect > 0.9) and a > 0.85 probability of declaring superiority or the CDS intervention showing promise (final analysis posterior probability of intervention effect > 0.8). Iterative plan-do-study-act cycles are used to monitor the trial and provide targeted education to the workforce.DiscussionThrough incorporation of the trial into usual care workflows, relying on QI tools and resources to support trial conduct, and relying on Bayesian inference to determine whether the intervention is superior to usual care, REST EEC is a learning health system intervention that blends health system operations with active evidence generation to optimize the use of HFNC and associated patient outcomes.Trial registrationClinicalTrials.gov NCT05909566. Registered on June 18, 2023.

Bayesian Estimation Improves Prediction of Outcomes after Epilepsy Surgery.

Low power is a problem in many fields, as underpowered studies that find a statistically significant result will exaggerate the magnitude of the observed effect size. We quantified the statistical power and magnitude error of studies of epilepsy surgery outcomes. The median power across all studies was 14%. Studies with a median sample size or less (n<=56) and a statistically significant result exaggerated the true effect size by a factor of 5.4 (median odds ratio 9.3 vs. median true odds ratio 1.7), while the Bayesian estimate of the odds ratio only exaggerated the true effect size by a factor of 1.6 (2.7 vs. 1.7). We conclude that Bayesian estimation of odds ratio attenuates the exaggeration of significant effect sizes in underpowered studies. This approach could help improve patient counseling about the chance of seizure freedom after epilepsy surgery.

Psychosocial experiences are associated with human brain mitochondrial biology

Psychosocial experiences affect brain health and aging trajectories, but the molecular pathways underlying these associations remain unclear. Normal brain function relies on energy transformation by mitochondria oxidative phosphorylation (OxPhos). Two main lines of evidence position mitochondria both as targets and drivers of psychosocial experiences. On the one hand, chronic stress exposure and mood states may alter multiple aspects of mitochondrial biology; on the other hand, functional variations in mitochondrial OxPhos capacity may alter social behavior, stress reactivity, and mood. But are psychosocial exposures and subjective experiences linked to mitochondrial biology in the human brain? By combining longitudinal antemortem assessments of psychosocial factors with postmortem brain (dorsolateral prefrontal cortex) proteomics in older adults, we find that higher well-being is linked to greater abundance of the mitochondrial OxPhos machinery, whereas higher negative mood is linked to lower OxPhos protein content. Combined, positive and negative psychosocial factors explained 18 to 25% of the variance in the abundance of OxPhos complex I, the primary biochemical entry point that energizes brain mitochondria. Moreover, interrogating mitochondrial psychobiological associations in specific neuronal and nonneuronal brain cells with single-nucleus RNA sequencing (RNA-seq) revealed strong cell-type-specific associations for positive psychosocial experiences and mitochondria in glia but opposite associations in neurons. As a result, these "mind-mitochondria" associations were masked in bulk RNA-seq, highlighting the likely underestimation of true psychobiological effect sizes in bulk brain tissues. Thus, self-reported psychosocial experiences are linked to human brain mitochondrial phenotypes.

Prevalence of gastritis and gastric and duodenal ulcers in Russian Guard servicemen

Based on the annual statistical reports for 2018–2023 and the cumulative median prevalence of various studies in 2009–2020 in Russia, the prevalence of peptic ulcer with uncomplicated and complicated course and various forms of gastritis in servicemen of the Regardie of the North Caucasian District was estimated, and the current trends are explained. The incidence of peptic ulcer with uncomplicated and complicated course and various forms of gastritis among the servicemen of the Regardie of the North Caucasian District for the specified period ranged from 11.521% to 16.351% (confidence interval: 10.515–12.588 and 15.233–17.517, respectively) and from 27.212% to 51.889% (confidence interval: 25.791–28.669 and 50.316–53.460, respectively). Random effects analysis has demonstrated different true effect sizes relative to the overall average. The revealed statistical patterns are only the first stage in an ongoing study on the prevalence of upper gastrointestinal diseases among the servicemen of the Regardie of the North Caucasian District. In general, the prevalence of peptic ulcer disease, including with a complicated course, and various forms of gastritis among military personnel was 13.270% and 37.679%, respectively (confidence interval: 10.617–16.170 and 24.292–52.102, respectively), showing an upward trend. The expected prevalence of peptic ulcer and gastritis in 2023 was 16,351 and 51,889%, respectively, which is not accidental and depends on the impact of specific risk factors. The identification of risk factors enables the development of measures to prevent delayed complications of the pathology under study and improvement of health in servicemen of the Regardie of the North Caucasian District. Thus, the study of the health status of the general population and military personnel, in particular, and the effect of various environmental factors determines their social significance both in military medicine and the structure of the healthcare system.

