Odds Ratio In Case-control Studies Research Articles

Neonatal jaundice and autism spectrum disorder: a systematic review and meta-analysis.

Two meta-analyses concluded that jaundice was associated with an increased risk of autism. We hypothesize that these findings were due to methodological limitations of the studies included. Neonatal jaundice affects many infants and risks of later morbidity may prompt physicians towards more aggressive treatment. To conduct a systematic literature review and a meta-analysis of the association between neonatal jaundice and autism with particular attention given to low risk of bias studies. Pubmed, Scopus, Embase, Cochrane, and Google Scholar were searched for publications until February 2019. Data was extracted by use of pre-piloted structured sheets. Low risk of bias studies were identified through predefined criteria. A total of 32 studies met the inclusion criteria. The meta-analysis of six low risk of bias studies showed no association between neonatal jaundice and autism; cohort studies risk ratio 1.09, 95% CI, 0.99-1.20, case-control studies odds ratio 1.29 95% CI 0.95, 1.76. Funnel plot of all studies suggested a high risk of publication bias. We found a high risk of publication bias, selection bias, and potential confounding in all studies. Based on the low risk of bias studies there was no convincing evidence to support an association between neonatal jaundice and autism. Meta-analysis of data fromsix low risk of bias studies indicated no association between neonatal jaundice and autism spectrum disorder. Previous studies show inconsistent results, which may be explained by unadjusted confounding and selection bias. Funnel plot suggested high risk of publication bias when including all studies. There is no evidence to suggest jaundice should be treated more aggressively to prevent autism.

Hepatic Disorders With the Use of Remdesivir for Coronavirus 2019

Remdesivir is a nucleotide analog prodrug with antiviral activity against a broad spectrum of human coronavirus in cell cultures and mouse models including severe acute respiratory syndrome-associated coronavirus 2. Recently, the Food and Drug Agency (FDA) and the European Medicines Agency (EMA) recommended remdesivir for the treatment of patients hospitalized with severe coronavirus disease 2019 (COVID-19) infection.1,2 In the remdesivir clinical development program, some cases have raised concerns regarding potential hepatobiliary disorders associated with remdesivir, including in healthy volunteers and patients with COVID-19.3 In cohort studies of patients hospitalized for severe COVID-19 who were treated with compassionate-use remdesivir, elevated hepatic enzymes were the most frequent adverse drug reaction reported.4,5 In the first randomized, double-blind, placebo-controlled clinical trial assessing the effect of intravenous remdesivir in adults admitted to hospital with severe COVID-19 (n= 237), a higher proportion of remdesivir recipients than placebo recipients had dosing prematurely stopped by the investigators because of adverse events including aminotransferase or bilirubin increases (3 versus 0).6 Although there is no signal from the available data of severe hepatotoxicity or drug-induced liver injury in clinical trials, the number of patients exposed to remdesivir was too limited. Therefore, there is an urgent need to investigate the hepatic safety profile associated with remdesivir in COVID-19 patients.

Interpretation of clinical trial results: a committee opinion

This document provides guidance, background, and tips on how to recognize quality trials and focuses on evaluating the validity, importance, and relevance of clinical trial results. This document replaces the document of the same name, last published in 2008 (Fertil Steril® 2008;90:S114-20).

Association of proton pump inhibitors with risk of hepatic encephalopathy in advanced liver disease: A meta-analysis.

