Exploring miRNA-target gene pair detection in disease with coRmiT.

A wide range of approaches can be used to detect micro RNA (miRNA)-target gene pairs (mTPs) from expression data, differing in the ways the gene and miRNA expression profiles are calculated, combined and correlated. However, there is no clear consensus on which is the best approach across all datasets. Here, we have implemented multiple strategies and applied them to three distinct rare disease datasets that comprise smallRNA-Seq and RNA-Seq data obtained from the same samples, obtaining mTPs related to the disease pathology. All datasets were preprocessed using a standardized, freely available computational workflow, DEG_workflow. This workflow includes coRmiT, a method to compare multiple strategies for mTP detection. We used it to investigate the overlap of the detected mTPs with predicted and validated mTPs from 11 different databases. Results show that there is no clear best strategy for mTP detection applicable to all situations. We therefore propose the integration of the results of the different strategies by selecting the one with the highest odds ratio for each miRNA, as the optimal way to integrate the results. We applied this selection-integration method to the datasets and showed it to be robust to changes in the predicted and validated mTP databases. Our findings have important implications for miRNA analysis. coRmiT is implemented as part of the ExpHunterSuite Bioconductor package available from https://bioconductor.org/packages/ExpHunterSuite.

Meta-analysis of breast cancer risk for individuals with PALB2 pathogenic variants.

Multigene panel testing now allows efficient testing of many cancer susceptibility genes leading to a larger number of mutation carriers being identified. They need to be counseled about their cancer risk conferred by the specific gene mutation. An important cancer susceptibility gene is PALB2. Multiple studies reported risk estimates for breast cancer (BC) conferred by pathogenic variants in PALB2. Due to the diverse modalities of reported risk estimates (age-specific risk, odds ratio, relative risk, and standardized incidence ratio) and effect sizes, a meta-analysis combining these estimates is necessary to accurately counsel patients with this mutation. However, this is not trivial due to heterogeneity of studies in terms of study design and risk measure. We utilized a recently proposed Bayesian random-effects meta-analysis method that can synthesize estimates from such heterogeneous studies. We applied this method to combine estimates from 12 studies on BC risk for carriers of pathogenic PALB2 mutations. The estimated overall (meta-analysis-based) risk of BC is 12.80% (6.11%-22.59%) by age 50 and 48.47% (36.05%-61.74%) by age 80. Pathogenic mutations in PALB2 makes women more susceptible to BC. Our risk estimates can help clinically manage patients carrying pathogenic variants in PALB2.

Associations Between Flavonoid Intake and Subclinical Atherosclerosis: The MESA.

BACKGROUND: Flavonoids may play a role in mitigating atherosclerotic cardiovascular diseases, with evidence suggesting effects may differ between vascular beds. Studies examining associations with subclinical markers of atherosclerosis between subpopulations with different underlying risks of atherosclerosis are lacking. METHODS: Among 5599 participants from the MESA (Multi-Ethnic Study of Atherosclerosis), associations between dietary flavonoid intakes (estimated from a food frequency questionnaire) and subclinical measures of atherosclerosis (ankle-brachial index, carotid plaques and intima-media thickness, and coronary artery calcification) were examined using repeated measures models. Exposures and outcomes were measured at exam 1 (2000-2002) and exam 5 (2010-2011). Stratified analyses and interaction terms were used to explore effect modification by time, sex, race/ethnicity, and smoking status. RESULTS: In the analytic population, at baseline, ≈46% were males with a median age of 62 (interquartile range, 53-70) years and total flavonoid intakes of 182 (interquartile range, 98-308) mg/d. After multivariable adjustments, participants with the highest (quartile 4) versus lowest (quartile 1) total flavonoid intakes had 26% lower odds of having an ankle-brachial index <1 (odds ratio, 0.74 [95% CI, 0.60-0.92]) and 18% lower odds of having a carotid plaque (odds ratio, 0.82 [95% CI, 0.69-0.99]), averaged over exams 1 and 5. Moderate (quartile 3) to high (quartile 4) intakes of flavonols, flavanol monomers, and anthocyanins were associated with 19% to 34% lower odds of having an ankle-brachial index <1 and 18% to 20% lower odds of having carotid plaque. Participants with the highest intakes of anthocyanins (quartile 4) at baseline had a marginally slower rate of carotid plaque progression than those with moderate intakes (quartiles 2 and 3). There were no significant associations with intima-media thickness or coronary artery calcification. Observed associations did not differ by sex, race/ethnicity, or smoking status. CONCLUSIONS: In this multi-ethnic population, higher dietary flavonoid intakes were associated with lower odds of peripheral and carotid artery atherosclerosis. Increasing intakes of healthy, flavonoid-rich foods may protect against atherosclerosis in the peripheral and carotid arteries.