Effect of bempedoic acid on mortality and cardiovascular events in primary and secondary prevention: A post-hoc analysis of the CLEAR-outcomes trial

BackgroundThe effects of bempedoic acid on mortality in the secondary prevention setting have not been examined. MethodsWe used data from the overall and primary prevention reports of CLEAR – Outcomes to reconstruct data for the secondary prevention population. A Bayesian analyses was employed to calculate the posterior probability of benefit or harm for the outcomes of all-cause mortality, cardiovascular mortality, and major adverse cardiovascular events (MACE). Relative effect sizes are presented as risk ratios (RR) with 95% credible intervals (CrI), which represent the intervals that true effect sizes are expected to fall in with 95% probability, given the priors and model. ResultsIn primary prevention, the posterior probability of bempedoic acid decreasing all-cause and cardiovascular mortality was 99.4% (RR: 0.70; 95% CrI: 0.51 to 0.92) and 99.7% (RR: 0.58; 95% CrI: 0.38 to 0.86) respectively. In secondary prevention, the posterior probability of bempedoic acid increasing all-cause and cardiovascular mortality was 96.6% (RR: 1.15; 95% CrI: 0.99 to 1.33) and 97.2% (RR: 1.21; 95% CrI: 1.00 to 1.45) respectively. The probability of bemepdoic acid reducing MACE in the primary and secondary prevention settings was 99.9% (RR: 0.70; 95% CrI: 0.54 to 0.88) and 95.8% (RR: 0.92; 95% CrI: 0.84 to 1.01) respectively. ConclusionIn contrast to its effect in the primary prevention subgroup of CLEAR – Outcomes, bempedoic acid resulted in a more modest MACE reduction and a potential increase in mortality in the secondary prevention subgroup. Whether these findings represent true treatment effect heterogeneity or the play of chance requires further evidence.

How we learn to ignore singleton distractors: Suppressing saliency signals or specific features?

ABSTRACT Salient visual information can sometimes capture attention despite our goals. However, there are several ways we can minimize or eliminate such distraction. One such way is learned distractor rejection, in which we increasingly ignore salient, irrelevant distractors across repeated exposures. Here, we probe the mechanism underlying this learned rejection. What must be learned about the distractor to promote effective ignoring? Specifically, is feature rejection, alone, sufficient to ignore salient distractors, or do the items' saliency signals need to also be rejected? We used a modified version of the learned distractor rejection paradigm (Vatterott & Vecera, 2012) in which participants viewed training blocks containing either a salient singleton distractor or three non-salient “tripleton” distractors, followed by test blocks in which the distractor shared a feature (color) with the corresponding training blocks, but was always salient. Results revealed unexpected difficulties in replicating learned distractor rejection, suggesting the true effect size may be smaller than initially reported. With respect to our main objective, we found similar attenuation of singleton presence costs in the test blocks regardless of whether they followed singleton or tripleton training blocks. These results show that experience in rejecting saliency signals is not a requirement of learned distractor rejection.

Vitamin D and Cutaneous Melanoma Risk: An Umbrella Review of Systematic Reviews and Meta-Analyses.

Background: Vitamin D (VitD) properties can impact cancer cells. Despite the documented link between VitD levels and prevalence of several cancer types, conflicting findings have been reported for cutaneous melanoma (CM). Objective: This overview aims to compile the evidence from existing systematic reviews and meta-analyses, emphasizing the relationships between VitD serum levels, intake, receptor (VDR) gene polymorphisms, and CM risk. Methods: A literature search in electronic databases was conducted, based on certain inclusion criteria. Results: Twenty-one studies were included. Conflicting evidence between high VitD serum levels, dietary/supplementary intake, and CM risk is highlighted. VDR polymorphisms may play a role in the intricate CM pathogenesis. Also, high serum levels of VitD are associated with improved CM prognosis. Conclusions: This overview showed that the impact of VitD on CM is not clear, and thus further research is suggested to explore its true effect size on CM risk.

