Grant Number:	2R01CA129102-04 Interpret this number
Primary Investigator:	Taylor, Jeremy
Organization:	University Of Michigan At Ann Arbor
Project Title:	Statistical Methods for Cancer Biomarkers
Fiscal Year:	2012

DESCRIPTION (provided by applicant): Biomarkers in cancer research are considered a central component of the expected improvements in prevention, detection, treatment and monitoring. There are potentially useful in many different types of studies and for many different purposes. Critical questions are whether they are valid to use, how can they be utilized in a valid and efficient way, and then if they are used how confident is one in the conclusions that are obtained. The use of biomarkers to advance understanding in cancer science has great potential, but also has some risks. Biomarkers are subject to uncertainty in their measurement, they may not be measuring exactly the quantity of interest, and since they are not explicitly measures of symptoms their use to aid in decision making or evaluation of therapies in a clinical setting is subject to uncertainty. Thus careful analysis of data from studies that involve biomarkers is crucial. There are many statistical challenges that arise in such studies. This application is concerned with developing, evaluating and applying statistical methods for data that involves biomarkers. The first aim is concerned with adding biomarkers to prediction models that may be used to stratify or classify patients. In this aim we develop approaches for integrating data from other sources to improve the prediction models. This research will have broad applicability. Innovative aspects involve the use of targeted ridge regression, multi-kernel machine modeling, and importance sampling to incorporate information from the literature. The second aim is concerned with clinical trials where the biomarker is to be used to evaluate a therapy as a surrogate endpoint. Because of the nature of the scientific question causal modeling is very natural in this context. We propose to develop both potential outcomes and structural causal models. We will investigate both single trial and multi trial settings with different endpoint types. The third aim is concerned with therapies that may be effective only for a subgroup of patients, and to be useful this subgroup is determined by a small number of predictive biomarkers. For data from randomized clinical trials we suggest a unified modeling approach, and will investigate the use of single index models with variable selection and multivariate partial least squares to aid in the subgroup identification. Inference following subgroup identification is challenging, we suggest an innovative scheme to simulate data under an appropriate null distribution. All 3 aims in this proposal address fundamental and significant problems in translational oncology research. Successful completion of the aims will have an impact both in understanding and utilizing biomarkers and also in developing statistical methodology that can be more broadly applicable to other fields. PUBLIC HEALTH RELEVANCE: Biomarkers are considered a central component of the expected improvements in prevention, detection, treatment and monitoring in cancer. Critical questions about biomarkers are when and whether they are valid to use, how can they be utilized in a valid and efficient way, and then if they are used how confident is one in the conclusions that are obtained. This proposal is concerned with developing proper and efficient statistical methods for evaluation of biomarker data.




Improving prediction of linear regression models by integrating external information from heterogeneous populations: James-Stein estimators.
Authors: Han P. , Li H. , Park S.K. , Mukherjee B. , Taylor J.M.G. .
Source: Biometrics, 2024-07-01 00:00:00.0; 80(3), .
PMID: 39101548
Related Citations

Shrinkage priors for isotonic probability vectors and binary data modeling, with applications to dose-response modeling.
Authors: Boonstra P.S. , Owen D.R. , Kang J. .
Source: Pharmaceutical Statistics, 2024-02-23 00:00:00.0; , .
EPub date: 2024-02-23 00:00:00.0.
PMID: 38400582
Related Citations

Robust data integration from multiple external sources for generalized linear models with binary outcomes.
Authors: Choi K. , Taylor J.M.G. , Han P. .
Source: Biometrics, 2024-01-29 00:00:00.0; 80(1), .
PMID: 38364808
Related Citations

surtvep: An R package for estimating time-varying effects.
Authors: Luo L. , Wu W. , Taylor J.M.G. , Kang J. , Kleinsasser M.J. , He K. .
Source: Journal Of Open Source Software, 2024; 9(98), .
EPub date: 2024-06-28 00:00:00.0.
PMID: 39717690
Related Citations

Surrogacy validation for time-to-event outcomes with illness-death frailty models.
Authors: Roberts E.K. , Elliott M.R. , Taylor J.M.G. .
Source: Biometrical Journal. Biometrische Zeitschrift, 2023-09-29 00:00:00.0; , p. e2200324.
EPub date: 2023-09-29 00:00:00.0.
PMID: 37776057
Related Citations

