Grant Number:	1R01CA137420-01A1 Interpret this number
Primary Investigator:	Satagopan, Jaya
Organization:	Sloan-Kettering Inst Can Research
Project Title:	Study of Exposures, Behaviors, and Biomarkers in Cancer Epidemiology
Fiscal Year:	2009

DESCRIPTION (provided by applicant): It is now widely accepted that both environmental exposures and genetic factors contribute to most diseases. Cancer epidemiology studies often ascertain exposures and behavioral factors (referred to generally as exposure factors) through survey instruments (for example, questionnaires), and typically examine variants or blood levels of exposures or markers of exposures (biomarkers) in candidate genes or pathways to identify risk factors for disease or for disease precursors. The responses to questionnaire items may be correlated. Similarly, the biomarkers may be correlated due to common underlying biological function or linkage disequilibrium and may occur at a low frequency. These render data analysis a challenging task. Although analytic methods have been developed to address this challenge, there continues to be a need to investigate novel approaches for efficient analyses of exposure factors and biomarkers, and to develop optimal study designs for follow-up research. The long-term goals of this proposal are to address these needs through the following four specific aims. In Aim 1 we will examine how to conduct efficient analysis of correlated exposure factors and biomarkers. In Aim 2 we will examine how to evaluate the effects of routes of exposures and underlying biological characteristics in an efficient manner. The etiologic effects of the risk factors are likely to be complex due to a number of reasons, including gene-exposure interactions. Aim 3 will examine parsimonious analytic methods for evaluating interactions. In Aim 4 we will develop a novel study design for sampling an informative sub-population from an established cohort to evaluate additional risk factors, when evaluation of the full cohort is not feasible due to logistic or cost considerations. Our proposal is motivated by several collaborative studies. We will conduct simulations to investigate the properties of the methods proposed under each aim, and derive guidelines for their use in practical settings. We will conduct an empirical evaluation of the methods and guidelines using data from the collaborative studies. Our proposal has two major objectives. First, we intend to develop and improve research designs and methodologies for evaluating correlated risk factors in cancer epidemiology studies. Second, we intend to assess the practical relevance of these methods by conducting empirical investigations using data from various studies. We anticipate that the insights gained from these investigations will have a significant impact on our understanding of analysis and study designs for identifying risk factors of public health relevance in an efficient and parsimonious manner. PUBLIC HEALTH RELEVANCE: It is widely accepted that both environmental exposures and genetic factors contribute to most diseases. Cancer epidemiology studies often ascertain exposures and behavioral factors through survey instruments (for example, questionnaires), and examine susceptibility variants in candidate genes or blood levels of exposures or markers of exposures to identify risk factors for disease traits. The responses to questionnaire items may be correlated. Similarly, the genetic variants may exhibit correlation due to their common underlying biological function and may occur at a low frequency. These render data analysis a challenging task. The long-term goals of this proposal are to investigate novel methods for efficient analyses of correlated risk factors, and to develop optimal study designs for follow-up research.




Estimating Additive Interaction Effect in Stratified Two-Phase Case-Control Design.
Authors: Ni A. , Satagopan J.M. .
Source: Human Heredity, 2019; 84(2), p. 90-108.
EPub date: 2019-10-21 00:00:00.0.
PMID: 31634888
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A pilot study of neuropsychological functions, APOE and amyloid imaging in patients with gliomas.
Authors: Correa D.D. , Kryza-Lacombe M. , Zhou X. , Baser R.E. , Beattie B.J. , Beiene Z. , Humm J. , DeAngelis L.M. , Orlow I. , Weber W. , et al. .
Source: Journal Of Neuro-oncology, 2018 Feb; 136(3), p. 613-622.
EPub date: 2017-11-22 00:00:00.0.
PMID: 29168082
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A reconstructed melanoma data set for evaluating differential treatment benefit according to biomarker subgroups.
Authors: Satagopan J.M. , Iasonos A. , Kanik J.G. .
Source: Data In Brief, 2017 Jun; 12, p. 667-675.
EPub date: 2017-05-05 00:00:00.0.
PMID: 28560273
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Measuring differential treatment benefit across marker specific subgroups: The choice of outcome scale.
Authors: Satagopan J.M. , Iasonos A. .
Source: Contemporary Clinical Trials, 2017-02-22 00:00:00.0; , .
