When ignorance is bliss: Intentional agnosticism in drug approval

Valentyn Litvin1

  • 1Department of Economics, Northwestern University, Evanston, Illinois.

Health Economics
|December 10, 2019
PubMed

Insights

Public health agencies often exclude patient populations from drug trials, leading to approvals based on limited data. This study explores how ambiguity in prescription rates may encourage this exclusion, even without cost or necessity concerns.

Area of Science:

  • Health policy
  • Pharmaceutical regulation
  • Clinical trial design

Background:

  • Developed nations' health agencies rely on randomized controlled trials (RCTs) for drug approval.
  • RCTs frequently exclude diverse patient populations, leading to drug approvals based on limited treatment response data.
  • Some agencies have not mandated broader inclusion in trials, remaining uninformed about specific populations' drug responses.

Purpose of the Study:

  • To explore the decision-making process of health agencies regarding the exclusion of populations from drug approval trials.
  • To introduce a novel mechanism explaining intentional agency agnosticism towards specific populations' treatment effects.
  • To investigate how prescription rate ambiguity influences population exclusion in drug trials.

Main Methods:

  • Introduction of a theoretical mechanism for health agency agnosticism in drug approval.
  • Analysis of how ambiguity in on-label and off-label prescription rates impacts trial inclusion decisions.
  • Exploration of factors beyond trial necessity and cost that may drive population exclusion.

Main Results:

  • A novel mechanism is presented for health agencies intentionally remaining agnostic about certain populations' drug responses.
  • Ambiguity surrounding on-label and off-label prescription rates can incentivize the exclusion of populations from drug trials.
  • This exclusion can occur even when trial necessity and cost are not primary concerns.

Conclusions:

  • Health agencies may opt for intentional ignorance regarding specific populations' drug efficacy.
  • Uncertainty in prescription data can be a driving factor for excluding populations in drug approval processes.
  • The findings highlight a potential systemic issue in drug approval that may not be driven by traditional cost or necessity factors.

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