Skip to main content
Journal cover image

Interpreting incremental value of markers added to risk prediction models.

Publication ,  Journal Article
Pencina, MJ; D'Agostino, RB; Pencina, KM; Janssens, ACJW; Greenland, P
Published in: Am J Epidemiol
September 15, 2012

The discrimination of a risk prediction model measures that model's ability to distinguish between subjects with and without events. The area under the receiver operating characteristic curve (AUC) is a popular measure of discrimination. However, the AUC has recently been criticized for its insensitivity in model comparisons in which the baseline model has performed well. Thus, 2 other measures have been proposed to capture improvement in discrimination for nested models: the integrated discrimination improvement and the continuous net reclassification improvement. In the present study, the authors use mathematical relations and numerical simulations to quantify the improvement in discrimination offered by candidate markers of different strengths as measured by their effect sizes. They demonstrate that the increase in the AUC depends on the strength of the baseline model, which is true to a lesser degree for the integrated discrimination improvement. On the other hand, the continuous net reclassification improvement depends only on the effect size of the candidate variable and its correlation with other predictors. These measures are illustrated using the Framingham model for incident atrial fibrillation. The authors conclude that the increase in the AUC, integrated discrimination improvement, and net reclassification improvement offer complementary information and thus recommend reporting all 3 alongside measures characterizing the performance of the final model.

Duke Scholars

Altmetric Attention Stats
Dimensions Citation Stats

Published In

Am J Epidemiol

DOI

EISSN

1476-6256

Publication Date

September 15, 2012

Volume

176

Issue

6

Start / End Page

473 / 481

Location

United States

Related Subject Headings

  • Risk Factors
  • Risk Assessment
  • ROC Curve
  • Prognosis
  • Odds Ratio
  • Middle Aged
  • Logistic Models
  • Humans
  • Epidemiology
  • Data Interpretation, Statistical
 

Citation

APA
Chicago
ICMJE
MLA
NLM
Pencina, M. J., D’Agostino, R. B., Pencina, K. M., Janssens, A. C. J. W., & Greenland, P. (2012). Interpreting incremental value of markers added to risk prediction models. Am J Epidemiol, 176(6), 473–481. https://doi.org/10.1093/aje/kws207
Pencina, Michael J., Ralph B. D’Agostino, Karol M. Pencina, A Cecile J. W. Janssens, and Philip Greenland. “Interpreting incremental value of markers added to risk prediction models.Am J Epidemiol 176, no. 6 (September 15, 2012): 473–81. https://doi.org/10.1093/aje/kws207.
Pencina MJ, D’Agostino RB, Pencina KM, Janssens ACJW, Greenland P. Interpreting incremental value of markers added to risk prediction models. Am J Epidemiol. 2012 Sep 15;176(6):473–81.
Pencina, Michael J., et al. “Interpreting incremental value of markers added to risk prediction models.Am J Epidemiol, vol. 176, no. 6, Sept. 2012, pp. 473–81. Pubmed, doi:10.1093/aje/kws207.
Pencina MJ, D’Agostino RB, Pencina KM, Janssens ACJW, Greenland P. Interpreting incremental value of markers added to risk prediction models. Am J Epidemiol. 2012 Sep 15;176(6):473–481.
Journal cover image

Published In

Am J Epidemiol

DOI

EISSN

1476-6256

Publication Date

September 15, 2012

Volume

176

Issue

6

Start / End Page

473 / 481

Location

United States

Related Subject Headings

  • Risk Factors
  • Risk Assessment
  • ROC Curve
  • Prognosis
  • Odds Ratio
  • Middle Aged
  • Logistic Models
  • Humans
  • Epidemiology
  • Data Interpretation, Statistical