Using information criteria to select smoothing parameters when analyzing survival data with time-varying coefficient hazard models.
Authors: Luo L. , He K. , Wu W. , Taylor J.M. .
Source: Statistical Methods In Medical Research, 2023 Sep; 32(9), p. 1664-1679.
EPub date: 2023-07-05 00:00:00.0.
PMID: 37408385
Related Citations

Integrating Information from Existing Risk Prediction Models with No Model Details.
Authors: Han P. , Taylor J.M.G. , Mukherjee B. .
Source: The Canadian Journal Of Statistics = Revue Canadienne De Statistique, 2023 Jun; 51(2), p. 355-374.
EPub date: 2022-04-15 00:00:00.0.
PMID: 37346757
Related Citations

A synthetic data integration framework to leverage external summary-level information from heterogeneous populations.
Authors: Gu T. , Taylor J.M.G. , Mukherjee B. .
Source: Biometrics, 2023-03-06 00:00:00.0; , .
EPub date: 2023-03-06 00:00:00.0.
PMID: 36876883
Related Citations

Data integration: exploiting ratios of parameter estimates from a reduced external model.
Authors: Taylor J.M.G. , Choi K. , Han P. .
Source: Biometrika, 2023 Mar; 110(1), p. 119-134.
EPub date: 2022-04-12 00:00:00.0.
PMID: 36798840
Related Citations

Survival prediction models: an introduction to discrete-time modeling.
Authors: Suresh K. , Severn C. , Ghosh D. .
Source: Bmc Medical Research Methodology, 2022-07-26 00:00:00.0; 22(1), p. 207.
EPub date: 2022-07-26 00:00:00.0.
PMID: 35883032
Related Citations

MIAMI: Mutual Information-based Analysis of Multiplex Imaging data.
Authors: Seal S. , Ghosh D. .
Source: Bioinformatics (oxford, England), 2022-06-24 00:00:00.0; , .
EPub date: 2022-06-24 00:00:00.0.
PMID: 35748713
Related Citations

Utility based approach in individualized optimal dose selection using machine learning methods.
Authors: Li P. , Taylor J.M.G. , Boonstra P.S. , Lawrence T.S. , Schipper M.J. .
Source: Statistics In Medicine, 2022-03-28 00:00:00.0; , .
EPub date: 2022-03-28 00:00:00.0.
PMID: 35343595
Related Citations

Utility based approach in individualized optimal dose selection using machine learning methods.
Authors: Li P. , Taylor J.M.G. , Boonstra P.S. , Lawrence T.S. , Schipper M.J. .
Source: Statistics In Medicine, 2022-03-28 00:00:00.0; , .
EPub date: 2022-03-28 00:00:00.0.
PMID: 35343595
Related Citations

The association between inflammatory biomarkers and statin use among patients with head and neck squamous cell carcinoma.
Authors: Getz K.R. , Bellile E. , Zarins K.R. , Chinn S.B. , Taylor J.M.G. , Rozek L.S. , Wolf G.T. , Mondul A.M. .
Source: Head & Neck, 2022-03-25 00:00:00.0; , .
EPub date: 2022-03-25 00:00:00.0.
PMID: 35338544
Related Citations

Sufficient Dimension Reduction: An Information-Theoretic Viewpoint.
Authors: Ghosh D. .
Source: Entropy (basel, Switzerland), 2022-01-22 00:00:00.0; 24(2), .
EPub date: 2022-01-22 00:00:00.0.
PMID: 35205462
Related Citations

Profiling Parkinson's disease cognitive phenotypes via resting-state magnetoencephalography.
Authors: Simon O.B. , Rojas D.C. , Ghosh D. , Yang X. , Rogers S.E. , Martin C.S. , Holden S.K. , Kluger B.M. , Buard I. .
Source: Journal Of Neurophysiology, 2022-01-01 00:00:00.0; 127(1), p. 279-289.
EPub date: 2021-12-22 00:00:00.0.
PMID: 34936515
Related Citations