BACKGROUNDSeveral studies have explored the association between the use of proton pump inhibitors (PPIs) and the risk of developing hepatic encephalopathy (HE) in patients with advanced liver disease. However, the evidence-based conclusions are controversial. We hypothesized that using PPIs may increase the risk of HE in patients with advanced liver disease. If confirmed, clinicians must strictly adhere to the indications for PPI treatment in this population.AIMTo evaluate the pooled risk of HE in patients with advanced liver disease who use PPIs.METHODSThree electronic databases (PubMed, EMBASE, and the Cochrane Library) were searched from the date of database inception through January 8, 2019 to identify comparative studies evaluating the association between PPI use and the risk of HE. Data from the included studies were extracted. The random-effects model was used for pooling risk estimates and the corresponding 95% confidence intervals (CIs). Subgroup and sensitivity analyses were also performed.RESULTSIn total, 4342 patients from five case-control studies and 188053 patients from four cohort studies were included in this analysis. In patients with advanced liver disease, PPI use was associated with an elevated risk of developing HE, with significant heterogeneity. The pooled odds ratio for case-control studies was 2.58 (95%CI: 1.68-3.94, I2 = 72%). The pooled RR for cohort studies was 1.67 (95%CI: 1.30-2.14, I2 = 67%). The results of the subgroup analyses suggested that the heterogeneity may be the result of differences in the study designs and the definitions of PPI use. The sensitivity and subgroup analyses did not alter our findings.CONCLUSIONIn patients with advanced liver disease, PPI use is associated with an elevated risk of HE. Future large prospective studies are needed to confirm this association.

Gender and Risk of Congenital Hypothyroidism: A Systematic Review and Meta-Analysis

Background: Although numerous observational studies have investigated the association between gender and risk of congenital hypothyroidism, the role of gender as a risk factor for congenital hypothyroidism remains unknown.Thismeta-analysis was conducted to summarize the epidemiologic evidence of the effect of gender on the congenital hypothyroidism occurrence, and also to identify the sex ratio for congenital hypothyroidism. Materials and Methods: A comprehensive literature search of numerous electronic databases including PubMed, Scopus, EMBASE, and Science Direct was performed until February 1st, 2017. All studies designed case-control (six studies with 3,254 subjects) and cross-sectional studies (eight studies with 8,258,745 subjects) addressing the association by odds ratio (OR) and 95% confidence interval (95% CI) were included. Moreover, eleven cross-sectional studies were also included providing a sex ratio for congenital hypothyroidism. Pooled Mantel-Haenszel OR (MH OR) with 95% CI was estimated using the random-effects method. Results The overall summary results showed that girl gender is associated with an increased risk of congenital hypothyroidism (pooled MH OR=1.46; 95%CI: 1.10, 1.95). The pooled MH OR for case-control studies was 1.69 (95%CI: 1.35, 2.13), whereas the pooled MH OR for cross-sectional studies was 1.26 (95%CI: 1.00, 1.59). In addition, pooled female to male sex ratio of congenital hypothyroidism incidence was 1.35 (95%CI: 0.99, 1.83). Conclusion: The results of this meta-analysis provide evidence for a higher risk in girl gender for developing congenital hypothyroidism. More epidemiological and clinical studies are needed to explore why girl gender is at increased risk of congenital hypothyroidism compared with boy.

Efficient estimation of disease odds ratios for follow-up genetic association studies.

In the past decade, genome-wide association studies have identified thousands of susceptible variants associated with complex human diseases and traits. Conducting follow-up genetic association studies has become a standard approach to validate the findings of genome-wide association studies. One problem of high interest in genetic association studies is to accurately estimate the strength of the association, which is often quantified by odds ratios in case-control studies. However, estimating the association directly by follow-up studies is inefficient since this approach ignores information from the genome-wide association studies. In this article, an estimator called GFcom, which integrates information from genome-wide association studies and follow-up studies, is proposed. The estimator includes both the point estimate and corresponding confidence interval. GFcom is more efficient than competing estimators regarding MSE and the length of confidence intervals. The superiority of GFcom is particularly evident when the genome-wide association study suffers from severe selection bias. Comprehensive simulation studies and applications to three real follow-up studies demonstrate the performance of the proposed estimator. An R package, "GFcom", implementing our method is publicly available at https://github.com/JiyuanHu/GFcom .

