Evidence map›Paper›PMID 35880996›Full record

ArticleStatistical communications in infectious diseases2021

Confidence limits for the averted infections ratio estimated via the counterfactual placebo incidence rate.

David T Dunn, Oliver T Stirrup, David V Glidden

Abstract read
In one paragraph

Article in Statistical communications in infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Sample size estimation for the averted events ratio.Clinical trials (London, England) · 2026
    Article
  2. Article
  3. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

David T DunnInstitute for Global Health, University College London, London, UK.ORCID https://orcid.org/0000-0003-1836-4446
Oliver T StirrupInstitute for Global Health, University College London, London, UK.
David V GliddenDepartment of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA.

Funding

Statistical methods for clinical trials of novel PrEP agentsR01AI143357 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI GLIDDEN, DAVID V. · 2018 to 2021
$483k
NIAID NIH HHS R01 AI143357
6 · The paper itself

Abstract

Objectives: The averted infections ratio (AIR) is a novel measure for quantifying the preservation-of-effect in active-control non-inferiority clinical trials with a time-to-event outcome. In the main formulation, the AIR requires an estimate of the counterfactual placebo incidence rate. We describe two approaches for calculating confidence limits for the AIR given a point estimate of this parameter, a closed-form solution based on a Taylor series expansion (delta method) and an iterative method based on the profile-likelihood. Methods: For each approach, exact coverage probabilities for the lower and upper confidence limits were computed over a grid of values of (1) the true value of the AIR (2) the expected number of counterfactual events (3) the effectiveness of the active-control treatment. Results: Focussing on the lower confidence limit, which determines whether non-inferiority can be declared, the coverage achieved by the delta method is either less than or greater than the nominal coverage, depending on the true value of the AIR. In contrast, the coverage achieved by the profile-likelihood method is consistently accurate. Conclusions: The profile-likelihood method is preferred because of better coverage properties, but the simpler delta method is valid when the experimental treatment is no less effective than the control treatment. A complementary Bayesian approach, which can be applied when the counterfactual incidence rate can be represented as a prior distribution, is also outlined.

Indexed as

active-control trialaverted infectionsconfidence limitsnon-inferiority

Identifiers

PMID35880996
PMCPMC9204757

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.