title: Prediction of residual time to AIDS and death based on markers and cofactors.
abstract: A model was constructed that estimates the probability of an HIV-infected individual developing AIDS or dying within a certain time span if left untreated, based on the most recent CD4 lymphocyte count, HIV-1 RNA load, and HIV-1 phenotype, together with age, time since seroconversion, and two genetic cofactors. The model helps clinicians in deciding when to start highly active antiretroviral treatment (HAART). Data from the Amsterdam Cohort Study among homosexual men restricted to individuals with an estimated date of seroconversion (N = 280) were used. Individual predictions based on several combinations of marker and cofactor values were obtained, and their accuracy was measured using two indices of predictive value. CD4 lymphocyte count and HIV RNA load have the highest predictive value and act independently. The predictive value of the HIV phenotype is only slightly lower and greatly enhances predictions at high CD4 counts. The CCR5-Delta32 and CCR2-64I alleles have no additional predictive value. Some predictive value is lost by not knowing time since seroconversion, and some effect of calendar period is present. In summary, for prognosis, the markers CD4 count, HIV-1 RNA load, and HIV-1 phenotype (at a high CD4 count) are equally important, and the genetic cofactors considered are of no use.
authors.affiliation: Municipal Health Service, Cluster of Infectious Diseases, Nieuwe Achtergracht 100, 1018 WT Amsterdam, The Netherlands. rgeskus@gggd.amsterdam.nl
authors.forename: Ronald B
authors.initials: RB
authors.lastname: Geskus
authors.forename: Frank A
authors.initials: FA
authors.lastname: Miedema
authors.forename: Jaap
authors.initials: J
authors.lastname: Goudsmit
authors.forename: Peter
authors.initials: P
authors.lastname: Reiss
authors.forename: Hanneke
authors.initials: H
authors.lastname: Schuitemaker
authors.forename: Roel A
authors.initials: RA
authors.lastname: Coutinho
mesh_terms: D000328:Adult; D015415:Biomarkers / Q000097:blood; D018791:CD4 Lymphocyte Count; D015331:Cohort Studies; D018450:Disease Progression; D005260:Female; D015658:HIV Infections / Q000401:mortality* / Q000503:physiopathology*; D006801:Humans; D008954:Models, Biological; D011237:Predictive Value of Tests; D011379:Prognosis; D012367:RNA, Viral / Q000097:blood; D013997:Time Factors; D019562:Viral Load
chemical_list: D015415:Biomarkers; D012367:RNA, Viral