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John ioannidis

Sally J Wadsworth, John C DeFries, Erik G Willcutt, Bruce F Pennington, Richard K Olson
Because of recent concerns about the replication of published results in the behavioral and biomedical sciences (Ioannidis, PLoS Medicine, Vol. 2, 2005, p. e124; Open Science Collaboration, Science, Vol. 349, 2015, p. 943; Pashler & Wagenmakers, Perspectives on Psychological Science, Vol. 7, 2012, pp. 528-530), we have conducted a replication of our recently published analyses of longitudinal reading performance and attention deficit-hyperactivity disorder data from twin pairs selected for reading difficulties (Wadsworth et al...
October 17, 2016: Twin Research and Human Genetics: the Official Journal of the International Society for Twin Studies
Patrick G Sullivan, Joshua D Wallach, John P A Ioannidis
A wide variety of multivariable risk models have been developed to predict mortality in the setting of cardiac surgery; however, the relative utility of these models is unknown. This study investigated the literature related to comparisons made between established risk prediction models for perioperative mortality used in the setting of cardiac surgery. A systematic review was conducted to capture studies in cardiac surgery comparing the relative performance of at least 2 prediction models cited in recent guidelines (European System for Cardiac Operative Risk Evaluation [EuroSCORE II], Society for Thoracic Surgeons 2008 Cardiac Surgery Risk Models [STS] score, and Age, Creatinine, Ejection Fraction [ACEF] score) for the outcomes of 1-month or inhospital mortality...
August 23, 2016: American Journal of Cardiology
Susan Mayor
No abstract text is available yet for this article.
2016: BMJ: British Medical Journal
Nilah M Ioannidis, Joseph H Rothstein, Vikas Pejaver, Sumit Middha, Shannon K McDonnell, Saurabh Baheti, Anthony Musolf, Qing Li, Emily Holzinger, Danielle Karyadi, Lisa A Cannon-Albright, Craig C Teerlink, Janet L Stanford, William B Isaacs, Jianfeng Xu, Kathleen A Cooney, Ethan M Lange, Johanna Schleutker, John D Carpten, Isaac J Powell, Olivier Cussenot, Geraldine Cancel-Tassin, Graham G Giles, Robert J MacInnis, Christiane Maier, Chih-Lin Hsieh, Fredrik Wiklund, William J Catalona, William D Foulkes, Diptasri Mandal, Rosalind A Eeles, Zsofia Kote-Jarai, Carlos D Bustamante, Daniel J Schaid, Trevor Hastie, Elaine A Ostrander, Joan E Bailey-Wilson, Predrag Radivojac, Stephen N Thibodeau, Alice S Whittemore, Weiva Sieh
The vast majority of coding variants are rare, and assessment of the contribution of rare variants to complex traits is hampered by low statistical power and limited functional data. Improved methods for predicting the pathogenicity of rare coding variants are needed to facilitate the discovery of disease variants from exome sequencing studies. We developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, MutationTaster, LRT, GERP, SiPhy, phyloP, and phastCons...
October 6, 2016: American Journal of Human Genetics
Timothy E Sweeney, Winston A Haynes, Francesco Vallania, John P Ioannidis, Purvesh Khatri
Findings from clinical and biological studies are often not reproducible when tested in independent cohorts. Due to the testing of a large number of hypotheses and relatively small sample sizes, results from whole-genome expression studies in particular are often not reproducible. Compared to single-study analysis, gene expression meta-analysis can improve reproducibility by integrating data from multiple studies. However, there are multiple choices in designing and carrying out a meta-analysis. Yet, clear guidelines on best practices are scarce...
September 14, 2016: Nucleic Acids Research
John P A Ioannidis
POLICY POINTS: Currently, there is massive production of unnecessary, misleading, and conflicted systematic reviews and meta-analyses. Instead of promoting evidence-based medicine and health care, these instruments often serve mostly as easily produced publishable units or marketing tools. Suboptimal systematic reviews and meta-analyses can be harmful given the major prestige and influence these types of studies have acquired. The publication of systematic reviews and meta-analyses should be realigned to remove biases and vested interests and to integrate them better with the primary production of evidence...
