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What level of detail is necessary in describing a clinical study?

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About the Author
Proxima CRO Team
Isabella Schmitt, RAC
Director of Regulatory Affairs
Ms. Schmitt has also served in additional regulatory affairs and clinical research roles in which she contributed to multiple regulatory submissions and clinical affairs projects across a wide range of indications.

Ordinarily, applicants should include more detail when:

  • The study responses measured are of critical health importance. In most cases, such responses would be direct measures of a meaningful clinical outcome (e.g. mortality, stroke, acute myocardial infarction rates, fracture rates, symptom alleviation, or functional improvement), but could also include effects on important surrogate endpoints (e.g. cholesterol or hemoglobin A1c).
  • The study results demonstrate that a new agent offers a clear advantage over existing therapy.
  • The study results represent a significant advance in the treatment of a disease or condition, or provide important information about a drug’s activities relative to its therapeutic class.
  • The study enrolled a very specific population or used a very specific concomitant regimen, and the results may not be applicable to other populations.
  • The study results are not what would be expected for that drug class and indication — for example, when the study results demonstrate a particularly marginal response or a response for which the clinical meaning or implications are unclear.
  • The study uses an unfamiliar endpoint (e.g. a novel surrogate endpoint), or there are important limitations and uncertainties associated with an endpoint.

Applicants should include less detail when:

  • The new drug appears to have effects that are typical of its class.
  • The magnitude of the effect on clinical endpoints measured in the study is not readily translatable into effects in clinical practice. For example, exercise testing in a study of heart failure can demonstrate effectiveness, but does not translate to a quantifiable clinical outcome. Similarly, changes in HAM-D scores can be used to demonstrate effectiveness of an antidepressant, but the results for a given study are population and probably site-specific, and thus, do not necessarily translate to a numerically similar outcome in clinical practice.

In these cases, it could be useful to describe the study in general terms (e.g. population, duration, endpoints measured, and qualitative outcome) without providing detailed results.

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