Haitao Chu

Summary

Affiliation: University of North Carolina
Country: USA

Publications

  1. pmc On the estimation of disease prevalence by latent class models for screening studies using two screening tests with categorical disease status verified in test positives only
    Haitao Chu
    Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Stat Med 29:1206-18. 2010
  2. pmc Bivariate random effects meta-analysis of diagnostic studies using generalized linear mixed models
    Haitao Chu
    Department of Biostatistics and Lineberger Comprehensive Cancer Center, Univerity of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Med Decis Making 30:499-508. 2010
  3. doi request reprint A Bayesian approach estimating treatment effects on biomarkers containing zeros with detection limits
    Haitao Chu
    Department of Biostatistics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Stat Med 27:2497-508. 2008
  4. pmc The effect of HAART on HIV RNA trajectory among treatment-naïve men and women: a segmental Bernoulli/lognormal random effects model with left censoring
    Haitao Chu
    Department of Biostatistics and the Lineberger Comprehensive Cancer Center, The University of North Carolina, Chapel Hill, NC 27599, USA
    Epidemiology 21:S25-34. 2010
  5. doi request reprint Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection
    Haitao Chu
    Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Stat Med 28:2384-99. 2009
  6. pmc Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application
    Haitao Chu
    Department of Biostatistics and Lineberger Comprehensive Cancer Center, The University of North Carolina, Chapel Hill, NC 27599, USA
    Biostatistics 10:591-602. 2009
  7. pmc Sample size and power determination in joint modeling of longitudinal and survival data
    Liddy M Chen
    Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, U S A
    Stat Med 30:2295-309. 2011
  8. pmc Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690
    Joseph G Ibrahim
    Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
    BMC Med Res Methodol 12:183. 2012
  9. doi request reprint Estimation of risk ratios in cohort studies with common outcomes: a Bayesian approach
    Haitao Chu
    Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
    Epidemiology 21:855-62. 2010
  10. ncbi request reprint A general approach for sample size and statistical power calculations assessing of interventions using a mixture model in the presence of detection limits
    Lei Nie
    Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, 4000 Reservoir Road, Washington, DC 20057, USA
    Contemp Clin Trials 27:483-91. 2006