Increased Risk of Recurrent Stroke in Symptomatic Large Vessel Disease With Impaired BOLD Cerebrovascular Reactivity.

BACKGROUND: Impaired cerebrovascular reactivity (CVR) has been correlated with recurrent ischemic stroke. However, for clinical purposes, most CVR techniques are rather complex, time-consuming, and lack validation for quantitative measurements. The recent adaptation of a standardized hypercapnic stimulus in combination with a blood-oxygenation-level-dependent (BOLD) magnetic resonance imaging signal as a surrogate for cerebral blood flow offers a potential universally comparable CVR assessment. We investigated the association between impaired BOLD-CVR and risk for recurrent ischemic events. METHODS: We conducted a retrospective analysis of patients with symptomatic cerebrovascular large vessel disease who had undergone a prospective hypercapnic-challenged BOLD-CVR protocol at a single tertiary stroke referral center between June 2014 and April 2020. These patients were followed up for recurrent acute ischemic events for up to 3 years. BOLD-CVR (%BOLD signal change per mm Hg CO2) was calculated on a voxel-by-voxel basis. Impaired BOLD-CVR of the affected (ipsilateral to the vascular pathology) hemisphere was defined as an average BOLD-CVR, falling 2 SD below the mean BOLD-CVR of the right hemisphere in a healthy age-matched reference cohort (n=20). Using a multivariate Cox proportional hazards model, the association between impaired BOLD-CVR and ischemic stroke recurrence was assessed and Kaplan-Meier survival curves to visualize the acute ischemic stroke event rate. RESULTS: Of 130 eligible patients, 28 experienced recurrent strokes (median, 85 days, interquartile range, 5-166 days). Risk factors associated with an increased recurrent stroke rate included impaired BOLD-CVR, a history of atrial fibrillation, and heart insufficiency. After adjusting for sex, age group, and atrial fibrillation, impaired BOLD-CVR exhibited a hazard ratio of 10.73 (95% CI, 4.14-27.81; P<0.001) for recurrent ischemic stroke. CONCLUSIONS: Among patients with symptomatic cerebrovascular large vessel disease, those exhibiting impaired BOLD-CVR in the affected hemisphere had a 10.7-fold higher risk of recurrent ischemic stroke events compared with individuals with nonimpaired BOLD-CVR.

Intravenous Alteplase Versus Best Medical Therapy for Patients With Minor Stroke: A Systematic Review and Meta-Analysis.

