Growth patterns reflect response to antiretroviral therapy in HIV-positive infants: potential utility in resource-poor settings.
Laboratory monitoring of HIV-infected children is the current standard of care in the United States to guide the appropriate use of antiretroviral therapy (ART). Although ART is becoming a reality in some developing countries, laboratory monitoring of ART is costly, necessitating creative approaches to monitoring. As an initial step to guide monitoring of HIV progression in low resource settings, we assessed the utility of the physical examination to predict clinical progression of HIV. We conducted a retrospective cohort study of HIV-infected children using data from Pediatric AIDS Clinical Trials Group Protocol 300. We developed a clinical predictive model, and compared the utility of the clinical model to the change in HIV RNA viral load as diagnostic tests of ART failure. The clinical model incorporated treatment regimen, age, and height velocity: a three-level clinical predictive model provided likelihood ratios of 0.3, 3.9, and 14. For decline in RNA the likelihood ratios were 0.2 (> 1 log decline), 1.4, and 3.5 (> log increase). We developed a simple clinical predictive model that was able to predict clinical progression of HIV after initiation of new ART. The clinical model performed similarly to using changes in HIV RNA viral load. These data should be validated internationally and prospectively, because the test subjects were from a resource rich environment and growth patterns in undernourished children may be impacted differently by HIV and its treatment. The model was most pertinent to children 36 months of age or younger, and was conducted in children receiving monotherapy and dual therapy.
Duke Clinical Research Institute, Durham, North Carolina 27715, USA. danny.benjamin@duke.edu
D K
DK
Benjamin
W C
WC
Miller
R W
RW
Ryder
D J
DJ
Weber
E
E
Walter
R E
RE
McKinney
D019380:Anti-HIV Agents / Q000627:therapeutic use; D001827:Body Height / Q000187:drug effects; D001835:Body Weight / Q000187:drug effects; D015331:Cohort Studies; D015986:Confounding Factors, Epidemiologic; D003906:Developing Countries; D018450:Disease Progression; D016903:Drug Monitoring / Q000191:economics / Q000379:methods* / Q000592:standards; D005260:Female; D006128:Growth / Q000187:drug effects*; D006679:HIV Seropositivity / Q000188:drug therapy* / Q000821:virology; D015497:HIV-1 / Q000187:drug effects / Q000235:genetics; D006801:Humans; D007223:Infant; D007228:Infant Nutrition Disorders / Q000150:complications; D016015:Logistic Models; D008297:Male; D015999:Multivariate Analysis; D010808:Physical Examination / Q000191:economics / Q000379:methods* / Q000592:standards; D011237:Predictive Value of Tests; D012367:RNA, Viral / Q000097:blood; D012189:Retrospective Studies; D016896:Treatment Outcome; D019562:Viral Load
D019380:Anti-HIV Agents; D012367:RNA, Viral