Statistical Evaluation of a Biomarker

Department of Emergency Medicine and Surgery, Groupe Hospitalier Pitié-Salpêtrière, Paris, France.
Anesthesiology (Impact Factor: 5.88). 03/2010; 112(4):1023-40. DOI: 10.1097/ALN.0b013e3181d47604
Source: PubMed


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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Available from: Yannick Le Manach, Nov 14, 2014
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    Archives of Cardiovascular Diseases 02/2015; 108(2). DOI:10.1016/j.acvd.2014.11.001 · 1.84 Impact Factor
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    • "Biomarkers have been increasingly and widely used in clinical practice in recent years for disease diagnosis and prognosis based on their underlying pathological and physiologic mechanisms [1]. In these applications, biomarkers are used either to identify a subgroup of a study population or predict a disease outcome [2]. "
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    01/2014; 3(1):32-43. DOI:10.6000/1929-6029.2014.03.01.5
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    • "We analyzed the ability of time-adjusted MAP and highest dose of norepinephrine to predict worsening of AKI by calculating the AUC by ROC analysis with the primary endpoint. We assessed the best cutoff value by the Youden Index (sensitivity + specificity -1) [25]. We performed all statistical analyses using IBM SPSS Statistics 19.0 and 20.0 (IBM, Armonk, NY, USA) or NCSS 8 (Kaysville, UT, USA) software. "
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