EPub date: 2017-02-22 00:00:00.0.
PMID: 28254404
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Statistical Genetic Terminology.
Authors: Elston R.C. , Satagopan J. , Sun S. .
Source: Methods In Molecular Biology (clifton, N.j.), 2017; 1666, p. 1-9.
PMID: 28980238
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COMT, BDNF, and DTNBP1 polymorphisms and cognitive functions in patients with brain tumors.
Authors: Correa D.D. , Satagopan J. , Cheung K. , Arora A.K. , Kryza-Lacombe M. , Xu Y. , Karimi S. , Lyo J. , DeAngelis L.M. , Orlow I. .
Source: Neuro-oncology, 2016 10; 18(10), p. 1425-33.
EPub date: 2016-04-18 00:00:00.0.
PMID: 27091610
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Bayes And Empirical Bayes Methods For Reduced Rank Regression Models In Matched Case-control Studies
Authors: Satagopan J.M. , Sen A. , Zhou Q. , Lan Q. , Rothman N. , Langseth H. , Engel L.S. .
Source: Biometrics, 2016 Jun; 72(2), p. 584-95.
PMID: 26575519
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Quantifying Treatment Benefit In Molecular Subgroups To Assess A Predictive Biomarker
Authors: Iasonos A. , Chapman P.B. , Satagopan J.M. .
Source: Clinical Cancer Research : An Official Journal Of The American Association For Cancer Research, 2016-05-01 00:00:00.0; 22(9), p. 2114-20.
PMID: 27141007
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Statistical Interactions from a Growth Curve Perspective.
Authors: Devlin S.M. , Satagopan J.M. .
Source: Human Heredity, 2016; 82(1-2), p. 21-36.
EPub date: 2017-07-26 00:00:00.0.
PMID: 28743105
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Sunburn, Sun Exposure, And Sun Sensitivity In The Study Of Nevi In Children
Authors: Satagopan J.M. , Oliveria S.A. , Arora A. , Marchetti M.A. , Orlow I. , Dusza S.W. , Weinstock M.A. , Scope A. , Geller A.C. , Marghoob A.A. , et al. .
Source: Annals Of Epidemiology, 2015 Nov; 25(11), p. 839-43.
PMID: 26096189
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Predictors and long-term reproducibility of urinary phthalate metabolites in middle-aged men and women living in urban Shanghai.
Authors: Starling A.P. , Engel L.S. , Calafat A.M. , Koutros S. , Satagopan J.M. , Yang G. , Matthews C.E. , Cai Q. , Buckley J.P. , Ji B.T. , et al. .
Source: Environment International, 2015 Nov; 84, p. 94-106.
PMID: 26255822
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Prognostic And Predictive Values And Statistical Interactions In The Era Of Targeted Treatment
Authors: Satagopan J.M. , Iasonos A. , Zhou Q. .
Source: Genetic Epidemiology, 2015 Nov; 39(7), p. 509-17.
PMID: 26349638
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Genetic Factors Associated With Naevus Count And Dermoscopic Patterns: Preliminary Results From The Study Of Nevi In Children (sonic)
Authors: Orlow I. , Satagopan J.M. , Berwick M. , Enriquez H.L. , White K.A. , Cheung K. , Dusza S.W. , Oliveria S.A. , Marchetti M.A. , Scope A. , et al. .
Source: The British Journal Of Dermatology, 2015 Apr; 172(4), p. 1081-9.
PMID: 25307738
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Statistical Interactions And Bayes Estimation Of Log Odds In Case-control Studies
Authors: Satagopan J.M. , Olson S.H. , Elston R.C. .
Source: Statistical Methods In Medical Research, 2015-01-12 00:00:00.0; , .
PMID: 25586327
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Apoe Polymorphisms And Cognitive Functions In Patients With Brain Tumors
Authors: Correa D.D. , Satagopan J. , Baser R.E. , Cheung K. , Richards E. , Lin M. , Karimi S. , Lyo J. , DeAngelis L.M. , Orlow I. .
Source: Neurology, 2014-07-22 00:00:00.0; 83(4), p. 320-7.
PMID: 24944262
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Sun Exposure, Vitamin D Receptor Genetic Variants, And Risk Of Breast Cancer In The Agricultural Health Study
Authors: Engel L.S. , Satagopan J. , Sima C.S. , Orlow I. , Mujumdar U. , Coble J. , Roy P. , Yoo S. , Sandler D.P. , Alavanja M.C. .
