Pretreatment CD4 Cell Slope and Progression to AIDS or Death in HIV-Infected Patients Initiating Antiretroviral Therapy—The CASCADE Collaboration: A Collaboration of 23 Cohort Studies
Background:
CD4 cell count is a strong predictor of the subsequent risk of AIDS or death in HIV-infected patients initiating combination antiretroviral therapy (cART). It is not known whether the rate of CD4 cell decline prior to therapy is related to prognosis and should, therefore, influence the decision on when to initiate cART.
Methods and Findings:
We carried out survival analyses of patients from the 23 cohorts of the CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) collaboration with a known date of HIV seroconversion and with at least two CD4 measurements prior to initiating cART. For each patient, a pre-cART CD4 slope was estimated using a linear mixed effects model. Our primary outcome was time from initiating cART to a first new AIDS event or death. We included 2,820 treatment-naïve patients initiating cART with a median (interquartile range) pre-cART CD4 cell decline of 61 (46–81) cells/µl per year; 255 patients subsequently experienced a new AIDS event or death and 125 patients died. In an analysis adjusted for established risk factors, the hazard ratio for AIDS or death was 1.01 (95% confidence interval 0.97–1.04) for each 10 cells/µl per year reduction in pre-cART CD4 cell decline. There was also no association between pre-cART CD4 cell slope and survival. Alternative estimates of CD4 cell slope gave similar results. In 1,731 AIDS-free patients with >350 CD4 cells/µl from the pre-cART era, the rate of CD4 cell decline was also not significantly associated with progression to AIDS or death (hazard ratio 0.99, 95% confidence interval 0.94–1.03, for each 10 cells/µl per year reduction in CD4 cell decline).
Conclusions:
The CD4 cell slope does not improve the prediction of clinical outcome in patients with a CD4 cell count above 350 cells/µl. Knowledge of the current CD4 cell count is sufficient when deciding whether to initiate cART in asymptomatic patients.
: Please see later in the article for the Editors' Summary
Vyšlo v časopise:
Pretreatment CD4 Cell Slope and Progression to AIDS or Death in HIV-Infected Patients Initiating Antiretroviral Therapy—The CASCADE Collaboration: A Collaboration of 23 Cohort Studies. PLoS Med 7(2): e32767. doi:10.1371/journal.pmed.1000239
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pmed.1000239
Souhrn
Background:
CD4 cell count is a strong predictor of the subsequent risk of AIDS or death in HIV-infected patients initiating combination antiretroviral therapy (cART). It is not known whether the rate of CD4 cell decline prior to therapy is related to prognosis and should, therefore, influence the decision on when to initiate cART.
Methods and Findings:
We carried out survival analyses of patients from the 23 cohorts of the CASCADE (Concerted Action on SeroConversion to AIDS and Death in Europe) collaboration with a known date of HIV seroconversion and with at least two CD4 measurements prior to initiating cART. For each patient, a pre-cART CD4 slope was estimated using a linear mixed effects model. Our primary outcome was time from initiating cART to a first new AIDS event or death. We included 2,820 treatment-naïve patients initiating cART with a median (interquartile range) pre-cART CD4 cell decline of 61 (46–81) cells/µl per year; 255 patients subsequently experienced a new AIDS event or death and 125 patients died. In an analysis adjusted for established risk factors, the hazard ratio for AIDS or death was 1.01 (95% confidence interval 0.97–1.04) for each 10 cells/µl per year reduction in pre-cART CD4 cell decline. There was also no association between pre-cART CD4 cell slope and survival. Alternative estimates of CD4 cell slope gave similar results. In 1,731 AIDS-free patients with >350 CD4 cells/µl from the pre-cART era, the rate of CD4 cell decline was also not significantly associated with progression to AIDS or death (hazard ratio 0.99, 95% confidence interval 0.94–1.03, for each 10 cells/µl per year reduction in CD4 cell decline).
Conclusions:
The CD4 cell slope does not improve the prediction of clinical outcome in patients with a CD4 cell count above 350 cells/µl. Knowledge of the current CD4 cell count is sufficient when deciding whether to initiate cART in asymptomatic patients.