BACKGROUND: The efficacy of thrombolysis (IVT) in minor stroke (National Institutes of Health Stroke Scale score, 0-5) remains inconclusive. The aim of this study is to compare the effectiveness and safety of IVT with best medical therapy (BMT) by means of a systematic review and meta-analysis of randomized controlled trials and observational studies. METHODS: We searched the PubMed, Embase, Cochrane Library, and Web of Science databases to obtain articles related to IVT in minor stroke from inception until August 10, 2023. The primary outcome was an excellent functional outcome, defined as a modified Rankin Scale score of 0 or 1 at 90 days. The associations were calculated for the overall and preformulated subgroups by using the odds ratios (ORs). This study was registered with PROSPERO (CRD42023445856). RESULTS: A total of 20 high-quality studies, comprised of 13 397 patients with acute minor ischemic stroke, were included. There were no significant differences observed in the modified Rankin Scale scores of 0 to 1 (OR, 1.10 [95% CI, 0.89-1.37]) and 0 to 2 (OR, 1.16 [95% CI, 0.95-1.43]), mortality rates (OR, 0.67 [95% CI, 0.39-1.15]), recurrent stroke (OR, 0.89 [95% CI, 0.57-1.38]), and recurrent ischemic stroke (OR, 1.09 [95% CI, 0.68-1.73]) between the IVT and BMT group. There were differences between the IVT group and the BMT group in terms of early neurological deterioration (OR, 1.81 [95% CI, 1.17-2.80]), symptomatic intracranial hemorrhage (OR, 7.48 [95% CI, 3.55-15.76]), and hemorrhagic transformation (OR, 4.73 [95% CI, 2.40-9.34]). Comparison of modified Rankin Scale score of 0 to 1 remained unchanged in subgroup patients with nondisabling deficits or compared with those using antiplatelets. CONCLUSIONS: These findings indicate that IVT does not yield significant improvement in the functional prognosis of patients with acute minor ischemic stroke. Additionally, it is associated with an increased risk of symptomatic intracranial hemorrhage when compared with the BMT. Moreover, IVT may not have superiority over BMT in patients with nondisabling deficits or those using antiplatelets.

Variability in short-term mortality following repair of ruptured abdominal aortic aneurysms across centers and physicians.

BACKGROUND: Variation in the care management of repairs for ruptured infrarenal abdominal aortic aneurysms between centers and physicians, such as procedural volumes, may explain differences in mortality outcomes. First, we quantified the center and physician variability associated with 30- and 90-day mortality risk after ruptured open surgical repair (rOSR) and ruptured endovascular aneurysm repair (rEVAR). Second, we explored wheter part of this variability was attributable to procedural volume at the center and physician levels. METHODS: Two cohorts including rOSR and rEVAR procedures between 2013 and 2019 were analyzed from the Vascular Quality Initiative database. Thirty- and 90-day all-cause mortality rates were derived from linked Medicare claims data. The median odds ratio (MOR) (median mortality risk from low- to high-risk cluster) and intraclass correlation coefficient (ICC) (variability attributable to each cluster) for 30- and 90-day mortality risks associated with center and physician variability were derived using patient-level adjusted multilevel logistic regression models. Procedural volume was calculated at the center and physician levels and stratified by quartiles. The models were sequentially adjusted for volumes, and the difference in ICCs (without vs with accounting for volume) was calculated to describe the center and physician variability in mortality risk attributable to volumes. RESULTS: We included 450 rOSRs (mean age, 74.5 ± 7.6 years; 23.5% female) and 752 rEVARs (76.4 ± 8.4 years; 26.1% female). After rOSRs, the 30- and 90-day mortality rates were 32.9% and 38.7%, respectively. No variability across centers and physicians was noted (30- and 90-day MORs ≈1 and ICCs ≈0%). Neither center nor physician volume was associated with 30-day (P = .477 and P = .796) or 90-day mortality (P = .098 and P = .559). After rEVAR, the 30- and 90-day mortality rates were 21.3% and 25.5%, respectively. Significant center variability (30-day MOR, 1.82 [95% confidence interval (CI), 1.33-2.22]; ICC, 11% [95% CI, 2%-36%]; and 90-day MOR, 1.76 [95% CI, 1.37-2.09]; ICC, 10% [95% CI, 3%-30%]), but negligeable variability across physicians (30- and 90-day MORs ≈1 and ICCs ≈0%) were noted. Neither center nor physician volume were associated with 30-day (P = .076 and P = .336) or 90-day mortality risk (P = .066 and P = .584). The center variability attributable to procedural volumes was negligeable (difference in ICCs, 1% for 30-day mortality; 0% for 90-day mortality). CONCLUSIONS: Variability in practice from center to center was associated with short-term mortality outcomes in rEVAR, but not for rOSR. Physician variability was not associated with short-term mortality for rOSR or rEVAR. Annualized center and physician volumes did not significantly explain these associations. Further work is needed to identify center-level factors affecting the quality of care and outcomes for ruptured abdominal aortic aneurysms.

Noninvasive Risk Prediction Models for Heart Failure Using Proportional Jaccard Indices and Comorbidity Patterns.