Correction of odds ratios in case-control studies for exposure misclassification with partial knowledge of the degree of agreement among experts who assessed exposures

ObjectivesEstimates of association between exposures and diseases are often distorted by error in exposure classification. When the validity of exposure assessment is known, this can be used to adjust these...

Cadmium exposure and risk of prostate cancer: a meta-analysis of cohort and case-control studies among the general and occupational populations.

We aimed to evaluate the association of cadmium exposure with the risk of prostate cancer in both the general and occupational populations. Online database searches were performed for studies of prostate cancer risk and cadmium exposure. Twelve cohort studies (5 in the general, 7 in occupational populations) and 9 case-control studies (3 in the general, 6 in occupational populations) were identified. Five/seven cohort studies in the general and occupational populations consist of 78,263/13, 434 participants with a mean follow-up of 12.1/43.0 years, respectively. Case-control studies include 334 cases/670 controls in the general population, and 1,315 cases/4,477 controls in occupational populations. Comparing the highest to the lowest category of cadmium exposure in the general population, the weighted relative risk of prostate cancer incidence and mortality among cohort studies, and the weighted odds ratio in case-control studies were 1.05 (95%CI [0.91, 1.22]), 0.83 (95%CI [0.35, 1.98]), and 1.27 (95%CI [0.58,2.78]), respectively. For occupational populations, the weighted OR in case-control studies was 1.17 (95%CI [0.85, 1.62]), and the weighted standardized mortality ratio in cohort studies was 98 (95%CI [75, 126]). Accumulated epidemiological evidence does not support the hypothesis that cadmium exposure may increase the risk of prostate cancer in either the general or occupational populations.

Smoking as a risk factor for developing Multiple Sclerosis: A meta-analysis of observational studies.

The aim of this study was to improve and update the pool of available studies included in the previous meta-analyses, and to provide further evidence about smoking as a risk factor for MS. PubMed and Scopus searches were undertaken to identify studies investigating the association between cigarette smoking and MS. Odds ratio (OR), relative risk (RR) together with 95% confidence intervals (CIs) were calculated for case-control and cohort studies and prevalence rate for cross sectional. 33 studies were suitable for the meta-analysis. The summary OR for case control studies (ever versus never) was 1.40 (95% CI, 1.29 to 1.52) and 1.42 (1.26-1.60) for current vs. no-smokers. Smoking is associated with MS risk. Research using animal models can help to fully understand the mechanisms behind the association.

Meta-Analysis of Association of Obstructive Sleep Apnea With Glaucoma.

Previous studies suggested that obstructive sleep apnea (OSA) was associated with glaucoma. However, data on this issue are controversial. This study aims to use meta-analysis to determine whether OSA is related to glaucoma. We searched PubMed, Embase, the Cochrane library, the Web of Science, and the Chinese BioMedical Literature Database disk databases up to November 20, 2014 for related literature. The association of OSA with glaucoma was assessed by odds ratio (OR) with 95% confidence interval (CI) as the effect size. Then subgroup analysis was performed according to area and glaucoma type. Six primary studies (3 cohort study and 3 case-control studies) were included in this meta-analysis involving 2,288,701 participants. There was a significant association between OSA and glaucoma (adjusted-effect summary for case-control studies OR=2.46; 95% CI, 1.32-4.59, P=0.005) (adjusted-effect summary for cohort studies OR=1.43; 95% CI, 1.21-1.69, P=0.000). There was no significant publication bias. OSA was a risk factor for glaucoma. A large number of studies is needed to explore the mechanisms that link OSA with glaucoma.

Do corticosteroids reduce the mortality of influenza A (H1N1) infection? A meta-analysis.