September 2016: Milbank Quarterly
Divya Parmar, Charitini Stavropoulou, John P A Ioannidis
OBJECTIVE:  To systematically identify, critically appraise, and synthesise empirical studies about the impact of the 2008 financial crisis in Europe on health outcomes. DESIGN:  Systematic literature review. DATA SOURCES:  Structural searches of key databases, healthcare journals, and organisation based websites. REVIEW METHODS:  Empirical studies reporting on the impact of the financial crisis on health outcomes in Europe, published from January 2008 to December 2015, were included...
2016: BMJ: British Medical Journal
Vanesa Bellou, Lazaros Belbasis, Ioanna Tzoulaki, Lefkos T Middleton, John P A Ioannidis, Evangelos Evangelou
INTRODUCTION: Dementia is a heterogeneous neurodegenerative disease, whose etiology results from a complex interplay between environmental and genetic factors. METHODS: We searched PubMed to identify meta-analyses of observational studies that examined associations between nongenetic factors and dementia. We estimated the summary effect size using random-effects and fixed-effects model, the 95% CI, and the 95% prediction interval. We assessed the between-study heterogeneity (I-square), evidence of small-study effects, and excess significance...
September 4, 2016: Alzheimer's & Dementia: the Journal of the Alzheimer's Association
John P A Ioannidis, Kevin Boyack, Paul F Wouters
Citation metrics are increasingly used to appraise published research. One challenge is whether and how to normalize these metrics to account for differences across scientific fields, age (year of publication), type of document, database coverage, and other factors. We discuss the pros and cons for normalizations using different approaches. Additional challenges emerge when citation metrics need to be combined across multiple papers to appraise the corpus of scientists, institutions, journals, or countries, as well as when trying to attribute credit in multiauthored papers...
September 2016: PLoS Biology
John P A Ioannidis, Richard Klavans, Kevin W Boyack
[This corrects the article DOI: 10.1371/journal.pbio.1002501.].
August 2016: PLoS Biology
Chirag J Patel, Jianguang Ji, Jan Sundquist, John P A Ioannidis, Kristina Sundquist
It is a public health priority to identify the adverse and non-adverse associations between pharmaceutical medications and cancer. We search for and evaluate associations between all prescribed medications and longitudinal cancer risk in participants of the Swedish Cancer Register (N = 9,014,975). We associated 552 different medications with incident cancer risk (any, breast, colon, and prostate) during 5.5 years of follow-up (7/1/2005-12/31/2010) in two types of statistical models, time-to-event and case-crossover...
2016: Scientific Reports
Thomas Pa Debray, Ewoud Schuit, Orestis Efthimiou, Johannes B Reitsma, John Pa Ioannidis, Georgia Salanti, Karel Gm Moons
Network meta-analysis (NMA) is a common approach to summarizing relative treatment effects from randomized trials with different treatment comparisons. Most NMAs are based on published aggregate data (AD) and have limited possibilities for investigating the extent of network consistency and between-study heterogeneity. Given that individual participant data (IPD) are considered the gold standard in evidence synthesis, we explored statistical methods for IPD-NMA and investigated their potential advantages and limitations, compared with AD-NMA...
August 2, 2016: Statistical Methods in Medical Research
Michael J Joyner, Nigel Paneth, John P A Ioannidis
No abstract text is available yet for this article.
October 4, 2016: JAMA: the Journal of the American Medical Association
Amy E Kennedy, Muin J Khoury, John P A Ioannidis, Michelle Brotzman, Amy Miller, Crystal Lane, Gabriel Y Lai, Scott D Rogers, Chinonye Harvey, Joanne W Elena, Daniela Seminara
BACKGROUND: We report on the establishment of a web-based Cancer Epidemiology Descriptive Cohort Database (CEDCD). The CEDCD's goals are to enhance awareness of resources, facilitate interdisciplinary research collaborations, and support existing cohorts for the study of cancer-related outcomes. METHODS: Comprehensive descriptive data were collected from large cohorts established to study cancer as primary outcome using a newly developed questionnaire. These included an inventory of baseline and follow-up data, biospecimens, genomics, policies, and protocols...