Background: In the post-coronavirus disease 2019 (COVID-19) era, remote diagnosis and precision preventive medicine have emerged as pivotal clinical medicine applications. This study aims to develop a digital health-monitoring tool that utilizes electronic medical records (EMRs) as the foundation for performing a non-random correlation analysis among different comorbidity patterns for heart failure (HF). Methods: Novel similarity indices, including proportional Jaccard index (PJI), multiplication of the odds ratio proportional Jaccard index (OPJI), and alpha proportional Jaccard index (APJI), provide a fundamental framework for constructing machine learning models to predict the risk conditions associated with HF. Results: Our models were constructed for different age groups and sexes and yielded accurate predictions of high-risk HF across demographics. The results indicated that the optimal prediction model achieved a notable accuracy of 82.1% and an area under the curve (AUC) of 0.878. Conclusions: Our noninvasive HF risk prediction system is based on historical EMRs and provides a practical approach. The proposed indices provided simple and straightforward comparative indicators of comorbidity pattern matching within individual EMRs. All source codes developed for our noninvasive prediction models can be retrieved from GitHub.

Rejoinder to the discussion on "Bayesian meta-analysis of penetrance for cancer risk".

The five discussions of our paper provide several modeling alternatives, extensions, and generalizations that can potentially guide future research in meta-analysis. In this rejoinder, we briefly summarize and comment on some of those points.

Bayesian meta-analysis of penetrance for cancer risk.

Multi-gene panel testing allows many cancer susceptibility genes to be tested quickly at a lower cost making such testing accessible to a broader population. Thus, more patients carrying pathogenic germline mutations in various cancer-susceptibility genes are being identified. This creates a great opportunity, as well as an urgent need, to counsel these patients about appropriate risk-reducing management strategies. Counseling hinges on accurate estimates of age-specific risks of developing various cancers associated with mutations in a specific gene, ie, penetrance estimation. We propose a meta-analysis approach based on a Bayesian hierarchical random-effects model to obtain penetrance estimates by integrating studies reporting different types of risk measures (eg, penetrance, relative risk, odds ratio) while accounting for the associated uncertainties. After estimating posterior distributions of the parameters via a Markov chain Monte Carlo algorithm, we estimate penetrance and credible intervals. We investigate the proposed method and compare with an existing approach via simulations based on studies reporting risks for two moderate-risk breast cancer susceptibility genes, ATM and PALB2. Our proposed method is far superior in terms of coverage probability of credible intervals and mean square error of estimates. Finally, we apply our method to estimate the penetrance of breast cancer among carriers of pathogenic mutations in the ATM gene.

Assessing the optimal MRI descriptors to diagnose Ménière's disease and the added value of analysing the vestibular aqueduct.

OBJECTIVES: To evaluate the diagnostic performance and reliability of MRI descriptors used for the detection of Ménière's disease (MD) on delayed post-gadolinium MRI. To determine which combination of descriptors should be optimally applied and whether analysis of the vestibular aqueduct (VA) contributes to the diagnosis. MATERIALS AND METHODS: This retrospective single centre case-control study evaluated delayed post-gadolinium MRI of patients with Ménièriform symptoms examined consecutively between Dec 2017 and March 2023. Two observers evaluated 17 MRI descriptors of MD and quantified perilymphatic enhancement (PLE) in the cochlea. Definite MD ears according to the 2015 Barany Society criteria were compared to control ears. Cohen's kappa and diagnostic odds ratio (DORs) were calculated for each descriptor. Forward stepwise logistic regression determined which combination of MRI descriptors would best predict MD ears, and the area under the receiver operating characteristic curve for this model was measured. RESULTS: A total of 227 patients (mean age 48.3 ± 14.6, 99 men) with 96 definite MD and 78 control ears were evaluated. The presence of saccular abnormality (absent, as large as or confluent with the utricle) performed best with a DOR of 292.6 (95% confidence interval (CI), 38.305-2235.058). All VA descriptors demonstrated excellent reliability and with DORs of 7.761 (95% CI, 3.517-17.125) to 18.1 (95% CI, 8.445-39.170). Combining these saccular abnormalities with asymmetric cochlear PLE and an incompletely visualised VA correctly classified 90.2% of cases (sensitivity 84.4%, specificity 97.4%, AUC 0.938). CONCLUSION: Either absent, enlarged or confluent saccules are the best predictors of MD. Incomplete visualisation of the VA adds value to the diagnosis. CLINICAL RELEVANCE STATEMENT: A number of different MRI descriptors have been proposed for the diagnosis of Ménière's disease, but by establishing the optimally performing MRI features and highlighting new useful descriptors, there is an opportunity to improve the diagnostic performance of Ménière's disease imaging. KEY POINTS: • A comprehensive range of existing and novel vestibular aqueduct delayed post-gadolinium MRI descriptors were compared for their diagnostic performance in Ménière's disease. • Saccular abnormality (absent, confluent with or larger than the utricle) is a reliable descriptor and is the optimal individual MRI predictor of Ménière's disease. • The presence of this saccule descriptor or asymmetric perilymphatic enhancement and incomplete vestibular aqueduct visualisation will optimise the MRI diagnosis of Ménière's disease.