IntroductionCorticosteroids are used empirically in influenza A (H1N1) treatment despite lack of clear evidence for effective treatment. This study aims to assess the efficacy of corticosteroids treatment for H1N1 infection.MethodsSystematic review and meta-analysis were used to estimate the efficacy of corticosteroids for the prevention of mortality in H1N1 infection. Databases searched included MEDLINE, EMBASE, PubMed, Cochrane Central Register of Controlled Clinical Trials and so on, and bibliographies of retrieved articles, from April 2009 to October 2014. We included both cohort studies and case-control studies reported in English or Chinese that compared treatment effects between corticosteroids and non-corticosteroids therapy in inpatients with H1N1 virus infection. Cohort studies employed mortality as outcome, and case-control studies employed deaths as cases and survivors as controls; both were assessed in this meta-analysis.ResultsIn total twenty-three eligible studies were included. Both cohort studies (nine studies, n = 1,405) and case-control studies (14 studies, n = 4,700) showed a similar trend toward increased mortality (cohort studies relative risk was 1.85 with 95% confidence interval (CI) 1.46 to 2.33; case-control studies odds ratio was 4.22 with 95% CI 3.10 to 5.76). The results from both subgroup analyses and sensitive analyses were consistent with each other, showing that steroid treatment is associated with mortality. However, considering the fact that corticosteroids were tend to be used in sickest case-patients and heterogeneity was observed between studies, we cannot make a solid conclusion.ConclusionsAvailable evidence did not support the use of corticosteroids as standard care for patients with severe influenza. We conclude that further research is required.Electronic supplementary materialThe online version of this article (doi:10.1186/s13054-015-0764-5) contains supplementary material, which is available to authorized users.

Survival bias and drug interaction can attenuate cross-sectional case-control comparisons of genes with health outcomes. An example of the kinesin-like protein 6 (KIF6) Trp719Arg polymorphism and coronary heart disease.

BackgroundCase-control studies typically exclude fatal endpoints from the case set, which we hypothesize will substantially underestimate risk if survival is genotype-dependent. The loss of fatal cases is particularly nontrivial for studies of coronary heart disease (CHD) because of significantly reduced survival (34% one-year fatality following a coronary attack). A case in point is the KIF6 Trp719Arg polymorphism (rs20455). Whereas six prospective studies have shown that carriers of the KIF6 Trp719Arg risk allele have 20% to 50% greater CHD risk than non-carriers, several cross-sectional case-control studies failed to show that carrier status is related to CHD. Computer simulations were therefore employed to assess the impact of the loss of fatal events on gene associations in cross-sectional case-control studies, using KIF6 Trp719Arg as an example.ResultsTen replicates of 1,000,000 observations each were generated reflecting Canadian demographics. Cardiovascular disease (CVD) risks were assigned by the Framingham equation and events distributed among KIF6 Trp719Arg genotypes according to published prospective studies. Logistic regression analysis was used to estimate odds ratios between KIF6 genotypes. Results were examined for 33%, 41.5%, and 50% fatality rates for incident CVD.In the absence of any difference in percent fatalities between genotypes, the odds ratios (carriers vs. noncarriers) were unaffected by survival bias, otherwise the odds ratios were increasingly attenuated as the disparity between fatality rates increased between genotypes. Additional simulations demonstrated that statin usage, shown in four clinical trials to substantially reduce the excess CHD risk in the KIF6 719Arg variant, should also attenuate the KIF6 719Arg odds ratio in case-control studies.ConclusionsThese computer simulations show that exclusions of prior CHD fatalities attenuate odds ratios of case-control studies in proportion to the difference in the percent fatalities between genotypes. Disproportionate CHD survival for KIF6 Trip719Arg carriers is suggested by their 50% greater risk for recurrent myocardial infarction. This, and the attenuation of KIF6 719Arg carrier risk with statin use, may explain the genotype's weak association with CHD in cross-sectional case-control studies. The results may be relevant to the underestimation of risk in cross-sectional case-control studies of other genetic CHD-risk factors affecting survival.

