Evidence map›Paper›PMID 30521581›Full record

ArticlePloS one2018

An evaluation roadmap for critical quality attributes from tier 1 in analytical similarity assessment.

Kejian Wu, Haitao Pan, Chen Li, Qingbo Zhao, Ling Wang, Jielai Xia

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 85% of its field
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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

6 authors at 2 institutions in 2 countries.

Kejian WuDepartment of Health Statistics, Fourth Military Medical University, Xi'an, Shannxi, China.
Haitao PanDepartment of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee, United States of America.
Chen LiDepartment of Health Statistics, Fourth Military Medical University, Xi'an, Shannxi, China.
Qingbo ZhaoDepartment of Mathematics and Physics, Fourth Military Medical University, Xi'an, Shannxi, China.
Ling WangDepartment of Health Statistics, Fourth Military Medical University, Xi'an, Shannxi, China.
Jielai XiaDepartment of Health Statistics, Fourth Military Medical University, Xi'an, Shannxi, China.ORCID 0000-0003-1137-3198
Air Force Medical University · CNSt. Jude Children's Research Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Analytical similarity assessment of critical quality attributes (CQAs) serves as a foundation for the development of biosimilar products and facilitates an abbreviated subsequent clinical evaluation. In this study, we establish a statistical evaluation roadmap with statistical approaches for some selected CQAs from Tier 1, because they are most relevant to clinical outcomes and require the most rigorous statistical methods. In the roadmap, we incorporate 3 methods-ranking and tier assignment of quality attributes, the equivalence test, and the Mann-Whitney test for equivalence-that are important to determine analytical similarity between the reference and biosimilar products. For the equivalence test, we develop a power calculation formula based on the two one-sided tests procedure. Exact sample sizes can be numerically calculated. Then, we propose a flexible idea for selecting the number of reference lots (nR) and the number of biosimilar lots (nT) to adjust for serious unbalanced sample sizes. From results of extensive simulations under various parameter settings, we obtain a workable strategy to determine the optimum sample size combination (nT, nR) for the equivalence test of CQAs from Tier 1. R codes are provided to facilitate implementation of the roadmap and corresponding methods in practice.

Indexed as

Biosimilar PharmaceuticalsData Interpretation, StatisticalHumansUnited StatesUnited States Food and Drug AdministrationBiosimilar Pharmaceuticals

Identifiers

PMID30521581
PMCPMC6283468
OpenAlexW2904546609

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.