Approximated penalized maximum likelihood for exploratory factor analysis: an orthogonal case

The problem of penalized maximum likelihood (PML) for an exploratory factor analysis (EFA) model is studied in this paper. An EFA model is typically estimated using maximum likelihood and then the estimated loading matrix is rotated to obtain a sparse representation. Penalized maximum likelihood simultaneously fits the EFA model and produces a sparse loading matrix. To overcome some of the computational drawbacks of PML, an approximation to PML is proposed in this paper. It is further applied to an empirical dataset for illustration. A simulation study shows that the approximation naturally produces a sparse loading matrix and more accurately estimates the factor loadings and the covariance matrix, in the sense of having a lower mean squared error than factor rotations, under various conditions

Mediation modeling and analysis for high-throughput omics data

Abstract There is a strong need for powerful unified statistical methods for discovering underlying genetic architecture of complex traits with the assistance of omics information. In this paper, two methods aiming to detect novel association between the human genome and complex traits using intermediate omics data are developed based on statistical mediation modeling. We demonstrate theoretically that given proper mediators, the proposed statistical mediation models have better power than genome-wide association studies (GWAS) to detect associations missed in standard GWAS that ignore the mediators. For each of the modeling methods in this paper, an empirical example is given, where the association between a SNP and BMI missed by standard GWAS can be discovered by mediation analysis

Balancing the Benefits and Risks of 2 Doses of Dabigatran Compared With Warfarin in Atrial Fibrillation

ObjectivesThis study sought to compare the net clinical benefit of dabigatran 110 mg bid and 150 mg bid with that of warfarin in patients with atrial fibrillation (AF).BackgroundIn patients with AF, dabigatran 110 mg bid and 150 mg bid are associated with similar rates of death. However, the higher dose reduces ischemic stroke and increases bleeding compared with the lower dose. Therefore, there is uncertainty about how to evaluate the overall benefit of the 2 doses.MethodsIn 18,113 AF patients in the RE-LY (Randomized Evaluation of Long Term Anticoagulant Therapy) trial, we used a previously developed method for integrating ischemic and bleeding events as “ischemic stroke equivalents” in order to compare a weighted benefit of 2 doses of dabigatran with each other, and with that of warfarin.ResultsCompared with warfarin, there was a significant decrease in ischemic stroke equivalents with both dabigatran doses: –0.92 per 100 patient years (95% confidence interval [CI]: –1.74 to −0.21, p = 0.02) with dabigatran 110 mg bid and –1.08 (95% CI: –1.86 to −0.34, p = 0.01) with dabigatran 150 mg bid. There was no significant difference in ischemic stroke equivalents between the 2 doses: –0.16 (95% CI: –0.80 to 0.43) comparing dabigatran 150 mg bid with 110 bid. When including death in the weighted benefit calculations, the results were similar.ConclusionsOn a group level both doses of dabigatran as compared with warfarin have similar benefits when considering a weighted estimate including both efficacy and safety. The similar overall benefits of the 2 doses of dabigatran versus warfarin support individualizing the dose based on patient characteristics and physician and patient preferences. (Randomized Evaluation of Long Term Anticoagulant Therapy [RE-LY] With Dabigatran Etexilate; NCT00262600

The Number of Factors Problem

This chapter focuses on formal criteria to assess the dimensionality for exploratory factor modelling with the aim to facilitate the selection of a proper criterion in empirical practice. It introduces the different foundations that underlie the various criteria and provides an overview of currently available formal criteria, which we selected on the basis of their popularity in empirical practice and/or proven effectiveness. The chapter successively reviews principal component analysis (PCA)‐based methods and common factor analysis (CFA)‐based methods to assess the number of common factors. To assess the number of factors underlying an empirical data set, the chapter suggests some strategies. It explains the finding in many studies that the Kaiser criterion clearly yields inaccurate indications of the number of PCs and common factors, mostly indicating too many factors. Minimum average partial (MAP) performances in indicating the number of major factors deteriorated when the unique variances increased, with no clear tendency to over‐ or underindicate the number of factors

Long-Term Clinical Outcomes according to Initial Management and Thrombolysis In Myocardial Infarction Risk Score in Patients with Acute Non-ST-Segment Elevation Myocardial Infarction

PURPOSE: There is still debate about the timing of revascularization in patients with acute non-ST-segment elevation myocardial infarction (NSTEMI). We analyzed the long-term clinical outcomes of the timing of revascularization in patients with acute NSTEMI obtained from the Korea Acute Myocardial Infarction Registry (KAMIR). MATERIALS AND METHODS: 2,845 patients with acute NSTEMI (65.6 +/- 12.5 years, 1,836 males) who were enrolled in KAMIR were included in the present study. The therapeutic strategy of NSTEMI was categorized into early invasive (within 48 hours, 65.8 +/- 12.6 years, 856 males) and late invasive treatment (65.3 +/- 12.1 years, 979 males). The initial- and long-term clinical outcomes were compared between two groups according to the level of Thrombolysis In Myocardial Infarction (TIMI) risk score. RESULTS: There were significant differences in-hospital mortality and the incidence of major adverse cardiac events during one-year clinical follow-up between two groups (2.1% vs. 4.8%, p or= 5 points). CONCLUSIONS: The old age, high Killip class, low ejection fraction, high TIMI risk score, and late invasive treatment strategy are the independent predictors for the long-term clinical outcomes in patients with NSTEMI.ope

Clinical Benefit of Low Molecular Weight Heparin for ST-segment Elevation Myocardial Infarction Patients Undergoing Primary Percutaneous Coronary Intervention with Glycoprotein IIb/IIIa Inhibitor

The efficacy of low molecular weight heparin (LMWH) with low dose unfractionated heparin (UFH) during percutaneous coronary intervention (PCI) with or without glycoprotein (Gp) IIb/IIIa inhibitor compared to UFH with or without Gp IIb/IIIa inhibitor has not been elucidated. Between October 2005 and July 2007, 2,535 patients with ST elevation acute myocardial infarction (STEMI) undergoing PCI in the Korean Acute Myocardial Infarction Registry (KAMIR) were assigned to either of two groups: a group with Gp IIb/IIIa inhibitor (n=476) or a group without Gp IIb/IIIa inhibitor (n=2,059). These groups were further subdivided according to the use of LMWH with low dose UFH (n=219) or UFH alone (n=257). The primary end points were cardiac death or myocardial infarction during the 30 days after the registration. The primary end point occurred in 4.1% (9/219) of patients managed with LMWH during PCI and Gp IIb/IIIa inhibitor and 10.8% (28/257) of patients managed with UFH and Gp IIb/IIIa inhibitor (odds ratio [OR], 0.290; 95% confidence interval [CI], 0.132-0.634; P=0.006). Thrombolysis In Myocardial Infarction (TIMI) with major bleeding was observed in LMHW and UFH with Gp IIb/IIIa inhibitor (1/219 [0.5%] vs 1/257 [0.4%], P=1.00). For patients with STEMI managed with a primary PCI and Gp IIb/IIIa inhibitor, LMWH is more beneficial than UFH

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health