Fractional accumulative calibration-free odds (f-aCFO) design for delayed toxicity in phase I clinical trials.

The calibration-free odds (CFO) design has been demonstrated to be robust, model-free, and practically useful but faces challenges when dealing with late-onset toxicity. The emergence of the time-to-event (TITE) method and fractional method leads to the development of TITE-CFO and fractional CFO (fCFO) designs to accumulate delayed toxicity. Nevertheless, existing CFO-type designs have untapped potential because they primarily consider dose information from the current position and its two neighboring positions. To incorporate information from all doses, we propose the accumulative CFO (aCFO) design by utilizing data at all dose levels similar to a tug-of-war game where players distant from the center also contribute their strength. This approach enhances full information utilization while still preserving the model-free and calibration-free characteristics. Extensive simulation studies demonstrate performance improvement over the original CFO design, emphasizing the advantages of incorporating information from a broader range of dose levels. Furthermore, we propose to incorporate late-onset outcomes into the TITE-aCFO and f-aCFO designs, with f-aCFO displaying superior performance over existing methods in both fixed and random simulation scenarios. In conclusion, the aCFO and f-aCFO designs can be considered robust, efficient, and user-friendly approaches for conducting phase I trials without or with late-onsite toxicity.

Relationship Between Melatonin Receptor Agonists and Parkinson's Disease.

Parkinson's disease affects millions of people worldwide, and without significant progress in disease prevention and treatment, its incidence and prevalence could increase by more than 30% by 2030. Researchers have focused on targeting sleep and the circadian system as a novel treatment strategy for Parkinson's disease. This study investigated the association between melatonin receptor agonists and Parkinson's disease, using the Food and Drug Administration (FDA) Adverse Events Reporting System (FAERS). The target drugs were melatonin receptor agonists including ramelteon, tasimelteon, and agomelatine. Parkinson's disease cases were defined according to the Medical Dictionary for Regulatory Activities (MedDRA) 25.0; Standardized MedDRA Query (SMQ) using both the "narrow" and "broad" preferred terms (PTs) associated with Parkinson's disease. The association between melatonin receptor agonists (ramelteon, tasimelteon, and agomelatine) and Parkinson's disease was evaluated by the reporting odds ratio. Upon analyzing the data from all patients registered in the FAERS, ramelteon (ROR: 0.66, 95% confidence interval [95% CI]: 0.51-0.84) and tasimelteon (ROR: 0.49, 95% CI: 0.38-0.62) showed negative correlations with Parkinson's disease. Conversely, only agomelatine was positively correlated with Parkinson's disease (ROR: 2.63, 95% CI: 2.04-3.40). These results suggest that among the melatonin receptor agonists, ramelteon and tasimelteon are negatively correlated with Parkinson's disease. In contrast, agomelatine was shown to be positively correlated with Parkinson's disease. These results should be used in research to develop drugs for the treatment of Parkinson's disease, fully considering the limitations of the spontaneous reporting system.

Methods of determining optimal cut-point of diagnostic biomarkers with application of clinical data in ROC analysis: an update review.

