Evaluation of Prediction Models for Decision-Making: Beyond Calibration and Discrimination

PLoS Medicine

Volumn 10, Issue 7, 2013, Pages

  Holmberg, Lars ^a,b,c   Vickers, Andrew ^d  

^a UPPSALA UNIVERSITY HOSPITAL   (Sweden)

^b UPPSALA UNIVERSITY   (Sweden)

^c KING'S COLLEGE LONDON   (United Kingdom)

^d MEMORIAL SLOAN KETTERING CANCER CENTER   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; BREAST CANCER; CALIBRATION; CLINICAL DECISION MAKING; ENDOMETRIUM CANCER; HUMAN; MODEL; PREDICTION; PROSTATE CANCER; RECEIVER OPERATING CHARACTERISTIC;

EID: 84881235268     PISSN: 15491277     EISSN: 15491676     Source Type: Journal    
DOI: 10.1371/journal.pmed.1001491     Document Type: Article

References (14)

1. Pfeiffer RM, Park Y, Kreimer AR, Lacey JV Jr, Pee D, et al. (2013) Risk prediction for breast, endometrial, and ovarian cancer in white women aged 50 y or older: derivation and validation from population-based cohort studies. PLoS Med 10: e1001492 doi:10.1371/journal. pmed.1001492.
2. Schwartz LM, Woloshin S, Dvorin EL, Welch HG, (2006) Ratio measures in leading medical journals: structured review of accessibility of underlying absolute risks. BMJ 333: 1248-1250.
3. Ware JH, (2006) The limitations of risk factors as prognostic tools. New Engl J Med 355: 2615-2616.
4. Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P, (2004) Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic or screening marker. Am J Epidemiol 159: 882-890.
5. Mallett S, Haligan S, Thompson M, Collins GS, Altman DG, (2012) Interpreting diagnostic accuracy studies for patient care. BMJ 344: e3999.
6. Fall K, Garmo H, Andrén O, Bill-Axelson A, Adolfsson J, et al. (2007) Prostate-specific antigen levels as a predictor of lethal prostate cancer. J Natl Cancer Inst 99: 526-532.
7. Steyerberg EW, Vickers AJ, Cook NR, Gerds T, Gonen M, et al. (2010) Assessing the performance of prediction models: a framework for some traditional and novel measures. Epidemiology 21: 128-138.
8. Baker SG, Cook NR, Vickers A, Kramer BS, (2009) Using relative utility curves to evaluate risk prediction. J R Soc Ser A Stat Soc 172: 729-748.
9. Pencina MJ, D'Agostino RB, Steyerberg EW, (2011) Extension of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med 30: 11-21.
10. Vickers AJ, Elkin EB, (2006) Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 26: 565-574.
11. Cook NR, (2007) Use and misuse of the receiver operating characteristic curve in risk prediction. Circulation 115: 928-935.
12. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS, (2008) Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med 27: 157-172.
13. Pepe MS, Feng Z, Huang Y, Longton G, Prentice R, et al. (2007) Integrating the predictiveness of a marker with its performance as a classifier. Am J Epidemiol 167: 362-368.
14. Baker SG, (2009) Putting risk prediction in perspective: relative utility curves. J Natl Cancer Inst 101: 1538-1542.