Evidence map›Paper›PMID 30746568›Full record

ArticleThe AAPS journal2019

Incurred Sample Reanalysis: Time to Change the Sample Size Calculation?

Piotr J Rudzki, Przemysław Biecek, Michał Kaza

Abstract read
In one paragraph

Article in The AAPS journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
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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.

Piotr J RudzkiPharmacokinetics Department, Pharmaceutical Research Institute, 8 Rydygiera Street, 01-793, Warsaw, Poland. p.rudzki@ifarm.eu.ORCID 0000-0002-4622-4849
Przemysław BiecekFaculty of Mathematics and Information Science, Warsaw University of Technology, 75 Koszykowa Street, 00-662, Warsaw, Poland.ORCID 0000-0001-8423-1823
Michał KazaPharmacokinetics Department, Pharmaceutical Research Institute, 8 Rydygiera Street, 01-793, Warsaw, Poland.ORCID 0000-0001-6691-7725

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reliable results of pharmacokinetic and toxicokinetic studies are vital for correct decision making during drug discovery and development. Thus, ensuring high quality of bioanalytical methods is of critical importance. Incurred sample reanalysis (ISR)-one of the tools used to validate a method-is included in the bioanalytical regulatory recommendations. The methodology of this test is well established, but the estimation of the sample size is still commented on and contested. We have applied the hypergeometric distribution to evaluate ISR test passing rates in different clinical study sizes. We have tested both fixed rates of the clinical samples-as currently recommended by FDA and EMA-and a fixed number of ISRs. Our study revealed that the passing rate using the current sample size calculation is related to the clinical study size. However, the passing rate is much less dependent on the clinical study size when a fixed number of ISRs is used. Thus, we suggest using a fixed number of ISRs, e.g., 30 samples, for all studies. We found the hypergeometric distribution to be an adequate model for the assessment of similarities in original and repeated data. This model may be further used to optimize the sample size needed for the ISR test as well as to bridge data from different methods. This paper provides a basis to re-consider current ISR recommendations and implement a more statistically rationalized and risk-controlled approach.

Indexed as

Models, StatisticalQuality ControlValidation Studies as TopicClinical Trials as TopicHumansReproducibility of ResultsSample SizeSocieties, PharmaceuticalUnited StatesUnited States Food and Drug Administrationbioanalysisbioanalytical method validationbridging datahypergeometric distributionincurred sample reanalysis (ISR)

Identifiers

PMID30746568
PMCPMC6373415

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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.