Evidence map›Paper›PMID 25732246›Full record

ArticleThe AAPS journal2015

Pilot and Repeat Trials as Development Tools Associated with Demonstration of Bioequivalence.

Anders Fuglsang

Abstract read
In one paragraph

Article in The AAPS journal, 2015. 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. Unveiling the Potential of CPharmaceutics · 2024
    Article
  2. Predictive Potential of CPharmaceutics · 2023
    Article
  3. Article
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

1 author.

Anders Fuglsang, Hiort Lorenzens Vej 6c st.tv., 6100, Haderslev, Denmark, a.fuglsang@ymail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this work is to use simulated trials to study how pilot trials can be implemented in relation to bioequivalence testing, and how the use of the information obtained at the pilot stage can influence the overall chance of showing bioequivalence (power) or the chance of approving a truly bioinequivalent product (type I error). The work also covers the use of repeat pivotal trials since the difference between a pilot trial followed by a pivotal trial and a pivotal trial followed by a repeat trial is mainly a question of whether a conclusion of bioequivalence can be allowed after the first trial. Repeating a pivotal trial after a failed trial involves dual or serial testing of the bioequivalence null hypothesis, and the paper illustrates how this may inflate the type I error up to almost 10%. Hence, it is questioned if such practice is in the interest of patients. Tables for power, type I error, and sample sizes are provided for a total of six different decision trees which allow the developer to use either the observed geometric mean ratio (GMR) from the first or trial or to assume that the GMR is 0.95. In cases when the true GMR can be controlled so as not to deviate more from unity than 0.95, sequential design methods ad modum Potvin may be superior to pilot trials. The tables provide a quantitative basis for choosing between sequential designs and pivotal trials preceded by pilot trials.

Indexed as

PharmacokineticsResearch DesignClinical Trials as TopicComputer SimulationDecision TreesHumansPilot ProjectsSample SizeTherapeutic Equivalency

Identifiers

PMID25732246
PMCPMC4406973

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.