Evidence map›Paper›PMID 29760435›Full record

ReviewNature reviews. Rheumatology2018

Biomarkers as drug development tools: discovery, validation, qualification and use.

Virginia B Kraus

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Rheumatology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 109 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
109citing papers in PubMed, 2 pooled it
–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

109 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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  6. Non-Oncology Biomarkers in Precision Medicine: A Narrative Review.Therapeutic innovation & regulatory science · 2026
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49 more citing papers are in PubMed but not listed here.

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.

Virginia B KrausDuke Molecular Physiology Institute, Department of Medicine, Duke University School of Medicine, Durham, NC, USA. vbk@duke.edu.

Funding

Resource Core 3 - Metabolomics CoreP30AG028716 · NIA · DUKE UNIVERSITY · PI Sarah B. Peskoe · 2006 to 2026
$24.6M
NIA NIH HHS P30 AG028716
6 · The paper itself

Abstract

The 21st Century Cures Act, approved in the USA in December 2016, has encouraged the establishment of the national Precision Medicine Initiative and the augmentation of efforts to address disease prevention, diagnosis and treatment on the basis of a molecular understanding of disease. The Act adopts into law the formal process, developed by the FDA, of qualification of drug development tools, including biomarkers and clinical outcome assessments, to increase the efficiency of clinical trials and encourage an era of molecular medicine. The FDA and European Medicines Agency (EMA) have developed similar processes for the qualification of biomarkers intended for use as companion diagnostics or for development and regulatory approval of a drug or therapeutic. Biomarkers that are used exclusively for the diagnosis, monitoring or stratification of patients in clinical trials are not subject to regulatory approval, although their qualification can facilitate the conduct of a trial. In this Review, the salient features of biomarker discovery, analytical validation, clinical qualification and utilization are described in order to provide an understanding of the process of biomarker development and, through this understanding, convey an appreciation of their potential advantages and limitations.

Indexed as

BiomarkersDrug DevelopmentHumansPharmaceutical PreparationsPrecision MedicinePrognosisTreatment OutcomeUnited StatesUnited States Food and Drug AdministrationBiomarkersPharmaceutical Preparations

Identifiers

PMID29760435

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.