Evidence map›Paper›PMID 31997095›Full record

ReviewThe AAPS journal2020

Considerations for Soluble Protein Biomarker Blood Sample Matrix Selection.

Joel A Mathews, Yan G Ni, Connie Wang, Jon E Peterson, Chad Ray, Xuemei Zhao, Daoyu Duan, Sara Hamon, John Allinson, Martha Hokom and 1 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in The AAPS journal, 2020. 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

11 authors.

Joel A MathewsIonis Pharmaceuticals, 2855 Gazelle Rd., Carlsbad, California, 92010, USA. jmathews@ionisph.com.ORCID http://orcid.org/0000-0002-5535-8080
Yan G NiRegeneron, Tarrytown, New York, USA.
Connie WangNovartis, Cambridge, Massachusetts, USA.
Jon E PetersonBristol-Myers Squibb, Princeton, New Jersey, USA.
Chad RayZoetis, Kalamazoo, Michigan, USA.
Xuemei ZhaoMerck & Co., Kenilworth, New Jersey, USA.
Daoyu DuanRegeneron, Tarrytown, New York, USA.
Sara HamonRegeneron, Tarrytown, New York, USA.
John AllinsonImmunologix Laboratories, Tampa, Florida, USA.
Martha HokomGenentech, South San Francisco, California, USA.
Greta WegnerR&D Systems, Minneapolis, Minnesota, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Blood-based soluble protein biomarkers provide invaluable clinical information about patients and are used as diagnostic, prognostic, and pharmacodynamic markers. The most commonly used blood sample matrices are serum and different types of plasma. In drug development research, the impact of sample matrix selection on successful protein biomarker quantification is sometimes overlooked. The sample matrix for a specific analyte is often chosen based on prior experience or literature searches, without good understanding of the possible effects on analyte quantification. Using a data set of 32 different soluble protein markers measured in matched serum and plasma samples, we examined the differences between serum and plasma and discussed how platelet or immune cell activation can change the quantified concentration of the analyte. We have also reviewed the effect of anticoagulant on analyte quantification. Finally, we provide specific recommendations for biomarker sample matrix selection and propose a systematic and data-driven approach for sample matrix selection. This review is intended to raise awareness of the impact and considerations of sample matrix selection on biomarker quantification.

Indexed as

Blood Chemical AnalysisAnimalsAnticoagulantsBiomarkers, PharmacologicalBlood PlateletsBlood ProteinsHumansLeukocytesPredictive Value of TestsReproducibility of ResultsAnticoagulantsBiomarkers, PharmacologicalBlood Proteinsanticoagulantsbiomarkersplasmaplateletsserum

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.