Net reclassification improvement: A link between statistics and clinical practice

European Journal of Epidemiology

Volumn 28, Issue 1, 2013, Pages 21-23

  Leening, Maarten J G ^a   Cook, Nancy R ^b,c  

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b BRIGHAM AND WOMEN S HOSPITAL   (United States)

^c HARVARD SCHOOL OF PUBLIC HEALTH   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ANALYTICAL PARAMETERS; AREA UNDER THE CURVE; CALIBRATION; CARDIOVASCULAR RISK; CATEGORY CUT POINT; CLASSIFICATION; CLINICAL DECISION MAKING; CLINICAL PRACTICE; CONTINUOUS NET RECLASSIFICATION IMPROVEMENT; DIABETES MELLITUS; NET RECLASSIFICATION IMPROVEMENT; NOTE; PREDICTIVE VALUE; RISK ASSESSMENT; RISK CATEGORY; STATISTICAL ANALYSIS; VALIDATION PROCESS;

DIABETES MELLITUS, TYPE 2; FEMALE; HUMANS; MALE; MODELS, BIOLOGICAL; RISK ASSESSMENT; ROC CURVE;

EID: 84874943201     PISSN: 03932990     EISSN: 15737284     Source Type: Journal    
DOI: 10.1007/s10654-012-9759-6     Document Type: Note

References (29)

1. De Backer G, Ambrosioni E, Borch-Johnsen K, Brotons C, Cifkova R, Dallongeville J, et al. European guidelines on cardiovascular disease prevention in clinical practice. Third joint task force of european and other societies on cardiovascular disease prevention in clinical practice. Eur Heart J. 2003;24(17):1601-10.
2. 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). JAMA. 2001;285(19):2486-97.
3. Hlatky MA, Greenland P, Arnett DK, Ballantyne CM, Criqui MH, Elkind MS, et al. Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation. 2009;119(17):2408-16. doi: 10.1161/CIRCULATIONAHA.109.192278.
4. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143(1):29-36.
5. Harrell FE Jr, Califf RM, Pryor DB, Lee KL, Rosati RA. Evaluating the yield of medical tests. JAMA. 1982;247(18):2543-6.
6. Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P. Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004;159(9):882-90.
7. Pencina MJ, D'Agostino RB, Pencina KM, Janssens AC, Greenland P. Interpreting incremental value of markers added to risk prediction models. Am J Epidemiol. 2012;176(6):473-81. doi: 10.1093/aje/kws207.
8. Cook NR. Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation. 2007;115(7):928-35. doi: 10.1161/CIRCULATIONAHA. 106.672402.
9. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27(2):157-72. doi: 10.1002/sim.2929.
10. Muhlenbruch K, Heraclides A, Steyerberg EW, Joost HG, Boeing H, Schulze MB. Assessing improvement in disease prediction using net reclassification improvement: impact of risk cut-offs and number of risk categories. Eur J Epidemiol. 2012. doi: 10.1007/s10654-012-9744-0.
11. Mealiffe ME, Stokowski RP, Rhees BK, Prentice RL, Pettinger M, Hinds DA. Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information. J Natl Cancer Inst. 2010;102(21):1618-27. doi: 10.1093/jnci/djq388.
12. Mihaescu R, van Zitteren M, van Hoek M, Sijbrands EJ, Uitterlinden AG, Witteman JC, et al. Improvement of risk prediction by genomic profiling: reclassification measures versus the area under the receiver operating characteristic curve. Am J Epidemiol. 2010;172(3):353-61. doi: 10.1093/aje/kwq122.
13. Cook NR, Paynter NP. Comments on 'Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers' by M. J. Pencina, R. B. D'Agostino, Sr. and E. W. Steyerberg. Stat Med. 2012;31(1):93-5. doi: 10.1002/sim.4209.
14. Pencina MJ, D'Agostino RB Sr, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 2011;30(1):11-21. doi: 10.1002/sim.4085.
15. Cook NR, Ridker PM. Advances in measuring the effect of individual predictors of cardiovascular risk: the role of reclassification measures. Ann Intern Med. 2009;150(11):795-802.
16. Cook NR. Clinically relevant measures of fit? A note of caution. Am J Epidemiol. 2012;176(6):488-91.
17. Hosmer DW, Lemeshow S. Goodness of fit tests for the multiple logistic regression model. Commun Stat-Theory Methods. 1980;9(10):1043-69.
18. Cook NR, Paynter NP. Performance of reclassification statistics in comparing risk prediction models. Biom J. 2011;53(2):237-58. doi: 10.1002/bimj.201000078.
19. Vickers AJ, Cronin AM, Begg CB. One statistical test is sufficient for assessing new predictive markers. BMC Med Res Methodol. 2011;11:13. doi: 10.1186/1471-2288-11-13.
20. Demler OV, Pencina MJ, D'Agostino RB Sr. Misuse of DeLong test to compare AUCs for nested models. Stat Med. 2012;31(23):2577-87. doi: 10.1002/sim.5328.
21. Seshan VE, Gönen M, Begg CB. Comparing ROC curves derived from regression models. Stat Med. 2012. doi: 10.1002/sim.5648.
22. Steyerberg EW. Clinical prediction models: A practical approach to development, validation, and updating. New York: Springer; 2009.
23. Yeboah J, McClelland RL, Polonsky TS, Burke GL, Sibley CT, O'Leary D, et al. Comparison of novel risk markers for improvement in cardiovascular risk assessment in intermediate-risk individuals. JAMA. 2012;308(8):788-95. doi: 10.1001/jama.2012.9624.
24. Cook NR. Comments on 'Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond' by M. J. Pencina et al., Statistics in Medicine (DOI: 10.1002/sim.2929). Stat Med. 2008;27(2):191-5. doi: 10.1002/sim.2987.
25. Paynter NP, Cook NR. A bias-corrected net reclassification improvement for clinical subgroups. Med Decis Mak. 2012. doi: 10.1177/0272989X12461856.
26. Pauker SG, Kassirer JP. The threshold approach to clinical decision making. N Engl J Med. 1980;302(20):1109-17. doi: 10.1056/NEJM198005153022003.
27. Visvanathan K, Chlebowski RT, Hurley P, Col NF, Ropka M, Collyar D, et al. American society of clinical oncology clinical practice guideline update on the use of pharmacologic interventions including tamoxifen, raloxifene, and aromatase inhibition for breast cancer risk reduction. J Clin Oncol. 2009;27(19):3235-58. doi: 10.1200/JCO.2008.20.5179.
28. Munshi NC, Anderson KC, Bergsagel PL, Shaughnessy J, Palumbo A, Durie B, et al. Consensus recommendations for risk stratification in multiple myeloma: report of the International Myeloma Workshop Consensus Panel 2. Blood. 2011;117(18):4696-700. doi: 10.1182/blood-2010-10-300970.
29. Worth LJ, Worth LJ, Lingaratnam S, Taylor A, Hayward AM, Morrissey S, Cooney J, et al. Use of risk stratification to guide ambulatory management of neutropenic fever. Australian Consensus Guidelines 2011 Steering Committee. Intern Med J. 2011;41(1b):82-9. doi: 10.1111/j.1445-5994.2010.02339.x.