Literature DB >> 20234303

Statistical evaluation of a biomarker.

Patrick Ray1, Yannick Le Manach, Bruno Riou, Tim T Houle.   

Abstract

A biomarker may provide a diagnosis, assess disease severity or risk, or guide other clinical interventions such as the use of drugs. Although considerable progress has been made in standardizing the methodology and reporting of randomized trials, less has been accomplished concerning the assessment of biomarkers. Biomarker studies are often presented with poor biostatistics and methodologic flaws that precludes them from providing a reliable and reproducible scientific message. A host of issues are discussed that can improve the statistical evaluation and reporting of biomarker studies. Investigators should be aware of these issues when designing their studies, editors and reviewers when analyzing a manuscript, and readers when interpreting results.

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Year:  2010        PMID: 20234303     DOI: 10.1097/ALN.0b013e3181d47604

Source DB:  PubMed          Journal:  Anesthesiology        ISSN: 0003-3022            Impact factor:   7.892


  115 in total

Review 1.  A Review of Cutoffs for Nutritional Biomarkers.

Authors:  Ramkripa Raghavan; Fayrouz Sakr Ashour; Regan Bailey
Journal:  Adv Nutr       Date:  2016-01-15       Impact factor: 8.701

2.  A Urinary Metabolic Signature for Multiple Sclerosis and Neuromyelitis Optica.

Authors:  Teklab Gebregiworgis; Helle H Nielsen; Chandirasegaran Massilamany; Arunakumar Gangaplara; Jay Reddy; Zsolt Illes; Robert Powers
Journal:  J Proteome Res       Date:  2016-01-27       Impact factor: 4.466

Review 3.  How could biomarkers of ARDS and AKI drive clinical strategies?

Authors:  Armand Mekontso Dessap; Lorraine B Ware; Sean M Bagshaw
Journal:  Intensive Care Med       Date:  2016-01-28       Impact factor: 17.440

4.  Empiric transfusion strategies during life-threatening hemorrhage.

Authors:  Geoffrey R Nunns; Ernest E Moore; Gregory R Stettler; Hunter B Moore; Arsen Ghasabyan; Mitchell Cohen; Benjamin R Huebner; Christopher C Silliman; Anirban Banerjee; Angela Sauaia
Journal:  Surgery       Date:  2018-04-27       Impact factor: 3.982

Review 5.  Noncoding RNAs in Cardiovascular Disease: Pathological Relevance and Emerging Role as Biomarkers and Therapeutics.

Authors:  Roopesh S Gangwar; Sanjay Rajagopalan; Rama Natarajan; Jeffrey A Deiuliis
Journal:  Am J Hypertens       Date:  2018-01-12       Impact factor: 2.689

6.  Derivation and diagnostic accuracy of the surgical lung injury prediction model.

Authors:  Daryl J Kor; David O Warner; Anas Alsara; Evans R Fernández-Pérez; Michael Malinchoc; Rahul Kashyap; Guangxi Li; Ognjen Gajic
Journal:  Anesthesiology       Date:  2011-07       Impact factor: 7.892

7.  Acute mesenteric ischemia, procalcitonin, and intensive care unit.

Authors:  Marc Leone; Jean-Yves Lefrant; Claude Martin; Jean-Michel Constantin
Journal:  Intensive Care Med       Date:  2015-06-03       Impact factor: 17.440

8.  Effects of a recruitment maneuver on plasma levels of soluble RAGE in patients with diffuse acute respiratory distress syndrome: a prospective randomized crossover study.

Authors:  Matthieu Jabaudon; Nacim Hamroun; Laurence Roszyk; Renaud Guérin; Jean-Etienne Bazin; Vincent Sapin; Bruno Pereira; Jean-Michel Constantin
Journal:  Intensive Care Med       Date:  2015-03-20       Impact factor: 17.440

9.  Predicting fluid responsiveness in whom? A simulated example of patient spectrum influencing the receiver operating characteristics curve.

Authors:  Lars Øivind Høiseth; Jostein S Hagemo
Journal:  J Clin Monit Comput       Date:  2017-04-21       Impact factor: 2.502

10.  Machine-Learning Algorithms Predict Graft Failure After Liver Transplantation.

Authors:  Lawrence Lau; Yamuna Kankanige; Benjamin Rubinstein; Robert Jones; Christopher Christophi; Vijayaragavan Muralidharan; James Bailey
Journal:  Transplantation       Date:  2017-04       Impact factor: 4.939

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