Approaches for identifying and managing publication bias in meta-analysis

The consequences of publication bias in meta-analysis pose significant risks, potentially leading to erroneous conclusions within the meta-analytic framework. The objective of this article was to explore the methodologies for identifying publication bias and approaches for mitigating its effects. The techniques employed to detect publication bias can generally be distinguished into two major categories: graphical and statistical methodologies. Graphical approaches utilize techniques such as funnel plots and meta-plots, which visually depict the distribution of effect sizes and standard errors across studies. Statistical methods encompass various computations, including Fail-Safe N, rank correlation, Egger regression, tests for excess significance (TES), and selection models tailored for evaluating publication bias through quantitative analyses. The combination of these methods is recommended for a more comprehensive assessment, rather than relying on individual approaches. Methods for addressing publication bias include the trim and fill (T&amp;F) method, Publication Error and True Effect Size Estimation (PET-PEESE) method, and the Weight-Function Model, each offering unique strategies for adjusting effect size estimates. The selection of these methods should consider the specific characteristics of the meta-analysis under consideration, ensuring the most appropriate approach is employed. Publication bias poses a significant risk in the field of meta-analysis, and selecting methods for its identification and mitigation requires comprehensive consideration

Adjustment of selection bias for clinical trials: a simulation study

Clinical trial selection bias is a common issue, as patients are typically not selected randomly from a target population. Various statistical approaches have been proposed to adjust for this bias, including IPW (inverse probability weights), SPS (subclassification with propensity scores), and EVB (external validity bias). However, there has been very little statistical research to compare the performance of these methods in clinical trials. To bridge this gap, we conducted a simulation study using a patient population with seven covariates and a true treatment effect size of 0.5 (Cohen’s d). Next, we assessed the efficacy of the three statistical methods on nonrandom clinical trial samples with varying sizes and covariates. Based on our simulation results, EVB is the most effective method for adjusting clinical trial selection bias when there are seven covariates. SPS is the most effective method for adjusting clinical trial selection bias when there are three and five covariates. However, we observed that IPW's performance was inadequate, indicating that it may not be a suitable option for selection bias adjustment in clinical trials. In summary, our study sheds light on the effectiveness of various statistical methods in mitigating selection bias in clinical trials.

SWOG S2200 (PAPMET2): A phase II randomized trial of cabozantinib with or without atezolizumab in patients with advanced papillary renal cell carcinoma (PRCC).

TPS493 Background: The role of immune therapy is not established in PRCC. The S1500 (PAPMET) clinical trial established single agent cabozantinib as the standard of care for PRCC (PMID 33592176) with a median progression free survival (PFS) of 9.0 months compared to 5.6 months with sunitinib. Trials have shown activity of PD-(L)1 antagonists as monotherapy (PMID 33529058) or in combination with targeted therapy (PMID 34491815). In a single arm study of cabozantinib/nivolumab the median PFS was 12.5 months (PMID 35298296). There are no prior randomized studies of immune therapy in PRCC. Single arm trials often overestimate the true effect size (PMID 31218346), highlighting the unmet clinical need for a randomized clinical trial in PRCC. We hypothesize that the combination will have higher clinical activity than single agent cabozantinib. Methods: This is a prospective randomized phase II clinical trial conducted through the NCTN and led by SWOG. The primary endpoint is a comparison of PFS between cabozantinib and cabozantinib/atezolizumab. Secondary endpoints include comparison of objective response rate, overall survival and safety. Patients are treated with cabozantinib 60mg/day versus cabozantinib 60mg/day + atezolizumab 1200 mg q3 weeks. 200 patients will be enrolled and randomized 1:1. Key inclusion criteria include a pathologic confirmation of PRCC; presence of metastasis; 0-1 prior systemic lines of therapy for metastatic disease; and measurable disease as defined by RECIST 1.1 criteria. Prior treatment with adjuvant pembrolizumab is allowed if completed greater than 6 months before enrollment. Key exclusion criteria include clinically significant autoimmune disease; ongoing use of strong CYP3A4 inhibitors, strong CYP3A4 inducers. Planned correlatives include stool microbiome testing and genomic/transcriptomic analysis from blood and baseline tissue assays. Clinical trial information: NCT05411081 .

