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Ioannidis, John

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Ioannidis

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Ioannidis, John
Author's Publications: search.filters.isAuthorOfPublication.aa65d77a-9379-4de7-ad8d-a7430165f40f

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    Exclusion of Elderly People from Randomized Clinical Trials of Drugs for Ischemic Heart Disease
    (Wiley-Blackwell, 2017) Bourgeois, Florence; Orenstein, Liat; Ballakur, Sarita; Mandl, Kenneth; Ioannidis, John
    Objectives To measure exclusion of elderly adults from randomized trials studying drug interventions for ischemic heart disease (IHD) and describe the characteristics of these trials. Design Cross-sectional analysis. Setting Interventional clinical trials studying a drug intervention for IHD that started in 2006 and after were identified in ClinicalTrials.gov. Data were extracted on study features, including age-based inclusion criteria. Data on participants and their age distribution were collected from trial publications, investigator inquiry, and result data in ClinicalTrials.gov. Participants Individuals aged 65 and older. Measurements Proportion of trials excluding individuals based on age, mean age of trial participants, and proportion of enrolled participants aged 65 and older and 75 and older. Results Of 839 identified trials, 446 (53%) explicitly excluded elderly adults. The most-frequent upper age limits were 80 (n = 164) and 75 (n = 114), with a median upper age limit of 80 (interquartile range 75–80). Trials with upper age limit exclusions tended to be smaller (median number of participants 100 vs 201, P < .001) and were more likely to be funded primarily by nonindustry sources (78.3% vs 70.0%, P = .006). The overall mean age of trial participants was 62.7 (mean maximum age 74). The estimated proportion of participants aged 65 and older was 42.5% and the estimated proportion aged 75 and older was 12.3%. Conclusion Despite the high burden of IHD in elderly adults, the majority of drug trials do not enroll participants reflective of age-related prevalence of the disease.
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    Selection and Presentation of Imaging Figures in the Medical Literature
    (Public Library of Science, 2010) Siontis, George C. M.; Patsopoulos, Nikolaos; Vlahos, Antonios P.; Ioannidis, John
    Background: Images are important for conveying information, but there is no empirical evidence on whether imaging figures are properly selected and presented in the published medical literature. We therefore evaluated the selection and presentation of radiological imaging figures in major medical journals. Methodology/Principal Findings: We analyzed articles published in 2005 in 12 major general and specialty medical journals that had radiological imaging figures. For each figure, we recorded information on selection, study population, provision of quantitative measurements, color scales and contrast use. Overall, 417 images from 212 articles were analyzed. Any comment/hint on image selection was made in 44 (11%) images (range 0–50% across the 12 journals) and another 37 (9%) (range 0–60%) showed both a normal and abnormal appearance. In 108 images (26%) (range 0–43%) it was unclear whether the image came from the presented study population. Eighty-three images (20%) (range 0–60%) had any quantitative or ordered categorical value on a measure of interest. Information on the distribution of the measure of interest in the study population was given in 59 cases. For 43 images (range 0–40%), a quantitative measurement was provided for the depicted case and the distribution of values in the study population was also available; in those 43 cases there was no over-representation of extreme than average cases (p = 0.37). Significance: The selection and presentation of images in the medical literature is often insufficiently documented; quantitative data are sparse and difficult to place in context.
