ReviewJournal of the American Society of Nephrology : JASN2014
Key concepts and limitations of statistical methods for evaluating biomarkers of kidney disease.
Review in Journal of the American Society of Nephrology : JASN, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 2 of them syntheses that pooled it.
What it found
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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.
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.
Who cites it
28 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Neutrophil gelatinase-associated lipocalin as predictor of acute kidney injury requiring renal replacement therapy: A systematic review and meta-analysis.Frontiers in medicine · 2022Pooled it
- Biomarkers for prediction of renal replacement therapy in acute kidney injury: a systematic review and meta-analysis.Intensive care medicine · 2018Pooled it
- Artificial intelligence in biomarker discovery for diseases: diagnostic and therapeutic prospects.Signal transduction and targeted therapy · 2026Review
- Salivary short chain fatty acids serve as biomarkers of periodontal inflammatory burden.Scientific reports · 2025Article
- Design aspects for prognostic factor studies.BMJ open · 2025Review
- Biomarkers as Prognostic Predictors and Therapeutic Guide in Critically Ill Patients: Clinical Evidence.Journal of personalized medicine · 2023Review
- Biomarkers: Promising and valuable tools towards diagnosis, prognosis and treatment of Covid-19 and other diseases.Heliyon · 2023Review
- Preoperative NT-proBNP and LVEF for the prediction of acute kidney injury after noncardiac surgery: a single-centre retrospective study.BMC anesthesiology · 2022Article
- Predictive Value of Glycosylated Hemoglobin for Post-operative Acute Kidney Injury in Non-cardiac Surgery Patients.Frontiers in medicine · 2022Article
- Faecal Diagnostic Biomarkers for Colorectal Cancer.Cancers · 2021Article
- Applying Proteomics and Integrative "Omics" Strategies to Decipher the Chronic Kidney Disease-Related Atherosclerosis.International journal of molecular sciences · 2021Review
- Predicting survival after liver transplantation in patients with hepatocellular carcinoma using the LiTES-HCC score.Journal of hepatology · 2021Article
- Association of plasma level of high-mobility group box-1 with necroptosis and sepsis outcomes.Scientific reports · 2021Article
- A parsimonious score with a free web tool for predicting disability after an ischemic stroke: the Parsifal Score.Journal of neurology · 2020Article
- The Role of Prognostic and Predictive Biomarkers for Assessing Cardiovascular Risk in Chronic Kidney Disease Patients.BioMed research international · 2020Review
- TNF-α Production by Monocytes Stimulated With Epstein-Barr Virus-Peptides as a Marker of Immunosuppression-Related Adverse Events in Kidney Transplant Recipients.Kidney international reports · 2019Article
- Kidney Tubular Damage and Functional Biomarkers in Acute Kidney Injury Following Cardiac Surgery.Kidney international reports · 2019Article
- Utility of Biomarkers to Improve Prediction of Readmission or Mortality After Cardiac Surgery.The Annals of thoracic surgery · 2018Article
- Urinary epidermal growth factor, monocyte chemoattractant protein-1 or their ratio as predictors for rapid loss of renal function in type 2 diabetic patients with diabetic kidney disease.BMC nephrology · 2018Article
- Lipidomics and Biomarker Discovery in Kidney Disease.Seminars in nephrology · 2018Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Interest in developing and using novel markers of kidney injury is increasing. To maintain scientific rigour in these endeavors, a comprehensive understanding of statistical methodology is required to rigorously assess the incremental value of novel biomarkers in existing clinical risk prediction models. Such knowledge is especially relevant, because no single statistical method is sufficient to evaluate a novel biomarker. In this review, we highlight the strengths and limitations of various traditional and novel statistical methods used in the literature for biomarker studies and use biomarkers of AKI as examples to show limitations of some popular statistical methods.
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Registered trials
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.