Evidence map›Paper›PMID 33037534›Full record

ArticleJournal of pharmacokinetics and pharmacodynamics2021

The application of extreme value theory to pharmacometrics.

Peter L Bonate

Abstract read
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In one paragraph

Article in Journal of pharmacokinetics and pharmacodynamics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Peter L BonateAstellas, 1 Astellas Way, Northbrook, IL, 60062, USA. peter.bonate@astellas.com.ORCID http://orcid.org/0000-0002-3753-2831

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical trials are often analyzed by examining the means, e.g., what is the mean treatment effect or what is the mean treatment difference, but there are times when analysis of the maximums (or minimums) are of interest. For instance, what is the highest heart rate that could be observed or what the smallest treatment effect that could be expected? While inference on the means is based on the central limit theorem, the corresponding theorem for maximums or minimums is the Fisher-Tippett theorem, also called the extreme value theorem (EVT). This manuscript will introduce EVT to pharmacometricians, particularly block maxima analysis and peak over threshold analysis, and provide examples for how it can be applied to pharmacometric data, particularly the analysis of pharmacokinetics and ECG safety data, like QTcF intervals.

Indexed as

Data Interpretation, StatisticalMinimal Clinically Important DifferenceModels, BiologicalAcetanilidesCross-Over StudiesDatasets as TopicDrug-Related Side Effects and Adverse ReactionsElectrocardiographyFemaleHeart RateHumansMaleMoxifloxacinPharmacology, ClinicalPlacebosRandomized Controlled Trials as TopicAcetanilidesmirabegronMoxifloxacinPlacebosThiazolesExposure–responseFrechetGumbelQT intervalSafety analysisStatisticsWeibull

Identifiers

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.