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Statistical methods for assessment of added usefulness of new biomarkers.

Publication ,  Journal Article
Pencina, MJ; D'Agostino, RB; Vasan, RS
Published in: Clin Chem Lab Med
December 2010

The discovery and development of new biomarkers continues to be an exciting and promising field. Improvement in prediction of risk of developing disease is one of the key motivations in these pursuits. Appropriate statistical measures are necessary for drawing meaningful conclusions about the clinical usefulness of these new markers. In this review, we present several novel metrics proposed to serve this purpose. We use reclassification tables constructed on the basis of clinically meaningful disease risk categories to discuss the concepts of calibration, risk separation, risk discrimination, and risk classification accuracy. We discuss the notion that the net reclassification improvement (NRI) is a simple yet informative way to summarize information contained in risk reclassification tables. In the absence of meaningful risk categories, we suggest a 'category-less' version of the NRI and integrated discrimination improvement as metrics to summarize the incremental value of new biomarkers. We also suggest that predictiveness curves be preferred to receiver operating characteristic curves as visual descriptors of a statistical model's ability to separate predicted probabilities of disease events. Reporting of standard metrics, including measures of relative risk and the c statistic, is still recommended. These concepts are illustrated with a risk prediction example using data from the Framingham Heart Study.

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Published In

Clin Chem Lab Med

DOI

EISSN

1437-4331

Publication Date

December 2010

Volume

48

Issue

12

Start / End Page

1703 / 1711

Location

Germany

Related Subject Headings

  • Risk Assessment
  • Models, Statistical
  • Humans
  • Heart Diseases
  • General Clinical Medicine
  • Disease Susceptibility
  • Computational Biology
  • Biomarkers
  • 3205 Medical biochemistry and metabolomics
  • 3202 Clinical sciences
 

Citation

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Pencina, M. J., D’Agostino, R. B., & Vasan, R. S. (2010). Statistical methods for assessment of added usefulness of new biomarkers. Clin Chem Lab Med, 48(12), 1703–1711. https://doi.org/10.1515/CCLM.2010.340
Pencina, Michael J., Ralph B. D’Agostino, and Ramachandran S. Vasan. “Statistical methods for assessment of added usefulness of new biomarkers.Clin Chem Lab Med 48, no. 12 (December 2010): 1703–11. https://doi.org/10.1515/CCLM.2010.340.
Pencina MJ, D’Agostino RB, Vasan RS. Statistical methods for assessment of added usefulness of new biomarkers. Clin Chem Lab Med. 2010 Dec;48(12):1703–11.
Pencina, Michael J., et al. “Statistical methods for assessment of added usefulness of new biomarkers.Clin Chem Lab Med, vol. 48, no. 12, Dec. 2010, pp. 1703–11. Pubmed, doi:10.1515/CCLM.2010.340.
Pencina MJ, D’Agostino RB, Vasan RS. Statistical methods for assessment of added usefulness of new biomarkers. Clin Chem Lab Med. 2010 Dec;48(12):1703–1711.
Journal cover image

Published In

Clin Chem Lab Med

DOI

EISSN

1437-4331

Publication Date

December 2010

Volume

48

Issue

12

Start / End Page

1703 / 1711

Location

Germany

Related Subject Headings

  • Risk Assessment
  • Models, Statistical
  • Humans
  • Heart Diseases
  • General Clinical Medicine
  • Disease Susceptibility
  • Computational Biology
  • Biomarkers
  • 3205 Medical biochemistry and metabolomics
  • 3202 Clinical sciences