Source: Environmental Health Perspectives, 2014 Feb; 122(2), p. 165-71.
PMID: 24252436
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Allergies and risk of pancreatic cancer: a pooled analysis from the Pancreatic Cancer Case-Control Consortium.
Authors: Olson S.H. , Hsu M. , Satagopan J.M. , Maisonneuve P. , Silverman D.T. , Lucenteforte E. , Anderson K.E. , Borgida A. , Bracci P.M. , Bueno-de-Mesquita H.B. , et al. .
Source: American Journal Of Epidemiology, 2013-09-01 00:00:00.0; 178(5), p. 691-700.
EPub date: 2013-09-01 00:00:00.0.
PMID: 23820785
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Evaluation Of Removable Statistical Interaction For Binary Traits
Authors: Satagopan J.M. , Elston R.C. .
Source: Statistics In Medicine, 2013-03-30 00:00:00.0; 32(7), p. 1164-90.
PMID: 23018341
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Variants in activators and downstream targets of ATM, radiation exposure, and contralateral breast cancer risk in the WECARE study.
Authors: Brooks J.D. , Teraoka S.N. , Reiner A.S. , Satagopan J.M. , Bernstein L. , Thomas D.C. , Capanu M. , Stovall M. , Smith S.A. , Wei S. , et al. .
Source: Human Mutation, 2012 Jan; 33(1), p. 158-64.
PMID: 21898661
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Genetic Terminology
Authors: Elston,R.C. , Satagopan,J.M. , Sun,S. .
Source: Methods In Molecular Biology (clifton, N.j.), 2012; 850, p. 1-9.
PMID: 22307690
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Clinical And Dermoscopic Stability And Volatility Of Melanocytic Nevi In A Population-based Cohort Of Children In Framingham School System
Authors: Scope,A. , Dusza,S.W. , Marghoob,A.A. , Satagopan,J.M. , Braga Casagrande Tavoloni,J. , Psaty,E.L. , Weinstock,M.A. , Oliveria,S.A. , Bishop,M. , Geller,A.C. , et al. .
Source: The Journal Of Investigative Dermatology, 2011 Aug; 131(8), p. 1615-21.
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Properties Of Preliminary Test Estimators And Shrinkage Estimators For Evaluating Multiple Exposures - Application To Questionnaire Data From The Sonic Study
Authors: Satagopan J.M. , Zhou Q. , Oliveria S.A. , Dusza S.W. , Weinstock M.A. , Berwick M. , Halpern A.C. .
Source: Journal Of The Royal Statistical Society. Series C, Applied Statistics, 2011-08-01 00:00:00.0; 60(4), p. 619-632.
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Study Of Nevi In Children (sonic): Baseline Findings And Predictors Of Nevus Count
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Source: American Journal Of Epidemiology, 2009-01-01 00:00:00.0; 169(1), p. 41-53.
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Normalization Method For Transcriptional Studies Of Heterogeneous Samples--simultaneous Array Normalization And Identification Of Equivalent Expression
Authors: Qin,L.X. , Satagopan,J.M. .
Source: Statistical Applications In Genetics And Molecular Biology, 2009; 8(1), p. Article 10.
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Two-stage Designs For Gene-disease Association Studies With Sample Size Constraints
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Source: Biometrics, 2004 Sep; 60(3), p. 589-97.
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Age-adjusted International Prognostic Index Predicts Autologous Stem Cell Transplantation Outcome For Patients With Relapsed Or Primary Refractory Diffuse Large B-cell Lymphoma
Authors: Hamlin,P.A. , Zelenetz,A.D. , Kewalramani,T. , Qin,J. , Satagopan,J.M. , Verbel,D. , Noy,A. , Portlock,C.S. , Straus,D.J. , Yahalom,J. , et al. .
Source: Blood, 2003-09-15 00:00:00.0; 102(6), p. 1989-96.
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Optimal Two-stage Genotyping In Population-based Association Studies
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Source: Genetic Epidemiology, 2003 Sep; 25(2), p. 149-57.
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Two-stage Designs For Gene-disease Association Studies
Authors: Satagopan J.M. , Verbel D.A. , Venkatraman E.S. , Offit K.E. , Begg C.B. .
Source: Biometrics, 2002 Mar; 58(1), p. 163-70.
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