INTRODUCTION: An important application of ROC analysis is the determination of the optimal cut-point for biomarkers in diagnostic studies. This comprehensive review provides a framework of cut-point election for biomarkers in diagnostic medicine. METHODS: Several methods were proposed for the selection of optional cut-points. The validity and precision of the proposed methods were discussed and the clinical application of the methods was illustrated with a practical example of clinical diagnostic data of C-reactive protein (CRP), erythrocyte sedimentation rate (ESR) and malondialdehyde (MDA) for prediction of inflammatory bowel disease (IBD) patients using the NCSS software. RESULTS: Our results in the clinical data suggested that for CRP and MDA, the calculated cut-points of the Youden index, Euclidean index, Product and Union index methods were consistent in predicting IBD patients, while for ESR, only the Euclidean and Product methods yielded similar estimates. However, the diagnostic odds ratio (DOR) method provided more extreme values for the optimal cut-point for all biomarkers analyzed. CONCLUSION: Overall, the four methods including the Youden index, Euclidean index, Product, and IU can produce quite similar optimal cut-points for binormal pairs with the same variance. The cut-point determined with the Youden index may not agree with the other three methods in the case of skewed distributions while DOR does not produce valid informative cut-points. Therefore, more extensive Monte Carlo simulation studies are needed to investigate the conditions of test result distributions that may lead to inconsistent findings in clinical diagnostics.

Effectiveness of bevacizumab in the treatment of metastatic colorectal cancer: a systematic review and meta-analysis.

OBJECTIVE: To evaluate the benefit of bevacizumab under the comprehensive treatment strategy and its advantages over other drugs, so as to provide reference for the formulation of clinical plans. METHODS: As of October 1, 2022, the randomized controlled clinical trials of bevacizumab in combination with metastatic colorectal cancer published in PubMed, Cochrane Library and Medline databases were searched. The odds ratio (OR) and its 95% confidence interval (CI) were used to evaluate the short-term disease control effect and long-term survival of the treatment strategy. RESULTS: 21 RCTs (6665 patients; 3356 patients in the experimental group and 3309 patients in the control group; average age, 55-75 years) were treated with bevacizumab as the experimental group for metastatic colorectal cancer. BEV has stronger anti-tumor activity than the single treatment scheme (OR = 1.30, 95% CI: 1.11-1.52). And Benefits of the BEV group were 0.73 (0.55, 0.96), 1.26 (0.71, 2.24), 1.63 (0.92, 2.87) and 0.07 (0.02, 0.25) compared with CET, VAN, CED and PAN respectively. The disease control of BEV combined therapy was better (OR = 1.36, 95% CI: 1.04-1.78). The same as compared with cediranib (OR = 1.94, 95% CI: 1.06-3.55). However, the long-term prognosis of BEV, including the overall survival (HRs = 0.98, 95% CI: 0.84-1.15) and progression-free survival (HRs = 1.05,95% CI: 0.97-1.13) were not prolonged. The survival benefits of cetuximab and panitumumab were not reflected. CONCLUSION: The addition of BEV can enhance the anti-tumor ability and disease control, while cetuximab and panitumumab may have stronger ability. However, it did not effectively improve the survival of patients. A more reasonable and effective treatment plan needs more clinical experimental support.

Autoimmune disorders reported following COVID-19 vaccination: A disproportionality analysis using the WHO database.

