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  1. Article ; Online: Inverse publication reporting bias favouring null, negative results.

    Ioannidis, John P A

    BMJ evidence-based medicine

    2024  Volume 29, Issue 1, Page(s) 6–9

    MeSH term(s) Humans ; Negative Results ; Publication Bias ; Publishing
    Language English
    Publishing date 2024-01-19
    Publishing country England
    Document type Journal Article
    ISSN 2515-4478
    ISSN (online) 2515-4478
    DOI 10.1136/bmjebm-2023-112292
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: The Subjective Interpretation of the Medical Evidence.

    Bauchner, Howard / Ioannidis, John P A

    JAMA health forum

    2024  Volume 5, Issue 3, Page(s) e240213

    MeSH term(s) Evidence-Based Medicine
    Language English
    Publishing date 2024-03-01
    Publishing country United States
    Document type Journal Article
    ISSN 2689-0186
    ISSN (online) 2689-0186
    DOI 10.1001/jamahealthforum.2024.0213
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Prolific non-research authors in high impact scientific journals: meta-research study.

    Ioannidis, John P A

    Scientometrics

    2023  Volume 128, Issue 5, Page(s) 3171–3184

    Abstract: Journalistic papers published in high impact scientific journals can be very influential, especially in hot fields. This meta-research analysis aimed to evaluate the publication profiles, impact, and disclosures of conflicts of interest of non-research ... ...

    Abstract Journalistic papers published in high impact scientific journals can be very influential, especially in hot fields. This meta-research analysis aimed to evaluate the publication profiles, impact, and disclosures of conflicts of interest of non-research authors who had published > 200 Scopus-indexed papers in Nature, Science, PNAS, Cell, BMJ, Lancet, JAMA or New England Journal of Medicine. 154 prolific authors were identified, 148 of whom had published 67,825 papers in their main affiliated journal in a non-researcher capacity. Nature, Science, and BMJ have the lion's share of such authors. Scopus characterized 35% of the journalistic publications as full articles and another 11% as short surveys. 264 papers had received more than 100 citations. 40/41 most-cited papers in 2020-2022 were on hot COVID-19 topics. Of 25 massively prolific authors with > 700 publications in one of these journals, many were highly-cited (median citations 2273), almost all had published little or nothing in the Scopus-indexed literature other than in their main affiliated journal, and their influential writing covered diverse hot topics over the years. Of the 25, only 3 had a PhD degree in any subject matter, and 7 had a Master's degree in journalism. Only the BMJ offered conflicts of interest disclosures for prolific science writers in its website, but even then only 2 of the 25 massively prolific authors disclosed potential conflicts with some specificity. The practice of assigning so much power to non-researchers in shaping scientific discourse should be further debated and disclosures of potential conflicts of interest should be emphasized.
    Language English
    Publishing date 2023-04-12
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 435652-4
    ISSN 0138-9130
    ISSN 0138-9130
    DOI 10.1007/s11192-023-04687-5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Factors influencing estimated effectiveness of COVID-19 vaccines in non-randomised studies.

    Ioannidis, John P A

    BMJ evidence-based medicine

    2022  Volume 27, Issue 6, Page(s) 324–329

    Abstract: Non-randomised studies assessing COVID-19 vaccine effectiveness need to consider multiple factors that may generate spurious estimates due to bias or genuinely modify effectiveness. These include pre-existing immunity, vaccination misclassification, ... ...

    Abstract Non-randomised studies assessing COVID-19 vaccine effectiveness need to consider multiple factors that may generate spurious estimates due to bias or genuinely modify effectiveness. These include pre-existing immunity, vaccination misclassification, exposure differences, testing, disease risk factor confounding, hospital admission decision, treatment use differences, and death attribution. It is useful to separate whether the impact of each factor admission decision, treatment use differences, and death attribution. Steps and measures to consider for improving vaccine effectiveness estimation include registration of studies and of analysis plans; sharing of raw data and code; background collection of reliable information; blinded assessment of outcomes, e.g. death causes; using maximal/best information in properly-matched studies, multivariable analyses, propensity analyses, and other models; performing randomised trials, whenever possible, for suitable questions, e.g. booster doses or comparative effectiveness of different vaccination strategies; living meta-analyses of vaccine effectiveness; better communication with both relative and absolute metrics of risk reduction and presentation of uncertainty; and avoidance of exaggeration in communicating results to the general public.
    MeSH term(s) Humans ; COVID-19 Vaccines/therapeutic use ; COVID-19/epidemiology ; COVID-19/prevention & control ; Hospitalization ; Bias ; Uncertainty
    Chemical Substances COVID-19 Vaccines
    Language English
    Publishing date 2022-03-25
    Publishing country England
    Document type Journal Article
    ISSN 2515-4478
    ISSN (online) 2515-4478
    DOI 10.1136/bmjebm-2021-111901
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: Pre-registration of mathematical models.