Preference Externality Estimators: A Comparison of Border Approaches and IVs

This paper compares two estimators—the Border Approach and an Instrumental Variable (IV) estimator—using a unified framework where identifying variation arises from “preference externalities,” following the intuition in Waldfogel (2003) . We highlight two dimensions in favor of the IV approach. First, an econometric model of the data-generating process reveals that the border approach requires a set of identification assumptions that are not easily satisfied in practice: the ignorance of some payoff-relevant information and conflicting spatial correlation assumptions. The IV approach, in contrast, exhibits greater internal validity because it is derived from the model that generates the data. Second, the border approach suffers from representative issues when the true effect sizes are different between border and off-border regions. We use a common political advertising example to evaluate these estimators and suggest ways to evaluate or limit the above concerns, such as excluding localities that are a large share of the policy making region and evaluating spatial correlations of observables. We find the border approach’s representative issue to be substantial when the ignorance assumption is most plausible and observe that spatial correlations do not reflect those needed in the unobservables for consistency of the estimator. The IV, in contrast, does not exhibit concerns related to local average treatment effects. We also derive the specific conditions when the border approach can reduce bias relative to OLS. This paper was accepted by Raphael Thomadsen, marketing. Funding: This work was supported by National Natural Science Foundation of China (NSFC) [72072004, 72131001]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2023.4977 .

The Association of Vitamin D with Non-Melanoma Skin Cancer Risk: An Umbrella Review of Systematic Reviews and Meta-Analyses.

Background and Objectives: Previous studies revealed the anti-angiogenic, antiproliferative, and anti-inflammatory effects of Vitamin D (VitD) on cancer cells. Although this body of evidence supported the correlation of high VitD levels with reduced incidence rates for various malignancies, contradictory results were reported regarding non-melanoma skin cancer (NMSC). The aim of this overview was to summarize the available evidence from the existing pool of systematic reviews and meta-analyses, focusing on VitD serum status, dietary intake, and VitD receptor (VDR) polymorphisms in correlation to NMSC incidence. Materials and Methods: A literature search in electronic databases was conducted from inception to January 2023. The inclusion criteria were systematic reviews and meta-analyses published in peer-reviewed journals, evaluating VitD serum levels, dietary and/or supplementary intake, or VDR gene polymorphisms, and reporting data on NMSC. Results: A total of 10 studies were included in the data analysis models. A positive association between VitD serum levels and NMSC is highlighted. However, dietary/supplementation of VitD does not exhibit a likewise strong linkage to NMSC. Despite the contradictory findings, VDR polymorphisms may play a crucial role in the intricate NMSC pathogenesis. Conclusions: This umbrella review shows that high VitD levels are associated with increased NMSC incidence, potentially due to its direct correlation with increased sun exposure. Further research on VDR polymorphisms is suggested to explore their true effect size on NMSC risk.

Prevalence of indeterminate tuberculosis interferon-gamma release assays in COVID-19 patients: Systematic review and meta-analysis.

The reliability of interferon-gamma-release-assays (IGRAs) for tuberculosis (TB) testing in coronavirus disease 2019(COVID-19) patients is unknown. This study aimed to systematically review the prevalence of indeterminate TB-IGRA following SARS-CoV-2 infection or vaccination and to review associated factors. This systematic literature review was guided according to the PRISMA guidelines by searching PubMed, Scopus, Web of Science, Clinicalkey, and Cochrane Library. Studies reporting results of TB-IGRA tests (QuantiFERON [QFT]-TB, T-SPOT.TB) in COVID-19 patients or vaccines were included. The random effects model was used to assess the prevalence of indeterminate IGRA results. Heterogeneity was evaluated using the Τ 2 and 95% predictive interval. Of the 273 citations screened, 12 articles were included in the final analysis including a total of 2107 patients. The overall pooled effect size proportion of indeterminate QFT-TB results, estimated in eightstudies using the QFT-TB Plus assay, was 0.26 (95%CI: 0.205-0.324, Τ 2 = 0.158). The mean true effect size was 0.26 (95% predictive interval: [0.110-0.500]). A subgroup analysis was not undertaken due to the small number of studies. Indeterminate QFT-TB rates were associated with COVID-19 severity, steroid treatment, inflammation-related parameters, neutrophilia, and lymphopenia. Indeterminate QFT-TB results in COVID-19 patients occur in almost one-quarter of tests performed. Further studies are needed to assess associated factors.