Variants in FAM13A are associated with chronic obstructive pulmonary disease

Substantial evidence suggests that there is genetic susceptibility to chronic obstructive pulmonary disease (COPD). To identify common genetic risk variants, we performed a genome-wide association study in 2940 cases and 1380 smoking controls with normal lung function. We demonstrate a novel susceptibility locus at 4q22.1 in FAM13A (rs7671167, OR=0.76, P=8.6×10−8) and provide evidence of replication in one case-control and two family-based cohorts (for all studies, combined P=1.2×10−11).

JAK2V617F mutation for the early diagnosis of Ph− myeloproliferative neoplasms in patients with venous thromboembolism: a meta-analysis

Recent studies suggested that JAK2V617F mutation is frequent in patients with splanchnic vein thrombosis (SVT) but not in patients with other venous thromboembolic events (VTE). However, whether screening for the JAK2V617F mutation in VTE patients is justified remains unclear. Therefore, we performed a systematic review to assess the frequency of JAK2 mutation in VTE patients and the role of JAK2V617F mutation in the diagnosis of myeloproliferative neoplasms. MEDLINE and EMBASE databases were searched. Two reviewers independently performed study selection and extracted study characteristics. Pooled odds ratios of case-control studies and weighted mean proportion of the prevalence of JAK2V617F mutation of uncontrolled series were calculated. Twenty-four studies involving 3123 patients were included. Mean prevalence of JAK2 mutation was 32.7% (95% confidence interval, 25.5%-35.9%) in SVT patients. JAK2 mutation was associated with increased risk of SVT (odds ratio, 53.98; 95% confidence interval, 13.10-222.45). Mean prevalence of JAK2 mutation in other VTE patients was low (range, 0.88%-2.57%). Presence of JAK2V617F mutation in SVT patients was associated with a subsequent diagnosis of myeloproliferative neoplasm in many patients. JAK2 mutation is strongly associated with SVT, and routine screening of JAK2 mutation appears to be indicated in these patients.

A local likelihood method for estimating relative risk functions in case-control studies

A local likelihood method with constraints is developed for the case-control sample for estimating the unknown relative risk function and odds ratio. Our estimates can be reduced to simply solving two systems of estimating equations. One system of estimating equations is for estimating the relative risk function, and is identical to that based on the locally weighted logistic regression analysis under prospective sampling. Another system of estimating equations is for estimating the odds ratio, and is identical to that used in the traditional linear logistic regression analysis. Asymptotic properties of the estimators are presented. Two real examples and simulations are given to illustrate our method. The results confirm that our approach is useful for estimating the relative risk function and odds ratio in case-control studies.

Citrus Fruits Intake and Prostate Cancer Risk: A Quantitative Systematic Review

The purpose of this systematic review was to investigate the association between dietary intake of citrus fruits and prostate cancer risk. Authors searched electronic databases and the reference lists of publications of diet and prostate cancer studies until August 2007. All of the epidemiological studies that obtained individual data on dietary intake of citrus fruits and presented risk estimates of the association between intake of citrus fruits and risk of prostate cancer were identified and included. Using general variance-based methods, study-specific odds ratios (OR)/ relative risk (RR) and associated confidence interval (CI)/ standard error (SE) for highest versus lowest intake of citrus fruits level were extracted from each paper. Eleven articles including six case-control studies, one nested case-control study and four cohort studies, proved eligible. Overall summary OR using random effect model did not show an association in risk of prostate cancer with intake of citrus fruits (summary OR=1.03, 95% CI=0.89-1.19) with large heterogeneity across studies that we were unable to explain (I(2)=67.88%). The summary ORs in case-control studies and cohort studies were 1.10 (95% CI=0.97-1.22) and 1.05 (95% CI=0.96-1.14), respectively. Pooled results from observational studies did not show an association between intake of citrus fruits and the risk of prostate cancer, although results vary substantially across studies.