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    Insights into the genetic architecture of osteoarthritis from stage 1 of the arcOGEN study
    (BMJ Group, 2010) Panoutsopoulou, K; Southam, L; Wrayner, N; Zhai, G; Beazley, C; Thorleifsson, G; Arden, N K; Chapman, K; Deloukas, P; McCaskie, A; Ollier, W E R; Ralston, S H; Spector, T D; Valdes, A M; Wallis, G A; Arden, E; Battley, K; Blackburn, H; Blanco, F J; Bumpstead, S; Cupples, L A; Day-Williams, A G; Dixon, K; Doherty, S A; Esko, T; Evangelou, E; Felson, D; Gomez-Reino, J J; Gwilliam, R; Halldorsson, B V; Hauksson, V B; Ingvarsson, T; Jonsdottir, I; Jonsson, H; Keen, R; Kerkhof, H J M; Kloppenburg, M G; Koller, N; Lakenberg, N; Lane, N E; Metspalu, A; Meulenbelt, I; Nevitt, M C; Parimi, N; Potter, S C; Rego-Perez, I; Riancho, J A; Sherburn, K; Slagboom, P E; Stefansson, K; Styrkarsdottir, U; Sumillera, M; Swift, D; Thorsteinsdottir, U; Tsezou, A; Uitterlinden, A G; van Meurs, J B J; Watkins, B; Zmuda, J M; Zeggini, E; Loughlin, J; Ioannidis, John; Elliot, K S; Carr, A; Doherty, M; Wilkinson, J M; Gonzalez, A; Gordon, A; Hofman, A; Hunt, S E; Lee, A T; Wheeler, M; Mitchell, S; Zhu, Y; O'Neill, F
    Objectives: The genetic aetiology of osteoarthritis has not yet been elucidated. To enable a well-powered genome-wide association study (GWAS) for osteoarthritis, the authors have formed the arcOGEN Consortium, a UK-wide collaborative effort aiming to scan genome-wide over 7500 osteoarthritis cases in a two-stage genome-wide association scan. Here the authors report the findings of the stage 1 interim analysis. Methods: The authors have performed a genome-wide association scan for knee and hip osteoarthritis in 3177 cases and 4894 population-based controls from the UK. Replication of promising signals was carried out in silico in five further scans (44 449 individuals), and de novo in 14 534 independent samples, all of European descent. Results: None of the association signals the authors identified reach genome-wide levels of statistical significance, therefore stressing the need for corroboration in sample sets of a larger size. Application of analytical approaches to examine the allelic architecture of disease to the stage 1 genome-wide association scan data suggests that osteoarthritis is a highly polygenic disease with multiple risk variants conferring small effects. Conclusions: Identifying loci conferring susceptibility to osteoarthritis will require large-scale sample sizes and well-defined phenotypes to minimise heterogeneity.
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    Fifty-Year Fate and Impact of General Medical Journals
    (Public Library of Science, 2010) Ioannidis, John; Belbasis, Lazaros; Evangelou, Evangelos
    Background: Influential medical journals shape medical science and practice and their prestige is usually appraised by citation impact metrics, such as the journal impact factor. However, how permanent are medical journals and how stable is their impact over time? Methods and Results: We evaluated what happened to general medical journals that were publishing papers half a century ago, in 1959. Data were retrieved from ISI Web of Science for citations and PubMed (Journals function) for journal history. Of 27 eligible journals publishing in 1959, 4 have stopped circulation (including two of the most prestigious journals in 1959) and another 7 changed name between 1959 and 2009. Only 6 of these 27 journals have been published continuously with their initial name since they started circulation. The citation impact of papers published in 1959 gives a very different picture from the current journal impact factor; the correlation between the two is non-significant and very close to zero. Only 13 of the 5,223 papers published in 1959 received at least 5 citations in 2009. Conclusions: Journals are more permanent entities than single papers, but they are also subject to major change and their relative prominence can change markedly over time.
