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Registration and multiple outcome testing in the HEALing communities study.

Dennis M Gorman1, Ben G Fitzpatrick2

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Summary
This summary is machine-generated.

The HEALing Communities Study (HCS) reported a null result for its primary opioid overdose outcome. Subsequent analyses of additional outcomes may be subject to statistical errors due to uncorrected multiplicity.

Keywords:
False discovery rateFamilywise error rateHEALing Communities StudyMultiple outcome testingMultiplicityOpioid and drug overdoseType I error

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Area of Science:

  • Public Health
  • Clinical Trials
  • Biostatistics

Background:

  • The HEALing Communities Study (HCS) is a randomized control trial investigating interventions for opioid overdose.
  • The study initially registered one primary opioid overdose outcome.
  • Additional outcomes and sub-measures were introduced post-commencement of data collection.

Purpose of the Study:

  • To critically evaluate the statistical reporting practices of the HEALing Communities Study.
  • To assess the potential impact of uncorrected multiplicity on study conclusions regarding opioid overdose interventions.
  • To propose improvements for reporting clinical trial results, particularly concerning multiple outcome measures.

Main Methods:

  • Review of published protocols and findings from the HEALing Communities Study.
  • Analysis of the introduction of multiple outcome measures after study initiation.
  • Assessment of statistical testing procedures, focusing on the need for multiplicity correction.

Main Results:

  • The HCS reported a null finding for its primary, registered outcome.
  • Numerous additional outcomes were analyzed, with some reporting statistically significant results.
  • Multiplicity correction was not applied to these secondary and exploratory outcomes, increasing the risk of Type I errors.

Conclusions:

  • Conclusions regarding the HCS intervention's effectiveness based on uncorrected secondary outcomes are likely unreliable due to potential Type I errors.
  • Journal peer review is a critical juncture for addressing issues of multiplicity and ensuring accurate interpretation of clinical trial data.
  • Recommendations include limiting causal inferences from exploratory analyses and requiring multiplicity corrections or clear distinctions for P-values.