Publication speed in pharmacy practice journals: A comparative analysis

Background Scholarly publishing system relies on external peer review. However, the duration of publication process is a major concern for authors and funding bodies. Objective To evaluate the duration of the publication process in pharmacy practice journals compared with other biomedical journals indexed in PubMed. Methods All the articles published from 2009 to 2018 by the 33 pharmacy practice journals identified in Mendes et al. study and indexed in PubMed were gathered as study group. A comparison group was created through a random selection of 3000 PubMed PMIDs for each year of study period. Articles with publication dates outside the study period were excluded. Metadata of both groups of articles were imported from PubMed. The duration of editorial process was calculated with three periods: acceptance lag (days between 'submission date' and 'acceptance date'), lead lag (days between 'acceptance date' and 'online publication date'), and indexing lag (days between 'online publication date' and 'Entry date'). Null hypothesis significance tests and effect size measures were used to compare these periods between both groups. Results The 33 pharmacy practice journals published 26,256 articles between 2009 and 2018. Comparison group random selection process resulted in a pool of 23,803 articles published in 5,622 different journals. Acceptance lag was 105 days (IQR 57-173) for pharmacy practice journals and 97 days (IQR 56-155) for the comparison group with a null effect difference (Cohen's d 0.081). Lead lag was 13 (IQR 6-35) and 23 days (IQR 9-45) for pharmacy practice and comparison journals, respectively, which resulted in a small effect. Indexing lag was 5 days (IQR 2-46) and 4 days (IQR 2-12) for pharmacy practice and control journals, which also resulted in a small effect. Slight positive time trend was found in pharmacy practice acceptance lag, while slight negative trends were found for lead and indexing lags for both groups. Conclusions Publication process duration of pharmacy practice journals is similar to a general random sample of articles from all disciplines

Description of network meta-analysis geometry: A metrics design study

© 2019 Tonin et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Background The conduction and report of network meta-analysis (NMA), including the presentation of the network-plot, should be transparent. We aimed to propose metrics adapted from graph theory and social network-analysis literature to numerically describe NMA geometry. Methods A previous systematic review of NMAs of pharmacological interventions was performed. Data on the graph’s presentation were collected. Network-plots were reproduced using Gephi 0.9.1. Eleven geometric metrics were tested. The Spearman test for non-parametric correlation analyses and the Bland-Altman and Lin’s Concordance tests were performed (IBM SPSS Statistics 24.0). Results From the 477 identified NMAs only 167 graphs could be reproduced because they provided enough information on the plot characteristics. The median nodes and edges were 8 (IQR 6–11) and 10 (IQR 6–16), respectively, with 22 included studies (IQR 13–35). Metrics such as density (median 0.39, ranged 0.07–1.00), median thickness (2.0, IQR 1.0–3.0), percentages of common comparators (median 68%), and strong edges (median 53%) were found to contribute to the description of NMA geometry. Mean thickness, average weighted degree and average path length produced similar results than other metrics, but they can lead to misleading conclusions. Conclusions We suggest the incorporation of seven simple metrics to report NMA geometry. Editors and peer-reviews should ensure that guidelines for NMA report are strictly followed before publication

Antioxidant effects of vitamins in type 2 diabetes: A meta-analysis of randomized controlled trials

© 2018 The Author(s). Background: Vitamins are essential micronutrients with antioxidant potential that may provide a complementary treatment for patients with chronic diseases. Our aim was to assess the effect of vitamin supplementation on the antioxidant status and glycemic index of type 2 diabetes mellitus patients. Methods: We performed a systematic review with meta-analyses. Electronic searches were conducted in PubMed, Scopus, and Web of Science (December 2017). Randomized controlled trials evaluating the effect of any vitamin or vitamin complex supplementation on antioxidant status as primary outcome were included. The outcomes considered were: reduction of malondialdehyde (MDA); augmentation of glutathione peroxidase (GPx); changes in total antioxidant capacity (TAC), enhance in superoxide dismutase enzyme - SOD, and thiobarbituric acid reactive substances (TBARS). Outcomes of glycemic control were also evaluated. Pairwise meta-analyses were performed using software Review Manager 5.3. Results: Thirty trials fulfilled the inclusion criteria, but only 12 could be included in the meta-analyses of antioxidant outcomes. The most commonly studied vitamins were B, C, D and E. Vitamin E was related to significant reduction of blood glucose as well as glycated hemoglobin compared to placebo, while both vitamins C and E were mainly associated with reducing MDA and TBARS and elevating GPx, SOD and TAC, compared to placebo. However, outcome reports in this field are still inconsistent (e.g. because of a lack of standard measures). Conclusions: Supplementation of vitamin E may be a valuable strategy for controlling diabetes complications and enhancing antioxidant capacity. The effects of other micronutrients should be further investigated in larger and well-designed trials to properly place these complementary therapies in clinical practice

