Asymptotic distribution of ∆AUC, NRIs, and IDI based on theory of U‐statistics
Reads0
Chats0
TLDR
It is proved that the ∆AUC, NRIs, and IDI are asymptotically normal, unless they compare nested models under the null hypothesis, and when existing formulas for SE estimates can be used and when resampling methods such as the bootstrap should be used instead when comparing nested models.Abstract:
The change in area under the curve (∆AUC), the integrated discrimination improvement (IDI), and net reclassification index (NRI) are commonly used measures of risk prediction model performance. Some authors have reported good validity of associated methods of estimating their standard errors (SE) and construction of confidence intervals, whereas others have questioned their performance. To address these issues, we unite the ∆AUC, IDI, and three versions of the NRI under the umbrella of the U-statistics family. We rigorously show that the asymptotic behavior of ∆AUC, NRIs, and IDI fits the asymptotic distribution theory developed for U-statistics. We prove that the ∆AUC, NRIs, and IDI are asymptotically normal, unless they compare nested models under the null hypothesis. In the latter case, asymptotic normality and existing SE estimates cannot be applied to ∆AUC, NRIs, or IDI. In the former case, SE formulas proposed in the literature are equivalent to SE formulas obtained from U-statistics theory if we ignore adjustment for estimated parameters. We use Sukhatme-Randles-deWet condition to determine when adjustment for estimated parameters is necessary. We show that adjustment is not necessary for SEs of the ∆AUC and two versions of the NRI when added predictor variables are significant and normally distributed. The SEs of the IDI and three-category NRI should always be adjusted for estimated parameters. These results allow us to define when existing formulas for SE estimates can be used and when resampling methods such as the bootstrap should be used instead when comparing nested models. We also use the U-statistic theory to develop a new SE estimate of ∆AUC. Copyright © 2017 John Wiley & Sons, Ltd.read more
Citations
More filters
Journal ArticleDOI
Quantifying the added value of new biomarkers: how and how not.
TL;DR: This commentary provides an overview of methods currently used to evaluate new biomarkers, describes their strengths and limitations, and offers some suggestions on their use.
Journal ArticleDOI
Prediction of Cardiovascular Events by Type I Central Systolic Blood Pressure: A Prospective Study.
TL;DR: In conclusion, central BP measured with a type I device is statistically but likely not clinically superior to brachial BP in a general population without prior cardiovascular disease.
Journal ArticleDOI
Effects of Neutrophil-to-Lymphocyte Ratio Combined With Interleukin-6 in Predicting 28-Day Mortality in Patients With Sepsis.
TL;DR: In this paper, the authors evaluated the relationship between the neutrophil-to-lymphocyte ratio (NLR) combined with interleukin (IL)-6 on admission day and the 28-day mortality of septic patients.
Journal ArticleDOI
Preoperative positive urine nitrite and albumin-globulin ratio are independent risk factors for predicting postoperative fever after retrograde Intrarenal surgery based on a retrospective cohort
TL;DR: The preoperative urine nitrite, AGR, RIRS time, and preoperative urinary culture are found to be independent risk factors associated with postoperative fever after retrograding intrarenal surgery (RIRS) and a nomogram was developed taking these factors into account that accurately predicted POF after RIRs.
Journal ArticleDOI
Early-Onset Diabetes as Risk Factor for Pancreatic Cancer: miRNA Expression Profiling in Plasma Uncovers a Role for miR-20b-5p, miR-29a, and miR-18a-5p in Diabetes of Recent Diagnosis.
Francesca Tavano,Andrea Fontana,Tommaso Mazza,Domenica Gioffreda,Tommaso Biagini,Orazio Palumbo,Massimo Carella,Angelo Andriulli +7 more
TL;DR: The data highlighted the association betweenmiR-18a-5p and early-diabetes, and suggested for miR-20b- 5p and miR -29 a role in identifying early diabetes in PanC, albeit not as an early manifestation of cancer.
References
More filters
Journal ArticleDOI
Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III)
Scott M. Grundy,David W. Bilheimer,Alan Chait,Luther T. Clark,Margo A. Denke,Richard J. Havel,William R. Hazzard,Stephen B. Hulley,Donald B. Hunninghake,Robert A. Kreisberg,Penny M. Kris-Etherton,James M. McKenney,Michael A. Newman,Ernst J. Schaefer,Burton E. Sobel,Carolyn Somelofski,Milton C. Weinstein,H. Bryan Brewer,James I. Cleeman,Karen A. Donato,Nancy D. Ernst,Jeffrey M. Hoeg,Basil M. Rifkind,Jacques E. Rossouw,Christopher T. Sempos,Joanne M. Gallivan,Maureen N. Harris,Laurie Quint-Adler +27 more
TL;DR: Dairy therapy remains the first line of treatment of high blood cholesterol, and drug therapy is reserved for patients who are considered to be at high risk for CHD, and the fundamental approach to treatment is comparable.
Journal ArticleDOI
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
TL;DR: A representation and interpretation of the area under a receiver operating characteristic (ROC) curve obtained by the "rating" method, or by mathematical predictions based on patient characteristics, is presented and it is shown that in such a setting the area represents the probability that a randomly chosen diseased subject is (correctly) rated or ranked with greater suspicion than a random chosen non-diseased subject.
Journal ArticleDOI
Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach.
TL;DR: A nonparametric approach to the analysis of areas under correlated ROC curves is presented, by using the theory on generalized U-statistics to generate an estimated covariance matrix.
Journal ArticleDOI
Prediction of Coronary Heart Disease Using Risk Factor Categories
Peter W.F. Wilson,Ralph B. D'Agostino,Daniel Levy,Albert M. Belanger,Halit Silbershatz,William B. Kannel +5 more
TL;DR: A simple coronary disease prediction algorithm was developed using categorical variables, which allows physicians to predict multivariate CHD risk in patients without overt CHD.
Journal ArticleDOI
2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines
Neil J. Stone,Jennifer G. Robinson,Alice H. Lichtenstein,C. Noel Bairey Merz,Conrad B. Blum,Robert H. Eckel,Anne C. Goldberg,David Lee Gordon,Daniel Levy,Donald M. Lloyd-Jones,Patrick E. McBride,J. Sanford Schwartz,Susan T. Shero,Sidney C. Smith,Karol E. Watson,Peter W.F. Wilson +15 more
TL;DR: Preamble and Transition to ACC/AHA Guidelines to Reduce Cardiovascular Risk S2 The goals of the …