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Grant Details

Grant Number: 5R01CA193878-03 Interpret this number
Primary Investigator: Ning, Jing
Organization: University Of Tx Md Anderson Can Ctr
Project Title: Comparative Effectiveness of Cancer Research: Use Data From Multiple Sources
Fiscal Year: 2018
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? DESCRIPTION (provided by applicant): Although comparative effectiveness research (CER) in oncology has attracted substantial attention to provide timely treatment comparisons and improve health outcomes, considerable methodological gaps remain for utilizing multiple sources of data together with efficient statistical methods to assemble evidence in CER. The proposed study is directly motivated by our collaborations with breast cancer medical oncologists and surgeons in the investigation of inflammatory breast cancer (IBC), a rare but aggressive form of breast cancer. The primary objective of this proposal is to develop statistical methods and risk prediction models by combining cohort data containing detailed tumor biology variables with aggregate information with or without sampling error from population-based registry databases. In this project, (Aim 1) we propose statistical methods to utilize aggregate information from external data when analyzing primary cohort data with individual patient level data under both parametric and semiparametric models for survival data, and to provide a test procedure to evaluate the comparability of the information from primary cohort data and that from external data. We will further generalize the approaches to account for uncertainty of the aggregate information in the estimation and inference procedures for survival data (Aim 2). Furthermore, (Aim 3) we will link the primary cohort data with detailed risk profiles to external data without detailed risk factors to develop a novel comprehensive IBC-specific mortality risk prediction model, and provide an estimating approach to evaluate the performance of the established risk prediction model. From an application perspective, our proposed methods of maximizing the use of existing IBC cohort data by combining them with external registry databases is cost-effective and may directly improve evidence-based treatment guidelines for IBC patients. Although motivated by IBC research, the statistical methods will be useful for addressing the challenges of CER in any chronic disease, especially for rare diseases. All software for analytical and statistical tools developed in this project, once validated, will be made available to the broader research community.

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Mediation analysis in a case-control study when the mediator is a censored variable.
Authors: Wang J. , Ning J. , Shete S. .
Source: Statistics In Medicine, 2018-11-12 00:00:00.0; , .
EPub date: 2018-11-12 00:00:00.0.
PMID: 30421436
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Efficient two-stage designs and proper inference for animal studies.
Authors: Cai C. , Piao J. , Ning J. , Huang X. .
Source: Statistics In Biosciences, 2018 Apr; 10(1), p. 217-232.
EPub date: 2017-12-13 00:00:00.0.
PMID: 30294384
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Model diagnostics for the proportional hazards model with length-biased data.
Authors: Lee C.H. , Ning J. , Shen Y. .
Source: Lifetime Data Analysis, 2018-02-16 00:00:00.0; , .
EPub date: 2018-02-16 00:00:00.0.
PMID: 29450809
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Semiparametric model and inference for spontaneous abortion data with a cured proportion and biased sampling.
Authors: Piao J. , Ning J. , Chambers C.D. , Xu R. .
Source: Biostatistics (oxford, England), 2018-01-01 00:00:00.0; 19(1), p. 54-70.
PMID: 28525542
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Analysis of restricted mean survival time for length-biased data.
Authors: Lee C.H. , Ning J. , Shen Y. .
Source: Biometrics, 2017-09-08 00:00:00.0; , .
EPub date: 2017-09-08 00:00:00.0.
PMID: 28886217
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Model-free scoring system for risk prediction with application to hepatocellular carcinoma study.
Authors: Shen W. , Ning J. , Yuan Y. , Lok A.S. , Feng Z. .
Source: Biometrics, 2017-07-25 00:00:00.0; , .
EPub date: 2017-07-25 00:00:00.0.
PMID: 28742219
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Maximum likelihood estimation and EM algorithm of Copas-like selection model for publication bias correction.
Authors: Ning J. , Chen Y. , Piao J. .
Source: Biostatistics (oxford, England), 2017-07-01 00:00:00.0; 18(3), p. 495-504.
PMID: 28334132
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Estimating treatment effects in observational studies with both prevalent and incident cohorts.
Authors: Ning J. , Hong C. , Li L. , Huang X. , Shen Y. .
Source: The Canadian Journal Of Statistics = Revue Canadienne De Statistique, 2017 Jun; 45(2), p. 202-219.
EPub date: 2017-04-13 00:00:00.0.
PMID: 29056817
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Analyzing Semi-competing Risks Data With Missing Cause Of Informative Terminal Event
Authors: Zhou R. , Zhu H. , Bondy M. , Ning J. .
Source: Statistics In Medicine, 2017-02-28 00:00:00.0; 36(5), p. 738-753.
PMID: 27813148
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Semiparametric Density Ratio Modeling Of Survival Data From A Prevalent Cohort
Authors: Zhu H. , Ning J. , Shen Y. , Qin J. .
Source: Biostatistics (oxford, England), 2017 Jan; 18(1), p. 62-75.
PMID: 27354710
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A Response-adaptive Design Of Initial Therapy For Emergency Department Patients With Heart Failure
Authors: Wen S. , Ning J. , Collins S. , Berry D. .
Source: Contemporary Clinical Trials, 2017 Jan; 52, p. 46-53.
PMID: 27838474
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Conditional independence test by generalized Kendall's tau with generalized odds ratio.
Authors: Ji S. , Ning J. , Qin J. , Follmann D. .
Source: Statistical Methods In Medical Research, 2017-01-01 00:00:00.0; , p. 962280217695345.
EPub date: 2017-01-01 00:00:00.0.
PMID: 29298614
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A Bayesian Multi-stage Cost-effectiveness Design For Animal Studies In Stroke Research
Authors: Cai C. , Ning J. , Huang X. .
Source: Statistical Methods In Medical Research, 2016-07-08 00:00:00.0; , .
PMID: 27405325
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