This proposal describes training and research activities whose goal is to further the development of Dr. Hernan as an independent investigator in the area of causal inference from complex longitudinal HIV data. Dr. Hernan is a physician with graduate degrees in epidemiology and biostatistics. He is currently a research associate at the Harvard School of Public Health, where he works on the application and development of causal methods under the supervision of professor James Robins. His career goals are to become an academic investigator with a faculty appointment and to develop his research career on causal inference from longitudinal data. To accomplish his goals, Dr. Hernan will devote a large proportion of the first two years of the award to strengthening his background in causal methods. The proposed research career development plan includes specialized tutorials, independent study, coursework, seminars, and participation in working groups and scientific meetings. During the first two years he will also conduct supervised research project of increasing complexity. The last three years of the award will be research-intensive. Inferring valid causal inferences from longitudinal HIV studies requires the use of the appropriate methods for confounding and selection bias adjustment. Causal methods (such as marginal structural models and structural nested models) are the best methods available to estimate the effect of a treatment in or a cofactor on an outcome of interest from observational data and to adjust for dependent censoring, non-random non-compliance, treatment cross-over or termination, and the concurrent effect of additional non-randomized treatments in randomized clinical trials. On the other hand, standard methods, such as regression (e.g, logistic, Poison, Cox proportional hazards) models or stratification may produce effect estimates that cannot be endowed with a causal interpretation. A substantial part of the research is aimed at conducting a systematic evaluation of the relative advantages and disadvantages of causal and standard methods in HIV epidemiology. This evaluation will include the application of causal methods to answer substantive questions using actual HIV data sets (e.g., the MACS). Also, the research plan describes an evaluation of several common problems in longitudinal analysis and how they can be handled using causal methods. These problems include dependent censoring missing data, model misspecification, and unmeasured confounding.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Clinical Investigator Award (CIA) (K08)
Project #
1K08AI049392-01A1
Application #
6408206
Study Section
Special Emphasis Panel (ZRG1-SNEM-5 (01))
Program Officer
Dixon, Dennis O
Project Start
2001-07-01
Project End
2006-06-30
Budget Start
2001-07-01
Budget End
2002-06-30
Support Year
1
Fiscal Year
2001
Total Cost
$114,237
Indirect Cost
Name
Harvard University
Department
Public Health & Prev Medicine
Type
Schools of Public Health
DUNS #
City
Boston
State
MA
Country
United States
Zip Code
02115
Rosenberg, Philip S; Alter, Blanche P; Link, Daniel C et al. (2008) Neutrophil elastase mutations and risk of leukaemia in severe congenital neutropenia. Br J Haematol 140:210-3
Cole, Stephen R; Hernan, Miguel A; Anastos, Kathryn et al. (2007) Determining the effect of highly active antiretroviral therapy on changes in human immunodeficiency virus type 1 RNA viral load using a marginal structural left-censored mean model. Am J Epidemiol 166:219-27
Hernandez-Diaz, Sonia; Schisterman, Enrique F; Hernan, Miguel A (2006) The birth weight ""paradox"" uncovered? Am J Epidemiol 164:1115-20
Rosenberg, Philip S; Alter, Blanche P; Bolyard, Audrey A et al. (2006) The incidence of leukemia and mortality from sepsis in patients with severe congenital neutropenia receiving long-term G-CSF therapy. Blood 107:4628-35
Cole, Stephen R; Hernan, Miguel A; Margolick, Joseph B et al. (2005) Marginal structural models for estimating the effect of highly active antiretroviral therapy initiation on CD4 cell count. Am J Epidemiol 162:471-8
Hernan, Miguel A; Cole, Stephen R; Margolick, Joseph et al. (2005) Structural accelerated failure time models for survival analysis in studies with time-varying treatments. Pharmacoepidemiol Drug Saf 14:477-91
Sterne, Jonathan A C; Hernan, Miguel A; Ledergerber, Bruno et al. (2005) Long-term effectiveness of potent antiretroviral therapy in preventing AIDS and death: a prospective cohort study. Lancet 366:378-84
Cole, Stephen R; Hernan, Miguel A (2004) Adjusted survival curves with inverse probability weights. Comput Methods Programs Biomed 75:45-9
Brumback, Babette A; Hernan, Miguel A; Haneuse, Sebastien J P A et al. (2004) Sensitivity analyses for unmeasured confounding assuming a marginal structural model for repeated measures. Stat Med 23:749-67
Hernan, Miguel A; Hernandez-Diaz, Sonia; Robins, James M (2004) A structural approach to selection bias. Epidemiology 15:615-25

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