Evidence map›Paper›PMID 38915440›Full record

ReviewClinical kidney journal2024

Biomarkers in clinical epidemiology studies.

Carmine Zoccali, Giovanni Tripepi, Vianda Stel, Eduard L Fu, Francesca Mallamaci, Friedo Dekker, Kitty J Jager

Erratum issuedAbstract readReview
In one paragraph

Review in Clinical kidney journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Biomarker-Driven Treatments for Ovarian Cancer: Moving Beyond HRD?International journal of women's health · 2026
    Review
  5. Article
  6. Article
  7. Review
  8. Article
  9. Review
  10. Kynurenine Pathway after Kidney Transplantation: Friend or Foe?International journal of molecular sciences · 2024
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Carmine ZoccaliRenal Research Institute, New York, USA.ORCID https://orcid.org/0000-0002-6616-1996
Giovanni TripepiCNR-IFC, Institute of Clinical Physiology, Research Unit of Clinical Epidemio logy.
Vianda StelERA Registry, Amsterdam UMC location and the University of Amsterdam, Department of Medical Informatics, Amsterdam, The Netherlands.
Eduard L FuDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Francesca MallamaciCNR-IFC, Institute of Clinical Physiology, Research Unit of Clinical Epidemio logy.
Friedo DekkerDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.
Kitty J JagerDepartment of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper discusses the use of biomarkers in clinical practice and biomedical research. Biomarkers are measurable characteristics that can be used to indicate the presence or absence of a disease or to track the progression of a disease. They can also be used to predict how a patient will respond to a particular treatment. Biomarkers have enriched clinical practice and disease prognosis by providing measurable characteristics that indicate biological processes. They offer valuable insights into disease susceptibility, progression, and treatment response, aiding drug development and personalized medicine. However, developing and implementing biomarkers come with challenges that must be addressed. Rigorous testing, standardization of assays, and consideration of ethical factors are crucial in ensuring the reliability and validity of biomarkers. Reliability is vital in biomarker research. It ensures accurate measurements by preventing biases and facilitating robust correlations with outcomes. Conversely, validation examines which and how many biomarkers correspond to theoretical constructs and external criteria, establishing their predictive value. Multiple biomarkers are sometimes necessary to represent the complex relationship between exposure and disease outcomes accurately. Susceptibility factors are pivotal in disease states' complex interaction among genetic and environmental factors. Gaining a comprehensive understanding of these factors is essential for effectively interpreting biomarker data and maximizing their clinical usefulness. Using well-validated biomarkers can improve diagnoses, more effective treatment evaluations, and enhanced disease prediction. This, in turn, will contribute to better patient outcomes and drive progress in medicine.

Indexed as

biomarkerscardiovascularCKDepidemiologyinflammation

Identifiers

PMID38915440
PMCPMC11195614

What OpenQuestion holds

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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.