    Ioannidis, John P A

    Mathematical biosciences

    2022  Volume 345, Page(s) 108782

    Abstract: Pre-registration is a research practice where a protocol is deposited in a repository before a scientific project is performed. The protocol may be publicly visible immediately upon deposition or it may remain hidden until the work is completed/published. ...

    Abstract Pre-registration is a research practice where a protocol is deposited in a repository before a scientific project is performed. The protocol may be publicly visible immediately upon deposition or it may remain hidden until the work is completed/published. It may include the analysis plan, outcomes, and/or information about how evaluation of performance (e.g. forecasting ability) will be made, Pre-registration aims to enhance the trust one can put on scientific work. Deviations from the original plan, may still often be desirable, but pre-registration makes them transparent. While pre-registration has been advocated and used to variable extent in diverse types of research, there has been relatively little attention given to the possibility of pre-registration for mathematical modeling studies. Feasibility of pre-registration depends on the type of modeling and the ability to pre-specify processes and outcomes. In some types of modeling, in particular those that involve forecasting or other outcomes that can be appraised in the future, trust in model performance would be enhanced through pre-registration. Pre-registration can also be seen as a component of a larger suite of research practices that aim to improve documentation, transparency, and sharing-eventually allowing better reproducibility of the research work. The current commentary discusses the evolving landscape of the concept of pre-registration as it relates to different mathematical modeling activities, the potential advantages and disadvantages, feasibility issues, and realistic goals.
    MeSH term(s) Models, Theoretical ; Reproducibility of Results
    Language English
    Publishing date 2022-01-25
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 1126-5
    ISSN 1879-3134 ; 0025-5564
    ISSN (online) 1879-3134
    ISSN 0025-5564
    DOI 10.1016/j.mbs.2022.108782
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1534: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  6. Article ; Online: High-cited favorable studies for COVID-19 treatments ineffective in large trials.

    Ioannidis, John P A

    Journal of clinical epidemiology

    2022  Volume 148, Page(s) 1–9

    Abstract: Objectives: To evaluate for coronavirus disease 2019 treatments without benefits in subsequent large randomized controlled trials (RCTs) how many of their most-cited clinical studies had declared favorable results.: Study design and setting: Scopus ... ...

    Abstract Objectives: To evaluate for coronavirus disease 2019 treatments without benefits in subsequent large randomized controlled trials (RCTs) how many of their most-cited clinical studies had declared favorable results.
    Study design and setting: Scopus searches (December 23, 2021) identified articles on lopinavir-ritonavir, hydroxychloroquine, azithromycin, remdesivir, convalescent plasma, colchicine, or interferon (index interventions) that represented clinical trials and had >150 citations. Their conclusions were correlated with study design features. The 10 most recent citations for the most-cited article on each index intervention were examined on whether they were critical to the highly cited study. Altmetric scores were also obtained.
    Results: Forty eligible articles of clinical studies had received >150 citations. Twenty of forty (50%) had favorable conclusions and four were equivocal. Highly cited articles with favorable conclusions were rarely RCTs (3/20), although those without favorable conclusions were mostly RCTs (15/20, P = 0.0003). Only one RCT with favorable conclusions had >160 patients. Citation counts correlated strongly with Altmetric scores, especially news items. Only nine (15%) of 60 recent citations to the most highly cited studies with favorable or equivocal conclusions were critical.
    Conclusion: Many clinical studies with favorable conclusions for largely ineffective coronavirus disease 2019 treatments are uncritically heavily cited and disseminated. Early observational studies and small randomized trials may cause spurious claims of effectiveness that get perpetuated.
    MeSH term(s) Humans ; COVID-19/drug therapy ; Lopinavir/therapeutic use ; Ritonavir/therapeutic use ; Hydroxychloroquine/therapeutic use ; Azithromycin ; Interferons ; Colchicine
    Chemical Substances Lopinavir (2494G1JF75) ; Ritonavir (O3J8G9O825) ; Hydroxychloroquine (4QWG6N8QKH) ; Azithromycin (83905-01-5) ; Interferons (9008-11-1) ; Colchicine (SML2Y3J35T)
    Language English
    Publishing date 2022-04-06
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 639306-8
    ISSN 1878-5921 ; 0895-4356
    ISSN (online) 1878-5921
    ISSN 0895-4356
    DOI 10.1016/j.jclinepi.2022.04.001
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    In stock of ZB MED Cologne/Königswinter

    Uh III Zs.206: Show issues Location:
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  7. Article ; Online: Systematic reviews for basic scientists: a different beast.