Collaborators

Detail Information

Publications38

  1. pmc On the estimation of disease prevalence by latent class models for screening studies using two screening tests with categorical disease status verified in test positives only
    Haitao Chu
    Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Stat Med 29:1206-18. 2010
    ..In summary, further research is needed to reduce the impact of model misspecification on the estimation of disease prevalence in such settings...
  2. pmc Bivariate random effects meta-analysis of diagnostic studies using generalized linear mixed models
    Haitao Chu
    Department of Biostatistics and Lineberger Comprehensive Cancer Center, Univerity of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Med Decis Making 30:499-508. 2010
    ....
  3. doi request reprint A Bayesian approach estimating treatment effects on biomarkers containing zeros with detection limits
    Haitao Chu
    Department of Biostatistics and Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Stat Med 27:2497-508. 2008
    ..Stat. Med. 2005; 24:2053-2067) through simulation studies and a randomized chemoprevention trial conducted in Qidong, People's Republic of China...
  4. pmc The effect of HAART on HIV RNA trajectory among treatment-naïve men and women: a segmental Bernoulli/lognormal random effects model with left censoring
    Haitao Chu
    Department of Biostatistics and the Lineberger Comprehensive Cancer Center, The University of North Carolina, Chapel Hill, NC 27599, USA
    Epidemiology 21:S25-34. 2010
    ..Highly active antiretroviral therapy (HAART) rapidly suppresses human immunodeficiency virus (HIV) viral replication and reduces circulating viral load, but the long-term effects of HAART on viral load remain unclear...
  5. doi request reprint Meta-analysis of diagnostic accuracy studies accounting for disease prevalence: alternative parameterizations and model selection
    Haitao Chu
    Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Stat Med 28:2384-99. 2009
    ..In summary, the proposed trivariate random effects models are novel and can be very useful in practice for meta-analysis of diagnostic accuracy studies...
  6. pmc Estimation and inference for case-control studies with multiple non-gold standard exposure assessments: with an occupational health application
    Haitao Chu
    Department of Biostatistics and Lineberger Comprehensive Cancer Center, The University of North Carolina, Chapel Hill, NC 27599, USA
    Biostatistics 10:591-602. 2009
    ..The performance of this method is investigated through simulation studies and applied to the National Occupational Hazard Survey, a case-control study assessing the association between asbestos exposure and mesothelioma...
  7. pmc Sample size and power determination in joint modeling of longitudinal and survival data
    Liddy M Chen
    Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, U S A
    Stat Med 30:2295-309. 2011
    ..Optimal frequency of repeated measurements also depends on the nature of the trajectory with higher polynomial trajectories and larger measurement error requiring more frequent measurements...
  8. pmc Bayesian methods in clinical trials: a Bayesian analysis of ECOG trials E1684 and E1690
    Joseph G Ibrahim
    Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
    BMC Med Res Methodol 12:183. 2012
    ..The analyses of E1684 and E1690 were carried out separately when the results were published, and there were no further analyses trying to perform a single analysis of the combined trials...
  9. doi request reprint Estimation of risk ratios in cohort studies with common outcomes: a Bayesian approach
    Haitao Chu
    Department of Biostatistics, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
    Epidemiology 21:855-62. 2010
    ..We propose a novel Bayesian approach for the estimation of the risk ratio from the log binomial model that addresses drawbacks of existing approaches. Posterior computation can be accomplished easily using the WinBUGs code provided...
  10. ncbi request reprint A general approach for sample size and statistical power calculations assessing of interventions using a mixture model in the presence of detection limits
    Lei Nie
    Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, 4000 Reservoir Road, Washington, DC 20057, USA
    Contemp Clin Trials 27:483-91. 2006
    ..The simulation results illustrate that the proposed methods provide adequate sample size estimates. However, when the aforementioned irregularity occurs, our methods are restricted and further research is needed...
  11. pmc On estimation of vaccine efficacy using validation samples with selection bias
    Daniel O Scharfstein
    Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Biostatistics 7:615-29. 2006
    ..Our approach is generally applicable to studies with missing binary outcomes with categorical covariates...
  12. doi request reprint Random effects regression models for trends in standardised mortality ratios
    David B Richardson
    Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
    Occup Environ Med 70:133-9. 2013
    ..However, because the distribution of people with respect to age usually changes as calendar time advances, comparisons of SMRs across calendar periods can produce misleading results...
