PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 9750246

Estimating a treatment effect from multidimensional longitudinal data.

S M Gray·R Brookmeyer
View original source ↗Export metadata ↓

Abstract

Multidimensional longitudinal data result when researchers measure an outcome through time that is quantified by many different response variables. These response variables are often defined on different numerical scales. The objective of this paper is to present a method to summarize and estimate an overall treatment effect from this type of longitudinal data. A regression model is proposed that assumes the treatment effect can be parameterized as an acceleration or deceleration of the time scale of each response variable's trajectory. Generalized estimating equations are used to estimate the model parameters. Cognitive and functional ability data from Alzheimer's disease patients and quality of life data from an AIDS clinical trial are used to illustrate the model.

Explore related subjects

Acquired Immunodeficiency SyndromeAllelesAlzheimer DiseaseApolipoproteins EBiometryClinical Trials as TopicCognitionData Interpretation, StatisticalHumansLongitudinal StudiesModels, StatisticalQuality of LifeRegression AnalysisTreatment OutcomeJournal ArticleResearch Support, U.S. Gov't, P.H.S.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

S M Gray, R Brookmeyer. 1998. Estimating a treatment effect from multidimensional longitudinal data.. https://pubmed.ncbi.nlm.nih.gov/9750246/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2001

Low or no antibody responses to human immunodeficiency virus type 1 Nef in infected carriers with subtype E, in contrast to subtype B that showed antibodies preferentially recognizing subtype-specific Nef epitopes.

The viral accessory gene product Nef has been shown to play an important role in human immunodeficiency virus type 1 (HIV-1)-induced pathogenesis. Only little information is available regarding the differences in the host immune responses against Nef protein and its function in vivo among different subtypes of HIV-1. In the present study, we showed marked differences in the immune responses to Nef protein between subtypes B and E. The amino acid sequence in subtype E Nef showed 72% homology with that in subtype B. Most murine monoclonal antibodies obtained by immunization with subtype B or E Nef protein showed cross-reactivity with both Nef proteins (80 and 67%, respectively). Next, we focused on the immune responses among infected Japanese and Thai individuals. Subtyping of the individuals into B and E was carried out by enzyme-linked immunosorbent assay (ELISA) using synthetic peptides corresponding to the V3 loop representing the principal neutralizing domain. Most of the sera from these individuals reacted strongly with Gag p24 proteins derived from subtypes B and E at similar levels. However, the immune responses among these individuals to Nef protein were markedly different. Some subtype B-infected Japanese and Thai individuals (40 and 35%, respectively) showed higher levels of anti-Nef antibodies, although these antibodies preferentially recognized epitopes specific to subtype B. On the other hand, most of the subtype E-infected Japanese and Thai individuals showed low or no antibody responses to Nef proteins. Thus, immune responses to Nef were markedly different between subtypes B- and E-infected carriers, suggesting different function(s) for Nef in AIDS pathogenesis. Further, vaccine design must take into account the different subtypes of HIV-1.

Acquired Immunodeficiency Syndrome↗