Evidence map›Paper›PMID 22875755›Full record

ArticleAmerican journal of epidemiology2012

Interpreting incremental value of markers added to risk prediction models.

Michael J Pencina, Ralph B D'Agostino, Karol M Pencina, A Cecile J W Janssens, Philip Greenland

Abstract read
In one paragraph

Article in American journal of epidemiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 264 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
264citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

264 citing papers in PubMed, 4 syntheses or guidelines pooled it.

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  7. Derivation and validation of the ISAR score to predict the risk of repeat percutaneous coronary intervention for recurrent drug-eluting stent restenosis.EuroIntervention : journal of EuroPCR in collaboration with the Working Group on Interventional Cardiology of the European Society of Cardiology · 2023
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  16. Genome-scale perturbation signatures from primary human CD4bioRxiv : the preprint server for biology · 2026
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204 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

5 authors.

Michael J PencinaDepartment of Biostatistics, Boston University, Massachusetts, USA. mpencina@bu.edu
Ralph B D'Agostino
Karol M Pencina
A Cecile J W Janssens
Philip Greenland

Funding

MULTIDISCIPLINARY CLINICAL AND TRANSLATIONAL SCIENCE (MCTS) PROGRAM (UL1)UL1RR025741 · NCRR · NORTHWESTERN UNIVERSITY AT CHICAGO · PI GREENLAND, PHILIP · 2008 to 2011
$24.7M
Multidisciplinary Clinical and Translational Science (MCTS) Program (UL1)UL1TR000150 · NCATS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI LLOYD-JONES, DONALD M · 2012 to 2013
$10.1M
Risk prediction of atrial fibrillation: clinical, biological and genetic markersRC1HL101056 · NHLBI · BOSTON UNIVERSITY MEDICAL CAMPUS · PI ALONSO, ALVARO, BENJAMIN, EMELIA J. · 2009 to 2010
$967k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
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NCATS NIH HHS UL1 TR000150NCRR NIH HHS UL1 RR025741NCRR NIH HHS UL1RR025741NHLBI NIH HHS 1 RC1HL101056NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01-HC-25195NHLBI NIH HHS RC1 HL101056
6 · The paper itself

Abstract

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.

Indexed as

Data Interpretation, StatisticalLogistic ModelsROC CurveAdultAgedAged, 80 and overAtrial FibrillationBiomarkersComputer SimulationHumansMiddle AgedOdds RatioPrognosisRisk AssessmentRisk FactorsBiomarkers

Identifiers

PMID22875755
PMCPMC3530349

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.