Professional Education

  • Doctor of Philosophy, Universite Claude-Bernard (Lyon I) (2017)

Stanford Advisors

All Publications

  • Calibrating the Scientific Ecosystem Through Meta-Research Annual Review of Statistics and Its Application Tom, H. E., Stylianos, S., Janiaud, P., Danchev, V., Crüwell, S., Goodman, S. N., Ioannidis, J. P. 2020; 7
  • Do patients with cystic fibrosis participating in clinical trials demonstrate placebo response? A meta-analysis. Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society Coton, J., Le, H., Veuillet, V., Janiaud, P., Cucherat, M., Kassai-Koupai, B., Gueyffier, F., Reix, P. 2019


    BACKGROUND: Patients' and families' expectation that a cure for cystic fibrosis (CF) will be found is high. In other debilitating conditions, high expectation has been shown to drive a strong placebo response (PR). Therefore, our goal was to evaluate PR on objective continuous outcomes (FEV1, BMI) and the CF Questionnaire Revised-Respiratory Domain (CFQR-RD) monitored during randomised clinical trials (RCTs) for CF.METHODS: We conducted a meta-analysis after a systematic review of the literature carried out to identify RCTs with FEV1, CFQR-RD and BMI as outcome measures. The standardised mean difference (SMD) was calculated to estimate the PR. A meta-regression analysis was conducted to assess other contributing factors on PR such as study design, trial duration, patient age and disease severity.RESULTS: Out of 289 RCTs found in the search, we identified 61 articles (published from 1987 to 2017) with respectively 59, 17 and 9 reporting FEV1, CFQR-RD and BMI at the start and at the end of the RCTs. No significant PR was found on FEV1 or CFQR-RD. However, a small but significant PR was found on BMI SMD, 0.09 (95% CI (0.01; 0.17); p = 0.03).CONCLUSION: The PR seems higher when measuring BMI. However, it is not clear whether this improvement can be explained by a PR alone.

    View details for PubMedID 30772244

  • New clinical trial designs in the era of precision medicine: An overview of definitions, strengths, weaknesses, and current use in oncology. Cancer treatment reviews Janiaud, P., Serghiou, S., Ioannidis, J. P. 2018; 73: 20–30


    With expanding knowledge in tumor biology and biomarkers, oncology therapies are increasingly moving away from the "one-size-fits-all" rationale onto biomarker-driven therapies tailored according to patient-specific characteristics, most commonly the tumor's molecular profile. The advent of precision medicine in oncology has been accompanied by the introduction of novel clinical trial designs that aim to identify biomarker-matched subgroups of patients that will benefit the most from targeted therapies. This innovation comes with the promise of answering more treatment questions, more efficiently and in less time. In this article, we give an overview of the different biomarker-based designs, comparing the features of enrichment, randomize-all, umbrella, and basket trials, and highlighting their advantages and disadvantages. We focus more on the novel designs known as master protocols, which include umbrella and basket trials. We have also conducted a search in for registered oncology-related protocols of ongoing or completed trials labeled as umbrella or basket trials for solid tumors; we also included additional relevant trials retrieved from other reviews. We present and discuss the key features of the 30 eligible basket trials and 27 eligible umbrella trials. Only a minority of them are randomized (2 and 9, respectively), including three trials with adaptive randomization. Five of these trials have been completed as of July 2018. Precision medicine trial designs fuel new hopes for identifying best treatments, but there is also the potential for hype. The benefits and challenges associated with their use will need continued monitoring.

    View details for PubMedID 30572165

  • Correction to: Industry-funded versus non-profit-funded critical care research: a meta-epidemiological overview. Intensive care medicine Janiaud, P., Cristea, I., Ioannidis, J. P. 2018


    The original article can be found online.

    View details for PubMedID 30406805

  • Industry-funded versus non-profit-funded critical care research: a meta-epidemiological overview. Intensive care medicine Janiaud, P., Cristea, I., Ioannidis, J. P. 2018


    PURPOSE: To study the landscape of funding in intensive care research and assess whether the reported outcomes of industry-funded randomized controlled trials (RCTs) are more favorable.METHODS: We systematically assembled meta-analyses evaluating any type of intervention in the critical care setting and reporting the source of funding for each included RCT. Furthermore, when the intervention was a drug or biologic, we searched also the original RCT articles, when their funding information was unavailable in the meta-analysis. We then qualitatively summarized the sources of funding. For binary outcomes, separate summary odds ratios were calculated for trials with and without industry funding. We then calculated the ratio of odds ratios (RORs) and the summary ROR (sROR) across topics. ROR<1 implies that the experimental intervention is relatively more favorable in trials with industry funding compared with trials without industry funding. For RCTs included in the ROR analysis, we also examined the conclusions of their abstract.RESULTS: Across 67 topics with 568 RCTs, 88 were funded by industry and another 73 had both industry and non-profit funding. Across 33 topics with binary outcomes, the sROR was 1.10 [95% CI (0.96-1.26), I2=1%]. Conclusions were not significantly more commonly unfavorable for the experimental arm interventions in industry-funded trials (21.3%) compared with trials without industry funding (18.2%).CONCLUSION: Industry-funded RCTs are the minority in intensive care. We found no evidence that industry-funded trials in intensive care yield more favorable results or are less likely to reach unfavorable conclusions.