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    Laboratory Mouse Models for the Human Genome-Wide Associations
    (Public Library of Science, 2010) Kitsios, Georgios D.; Tangri, Navdeep; Castaldi, Peter J.; Ioannidis, John
    The agnostic screening performed by genome-wide association studies (GWAS) has uncovered associations for previously unsuspected genes. Knowledge about the functional role of these genes is crucial and laboratory mouse models can provide such information. Here, we describe a systematic juxtaposition of human GWAS-discovered loci versus mouse models in order to appreciate the availability of mouse models data, to gain biological insights for the role of these genes and to explore the extent of concordance between these two lines of evidence. We perused publicly available data (NHGRI database for human associations and Mouse Genome Informatics database for mouse models) and employed two alternative approaches for cross-species comparisons, phenotype- and gene-centric. A total of 293 single gene-phenotype human associations (262 unique genes and 69 unique phenotypes) were evaluated. In the phenotype-centric approach, we identified all mouse models and related ortholog genes for the 51 human phenotypes with a comparable phenotype in mice. A total of 27 ortholog genes were found to be associated with the same phenotype in humans and mice, a concordance that was significantly larger than expected by chance (p<0.001). In the gene-centric approach, we were able to locate at least 1 knockout model for 60% of the 262 genes. The knockouts for 35% of these orthologs displayed pre- or post-natal lethality. For the remaining non-lethal orthologs, the same organ system was involved in mice and humans in 71% of the cases (p<0.001). Our project highlights the wealth of available information from mouse models for human GWAS, catalogues extensive information on plausible physiologic implications for many genes, provides hypothesis-generating findings for additional GWAS analyses and documents that the concordance between human and mouse genetic association is larger than expected by chance and can be informative.
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    Evaluation of Association of HNF1B Variants with Diverse Cancers: Collaborative Analysis of Data from 19 Genome-Wide Association Studies
    (Public Library of Science, 2010) Elliott, Katherine S.; Zeggini, Eleftheria; McCarthy, Mark I.; Gudmundsson, Julius; Sulem, Patrick; Stacey, Simon N.; Thorlacius, Steinunn; Amundadottir, Laufey; Grönberg, Henrik; Xu, Jianfeng; Gaborieau, Valerie; Eeles, Rosalind A.; Neal, David E.; Donovan, Jenny L.; Hamdy, Freddie C.; Muir, Kenneth; Hwang, Shih-Jen; Spitz, Margaret R.; Zanke, Brent; Carvajal-Carmona, Luis; Brown, Kevin M.; Hayward, Nicholas K.; Macgregor, Stuart; Tomlinson, Ian P. M.; Lemire, Mathieu; Amos, Christopher I.; Murabito, Joanne M.; Isaacs, William B.; Easton, Douglas F.; Brennan, Paul; Barkardottir, Rosa B.; Gudbjartsson, Daniel F.; Rafnar, Thorunn; Chanock, Stephen J.; Stefansson, Kari; Australian Melanoma Family Study Investigators; The PanScan Consortium; Hunter, David; Ioannidis, John
    Background: Genome-wide association studies have found type 2 diabetes-associated variants in the HNF1B gene to exhibit reciprocal associations with prostate cancer risk. We aimed to identify whether these variants may have an effect on cancer risk in general versus a specific effect on prostate cancer only. Methodology/Principal Findings: In a collaborative analysis, we collected data from GWAS of cancer phenotypes for the frequently reported variants of HNF1B, rs4430796 and rs7501939, which are in linkage disequilibrium (r2 = 0.76, HapMap CEU). Overall, the analysis included 16 datasets on rs4430796 with 19,640 cancer cases and 21,929 controls; and 21 datasets on rs7501939 with 26,923 cases and 49,085 controls. Malignancies other than prostate cancer included colorectal, breast, lung and pancreatic cancers, and melanoma. Meta-analysis showed large between-dataset heterogeneity that was driven by different effects in prostate cancer and other cancers. The per-T2D-risk-allele odds ratios (95% confidence intervals) for rs4430796 were 0.79 (0.76, 0.83)] per G allele for prostate cancer (p<10−15 for both); and 1.03 (0.99, 1.07) for all other cancers. Similarly for rs7501939 the per-T2D-risk-allele odds ratios (95% confidence intervals) were 0.80 (0.77, 0.83) per T allele for prostate cancer (p<10−15 for both); and 1.00 (0.97, 1.04) for all other cancers. No malignancy other than prostate cancer had a nominally statistically significant association. Conclusions/Significance: The examined HNF1B variants have a highly specific effect on prostate cancer risk with no apparent association with any of the other studied cancer types.