A case study evaluating the effect of clustering, publication bias, and heterogeneity on the meta-analysis estimates in implant dentistry.

Meta-analyses may provide imprecise estimates when important meta-analysis parameters are not considered during the synthesis. The aim of this case study was to highlight the influence of meta-analysis parameters that can affect reported estimates using as an example pre-existing meta-analyses on the association between implant survival and sinus membrane perforation. PubMed was searched on 7 July 2021 for meta-analyses comparing implant failure in perforated and non-perforated sinus membranes.

Automated machine learning for genome wide association studies.

Motivation: Genome-wide association studies (GWAS) present several computational and statistical challenges for their data analysis, including knowledge discovery, interpretability, and translation to clinical practice.

Results: We develop, apply, and comparatively evaluate an automated machine learning (AutoML) approach, customized for genomic data that delivers reliable predictive and diagnostic models, the set of genetic variants that are important for predictions (called a biosignature), and an estimate of the out-of-sample predictive power. This AutoML approach discovers variants with higher predictive performance compared to standard GWAS methods, computes an individual risk prediction score, generalizes to new, unseen data, is shown to better differentiate causal variants from other highly correlated variants, and enhances knowledge discovery and interpretability by reporting multiple equivalent biosignatures.

Are treatment effect assumptions in orthodontic studies overoptimistic?

Background: At the clinical trial design stage, assumptions regarding the treatment effects to be detected should be appropriate so that the required sample size can be calculated. There is evidence in the medical literature that sample size assumption can be overoptimistic. The aim of this study was to compare the distribution of the assumed effects versus that of the observed effects as a proxy for overoptimistic treatment effect assumptions at the study design stage.

Psychometrics of health-related quality of life questionnaires in bronchiectasis: a systematic review and meta-analysis.

Introduction: Understanding the psychometric properties of health-related quality of life (HRQoL) questionnaires can help inform selection in clinical trials. Our objective was to assess the psychometric properties of HRQoL questionnaires in bronchiectasis using a systematic review and meta-analysis of the literature.

Methods: A literature search was conducted.