    View details for PubMedID 30151688

  • Assessment of Pragmatism in Recently Published Randomized Clinical Trials. JAMA internal medicine Janiaud, P., Dal-Re, R., Ioannidis, J. P. 2018

    View details for PubMedID 30039169

  • Real-world evidence: How pragmatic are randomized controlled trials labeled as pragmatic? BMC MEDICINE Dal-Re, R., Janiaud, P., Ioannidis, J. A. 2018; 16: 49


    Pragmatic randomized controlled trials (RCTs) mimic usual clinical practice and they are critical to inform decision-making by patients, clinicians and policy-makers in real-world settings. Pragmatic RCTs assess effectiveness of available medicines, while explanatory RCTs assess efficacy of investigational medicines. Explanatory and pragmatic are the extremes of a continuum. This debate article seeks to evaluate and provide recommendation on how to characterize pragmatic RCTs in light of the current landscape of RCTs. It is supported by findings from a PubMed search conducted in August 2017, which retrieved 615 RCTs self-labeled in their titles as "pragmatic" or "naturalistic". We focused on 89 of these trials that assessed medicines (drugs or biologics).36% of these 89 trials were placebo-controlled, performed before licensing of the medicine, or done in a single-center. In our opinion, such RCTs overtly deviate from usual care and pragmatism. It follows, that the use of the term 'pragmatic' to describe them, conveys a misleading message to patients and clinicians. Furthermore, many other trials among the 615 coined as 'pragmatic' and assessing other types of intervention are plausibly not very pragmatic; however, this is impossible for a reader to tell without access to the full protocol and insider knowledge of the trial conduct. The degree of pragmatism should be evaluated by the trial investigators themselves using the PRECIS-2 tool, a tool that comprises 9 domains, each scored from 1 (very explanatory) to 5 (very pragmatic).To allow for a more appropriate characterization of the degree of pragmatism in clinical research, submissions of RCTs to funders, research ethics committees and to peer-reviewed journals should include a PRECIS-2 tool assessment done by the trial investigators. Clarity and accuracy on the extent to which a RCT is pragmatic will help understand how much it is relevant to real-world practice.

    View details for PubMedID 29615035

  • Data sharing and reanalysis of randomized controlled trials in leading biomedical journals with a full data sharing policy: survey of studies published in The BMJ and PLOS Medicine BMJ-BRITISH MEDICAL JOURNAL Naudet, F., Sakarovitch, C., Janiaud, P., Cristea, I., Fanelli, D., Moher, D., Ioannidis, J. A. 2018; 360: 1–11


    To explore the effectiveness of data sharing by randomized controlled trials (RCTs) in journals with a full data sharing policy and to describe potential difficulties encountered in the process of performing reanalyses of the primary outcomes.Survey of published RCTs.PubMed/Medline.RCTs that had been submitted and published by The BMJ and PLOS Medicine subsequent to the adoption of data sharing policies by these journals.The primary outcome was data availability, defined as the eventual receipt of complete data with clear labelling. Primary outcomes were reanalyzed to assess to what extent studies were reproduced. Difficulties encountered were described.37 RCTs (21 from The BMJ and 16 from PLOS Medicine) published between 2013 and 2016 met the eligibility criteria. 17/37 (46%, 95% confidence interval 30% to 62%) satisfied the definition of data availability and 14 of the 17 (82%, 59% to 94%) were fully reproduced on all their primary outcomes. Of the remaining RCTs, errors were identified in two but reached similar conclusions and one paper did not provide enough information in the Methods section to reproduce the analyses. Difficulties identified included problems in contacting corresponding authors and lack of resources on their behalf in preparing the datasets. In addition, there was a range of different data sharing practices across study groups.Data availability was not optimal in two journals with a strong policy for data sharing. When investigators shared data, most reanalyses largely reproduced the original results. Data sharing practices need to become more widespread and streamlined to allow meaningful reanalyses and reuse of data.Open Science Framework

    View details for PubMedID 29440066