Prospective accuracy for longitudinal markers

Biometrics

Volumn 63, Issue 2, 2007, Pages 332-341

  Zheng, Yingye ^a   Heagerty, Patrick J ^b  

^a Fred Hutchinson Cancer Research Center   (United States)

^b UNIVERSITY OF WASHINGTON   (United States)

Author keywords

Longitudinal data; Multivariate survival outcome; Sensitivity; Specificity

Indexed keywords

DIAGNOSIS;

DIAGNOSTIC ACCURACY; FUNCTION OF TIME; LONGITUDINAL DATA; MEDICAL DECISION MAKING; MULTIVARIATE SURVIVAL OUTCOME; PROSPECTIVES; RECEIVER OPERATING CHARACTERISTIC CURVES; REPEATED MEASUREMENTS; SENSITIVITY; SPECIFICITY;

BIOMETRICS;

BIOLOGICAL MARKER; CD4 ANTIGEN;

ACQUIRED IMMUNE DEFICIENCY SYNDROME; DISEASE INCIDENCE; DISEASE SEVERITY; DISEASE TREATMENT; ESTIMATION METHOD; HEALTH STATUS; MORTALITY; SENSITIVITY ANALYSIS; SURVIVAL;

ARTICLE; BIVARIATE ANALYSIS; DISCRIMINANT ANALYSIS; DISEASE MARKER; DISEASE PREDISPOSITION; FORECASTING; HEALTH STATUS; INCIDENCE; INFORMATION PROCESSING; LONGITUDINAL STUDY; MATHEMATICAL MODEL; MEDICAL DECISION MAKING; METHODOLOGY; MORTALITY; PROGNOSIS; PROSPECTIVE STUDY; ROC CURVE; STATISTICAL ANALYSIS; TIME;

EID: 34547662942     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2006.00726.x     Document Type: Article

References (21)

1. Cai, T. and Pepe, M. S. (2002). Semiparametric receiver operating characteristic analysis to evaluate biomarkers for disease. Journal of the American Statistical Association 97, 1099 1107.
2. Etzioni, R., Pepe, M., Longton, G., Hu, C., and Goodman, G. (1999). Incorporating the time dimension in receiver operating characteristic curves: A case study of prostate cancer. Medical Decision Making 19, 242 251.
3. Hanley, J. A. (1989). Receiver operating characteristic ROC methodology: The state of the art. Critical Reviews in Diagnostic Imaging 29, 307 335.
4. Heagerty, P. and Zheng, Y. (2005). Survival model accuracy and ROC curves. Biometrics 61, 92 105.
5. Heagerty, P. J. and Pepe, M. S. (1999). Semiparametric estimation of regression quantiles with application to standardizing weight for height and age in US children. Applied Statistics 48, 533 551.
6. Heagerty, P. J., Lumley, T., and Pepe, M. S. (2000). Time-dependent ROC curves for censored survival data and a diagnostic marker. Biometrics 56, 337 344.
7. Henderson, R., Diggle, P., and Dobson, A. (1997). A joint model for survival and longitudinal data measured with error. Biometrics 53, 330 339.
8. Kaslow, R. A., Ostrow, D. G., Detels, R., Phair, J. P., Polk, B. F., and Rinaldo, C. R. A. (1987). The multicentre aids cohort study: Rationale, organization, and selected characteristics of the participants. American Journal of Epidemiology 1, 310 318.
9. Lin, H., Scharfstein, D., and Rosenheck, R. (2004). Analysis of longitudinal data with informative follow-up. Journal of the Royal Statistical Society Series B 66, 791 813.
10. Lipsitz, S. R., Fitzmaurice, G. M., Ibrahim, J. G., Gelber, R., and Lipshultz, S. (2002). Parameter estimation in longitudinal studies with outcome-dependent follow-up. Biometrics 58, 621 630.
11. Little, R. J. A. and Rubin, D. B. (1987). Statistical Analysis with Missing Data. New York : Wiley.
12. Margolick, J. B., Muñoz, A., Donnenberg, A. D., Park, L. P., Galai, N., Giorgi, J. V., O'Gorman, M. R. G., and Ferbas, J. (1995). Failure of T-cell homeostasis preceding aids in HIV-1 infection. Nature Medicine 1, 674 680.
13. Pepe, M. S. and Couper, D. (1997). Modeling partly conditional means with longitudinal data. Journal of the American Statistical Association 92, 991 998.
14. Ransohoff, D. (2004). Rules of evidence for cancer molecular-marker discovery and validation. Nature Reviews Cancer 4, 309 314.
15. Shi, M., Taylor, J. M. G., Currier, R., Tang, H., Hoover, D., Chmiel, J., and Bryant, J. (1996). Replacing time since human immunodeficiency virus infection by marker values in predicting residual time to acquired immunodeficiency syndrome diagnosis. Journal of Acquired Immune Deficiency Syndromes 12, 309 316.
16. Slate, E. H. and Turnbull, B. W. (2000). Statistical models for longitudinal biomarkers of disease onset. Statistics in Medicine 19, 617 637.
17. Tsiatis, A. A., DeGruttola, V., and Wulfsohn, M. S. (1995). Modeling the relationship of survival to longitudinal data measured with error. Applications to survival and CD4 counts in patients with AIDS. Journal of the American Statistical Association 90, 27 37.
18. Wulfsohn, M. S. and Tsiatis, A. A. (1997). A joint model for survival and longitudinal data measured with error. Biometrics 53, 330 339.
19. Zheng, Y. and Heagerty, P. (2004). Semiparametric estimation of time-dependent ROC curves for longitudinal marker data. Biostatistics 5, 615 632.
20. Zheng, Y. and Heagerty, P. (2005). Partly conditional survival models for longitudinal data. Biometrics 61, 379 391.
21. Zweig, M. H. and Campbell, G. (1993). Receiver-operator characteristic plots: A fundamental evaluation tool in clinical medicine. Clinical Chemistry 39, 561 577.