Dealing with missing predictor values when applying clinical prediction models

Clinical Chemistry

Volumn 55, Issue 5, 2009, Pages 994-1001

  Janssen, Kristel J M ^a   Vergouwe, Yvonne ^a   Donders, A Rogier T ^b   Harrell Jr , Frank E ^c   Chen, Qingxia ^c   Grobbee, Diederick E ^a   Moons, Karel G M ^a  

^a UNIVERSITY MEDICAL CENTER UTRECHT   (Netherlands)

^b RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

^c VANDERBILT UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

D DIMER;

ADULT; ARTICLE; CALIBRATION; CARDIOVASCULAR RISK; CONTROLLED STUDY; DEEP VEIN THROMBOSIS; FEMALE; HUMAN; MAJOR CLINICAL STUDY; MALE; PREDICTION AND FORECASTING; PREDICTOR VARIABLE; PRIMARY MEDICAL CARE; VALIDATION STUDY;

COHORT STUDIES; DATA INTERPRETATION, STATISTICAL; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, BIOLOGICAL; MODELS, STATISTICAL; PREDICTIVE VALUE OF TESTS; VENOUS THROMBOSIS;

EID: 65949095017     PISSN: 00099147     EISSN: 15308561     Source Type: Journal    
DOI: 10.1373/clinchem.2008.115345     Document Type: Article

References (30)

1. Auld PA, Rudolp AJ, Avery ME, Cherry RB, Drorbaugh JE, Kay JL, Smith CA. Responsiveness and resuscitation of the newborn: the use of the Apgar score. Am J Dis Child 1961;101:713-724
2. Kannel WB, McGee D, Gordon T. A general cardiovascular risk profile: the Framingham Study. Am J Cardiol 1976;38:46-51.
3. Altman DG, Royston P. What do we mean by validating a prognostic model? Stat Med 2000;19:453-473
4. Harrell FE, Jr, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med 1996;15:361-387
5. Justice AC, Covinsky KE, Berlin JA. Assessing the generalizability of prognostic information. Ann Intern Med 1999;130:515-524 (Pubitemid 29135805)
6. Reilly BM, Evans AT. Translating clinical research into clinical practice: impact of using prediction rules to make decisions. Ann Intern Med 2006;144:201-209 (Pubitemid 46780691)
7. Greenland S, Finkle WD. A critical look at methods for handling missing covariates in epidemiologic regression analyses. Am J Epidemiol 1995;142:1255-1264 (Pubitemid 26006424)
8. Little RJ. Regression with missing X's: a review. J Am Stat Assoc 1992;87:1227-1237
9. Little RJ, Rubin DB. Statistical analysis with missing data. Hoboken (NJ): John Wiley & Sons; 1987. 278 p.
10. Rubin DB. Multiple imputation for nonresponse in surveys. Hoboken (NJ): John Wiley & Sons; 1987. 285 p.
11. Rubin DB. Multiple Imputation after 18+ years. J Am Stat Assoc 1996;91:473-489 (Pubitemid 126092304)
12. Schafer JL. Analysis of incomplete multivariate data. London: Chapman & Hall/CRC; 1997. 420 p. (Monographs on statistics and applied probability 72).
13. Donders AR, van der Heijden GJ, Stijnen T, Moons KG. Review: a gentle introduction to imputation of missing values. J Clin Epidemiol 2006;59:1087-1091 (Pubitemid 44374314)
14. Moons KG, Donders RA, Stijnen T, Harrell FE, Jr. Using the outcome for imputation of missing predictor values was preferred. J Clin Epidemiol 2006;59:1092-1101
15. Rubin DB, Schenker N. Multiple imputation in health-care databases: an overview and some applications. Stat Med 1991;10:585-598
16. Schafer JL, Graham JW. Missing data: our view of the state of the art. Psychol Methods 2002;7:147-177
17. Bleeker SE, Moons KG, Derksen-Lubsen G, Grobbee DE, Moll HA. Predicting serious bacterial infection in young children with fever without apparent source. Acta Paediatr 2001;90:1226-1232 (Pubitemid 33144982)
18. Hirsh J, Hoak J. Management of deep vein thrombosis and pulmonary embolism: a statement for healthcare professionals. Council on Thrombosis (in consultation with the Council on Cardiovascular Radiology), American Heart Association. Circulation 1996;93:2212-2245
19. Oudega R, Moons KG, Hoes AW. Ruling out deep venous thrombosis in primary care: a simple diagnostic algorithm including D-dimer testing. Thromb Haemost 2005;94:200-205 (Pubitemid 40974725)
20. Toll DB, Oudega R, Bulten RJ, Hoes AW, Moons KG. Excluding deep vein thrombosis safely in primary care. J Fam Pract 2006;55:613-618 (Pubitemid 44077973)
21. Oudega R, Moons KG, Hoes AW. Limited value of patient history and physical examination in diagnosing deep vein thrombosis in primary care. Fam Pract 2005;22:86-91. (Pubitemid 40309610)
22. Oudega R, Hoes AW, Moons KG. The Wells rule does not adequately rule out deep venous thrombosis in primary care patients. Ann Intern Med 2005;143:100-107 (Pubitemid 40994300)
23. Toll DB, Oudega R, Vergouwe Y, Moons KG, Hoes AW. A new diagnostic rule for deep vein thrombosis: safety and efficiency in clinically relevant subgroups. Fam Pract 2008;25:3-8.
24. Harrell FE, Jr. Regression modeling strategies: with applications to linear models, logistic regression, and survival analysis. New York: Springer- Verlag; 2001. 568 p.
25. Steyerberg EW, Eijkemans MJ, Harrell FE, Jr, Habbema JD. Prognostic modelling with logistic regression analysis: a comparison of selection and estimation methods in small data sets. Stat Med 2000;19:1059-1079 (Pubitemid 30238915)
26. Marshall G, Warner B, MaWhinney S, Hammermeister K. Prospective prediction in the presence of missing data. Stat Med 2002;21:561-570 (Pubitemid 34141377)
27. Harrell FE, Jr, Lee KL, Califf RM, Pryor DB, Rosati RA. Regression modelling strategies for improved prognostic prediction. Stat Med 1984;3:143-152 (Pubitemid 14052973)
28. Hanley J, McNeil B. A method of comparing the areas under receiver operating characteristic curves derived from the same cases. Radiology 1983;148:839-843
29. Miller ME, Langefeld CD, Tierney WM, Hui SL, McDonald CJ. Validation of probabilistic predictions. Med Decis Making 1993;13:49-58. (Pubitemid 23019919)
30. Cox DR. Two further applications of a model for binary regression. Biometrika 1958;45:562-565