Multiple imputation with missing data indicators.
Authors: Beesley L.J. , Bondarenko I. , Elliot M.R. , Kurian A.W. , Katz S.J. , Taylor J.M. .
Source: Statistical Methods In Medical Research, 2021-10-13 00:00:00.0; , p. 9622802211047346.
EPub date: 2021-10-13 00:00:00.0.
PMID: 34643465
Related Citations

A novel approach to understanding Parkinsonian cognitive decline using minimum spanning trees, edge cutting, and magnetoencephalography.
Authors: Simon O.B. , Buard I. , Rojas D.C. , Holden S.K. , Kluger B.M. , Ghosh D. .
Source: Scientific Reports, 2021-10-05 00:00:00.0; 11(1), p. 19704.
EPub date: 2021-10-05 00:00:00.0.
PMID: 34611218
Related Citations

Incorporating baseline covariates to validate surrogate endpoints with a constant biomarker under control arm.
Authors: Roberts E.K. , Elliott M.R. , Taylor J.M.G. .
Source: Statistics In Medicine, 2021-09-15 00:00:00.0; , .
EPub date: 2021-09-15 00:00:00.0.
PMID: 34528260
Related Citations

Step-adjusted tree-based reinforcement learning for evaluating nested dynamic treatment regimes using test-and-treat observational data.
Authors: Tang M. , Wang L. , Gorin M.A. , Taylor J.M.G. .
Source: Statistics In Medicine, 2021-09-07 00:00:00.0; , .
EPub date: 2021-09-07 00:00:00.0.
PMID: 34490942
Related Citations

Accounting for not-at-random missingness through imputation stacking.
Authors: Beesley L.J. , Taylor J.M.G. .
Source: Statistics In Medicine, 2021-08-29 00:00:00.0; , .
EPub date: 2021-08-29 00:00:00.0.
PMID: 34459011
Related Citations

Generalizability of heterogeneous treatment effects based on causal forests applied to two randomized clinical trials of intensive glycemic control.
Authors: Raghavan S. , Josey K. , Bahn G. , Reda D. , Basu S. , Berkowitz S.A. , Emanuele N. , Reaven P. , Ghosh D. .
Source: Annals Of Epidemiology, 2021-07-17 00:00:00.0; , .
EPub date: 2021-07-17 00:00:00.0.
PMID: 34280545
Related Citations

A meta-inference framework to integrate multiple external models into a current study.
Authors: Gu T. , Taylor J.M.G. , Mukherjee B. .
Source: Biostatistics (oxford, England), 2021-07-16 00:00:00.0; , .
EPub date: 2021-07-16 00:00:00.0.
PMID: 34269371
Related Citations

A copula-based approach for dynamic prediction of survival with a binary time-dependent covariate.
Authors: Suresh K. , Taylor J.M.G. , Tsodikov A. .
Source: Statistics In Medicine, 2021-06-14 00:00:00.0; , .
EPub date: 2021-06-14 00:00:00.0.
PMID: 34124771
Related Citations

Evaluation of predictive model performance of an existing model in the presence of missing data.
Authors: Li P. , Taylor J.M.G. , Spratt D.E. , Karnes R.J. , Schipper M.J. .
Source: Statistics In Medicine, 2021-04-11 00:00:00.0; , .
EPub date: 2021-04-11 00:00:00.0.
PMID: 33843085
Related Citations

Covariate adjustment via propensity scores for recurrent events in the presence of dependent censoring.
Authors: Cho Y. , Ghosh D. .
Source: Communications In Statistics: Theory And Methods, 2021; 50(1), p. 216-236.
EPub date: 2019-07-15 00:00:00.0.
PMID: 33716388
Related Citations

ANALYSIS OF REGRESSION DISCONTINUITY DESIGNS USING CENSORED DATA.
Authors: Cho Y. , Hu C. , Ghosh D. .
Source: Journal Of Statistical Research, 2021; 55(1), p. 225-248.
EPub date: 2021-09-03 00:00:00.0.
PMID: 35755402
Related Citations

