Evidence map›Paper›PMID 30945035›Full record

ArticleThe AAPS journal2019

Trial Design and Statistical Considerations on the Assessment of Pharmacodynamic Similarity.

Peijuan Zhu, Chyi-Hung Hsu, Jason Liao, Steven Xu, Liping Zhang, Honghui Zhou

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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. Review
  2. 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

6 authors.

Peijuan ZhuJanssen Research and Development Inc, Raritan, NJ, USA. pzhu9@its.jnj.com.ORCID 0000-0003-3636-7640
Chyi-Hung HsuJanssen Research and Development Inc, Raritan, NJ, USA.
Jason LiaoMerck & Co., Inc, North Wales, PA, USA.
Steven XuJanssen Research and Development Inc, Raritan, NJ, USA.
Liping ZhangJanssen Research and Development Inc, Raritan, NJ, USA.
Honghui ZhouJanssen Research & Development Inc, Spring House, PA, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pharmacodynamics (PD) similarity is an important component to support the claim of similarity between two drugs or devices. This article investigates the trial design and statistical considerations in the equivalence test of PD endpoints. Using bone resorption marker CTX as a case study, the relationship between the PD readouts and drug potency was explored to evaluate the sensitivity of the PD endpoint and guide equivalence margin selection. For PD data that have high baseline variability, one conventional similarity assessment method was to apply baseline-normalization followed by the standard bioequivalence (BE) test (Lancet Haematol. 4:e350-61, 2017, Ann Rheum Dis. 2017). This study showcased the drawbacks of the conventional method for PD data that were close to inhibition saturation, as the baseline-normalization significantly skewed the distribution of the PD data toward non-log-normal. In such cases, the standard BE test can produce an inflated type I error. Alternatively, ANCOVA, when applied to the un-normalized PD data with the baseline as a covariate, produced a satisfactory type I error with sufficient power. Therefore, ANCOVA was recommended for equivalence test of PD markers that has a saturated inhibition profile and high variability at baseline. Moreover, the relationship between PD readouts and drug potency was used to explore the sensitivity of the PD endpoint and it could help justify the equivalence margins, since the standard 80% to 125% BE margin often does not apply to PD. Finally, a decision tree was proposed to help guide the design of the PD equivalence study in the choice of PD endpoints and statistical methods.

Indexed as

Clinical Trials as TopicModels, BiologicalResearch DesignTherapeutic EquivalencyAnalysis of VarianceCollagen Type IComputer SimulationDatasets as TopicDecision TreesDenosumabHumansOsteoporosisPeptidesRegression AnalysisCollagen Type Icollagen type I trimeric cross-linked peptideDenosumabPeptidesAnalysis of covariance (ANCOVA)Baseline normalizationEquivalencePharmacodynamics (PD)Statistical testTrial simulation

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Registered trials

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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.