Grant Number:	1R01CA117841-01A2 Interpret this number
Primary Investigator:	Richardson, David
Organization:	Univ Of North Carolina Chapel Hill
Project Title:	Cohort Analysis Methods for Occupational Cancer Studies
Fiscal Year:	2007

DESCRIPTION (provided by applicant): Epidemiologic investigations of associations between protracted low level occupational exposures and cancer mortality routinely encounter the following problems: 1) potential latency effects between exposure and disease; 2) potential bias resulting from exposure measurement error; and, 3) potential bias resulting from health-related selection out of employment (i.e., the healthy worker survivor effect). The identified problems are of direct relevance to worker protection, as each is a source of bias that may lead to spurious conclusions about the adverse effects of occupational hazards. The goal of this project is to improve the analytical tools available to address these problems. We will develop a conceptual description of each problem, develop a simple analytical tool (or tools) to reduce or eliminate the potential bias, evaluate the proposed analytical method via simulation analyses, and then illustrate the application of the proposed method using empirical data. We will begin by exploring the use of flexible latency models for occupational cancer studies. Via simulation analyses, we will evaluate the use of these flexible models for reducing bias due to mis-specification of exposure lag assumptions; and, in empirical analyses of rubber hydrochloride and asbestos textile worker cohort data, we will illustrate the application of these methods. Next, we will develop an approach to control for bias that can arise when grouped data are used to assign exposure scores, as in a job-exposure matrix. The use of assigned exposure values is often assumed to result in a Berkson error model that does not produce biased risk estimates. Using simulated data, we will evaluate the conditions under which the Berkson model applies, and develop approaches to exploit this error model to reduce bias. We will illustrate these approaches with empirical data from a cohort study of electrical utility workers. Finally, we will identify the conditions under which non-standard regression methods (e.g., G-estimation) are necessary in cohort studies to control for the healthy worker survivor effect. We will use simulation methods to explore these conditions, and develop simple analytical tools to guide investigators on when to use G-estimation. The proposal addresses the NORA priority area on cancer research methods. The results of the proposed research will further improve the analytic methods used in occupational cancer studies.




The Parametric G-formula For Time-to-event Data: Intuition And A Worked Example
Authors: Keil A.P. , Edwards J.K. , Richardson D.B. , Naimi A.I. , Cole S.R. .
Source: Epidemiology (cambridge, Mass.), 2014 Nov; 25(6), p. 889-97.
PMID: 25140837
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Occupational Radon Exposure And Lung Cancer Mortality: Estimating Intervention Effects Using The Parametric G-formula
Authors: Edwards J.K. , McGrath L.J. , Buckley J.P. , Schubauer-Berigan M.K. , Cole S.R. , Richardson D.B. .
Source: Epidemiology (cambridge, Mass.), 2014 Nov; 25(6), p. 829-34.
PMID: 25192403
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Accounting For Outcome Misclassification In Estimates Of The Effect Of Occupational Asbestos Exposure On Lung Cancer Death
Authors: Edwards J.K. , Cole S.R. , Chu H. , Olshan A.F. , Richardson D.B. .
Source: American Journal Of Epidemiology, 2014-03-01 00:00:00.0; 179(5), p. 641-7.
PMID: 24352593
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Estimating The Effect Of Cumulative Occupational Asbestos Exposure On Time To Lung Cancer Mortality: Using Structural Nested Failure-time Models To Account For Healthy-worker Survivor Bias
Authors: Naimi A.I. , Cole S.R. , Hudgens M.G. , Richardson D.B. .
Source: Epidemiology (cambridge, Mass.), 2014 Mar; 25(2), p. 246-54.
PMID: 24487207
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Causal Inference In Occupational Epidemiology: Accounting For The Healthy Worker Effect By Using Structural Nested Models
Authors: Naimi A.I. , Richardson D.B. , Cole S.R. .
Source: American Journal Of Epidemiology, 2013-12-15 00:00:00.0; 178(12), p. 1681-6.
PMID: 24077092
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A Bayesian Approach To Strengthen Inference For Case-control Studies With Multiple Error-prone Exposure Assessments
Authors: Zhang J. , Cole S.R. , Richardson D.B. , Chu H. .
Source: Statistics In Medicine, 2013-11-10 00:00:00.0; 32(25), p. 4426-37.
PMID: 23661263
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Assessing The Component Associations Of The Healthy Worker Survivor Bias: Occupational Asbestos Exposure And Lung Cancer Mortality
Authors: Naimi A.I. , Cole S.R. , Hudgens M.G. , Brookhart M.A. , Richardson D.B. .