October 2016: Cancer Epidemiology, Biomarkers & Prevention
John P A Ioannidis
Science has always relied on reproducibility to build confidence in experimental results. Now, the most comprehensive investigation ever done about the rate and predictors of reproducibility in social and cognitive sciences has found that regardless of the analytic method or criteria used, fewer than half of the original findings were successfully replicated. While a failure to reproduce does not necessarily mean the original report was incorrect, the results suggest that more rigorous methods are long overdue...
November 2015: Cerebrum: the Dana Forum on Brain Science
Joanna IntHout, John P A Ioannidis, Maroeska M Rovers, Jelle J Goeman
OBJECTIVES: Evaluating the variation in the strength of the effect across studies is a key feature of meta-analyses. This variability is reflected by measures like τ(2) or I(2), but their clinical interpretation is not straightforward. A prediction interval is less complicated: it presents the expected range of true effects in similar studies. We aimed to show the advantages of having the prediction interval routinely reported in meta-analyses. DESIGN: We show how the prediction interval can help understand the uncertainty about whether an intervention works or not...
2016: BMJ Open
Maria Elena Flacco, Lamberto Manzoli, Stefania Boccia, Anna Puggina, Annalisa Rosso, Carolina Marzuillo, Giacomo Scaioli, Maria Rosaria Gualano, Walter Ricciardi, Paolo Villari, John P A Ioannidis
OBJECTIVES: To evaluate the research agenda of registered randomized trials comparing generic and brand-name drugs in terms of who sponsors them, whether they are published promptly, and whether they find favorable results. METHODS: We included randomized trials comparing the safety or efficacy of brand-name vs generic medications that were registered in or other registries from January 1, 2000, through July 31, 2015. To identify published articles or results generated from such trials, we searched PubMed, Scopus, Google, and registry databases...
August 2016: Mayo Clinic Proceedings
Lars G Hemkens, Despina G Contopoulos-Ioannidis, John P A Ioannidis
BACKGROUND: Studies that use routinely collected health data (RCD studies) are advocated to complement evidence from randomized controlled trials (RCTs) for comparative effectiveness research and to inform health care decisions when RCTs would be unfeasible. We aimed to evaluate the current use of routinely collected health data to complement RCT evidence. METHODS: We searched PubMed for RCD studies published to 2010 that evaluated the comparative effectiveness of medical treatments on mortality using propensity scores...
April 2016: CMAJ Open
Shanil Ebrahim, Luis Montoya, Mostafa Kamal El Din, Zahra N Sohani, Arnav Agarwal, Sheena Bance, Juliann Saquib, Nazmus Saquib, John P A Ioannidis
OBJECTIVE: To assess the frequency and features of secondary publications of RCTs. STUDY DESIGN AND SETTING: For 191 RCTs published in high-impact journals in 2009, we searched for secondary publications co-authored by at least one same author of the primary trial publication. We evaluated the probability of having secondary publications, characteristics of the primary trial publication that predict having secondary publications, types of secondary analyses conducted, and statistically significance of those analyses...
July 4, 2016: Journal of Clinical Epidemiology
John P A Ioannidis, Richard Klavans, Kevin W Boyack
Many fields face an increasing prevalence of multi-authorship, and this poses challenges in assessing citation metrics. Here, we explore multiple citation indicators that address total impact (number of citations, Hirsch H index [H]), co-authorship adjustment (Schreiber Hm index [Hm]), and author order (total citations to papers as single; single or first; or single, first, or last author). We demonstrate the correlation patterns between these indicators across 84,116 scientists (those among the top 30,000 for impact in a single year [2013] in at least one of these indicators) and separately across 12 scientific fields...
July 2016: PLoS Biology
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