Sample size calculation based on risk ratio under multiple matching

To increase the efficiency of comparisons between treatments in clinical trials, we may consider the use of a multiple matching design, in which, for each patient receiving the experimental treatment, we match with more than one patient receiving the standard treatment. To assess the efficacy of the experimental treatment, the risk ratio ( RR) of patient responses between two treatments is certainly one of the most commonly used measures. Because the probability of patient responses in clinical trial is often not small, the odds ratio ( OR), of which the practical interpretation is not easily understood, cannot approximate RR well. Thus, all sample size formulae in terms of OR for case-control studies with multiple matched controls per case can be of limited use here. In this paper, we develop three sample size formulae based on RR for randomized trials with multiple matching. We propose a test statistic for testing the equality of RR under multiple matching. On the basis of Monte Carlo simulation, we evaluate the performance of the proposed test statistic with respect to Type I error. To evaluate the accuracy and usefulness of the three sample size formulae developed in this paper, we further calculate their simulated powers and compare them with those of the sample size formula ignoring matching and the sample size formula based on OR for multiple matching published elsewhere. Finally, we include an example that employs the multiple matching study design about the use of the supplemental ascorbate in the supportive treatment of terminal cancer patients to illustrate the use of these formulae.

Effect measures in prevalence studies.

There is still considerable confusion and debate about the appropriate methods for analyzing prevalence studies, and a number of recent papers have argued that prevalence ratios are the preferred method and that prevalence odds ratios should not be used. These arguments assert that the prevalence ratio is obviously the better measure and the odds ratio is “unintelligible.” They have often been accompanied by demonstrations that when a disease is common the prevalence ratio and the prevalence odds ratio may differ substantially. However, this does not tell us which measure is the more valid to use. In fact, the prevalence odds ratio a) estimates the incidence rate ratio with fewer assumptions than are required for the prevalence ratio; b) can be estimated using the same methods as for the odds ratio in case–control studies, namely, the Mantel–Haenszel method and logistic regression; and c) provides practical, analytical, and theoretical consistency between analyses of a prevalence study and prevalence case–control analyses based on the same study population. For these reasons, the prevalence odds ratio will continue to be one of the standard methods for analyzing prevalence studies and prevalence case–control studies.

Concordance odds ratios and approximate rate ratios in longitudinal twin studies.

Odds ratios derived from probandwise concordance rates are usually interpreted as increased risks in twins. Though the odds ratios in case-control studies have been shown to reflect rate ratios, few studies focused on such relationships in twin studies. The authors derived an approximate formula for the ratios of person-time incidence rates after the random assignment of twins into index twins and co-twins, i.e., incidence rate ratios. The resulting rate ratio was estimated as the product of the concordance odds ratio and a term that reflect the follow-up duration and the average time to occurrence of disease. Odds ratios coincide with rate ratios when the average time to occurrence of disease is half the duration of follow-up, although in studies spanning several decades these two measures might be different. The authors illustrated that when the incidence rate is not constant over the follow-up period as in longitudinal twin studies, the conventional odds ratio should not be used as an estimator of rate ratio.

Estimating crude or common odds ratios in case-control studies with informatively missing exposure data.

In case-control studies, the crude odds ratio derived from a 2 x 2 table and the common odds ratio adjusted for stratification variables are staple measures of exposure-disease association. While missing exposure data are encountered in the majority of such studies, formal attempts to deal with them are rare, and a complete-case analysis is the norm. Furthermore, the probability that exposure is missing may depend on true exposure status, so the missing-at-random assumption is often unreasonable. In this paper, the authors present an adjustment to the usual product binomial likelihood to properly account for missing data. Estimation of model parameters without restrictive assumptions requires an additional data collection effort akin to a validation study. Closed-form results are provided to facilitate point and confidence interval estimation of crude and common odds ratios after properly accounting for informatively missing data. Simulations assess performance of the likelihood-based estimates and inferences, and they display the potential for bias in complete-case analyses. An example is presented to illustrate the approach.