Statin use and head and neck squamous cell carcinoma outcomes.
Authors: Getz K.R. , Bellile E. , Zarins K.R. , Rullman C. , Chinn S.B. , Taylor J.M.G. , Rozek L.S. , Wolf G.T. , Mondul A.M. .
Source: International Journal Of Cancer, 2020-12-15 00:00:00.0; , .
EPub date: 2020-12-15 00:00:00.0.
PMID: 33320960
Related Citations

A stacked approach for chained equations multiple imputation incorporating the substantive model.
Authors: Beesley L.J. , Taylor J.M.G. .
Source: Biometrics, 2020-09-13 00:00:00.0; , .
EPub date: 2020-09-13 00:00:00.0.
PMID: 32920819
Related Citations

Quantifying the incremental value of deep learning: Application to lung nodule detection.
Authors: Warsavage T. , Xing F. , Barón A.E. , Feser W.J. , Hirsch E. , Miller Y.E. , Malkoski S. , Wolf H.J. , Wilson D.O. , Ghosh D. .
Source: Plos One, 2020; 15(4), p. e0231468.
EPub date: 2020-04-14 00:00:00.0.
PMID: 32287288
Related Citations

A Gaussian copula approach for dynamic prediction of survival with a longitudinal biomarker.
Authors: Suresh K. , Taylor J.M.G. , Tsodikov A. .
Source: Biostatistics (oxford, England), 2019-12-10 00:00:00.0; , .
EPub date: 2019-12-10 00:00:00.0.
PMID: 31820798
Related Citations

Synthetic data method to incorporate external information into a current study.
Authors: Gu T. , Taylor J.M.G. , Cheng W. , Mukherjee B. .
Source: The Canadian Journal Of Statistics = Revue Canadienne De Statistique, 2019 Dec; 47(4), p. 580-603.
EPub date: 2019-06-26 00:00:00.0.
PMID: 32773922
Related Citations

A utility approach to individualized optimal dose selection using biomarkers.
Authors: Li P. , Taylor J.M.G. , Kong S. , Jolly S. , Schipper M.J. .
Source: Biometrical Journal. Biometrische Zeitschrift, 2019-11-06 00:00:00.0; , .
EPub date: 2019-11-06 00:00:00.0.
PMID: 31692022
Related Citations

Accounting for established predictors with the multistep elastic net.
Authors: Chase E.C. , Boonstra P.S. .
Source: Statistics In Medicine, 2019-07-17 00:00:00.0; , .
EPub date: 2019-07-17 00:00:00.0.
PMID: 31313344
Related Citations

Informing a Risk Prediction Model for Binary Outcomes with External Coefficient Information.
Authors: Cheng W. , Taylor J.M.G. , Gu T. , Tomlins S.A. , Mukherjee B. .
Source: Journal Of The Royal Statistical Society. Series C, Applied Statistics, 2019 Jan; 68(1), p. 121-139.
EPub date: 2018-08-13 00:00:00.0.
PMID: 31105344
Related Citations

Empirical Bayes Estimation and Prediction Using Summary-Level Information From External Big Data Sources Adjusting for Violations of Transportability.
Authors: Estes J.P. , Mukherjee B. , Taylor J.M.G. .
Source: Statistics In Biosciences, 2018 Dec; 10(3), p. 568-586.
EPub date: 2018-05-14 00:00:00.0.
PMID: 31123532
Related Citations

Individualized survival prediction for patients with oropharyngeal cancer in the human papillomavirus era.
Authors: Beesley L.J. , Hawkins P.G. , Amlani L.M. , Bellile E.L. , Casper K.A. , Chinn S.B. , Eisbruch A. , Mierzwa M.L. , Spector M.E. , Wolf G.T. , et al. .
Source: Cancer, 2018-10-06 00:00:00.0; , .
EPub date: 2018-10-06 00:00:00.0.
PMID: 30291798
Related Citations

Incorporating historical models with adaptive Bayesian updates.
Authors: Boonstra P.S. , Barbaro R.P. .
Source: Biostatistics (oxford, England), 2018-09-21 00:00:00.0; , .
EPub date: 2018-09-21 00:00:00.0.
PMID: 30247557
Related Citations

