Making Prospective Registration of Observational Research a Reality

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Science Translational Medicine  19 Feb 2014:
Vol. 6, Issue 224, pp. 224cm1
DOI: 10.1126/scitranslmed.3007513



  • Table 1 Rationale for registration of CTs.

    The Ottawa statement is provided in (21). All rationales listed are applicable to OSs.

    • Respect the investigator-participant covenant to contribute to biomedical knowledge by making trial methods and results public
    • Provide global open access to information
    • Reduce unnecessary duplication of invested research resources through awareness of existing trials
    • Assure accountability with regard to global standards for ethical research
    • Enable monitoring of adherence to ethical principles and process
    • Increase the reliability and availability of evidence on which health care decisions are based
    • Improve trial participation
    • Increase opportunities for collaboration
    • Ensure transparency of trial design and methods
    • Provide open review of protocols to improve trial quality and refine methods
    • Provide means for identification and prevention of biased underreporting or over-reporting of research
    • Accelerate knowledge creation
  • Table 2

    Scientific, ethical, and moral reasons to support prospective registration of CTs [WHO, (33)].

    1. There is a need to ensure that decisions about health care are informed by all of the available evidence.*
    2. It is difficult to make informed decisions if publication bias and selective reporting are present.*
    3. The Declaration of Helsinki states that “every trial must be registered in a publicly accessible database before recruitment of the first subject.”
    4. Improving awareness of similar or identical trials will make it possible for researchers and funding agencies to avoid unnecessary duplication.*
    5. Describing clinical trials in progress can make it easier to identify gaps in clinical trials research.*
    6. Making researchers and potential participants aware of recruiting trials may facilitate recruitment.*
    7. Enabling researchers and health-care practitioners to identify trials in which they may have an interest could result in more effective collaboration among researchers. The type of collaboration may include prospective meta-analysis.*
    8. Registries checking data as part of the registration process may lead to improvements in the quality of clinical trials by making it possible to identify potential problems (such as problematic randomization methods) early in the research process.

    *Reasons applicable to OSs. This wording has been broadened in the 2013 revision of the Declaration of Helsinki (30): “Every research study involving human subjects must be registered in a publicly accessible database before recruitment of the first subject.”

    • Table 3

      Sharing OSs with the scientific community. Access could be extended to a lay audience; however, the nature of the information will be most useful to scientists. Modified from Khoury et al. (26).

      Information type Comments
      Data set registrationShould be feasible to achieve in large scale; each data set registers the variables that it has collected and their definitions; this would allow knowing how many studies with how many participants who have measured variables or markers of interest, instead of guessing what data are available on that marker beyond what has been published
      Availability of detailed dataIndividual-level (raw) data are made available; this practice may be subject to policy/consent/privacy constraints for past studies and their data; easier to anticipate and encourage in the design of future studies
      Availability of data, protocols, and analyses codesOptimal ability to evaluate the reproducibility of analyses, to maximize the integration of information across diverse studies, and to allow improvements on future studies based on exact knowledge of what was done in previous studies
      Live streaming of analysesInvestigators not only post all their data and protocols online, but analyses are done and shown in real time to the wider community as they happen. Live streaming can be coupled with crowd sourcing of analyses across large communities of analysts

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