  13. pmc A prognostic signature of defective p53-dependent G1 checkpoint function in melanoma cell lines
    Craig Carson
    Department of Dermatology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
    Pigment Cell Melanoma Res 25:514-26. 2012
    ..Thus, p53 function, radio-sensitivity, and metastatic spread may be estimated in melanomas from a signature of gene expression...
  14. pmc Illustrating bias due to conditioning on a collider
    Stephen R Cole
    Department of Epidemiology, UNC Gillings School of Global Public Health, Chapel Hill, NC, USA
    Int J Epidemiol 39:417-20. 2010
    ..In both examples, conditioning on the common effect imparts an association between two otherwise independent variables; we call this selection bias...
  15. doi request reprint Meta-analysis of randomized trials on the association of prophylactic acyclovir and HIV-1 viral load in individuals coinfected with herpes simplex virus-2
    Christina Ludema
    Department of Epidemiology, University of North Carolina, Chapel Hill, USA
    AIDS 25:1265-9. 2011
    ..To summarize the randomized evidence regarding the association between acyclovir use and HIV-1 replication as measured by plasma HIV-1 RNA viral load among individuals coinfected with herpes simplex virus (HSV)-2...
  16. ncbi request reprint Bayesian estimation of vaccine efficacy
    Haitao Chu
    Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
    Clin Trials 1:306-14. 2004
    ..We illustrate the methods using the data from two pertussis vaccine studies and the H. influenza Type B preventive trial...
  17. ncbi request reprint Estimating vaccine efficacy using auxiliary outcome data and a small validation sample
    Haitao Chu
    Department of Biostatistics, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30322, USA
    Stat Med 23:2697-711. 2004
    ..Comparing the performance of these approaches using data from a field study of influenza vaccine and simulations, we recommend to use the Bayesian method in this situation...
  18. pmc Estimating the odds ratio when exposure has a limit of detection
    Stephen R Cole
    Department of Epidemiology and Center for AIDS Research, University of Northern California at Chapel Hill, NC, USA
    Int J Epidemiol 38:1674-80. 2009
    ..In epidemiologic research, little emphasis has been placed on methods to account for left-hand censoring of 'exposures' due to a limit of detection (LOD)...
  19. pmc A statistical framework for Illumina DNA methylation arrays
    Pei Fen Kuan
    Department of Biostatistics, Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, NC 27599, USA
    Bioinformatics 26:2849-55. 2010
    ..It is desirable to have an approach that incorporates the whole data, but accounts for the different quality of individual observations...
  20. doi request reprint Basic concepts and methods for joint models of longitudinal and survival data
    Joseph G Ibrahim
    Department of Biostatistics, University of North Carolina, Chapel Hill, NC 27599, USA
    J Clin Oncol 28:2796-801. 2010
    ..To demonstrate our points throughout, we present an analysis from the Eastern Cooperative Oncology Group trial E1193, as well as examine some operating characteristics of joint models through simulation studies...
  21. pmc NF-kB and Bcl-3 activation are prognostic in metastatic colorectal cancer
    Soham D Puvvada
    Department of Internal Medicine, Lineberger Comprehensive Cancer Center, Chapel Hill, NC 27599 7305, USA
    Oncology 78:181-8. 2010
    ..The goal of this study was to correlate the activation status of NF-kappaB and Bcl-3 with clinical outcome in a group of patients with metastatic colorectal cancer (CRC)...
  22. pmc Efficacy of NNRTI-based antiretroviral therapy initiated during acute HIV infection
    Cynthia L Gay
    University of North Carolina at Chapel Hill, NC 27599, USA
    AIDS 25:941-9. 2011
    ..Characterize responses to non-nucleoside reverse transcriptase inhibitor (NNRTI)-based antiretroviral treatment (ART) initiated during acute HIV infection (AHI)...
  23. ncbi request reprint Estimating heterogeneous transmission with multiple infectives using MCMC methods
    Haitao Chu
    Department of Biostatistics, Rollins School of Public Health, Emory University, 1518 Clifton Road NE, Atlanta, GA 30322, USA
    Stat Med 23:35-49. 2004
    ..Parameters are estimated using Markov chain Monte Carlo methods...
  24. pmc Comparison of viral Env proteins from acute and chronic infections with subtype C human immunodeficiency virus type 1 identifies differences in glycosylation and CCR5 utilization and suggests a new strategy for immunogen design
    Li Hua Ping
    UNC Center for AIDS Research, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
    J Virol 87:7218-33. 2013
    ..We suggest that the occasional absence of glycosylation sites encoded in the conserved regions of env, further reduced in transmitted viruses, could expose specific surface structures on the protein as antibody targets...
  25. doi request reprint Missing data in clinical studies: issues and methods
    Joseph G Ibrahim
    Department of Biostatistics, University of North Carolina, CB 7420, Chapel Hill, NC 27599, USA
    J Clin Oncol 30:3297-303. 2012