Prognostic Value of FDG-PET/CT Metabolic Parameters in Metastatic Radioiodine-Refractory Differentiated Thyroid Cancer.
Authors: Manohar P.M. , Beesley L.J. , Bellile E.L. , Worden F.P. , Avram A.M. .
Source: Clinical Nuclear Medicine, 2018 Sep; 43(9), p. 641-647.
PMID: 30015659
Related Citations

Redefining Perineural Invasion: Integration of Biology With Clinical Outcome.
Authors: Schmitd L.B. , Beesley L.J. , Russo N. , Bellile E.L. , Inglehart R.C. , Liu M. , Romanowicz G. , Wolf G.T. , Taylor J.M.G. , D'Silva N.J. .
Source: Neoplasia (new York, N.y.), 2018 Jul; 20(7), p. 657-667.
EPub date: 2018-05-23 00:00:00.0.
PMID: 29800815
Related Citations

Improving estimation and prediction in linear regression incorporating external information from an established reduced model.
Authors: Cheng W. , Taylor J.M.G. , Vokonas P.S. , Park S.K. , Mukherjee B. .
Source: Statistics In Medicine, 2018-01-24 00:00:00.0; , .
EPub date: 2018-01-24 00:00:00.0.
PMID: 29365342
Related Citations

Estimating the Optimal Personalized Treatment Strategy Based on Selected Variables to Prolong Survival via Random Survival Forest with Weighted Bootstrap.
Authors: Shen J. , Wang L. , Daignault S. , Spratt D.E. , Morgan T.M. , Taylor J.M.G. .
Source: Journal Of Biopharmaceutical Statistics, 2018; 28(2), p. 362-381.
EPub date: 2017-10-25 00:00:00.0.
PMID: 28934002
Related Citations

Comparison of joint modeling and landmarking for dynamic prediction under an illness-death model.
Authors: Suresh K. , Taylor J.M.G. , Spratt D.E. , Daignault S. , Tsodikov A. .
Source: Biometrical Journal. Biometrische Zeitschrift, 2017 Nov; 59(6), p. 1277-1300.
EPub date: 2017-05-16 00:00:00.0.
PMID: 28508545
Related Citations

Covariate adjustment using propensity scores for dependent censoring problems in the accelerated failure time model.
Authors: Cho Y. , Hu C. , Ghosh D. .
Source: Statistics In Medicine, 2017-10-10 00:00:00.0; , .
EPub date: 2017-10-10 00:00:00.0.
PMID: 29023972
Related Citations

Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.
Authors: Conlon A. , Taylor J. , Li Y. , Diaz-Ordaz K. , Elliott M. .
Source: Statistics In Medicine, 2017-08-08 00:00:00.0; , .
EPub date: 2017-08-08 00:00:00.0.
PMID: 28786131
Related Citations

Surrogacy assessment using principal stratification and a Gaussian copula model.
Authors: Conlon A. , Taylor J. , Elliott M.R. .
Source: Statistical Methods In Medical Research, 2017 Feb; 26(1), p. 88-107.
PMID: 24947559
Related Citations

Increasing efficiency for estimating treatment-biomarker interactions with historical data.
Authors: Boonstra P.S. , Taylor J.M. , Mukherjee B. .
Source: Statistical Methods In Medical Research, 2016 Dec; 25(6), p. 2959-2971.
EPub date: 2014-05-21 00:00:00.0.
PMID: 24855118
Related Citations

Individualized Risk Prediction Of Outcomes For Oral Cavity Cancer Patients
Authors: Prince V. , Bellile E.L. , Sun Y. , Wolf G.T. , Hoban C.W. , Shuman A.G. , Taylor J.M. .
Source: Oral Oncology, 2016 Dec; 63, p. 66-73.
PMID: 27939002
Related Citations

Estimation Of The Optimal Regime In Treatment Of Prostate Cancer Recurrence From Observational Data Using Flexible Weighting Models
Authors: Shen J. , Wang L. , Taylor J.M. .
Source: Biometrics, 2016-11-28 00:00:00.0; , .
PMID: 27893926
Related Citations

A modified risk set approach to biomarker evaluation studies.
Authors: Ghosh D. .
Source: Statistics In Biosciences, 2016 Oct; 8(2), p. 395-406.
EPub date: 2016-08-22 00:00:00.0.
PMID: 28989545
Related Citations