    Ioannidis, John P A

    Physiological reviews

    2022  Volume 103, Issue 1, Page(s) 1–5

    Language English
    Publishing date 2022-09-01
    Publishing country United States
    Document type Editorial
    ZDB-ID 209902-0
    ISSN 1522-1210 ; 0031-9333
    ISSN (online) 1522-1210
    ISSN 0031-9333
    DOI 10.1152/physrev.00028.2022
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    In stock of ZB MED Cologne/Königswinter

    Uc I Zs.166: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  8. Article ; Online: Estimating conditional vaccine effectiveness.

    Ioannidis, John P A

    European journal of epidemiology

    2022  Volume 37, Issue 9, Page(s) 885–890

    Abstract: Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness ... ...

    Abstract Vaccine effectiveness for COVID-19 is typically estimated for different outcomes that often are hierarchical in severity (e.g. any documented infection, symptomatic infection, hospitalization, death) and subsets of each other. Conditional effectiveness for a more severe outcome conditional on a less severe outcome is the protection offered against the severe outcome (e.g. death) among those who already sustained the less severe outcome (e.g. documented infection). The concept applies also to the protection offered by previous infection rather than vaccination. Formulas and a nomogram are provided here for calculating conditional effectiveness. Illustrative examples are presented from recent vaccine effectiveness studies, including situations where effectiveness for different outcomes changed at different pace over time. E(death | documented infection) is the percent decrease in the case fatality rate and E(death | infection) is the percent decrease in the infection fatality rate (IFR). Conditional effectiveness depends on many factors and should not be misinterpreted as a causal effect estimate. However, it may be used for better personalized communication of the benefits of vaccination, considering also IFR and epidemic activity in public health decision-making and communication.
    MeSH term(s) COVID-19/epidemiology ; COVID-19/prevention & control ; Epidemics ; Hospitalization ; Humans ; Vaccination ; Vaccine Efficacy
    Language English
    Publishing date 2022-09-26
    Publishing country Netherlands
    Document type Journal Article
    ZDB-ID 632614-6
    ISSN 1573-7284 ; 0393-2990
    ISSN (online) 1573-7284
    ISSN 0393-2990
    DOI 10.1007/s10654-022-00911-3
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 2090: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  9. Article ; Online: Science with or without statistics: Discover-generalize-replicate? Discover-replicate-generalize?

    Ioannidis, John P A

    The Behavioral and brain sciences

    2022  Volume 45, Page(s) e23

    Abstract: Overstated generalizability (external validity) is common in research. It may coexist with inflation of the magnitude and statistical support for effects and dismissal of internal validity problems. Generalizability may be secured before attempting ... ...

    Abstract Overstated generalizability (external validity) is common in research. It may coexist with inflation of the magnitude and statistical support for effects and dismissal of internal validity problems. Generalizability may be secured before attempting replication of proposed discoveries or replication may precede efforts to generalize. These opposite approaches may decrease or increase, respectively, the use of inferential statistics with advantages and disadvantages.
    MeSH term(s) Humans ; Research Design
    Language English
    Publishing date 2022-02-10
    Publishing country England
    Document type Journal Article ; Comment
    ZDB-ID 423721-3
    ISSN 1469-1825 ; 0140-525X
    ISSN (online) 1469-1825
    ISSN 0140-525X
    DOI 10.1017/S0140525X21000054
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    In stock of ZB MED Cologne/Königswinter

    Zs.A 1470: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  10. Article ; Online: Reproducibility: Has Cancer Biology Failed beyond Repair?

    Ioannidis, John P A

    Clinical chemistry

    2022  Volume 68, Issue 8, Page(s) 1005–1007

    MeSH term(s) Biology ; Humans ; Neoplasms ; Reproducibility of Results
    Language English
    Publishing date 2022-03-05
    Publishing country England
    Document type Journal Article
    ZDB-ID 80102-1
    ISSN 1530-8561 ; 0009-9147
    ISSN (online) 1530-8561
    ISSN 0009-9147
    DOI 10.1093/clinchem/hvac030
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    In stock of ZB MED Cologne/Königswinter

    Ud II Zs.171: Show issues Location:
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