    ..Although the main area of application discussed here is cancer, the issues and methods we discuss apply to any type of study...
  26. pmc Lagging exposure information in cumulative exposure-response analyses
    David B Richardson
    Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, NC 27599, USA
    Am J Epidemiol 174:1416-22. 2011
    ..Lagging exposure assignment by a constant will lead to bias toward the null if the distribution of latency periods is not a fixed constant. Direct estimation of latency periods can minimize bias and improve confidence interval coverage...
  27. pmc Abasic sites preferentially form at regions undergoing DNA replication
    Paul D Chastain
    Department of Pathology and Laboratory Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599 7525, USA
    FASEB J 24:3674-80. 2010
    ..They also reveal that there is increased susceptibility to oxidative damage in DNA regions undergoing replication, which may explain the previously observed clustering of AP sites...
  28. pmc DNA-methylation profiling distinguishes malignant melanomas from benign nevi
    Kathleen Conway
    Department of Epidemiology, School of Public Health, University of North Carolina, Chapel Hill, NC, USA
    Pigment Cell Melanoma Res 24:352-60. 2011
    ..This first report of a DNA-methylation signature discriminating melanomas from nevi indicates that DNA methylation appears promising as an additional tool for enhancing melanoma diagnosis...
  29. ncbi request reprint Multiple-imputation for measurement-error correction
    Stephen R Cole
    Department of Epidemiology, 615 Norht Wolfe Street, E7640, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Int J Epidemiol 35:1074-81. 2006
    ..There are many methods for measurement-error correction. These methods remain rarely used despite the ubiquity of measurement error...
  30. ncbi request reprint Re: "Confidence intervals for biomarker-based human immunodeficiency virus incidence estimates and differences using prevalent data"
    Stephen R Cole
    Am J Epidemiol 166:861-2. 2007
  31. ncbi request reprint Confidence intervals for biomarker-based human immunodeficiency virus incidence estimates and differences using prevalent data
    Stephen R Cole
    Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
    Am J Epidemiol 165:94-100. 2007
    ..The Monte Carlo-based CI may be preferable to competing methods because of the ease of extension to the incidence difference or to exploration of departures from assumptions...
  32. ncbi request reprint Sample size and statistical power assessing the effect of interventions in the context of mixture distributions with detection limits
    Haitao Chu
    Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Stat Med 25:2647-57. 2006
    ..A Monte Carlo simulation study is conducted to investigate the performance of the proposed methods...
  33. ncbi request reprint Individual variation in CD4 cell count trajectory among human immunodeficiency virus-infected men and women on long-term highly active antiretroviral therapy: an application using a Bayesian random change-point model
    Haitao Chu
    Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
    Am J Epidemiol 162:787-97. 2005
    ..At the individual level, 35% of men in the Multicenter AIDS Cohort Study versus 25% of women in the Women's Interagency HIV Study had a statistically significant change in CD4 cell count trajectory within 7 years after HAART initiation...
  34. ncbi request reprint Assessing the effect of interventions in the context of mixture distributions with detection limits
    Haitao Chu
    Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, 615 N Wolfe Street, Baltimore, MD 21205, U S A
    Stat Med 24:2053-67. 2005
    ..We illustrate our methods using data from a randomized clinical trial conducted in Qidong, People's Republic of China...
  35. ncbi request reprint Parametric survival analysis and taxonomy of hazard functions for the generalized gamma distribution
    Christopher Cox
    Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Baltimore, MD 21205, USA
    Stat Med 26:4352-74. 2007
    ..Description of standard statistical software (Stata, SAS and S-Plus) for the computations is included and available at http://statepi.jhsph.edu/software...
  36. ncbi request reprint Estimating biomarker-based HIV incidence using prevalence data in high risk groups with missing outcomes
    Haitao Chu
    Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Biom J 48:772-9. 2006
    ..Our methods can be applied to estimate the incidence of other diseases from prevalence data using similar testing algorithms when missing data is present...
  37. ncbi request reprint Bivariate meta-analysis of sensitivity and specificity with sparse data: a generalized linear mixed model approach
    Haitao Chu
    J Clin Epidemiol 59:1331-2; author reply 1332-3. 2006
  38. ncbi request reprint Sensitivity analysis of misclassification: a graphical and a Bayesian approach
    Haitao Chu
    Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
    Ann Epidemiol 16:834-41. 2006
    ..Misclassification can produce bias in measures of association. Sensitivity analyses have been suggested to explore the impact of such bias, but do not supply formally justified interval estimates...