CD4 lymphocyte decline and survival in human immunodeficiency virus infection. The Military Medical Consortium for Applied Retroviral Research. 1992

J J Drabick, and W J Williams, and D B Tang, and W Sun, and R C Chung
Department of Bacterial Diseases, Walter Reed Army Institute of Research, Washington, DC 20307-5100.

The loss of the CD4 lymphocyte is the central pathophysiologic event in the progression of human immunodeficiency virus (HIV) infection. This retrospective study, based on review of data from deceased HIV patients followed in a single HIV clinic, was conducted to determine if the rate of CD4 lymphocyte decline was predictive of survival. Forty of 172 patients met defined criteria for inclusion in this study. For each patient, CD4-cell counts showed approximate exponential decline over time. A Cox regression analysis was used to assess the association of CD4 cell decline (half-life), race, age, gender, initial CD4-cell count, and treatment (anti-Pneumocystis carinii pneumonia prophylaxis and/or zidovudine vs. no therapy) on total survival (from initial CD4 cell count) and on remaining survival time after reaching a CD4 cell count of 100 (estimated). For all patients, the rate of CD4 cell decline was predictive of total survival (p = .009) but not for survival after reaching a count of 100 (p = .6). For patients who had never received therapy (6 patients), however, the CD4 half-life remained associated with survival time from 100 CD4 cells (p < .05) as opposed to the treated patients. Therapy was the single variable most predictive of both survival endpoints, resulting in an increase in median total survival of 27.2 mo (p < .00001) and of 15.4 mo from a CD4 cell count of 100 (p < .00004). Nonwhites had a slight survival disadvantage compared to whites (p = .08 overall; p = .02 from CD4 cell count of 100).(ABSTRACT TRUNCATED AT 250 WORDS)

UI MeSH Term Description Entries
D007958 Leukocyte Count The number of WHITE BLOOD CELLS per unit volume in venous BLOOD. A differential leukocyte count measures the relative numbers of the different types of white cells. Blood Cell Count, White,Differential Leukocyte Count,Leukocyte Count, Differential,Leukocyte Number,White Blood Cell Count,Count, Differential Leukocyte,Count, Leukocyte,Counts, Differential Leukocyte,Counts, Leukocyte,Differential Leukocyte Counts,Leukocyte Counts,Leukocyte Counts, Differential,Leukocyte Numbers,Number, Leukocyte,Numbers, Leukocyte
D008297 Male Males
D011379 Prognosis A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations. Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D005260 Female Females
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D000328 Adult A person having attained full growth or maturity. Adults are of 19 through 44 years of age. For a person between 19 and 24 years of age, YOUNG ADULT is available. Adults
D013997 Time Factors Elements of limited time intervals, contributing to particular results or situations. Time Series,Factor, Time,Time Factor
D014481 United States A country in NORTH AMERICA between CANADA and MEXICO.
D015233 Models, Statistical Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc. Probabilistic Models,Statistical Models,Two-Parameter Models,Model, Statistical,Models, Binomial,Models, Polynomial,Statistical Model,Binomial Model,Binomial Models,Model, Binomial,Model, Polynomial,Model, Probabilistic,Model, Two-Parameter,Models, Probabilistic,Models, Two-Parameter,Polynomial Model,Polynomial Models,Probabilistic Model,Two Parameter Models,Two-Parameter Model
D015496 CD4-Positive T-Lymphocytes A critical subpopulation of T-lymphocytes involved in the induction of most immunological functions. The HIV virus has selective tropism for the T4 cell which expresses the CD4 phenotypic marker, a receptor for HIV. In fact, the key element in the profound immunosuppression seen in HIV infection is the depletion of this subset of T-lymphocytes. T4 Cells,T4 Lymphocytes,CD4-Positive Lymphocytes,CD4 Positive T Lymphocytes,CD4-Positive Lymphocyte,CD4-Positive T-Lymphocyte,Lymphocyte, CD4-Positive,Lymphocytes, CD4-Positive,T-Lymphocyte, CD4-Positive,T-Lymphocytes, CD4-Positive,T4 Cell,T4 Lymphocyte

Related Publications

J J Drabick, and W J Williams, and D B Tang, and W Sun, and R C Chung
April 1994, Southern medical journal,
J J Drabick, and W J Williams, and D B Tang, and W Sun, and R C Chung
April 1992, Military medicine,
J J Drabick, and W J Williams, and D B Tang, and W Sun, and R C Chung
March 1993, Journal of the American Academy of Dermatology,
J J Drabick, and W J Williams, and D B Tang, and W Sun, and R C Chung
July 1993, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America,
J J Drabick, and W J Williams, and D B Tang, and W Sun, and R C Chung
October 1995, Journal of acquired immune deficiency syndromes and human retrovirology : official publication of the International Retrovirology Association,
Copied contents to your clipboard!