Source: Annals Of Epidemiology, 2013 Jun; 23(6), p. 334-41.
PMID: 23683709
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Analysis Of Occupational Asbestos Exposure And Lung Cancer Mortality Using The G Formula
Authors: Cole S.R. , Richardson D.B. , Chu H. , Naimi A.I. .
Source: American Journal Of Epidemiology, 2013-05-01 00:00:00.0; 177(9), p. 989-96.
PMID: 23558355
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Accounting For Misclassified Outcomes In Binary Regression Models Using Multiple Imputation With Internal Validation Data
Authors: Edwards J.K. , Cole S.R. , Troester M.A. , Richardson D.B. .
Source: American Journal Of Epidemiology, 2013-05-01 00:00:00.0; 177(9), p. 904-12.
PMID: 24627573
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Missing Doses In The Life Span Study Of Japanese Atomic Bomb Survivors
Authors: Richardson D.B. , Wing S. , Cole S.R. .
Source: American Journal Of Epidemiology, 2013-03-15 00:00:00.0; 177(6), p. 562-8.
PMID: 23429722
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Random Effects Regression Models For Trends In Standardised Mortality Ratios
Authors: Richardson D.B. , Cole S.R. , Chu H. .
Source: Occupational And Environmental Medicine, 2013 Feb; 70(2), p. 133-9.
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Regression Models For The Effects Of Exposure Rate And Cumulative Exposure
Authors: Richardson D.B. , Cole S.R. , Langholz B. .
Source: Epidemiology (cambridge, Mass.), 2012 Nov; 23(6), p. 892-9.
PMID: 23007044
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Background Stratified Poisson Regression Analysis Of Cohort Data
Authors: Richardson D.B. , Langholz B. .
Source: Radiation And Environmental Biophysics, 2012 Mar; 51(1), p. 15-22.
PMID: 22193911
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Model Averaging In The Analysis Of Leukemia Mortality Among Japanese A-bomb Survivors
Authors: Richardson D.B. , Cole S.R. .
Source: Radiation And Environmental Biophysics, 2012 Mar; 51(1), p. 93-5; discussion 97-100.
PMID: 22228541
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Bayesian posterior distributions without Markov chains.
Authors: Cole S.R. , Chu H. , Greenland S. , Hamra G. , Richardson D.B. .
Source: American Journal Of Epidemiology, 2012-03-01 00:00:00.0; 175(5), p. 368-75.
EPub date: 2012-03-01 00:00:00.0.
PMID: 22306565
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Lagging Exposure Information In Cumulative Exposure-response Analyses
Authors: Richardson D.B. , Cole S.R. , Chu H. , Langholz B. .
Source: American Journal Of Epidemiology, 2011-12-15 00:00:00.0; 174(12), p. 1416-22.
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A Comparison Of Methods To Estimate The Hazard Ratio Under Conditions Of Time-varying Confounding And Nonpositivity
Authors: Naimi A.I. , Cole S.R. , Westreich D.J. , Richardson D.B. .
Source: Epidemiology (cambridge, Mass.), 2011 Sep; 22(5), p. 718-23.
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Hierarchical Latency Models For Dose-time-response Associations
Authors: Richardson D.B. , MacLehose R.F. , Langholz B. , Cole S.R. .
Source: American Journal Of Epidemiology, 2011-03-15 00:00:00.0; 173(6), p. 695-702.
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Bias In The Estimation Of Exposure Effects With Individual- Or Group-based Exposure Assessment
Authors: Kim H.M. , Richardson D. , Loomis D. , Van Tongeren M. , Burstyn I. .
Source: Journal Of Exposure Science & Environmental Epidemiology, 2011 Mar-Apr; 21(2), p. 212-21.
PMID: 20179749
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Flexible Modeling Of The Cumulative Effects Of Time-dependent Exposures On The Hazard
Authors: Hauptmann M. , Richardson D.B. .
Source: Statistics In Medicine, 2011-01-30 00:00:00.0; 30(2), p. 197; author reply 198-9.
PMID: 21204123
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Discrete Time Hazards Models For Occupational And Environmental Cohort Analyses
Authors: Richardson D.B. .
Source: Occupational And Environmental Medicine, 2010 Jan; 67(1), p. 67-71.
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Latency Models For Analyses Of Protracted Exposures
Authors: Richardson D.B. .
Source: Epidemiology (cambridge, Mass.), 2009 May; 20(3), p. 395-9.
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