PURPOSE: Owing to adverse event following immunization (AEFI) related to autoimmune disorders and coronavirus disease 2019 (COVID-19) vaccines sharing common biological mechanisms, identifying the risk of AEFIs associated with COVID-19 vaccines remains a critical unmet need. We aimed to assess the potential safety signals for 16 AEFIs and explore co-reported adverse events (AEs) and drugs using the global database of the World Health Organization, VigiBase. METHODS: We assessed the occurrence of 16 AEFIs following COVID-19 vaccination through the Standardized MedDRA Queries group "Immune-mediated/Autoimmune Disorders" from MedDRA and performed a disproportionality analysis using reporting odds ratio (ROR) and information component (IC) with 95% confidence intervals (CIs). RESULTS: We identified 25,219 events associated with COVID-19 vaccines in VigiBase. Although rare, we detected four potential safety signals related to autoimmune disorders following COVID-19 vaccination, including ankylosing spondylitis or psoriatic arthritis (ROR 1.86; 95% CI 1.53-2.27), inflammatory bowel disease (ROR 1.77; 95% CI 1.60-1.96), polymyalgia rheumatica (ROR 1.42; 95% CI 1.30-1.55), and thyroiditis (ROR 1.40; 95% CI 1.30-1.50), with positive IC025 values. The top co-reported AEs were musculoskeletal disorders, and immunosuppressants were the most representative co-reported drugs. CONCLUSION: In addressing the imperative to comprehend AEFI related to autoimmune disorders following COVID-19 vaccination, our study identified four potential safety signals. Thus, our research underscores the importance of proactive safety monitoring for the identification of the four AEFIs following COVID-19 vaccination, considering the associated advantages.

Association between prenatal air pollutant exposure and autism spectrum disorders in young children: A matched case-control study in Canada.

The direction and magnitude of association between maternal exposure to ambient air pollutants across gestational windows and offspring risk of autism spectrum disorders (ASD) remains unclear. We sought to evaluate the time-varying effects of prenatal air pollutant exposure on ASD. We conducted a matched case-control study of singleton term children born in Ontario, Canada from 1-Apr-2012 to 31-Dec-2016. Provincial birth registry data were linked with applied behavioural analysis services and ambient air pollutant datasets to ascertain prenatal exposure to nitrogen dioxide (NO2), ground-level ozone (O3), fine particulate matter (PM2.5), and ASD diagnoses. Covariate balance between cases and controls was established using coarsened exact matching. Conditional logistic regression was used to assess the association between prenatal air pollutant exposure and ASD. Distributed lag non-linear models (DLNM) were used to examine the effects of single-pollutant exposure by prenatal week. Sensitivity analyses were conducted to assess the impact of exposure period on the observed findings. The final sample included 1589 ASD cases and 7563 controls. Compared to controls, cases were more likely to be born to mothers living in urban areas, delivered by Caesarean section, and assigned male sex at birth. NO2 was a consistent and significant contributor to ASD risk after accounting for co-exposure to O3, PM2.5 and covariates. The odds ratio per interquartile range increase was 2.1 (95%CI 1.8-2.3) pre-conception, 2.2 (2.0-2.5) for the 1st trimester, 2.2 (1.9-2.5) for the 2nd trimester, and 2.1 (1.9-2.4) for the 3rd trimester. In contrast, findings for O3 and PM2.5 with ASD were inconsistent. Findings from DLNM and sensitivity analyses were similar. Exposure to NO2 before and during pregnancy was significantly associated with ASD in offspring. The relationship between prenatal O3 and PM2.5 exposure and ASD remains unclear. Further investigation into the combined effects of multi-pollutant exposure on child neurodevelopment is warranted.

Evaluating treatment efficacy in hospitalized COVID-19 patients, with applications to Adaptive COVID-19 Treatment Trials.

BACKGROUND: The current endpoints for therapeutic trials of hospitalized COVID-19 patients capture only part of the clinical course of a patient and have limited statistical power and robustness. METHODS: We specify proportional odds models for repeated measures of clinical status, with a common odds ratio of lower severity over time. We also specify the proportional hazards model for time to each level of improvement or deterioration of clinical status, with a common hazard ratio for overall treatment benefit. We apply these methods to Adaptive COVID-19 Treatment Trials. RESULTS: For remdesivir versus placebo, the common odds ratio was 1.48 (95% confidence interval (CI) = 1.23-1.79; p < 0.001), and the common hazard ratio was 1.27 (95% CI = 1.09-1.47; p = 0.002). For baricitinib plus remdesivir versus remdesivir alone, the common odds ratio was 1.32 (95% CI = 1.10-1.57; p = 0.002), and the common hazard ratio was 1.30 (95% CI = 1.13-1.49; p < 0.001). For interferon beta-1a plus remdesivir versus remdesivir alone, the common odds ratio was 0.95 (95% CI = 0.79-1.14; p = 0.56), and the common hazard ratio was 0.98 (95% CI = 0.85-1.12; p = 0.74). CONCLUSIONS: The proposed methods comprehensively characterize the treatment effects on the entire clinical course of a hospitalized COVID-19 patient.