: Please see later in the article for the Editors' Summary
Zdroje
1. MellorsJW
MargolickJB
PhairJP
RinaldoCR
DetelsR
2007 Prognostic value of HIV-1 RNA, CD4 cell count, and CD4 cell count slope for progression to AIDS and death in untreated HIV-1 infection. JAMA 297 2349 2350
2. EggerM
MayM
CheneG
PhillipsAN
LedergerberB
2002 Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet 360 119 129
3. MayM
PorterK
SterneJA
RoystonP
EggerM
2005 Prognostic model for HIV-1 disease progression in patients starting antiretroviral therapy was validated using independent data. J Clin Epidemiol 58 1033 1041
4. MayM
SterneJA
SabinC
CostagliolaD
JusticeAC
2007 Prognosis of HIV-1-infected patients up to 5 years after initiation of HAART: collaborative analysis of prospective studies. AIDS 21 1185 1197
5. PhillipsA
PezzottiP
2004 Short-term risk of AIDS according to current CD4 cell count and viral load in antiretroviral drug-naive individuals and those treated in the monotherapy era. AIDS 18 51 58
6. HammerSM
EronJJJr
ReissP
SchooleyRT
ThompsonMA
2008 Antiretroviral treatment of adult HIV infection: 2008 recommendations of the International AIDS Society-USA panel. JAMA 300 555 570
7. Panel on Antiretroviral Guidelines for Adults and Adolescents 2009 Guidelines for the use of antiretroviral agents in HIV-1-infected adults and adolescents. Department of Health and Human Services. Available: http://www.aidsinfo.nih.gov/Guidelines/. Accessed 26 January 2010
8. European AIDS Clinical Society 2009 Guidelines: clinical management and treatment of HIV infected adults in Europe (version 5). Available: http://www.europeanaidsclinicalsociety.org/guidelines.asp. Accessed 16 November 2009
9. SterneJA
MayM
CostagliolaD
2009 Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies. Lancet 373 1352 1363
10. KitahataMM
GangeSJ
AbrahamAG
MerrimanB
SaagMS
2009 Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med 360 1815 1826
11. RodriguezB
SethiAK
CheruvuVK
MackayW
BoschRJ
2006 Predictive value of plasma HIV RNA level on rate of CD4 T-cell decline in untreated HIV infection. JAMA 296 1498 1506
12. PorterK
BabikerA
WalkerS
DarbyshireJ
GillN
2000 Changes in the uptake of antiretroviral therapy and survival in people with known duration of HIV infection in Europe: results from CASCADE. HIV Med 1 224 231
13. CASCADE Collaboration 2009 CASCADE: participating cohorts. Available: http://www.cascade-collaboration.org. Accessed 8 June 2009
14. CheneG
SterneJA
MayM
CostagliolaD
LedergerberB
2003 Prognostic importance of initial response in HIV-1 infected patients starting potent antiretroviral therapy: analysis of prospective studies. Lancet 362 679 686
15. HarrellFE
2001 Regression modeling strategies with applications to linear models, logistic regression, and survival analysis. New York Springer
16. HendersonR
DiggleP
DobsonA
2000 Joint modelling of longitudinal measurements and event time data. Biostatistics 1 465 480
17. TaylorJM
CumberlandWG
TaylorJM
1994 A stochastic model for analysis of longitudinal AIDS data. J Am Stat Assoc 89 727 736
18. TaylorJM
LawN
1998 Does the covariance structure matter in longitudinal modelling for the prediction of future CD4 counts? Stat Med 17 2381 2394
19. R Development Core Team 2008 R: a language and environment for statistical computing (version 2.8.0). Available: http://www.R-project.org. Accessed 10 October 2008
20. RizopoulosD
2008 Package JM: joint modelling of longitudinal and survival data (version 0.2–1). Available: http://www.cran.r-project.org/web/packages/JM. Accessed 10 October 2008
21. BraitsteinP
BrinkhofMW
DabisF
SchechterM
BoulleA
2006 Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet 367 817 824
22. WolbersM
BucherHC
FurrerH
RickenbachM
CavassiniM
2008 Delayed diagnosis of HIV infection and late initiation of antiretroviral therapy in the Swiss HIV Cohort Study. HIV Med 9 397 405
23. CozziLA
SabinCA
PhillipsAN
LeeCA
PezzottiP
1998 The rate of CD4 decline as a determinant of progression to AIDS independent of the most recent CD4 count: the Italian Seroconversion Study. Epidemiol Infect 121 369 376
24. AledortLM
HilgartnerMW
PikeMC
GjersetGF
KoerperMA
1992 Variability in serial CD4 counts and relation to progression of HIV-I infection to AIDS in haemophilic patients. BMJ 304 212 216
25. PhillipsAN
LeeCA
ElfordJ
JanossyG
TimmsA
1991 Serial CD4 lymphocyte counts and development of AIDS. Lancet 337 389 392
26. HallettTB
GregsonS
DubeS
GarnettGP
2008 The impact of monitoring HIV patients prior to treatment in resource-poor settings: insights from mathematical modelling. PLoS Med 5 e53 doi:10.1371/journal.pmed.0050053
Štítky
Interné lekárstvoČlánok vyšiel v časopise
PLOS Medicine
2010 Číslo 2
- Statiny indukovaná myopatie: Jak na diferenciální diagnostiku?
- MUDr. Dana Vondráčková: Hepatopatie sú pri liečbe metamizolom väčším strašiakom ako agranulocytóza
- Vztah mezi statiny a rizikem vzniku nádorových onemocnění − metaanalýza
- Nech brouka žít… Ať žije astma!
- Parazitičtí červi v terapii Crohnovy choroby a dalších zánětlivých autoimunitních onemocnění
Najčítanejšie v tomto čísle
- Packages of Care for Attention-Deficit Hyperactivity Disorder in Low- and Middle-Income Countries
- Measuring hsCRP—An Important Part of a Comprehensive Risk Profile or a Clinically Redundant Practice?
- Developing Global Maps of the Dominant Vectors of Human Malaria
- Guidance for Developers of Health Research Reporting Guidelines