Grant Number:	5R01CA094893-03 Interpret this number
Primary Investigator:	Fine, Jason
Organization:	University Of Wisconsin-Madison
Project Title:	Frailty Models and Survival Analysis in Cancer Research
Fiscal Year:	2005

DESCRIPTION (provided by applicant): The Kaplan Meier estimator, the Iogrank test, and the proportional hazards model are reported in an extremely high percentage of oncology articles in the premier medical journals. There is good reason for this orthodoxy. Their theoretical properties are well understood, they are robust, and they are available in standard statistical software. Unfortunately, the methods are based on strong simplifying assumptions and difficulties may arise when the assumptions are violated. The proposed research will investigate three such topics arising in cancer and other chronic disease studies. The unifying theme is the novel application of semiparametric frailty models to address the limitations of the existing methods. In practice, it is often the case that a terminating event (death or drop out) censors a non terminating event (morbidity), but not vice versa. The Kaplan Meier estimator for the terminating event may not be valid if censoring by the terminating event is informative. In Aim 1, I will use a frailty model to estimate the joint distribution of the events. The approach is valuable in evaluating the strength and marginal distribution of surrogate endpoints. In medical studies, predictive models based on the proportional hazards assumption are invariably misspecified. The may include prognostic factors which are dichotomized for ease of interpretation and may omit covariates which are scientifically relevant. In Aim 2, I will consider the robustness of inferences for a general class of univariate proportional hazards frailty regression models which are more flexible than the standard model but may still be misspecified. In population based studies, residual familial correlations after controlling for environmental risk factors may be indicative of a genetic etiology. Multivariate models which incorporate covariates via proportional hazards assumptions are popular. However, the approach may not be appropriate when the regression model is incorrect, as occurs when important covariates are omitted. In Aim 3, I will propose a general class of multivariate non-proportional hazards frailty regression models which are robust to such misspecification. In all of the Aims, existing methods for frailty models are unsuitable for the proposed applications and original methodology or theoretical justification is needed.




Multicategory Reclassification Statistics For Assessing Improvements In Diagnostic Accuracy
Authors: Li J. , Jiang B. , Fine J.P. .
Source: Biostatistics (oxford, England), 2013 Apr; 14(2), p. 382-94.
PMID: 23197381
Related Citations

A Regression Approach To Roc Surface, With Applications To Alzheimer's Disease
Authors: Li J. , Zhou A.X. , Fine J.P. .
Source: Science China. Mathematics, 2012 Aug; 55(8), p. 1583-1595.
PMID: 24459466
Related Citations

Competing risks regression for clustered data.
Authors: Zhou B. , Fine J. , Latouche A. , Labopin M. .
Source: Biostatistics (oxford, England), 2012 Jul; 13(3), p. 371-83.
PMID: 22045910
Related Citations

Cumulative Incidence Association Models For Bivariate Competing Risks Data
Authors: Cheng Y. , Fine J.P. .
Source: Journal Of The Royal Statistical Society. Series B, Statistical Methodology, 2012-03-01 00:00:00.0; 74(2), p. 183-202.
PMID: 22505835
Related Citations

Assessing The Dependence Of Sensitivity And Specificity On Prevalence In Meta-analysis
Authors: Li,J. , Fine,J.P. .
Source: Biostatistics (oxford, England), 2011 Oct; 12(4), p. 710-22.
PMID: 21525421
Related Citations

A proportional hazards regression model for the subdistribution with right-censored and left-truncated competing risks data.
Authors: Zhang X. , Zhang M.J. , Fine J. .
Source: Statistics In Medicine, 2011-07-20 00:00:00.0; 30(16), p. 1933-51.
EPub date: 2011-05-09 00:00:00.0.
PMID: 21557288
Related Citations

Competing Risks Regression For Stratified Data
Authors: Zhou,B. , Latouche,A. , Rocha,V. , Fine,J. .
Source: Biometrics, 2011 Jun; 67(2), p. 661-70.
PMID: 21155744
Related Citations

Weighted Area Under The Receiver Operating Characteristic Curve And Its Application To Gene Selection
Authors: Li J. , Fine J.P. .
Source: Journal Of The Royal Statistical Society. Series C, Applied Statistics, 2010 Aug; 59(4), p. 673-692.
PMID: 25125706
Related Citations

Uncovering Symptom Progression History From Disease Registry Data With Application To Young Cystic Fibrosis Patients
Authors: Yan,J. , Cheng,Y. , Fine,J.P. , Lai,H.J. .
Source: Biometrics, 2010 Jun; 66(2), p. 594-602.
PMID: 19522871
Related Citations

A Global Sensitivity Test For Evaluating Statistical Hypotheses With Nonidentifiable Models
Authors: Todem,D. , Fine,J. , Peng,L. .
Source: Biometrics, 2010 Jun; 66(2), p. 558-66.
PMID: 19645705
Related Citations

Semiparametric Regression Models And Sensitivity Analysis Of Longitudinal Data With Nonrandom Dropouts
Authors: Todem D. , Kim K. , Fine J. , Peng L. .
Source: Statistica Neerlandica, 2010-05-01 00:00:00.0; 64(2), p. 133-156.
PMID: 21258610
Related Citations

Association Analyses Of Clustered Competing Risks Data Via Cross Hazard Ratio
Authors: Cheng,Y. , Fine,J.P. , Bandeen-Roche,K. .
Source: Biostatistics (oxford, England), 2010 Jan; 11(1), p. 82-92.
PMID: 19826137
Related Citations

On Asymptotically Optimal Tests Under Loss of Identifiability in Semiparametric Models.
Authors: Song R. , Kosorok M.R. , Fine J.P. .
Source: Annals Of Statistics, 2009 Oct; 37(5A), p. 2409-2444.
PMID: 20454527
Related Citations

Nonparametric Association Analysis Of Exchangeable Clustered Competing Risks Data
Authors: Cheng,Y. , Fine,J.P. , Kosorok,M.R. .
Source: Biometrics, 2009 Jun; 65(2), p. 385-93.
PMID: 18549422
Related Citations

Summarizing differences in cumulative incidence functions.
Authors: Zhang M.J. , Fine J. .
Source: Statistics In Medicine, 2008-10-30 00:00:00.0; 27(24), p. 4939-49.
PMID: 18563792
Related Citations

Roc Analysis With Multiple Classes And Multiple Tests: Methodology And Its Application In Microarray Studies
Authors: Li,J. , Fine,J.P. .
Source: Biostatistics (oxford, England), 2008 Jul; 9(3), p. 566-76.
PMID: 18304996
Related Citations