Haplotype analysis of TP53 polymorphisms, Arg72Pro and Ins16, in BRCA1 and BRCA2 mutation carriers of French Canadian descent

Research articl

Identity by Descent Mapping of Founder Mutations in Cancer Using High-Resolution Tumor SNP Data

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the “missing” heritability in cancer. This method is freely available and can be used online at the FounderTracker website

New challenges for BRCA testing:a view from the diagnostic laboratory

Increased demand for BRCA testing is placing pressures on diagnostic laboratories to raise their mutation screening capacity and handle the challenges associated with classifying BRCA sequence variants for clinical significance, for example interpretation of pathogenic mutations or variants of unknown significance, accurate determination of large genomic rearrangements and detection of somatic mutations in DNA extracted from formalin-fixed, paraffin-embedded tumour samples. Many diagnostic laboratories are adopting next-generation sequencing (NGS) technology to increase their screening capacity and reduce processing time and unit costs. However, migration to NGS introduces complexities arising from choice of components of the BRCA testing workflow, such as NGS platform, enrichment method and bioinformatics analysis process. An efficient, cost-effective accurate mutation detection strategy and a standardised, systematic approach to the reporting of BRCA test results is imperative for diagnostic laboratories. This review covers the challenges of BRCA testing from the perspective of a diagnostics laboratory

Genetic variation in insulin-like growth factor signaling genes and breast cancer risk among BRCA1 and BRCA2 carriers

Abstract Introduction Women who carry mutations in BRCA1 and BRCA2 have a substantially increased risk of developing breast cancer as compared with the general population. However, risk estimates range from 20 to 80%, suggesting the presence of genetic and/or environmental risk modifiers. Based on extensive in vivo and in vitro studies, one important pathway for breast cancer pathogenesis may be the insulin-like growth factor (IGF) signaling pathway, which regulates both cellular proliferation and apoptosis. BRCA1 has been shown to directly interact with IGF signaling such that variants in this pathway may modify risk of cancer in women carrying BRCA mutations. In this study, we investigate the association of variants in genes involved in IGF signaling and risk of breast cancer in women who carry deleterious BRCA1 and BRCA2 mutations. Methods A cohort of 1,665 adult, female mutation carriers, including 1,122 BRCA1 carriers (433 cases) and 543 BRCA2 carriers (238 cases) were genotyped for SNPs in IGF1, IGF1 receptor (IGF1R), IGF1 binding protein (IGFBP1, IGFBP2, IGFBP5), and IGF receptor substrate 1 (IRS1). Cox proportional hazards regression was used to model time from birth to diagnosis of breast cancer for BRCA1 and BRCA2 carriers separately. For linkage disequilibrium (LD) blocks with multiple SNPs, an additive genetic model was assumed; and for single SNP analyses, no additivity assumptions were made. Results Among BRCA1 carriers, significant associations were found between risk of breast cancer and LD blocks in IGF1R (global P = 0.011 for LD block 2 and global P = 0.012 for LD block 11). Among BRCA2 carriers, an LD block in IGFBP2 (global P = 0.0145) was found to be associated with the time to breast cancer diagnosis. No significant LD block associations were found for the other investigated genes among BRCA1 and BRCA2 carriers. Conclusions This is the first study to investigate the role of genetic variation in IGF signaling and breast cancer risk in women carrying deleterious mutations in BRCA1 and BRCA2. We identified significant associations in variants in IGF1R and IRS1 in BRCA1 carriers and in IGFBP2 in BRCA2 carriers. Although there is known to be interaction of BRCA1 and IGF signaling, further replication and identification of causal mechanisms are needed to better understand these associations