Data from longitudinal studies have suggested that patients infected with HIV-1 might have cardiovascular abnormalities. These abnormalities may be the result of the treatments (AZT, etc.) or the HIV-1 virus itself. In this grant, we will develop methods to analyze longitudinal and survival studies of heart function in AIDS patients. Cardiotoxicity in AIDS patients could be a leading cause of morbidity and mortality. Development of methods leading to increased understanding of the cardiotoxicity could prove invaluable in determining the appropriate time to give cardioprotective therapies. The developed methods will be applied to the Pediatric Pulmonary and Cardiac Complications (P2C2) of Vertically Transmitted HIV Infection Study, which was a large, prospective longitudinal study designed to monitor heart disease and the progression of cardiac abnormalities in children born to HIV-infected women. To truly understand the change in heart function over time, new models and methods need to be developed that take into account multiple measures of heart function (LV mass, end-diastolic dimension, end-systolic dimension, fractional shortening, etc.). The models and associated statistical methods should be such that biases do not result because of higher rates of clinic visits by sicker patients, higher chance of dropout for sicker patients, missed clinic visits due to patients' health conditions, etc. In this grant, we develop appropriate models and methods to deal with these situations. We will examine the following six Specific Aims. Regression models for Longitudinal Discrete and Continuous Outcomes; A likelihood method for Longitudinal Studies with Informative Dropout; A Protective Estimator for Mixed Discrete and Continuous Outcomes Subject to Nonignorable Non-monotone Missingness; Methods for Estimation in Longitudinal Studies with Outcome-Dependent Follow-Up; and Prediction in Multivariate Survival Models; Sensitivity Analysis for the previous six aims.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Research Project (R01)
Project #
5R01AI060373-03
Application #
7161481
Study Section
AIDS Clinical Studies and Epidemiology Study Section (ACE)
Program Officer
Gezmu, Misrak
Project Start
2004-12-01
Project End
2007-11-30
Budget Start
2005-12-01
Budget End
2006-11-30
Support Year
3
Fiscal Year
2006
Total Cost
$265,433
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti et al. (2016) Approximate median regression for complex survey data with skewed response. Biometrics 72:1336-1347
Parzen, Michael; Ghosh, Souparno; Lipsitz, Stuart et al. (2011) A generalized linear mixed model for longitudinal binary data with a marginal logit link function. Ann Appl Stat 5:449-467
Parikh, Ankit; Natarajan, Sundar; Lipsitz, Stuart R et al. (2011) Iron deficiency in community-dwelling US adults with self-reported heart failure in the National Health and Nutrition Examination Survey III: prevalence and associations with anemia and inflammation. Circ Heart Fail 4:599-606
Jaffa, Miran A; Woolson, Robert F; Lipsitz, Stuart R (2011) Slope Estimation for Bivariate Longitudinal Outcomes Adjusting for Informative Right Censoring Using Discrete Survival Model: Application to the Renal Transplant Cohort. J R Stat Soc Ser A Stat Soc 174:387-402
Troxel, Andrea B; Lipsitz, Stuart R; Fitzmaurice, Garrett M et al. (2010) A weighted combination of pseudo-likelihood estimators for longitudinal binary data subject to non-ignorable non-monotone missingness. Stat Med 29:1511-21
Friedberg, Jennifer P; Lipsitz, Stuart R; Natarajan, Sundar (2010) Challenges and recommendations for blinding in behavioral interventions illustrated using a case study of a behavioral intervention to lower blood pressure. Patient Educ Couns 78:5-11
Lin, Lanjia; Bandyopadhyay, Dipankar; Lipsitz, Stuart R et al. (2010) Association models for clustered data with binary and continuous responses. Biometrics 66:287-93
Lin, Yan; Lipsitz, Stuart; Sinha, Debajyoti et al. (2009) Using Bayesian p-values in a 2 × 2 table of matched pairs with incompletely classified data. J R Stat Soc Ser C Appl Stat 58:237-246
Lin, Yan; Newcombe, Robert G; Lipsitz, Stuart et al. (2009) Fully specified bootstrap confidence intervals for the difference of two independent binomial proportions based on the median unbiased estimator. Stat Med 28:2876-90
Lipsitz, Stuart R; Fitzmaurice, Garrett M; Ibrahim, Joseph G et al. (2009) Joint generalized estimating equations for multivariate longitudinal binary outcomes with missing data: An application to AIDS data. J R Stat Soc Ser A Stat Soc 172:3-20

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