Medical diagnostic accuracy measures: an innovative approach based on the area under predictive values curves.

Positive and negative estimates are commonly used by clinicians to evaluate the likelihood of a disease stage being present based on test results. The predicted values are dependent on the prevalence of the underlying illness. However, for certain diseases or clinical conditions, the prevalence is unknown or different from one region to another or from one population to another, leading to an erroneous diagnosis. This article introduces innovative post-test diagnostic precision measures for continuous tests or biomarkers based on the combined areas under the predictive value curves for all possible prevalence values. The proposed measures do not vary as a function of the prevalence of the disease. They can be used to compare different diagnostic tests and/or biomarkers' abilities for rule-in, rule-out, and overall accuracy based on the combined areas under the predictive value curves. The relationship of the proposed measures to other diagnostic accuracy measures is discussed. We illustrate the proposed measures numerically and use a real data example on breast cancer.

Miettinen and Nurminen score statistics revisited.

It is commonly necessary to perform inferences on the difference, ratio, and odds ratio of two proportions p1 and p2 based on two independent samples. For this purpose, the most common asymptotic statistics are based on the score statistics (S-type statistics). As these do not correct the bias of the estimator of the product pi (1-pi), Miettinen and Nurminen proposed the MN-type statistics, which consist of multiplying the statistics S by (N-1)/N, where N is the sum of the two sample sizes. This paper demonstrates that the factor (N-1)/N is only correct in the case of the test of equality of two proportions, providing the estimation of the correct factor (AU-type statistics) and the minimum value of the same (AUM-type statistics). Moreover, this paper assesses the performance of the four-type statistics mentioned (S, MN, AU and AUM) in one and two-tailed tests, and for each of the three parameters cited (d, R and OR). We found that the AUM-type statistics are the best, followed by the MN type (whose performance was most similar to that of AU-type). Finally, this paper also provides the correct factors when the data are from a multinomial distribution, with the novelty that the MN and AU statistics are similar in the case of the test for the odds ratio.

Utility of the LACE index to assess risk of mortality and readmission in patients with spinal infections.

Retrospective cohort study. To assess the utility of the LACE index for predicting death and readmission in patients with spinal infections (SI). SIs are severe conditions, and their incidence has increased in recent years. The LACE (Length of stay, Acuity of admission, Comorbidities, Emergency department visits) index quantifies the risk of mortality or unplanned readmission. It has not yet been validated for SIs. LACE indices were calculated for all adult patients who underwent surgery for spinal infection between 2012 and 2021. Data were collected from a single academic teaching hospital. Outcome measures included the LACE index, mortality, and readmission rate within 30 and 90 days. In total, 164 patients were analyzed. Mean age was 64.6 (± 15.1) years, 73 (45%) were female. Ten (6.1%) patients died within 30 days and 16 (9.8%) died within 90 days after discharge. Mean LACE indices were 13.4 (± 3.6) and 13.8 (± 3.0) for the deceased patients, compared to 11.0 (± 2.8) and 10.8 (± 2.8) for surviving patients (p = 0.01, p < 0.001), respectively. Thirty-seven (22.6%) patients were readmitted ≤ 30 days and 48 (29.3%) were readmitted ≤ 90 days. Readmitted patients had a significantly higher mean LACE index compared to non-readmitted patients (12.9 ± 2.1 vs. 10.6 ± 2.9, < 0.001 and 12.8 ± 2.3 vs. 10.4 ± 2.8, p < 0.001, respectively). ROC analysis for either death or readmission within 30 days estimated a cut-off LACE index of 12.0 points (area under the curve [AUC] 95% CI, 0.757 [0.681-0.833]) with a sensitivity of 70% and specificity of 69%. Patients with SI had high LACE indices that were associated with high mortality and readmission rates. The LACE index can be applied to this patient population to predict the risk of early death or unplanned readmission.