Frank J. Palella, MD; Carl Armon, MSPH; Kate Buchacz, PhD, MPH; Stephen R. Cole, PhD; Joan S. Chmiel, PhD; Richard M. Novak, MD; Kathleen Wood, BSN; Anne C. Moorman, BSN; John T. Brooks, MD; HOPS (HIV Outpatient Study) Investigators
Disclaimer: The findings and conclusions in this paper are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
Grant Support: By the Centers for Disease Control and Prevention (contract no. 200-2006-18797).
Potential Financial Conflicts of Interest: None disclosed.
Reproducible Research Statement:Study protocol and statistical code: Available from the authors. Data set: The HOPS is a public-use data set and is available to readers. However, confidentiality protections that govern the HOPS data require authors to strip record identifiers; it will therefore take some time to make these data available. In addition, the CDC's heightened security procedures require persons who want to analyze HOPS data to 1) prepare a written proposal for CDC review and approval, 2) sign confidentiality and data use agreements, 3) conduct analyses in Atlanta, and 4) go through CDC security clearance for access to facilities. The authors would be happy to facilitate these procedures for persons interested in conducting analyses with HOPS project data and welcome these requests.
Requests for Single Reprints: Frank J. Palella Jr., MD, Division of Infectious Diseases, Northwestern University, Feinberg School of Medicine, 645 North Michigan Avenue, Suite 900, Chicago, IL 60611; e-mail, email@example.com.
Current Author Addresses: Dr. Palella: Division of Infectious Diseases, Northwestern University, Feinberg School of Medicine, 645 North Michigan Avenue, Suite 900, Chicago, IL 60611.
Mr. Armon: PO Box 1677, Boulder, CO 80306-1677.
Drs. Buchacz and Brooks: Epidemiology Branch, Division of HIV/AIDS Prevention, Centers for Disease Control and Prevention, 1600 Clifton Road, MS E-45, Atlanta, GA 30333.
Dr. Cole: Campus Box 7435, Department of Epidemiology, Gillings School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7435.
Dr. Chmiel: Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, Suite 1102, 680 North Lake Shore Drive, Chicago, IL 60611-4402.
Dr. Novak: 1801 West Taylor Street, Suite 3D, Chicago, IL 60612.
Ms. Wood: Cerner Corporation, 1953 Gallows Road, Suite 500, Vienna, VA 22182.
Ms. Moorman: National Center for HIV/AIDS, Viral Hepatitis, STD, and TB Prevention, Division of Viral Hepatitis, Epi/Surveillance Branch, Mailstop G-37, Centers for Disease Control and Prevention, 1600 Clifton Road, Atlanta, GA 30333.
Author Contributions: Conception and design: F.J. Palella, K. Buchacz, S.R. Cole, J.S. Chmiel, R.M. Novak, A.C. Moorman, J.T. Brooks.
Analysis and interpretation of the data: F.J. Palella, C. Armon, K. Buchacz, S.R. Cole, J.S. Chmiel, R.M. Novak, J.T. Brooks.
Drafting of the article: F.J. Palella, C. Armon, S.R. Cole, J.S. Chmiel, J.T. Brooks.
Critical revision of the article for important intellectual content: F.J. Palella, C. Armon, K. Buchacz, S.R. Cole, J.S. Chmiel, R.M. Novak, J.T. Brooks.
Final approval of the article: F.J. Palella, C. Armon, K. Buchacz, S.R. Cole, J.S. Chmiel, R.M. Novak, K. Wood, A.C. Moorman, J.T. Brooks.
Statistical expertise: C. Armon, K. Buchacz, S.R. Cole, J.S. Chmiel.
Obtaining of funding: K. Wood, J.T. Brooks.
Administrative, technical, or logistic support: K. Wood, A.C. Moorman.
Collection and assembly of data: K. Wood, A.C. Moorman.
For a list of the HOPS investigators, see Appendix 1.
Palella F., Armon C., Buchacz K., Cole S., Chmiel J., Novak R., Wood K., Moorman A., Brooks J., ; The Association of HIV Susceptibility Testing With Survival Among HIV-Infected Patients Receiving Antiretroviral Therapy: A Cohort Study. Ann Intern Med. 2009;151:73-84. doi: 10.7326/0003-4819-151-2-200907210-00003
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Published: Ann Intern Med. 2009;151(2):73-84.
HIV-1 genotypic and phenotypic susceptibility testing (GPT) optimizes antiretroviral selection, but its effect on survival is unknown.
To evaluate the association between GPT and survival.
10 U.S. HIV clinics.
2699 HIV-infected patients eligible for GPT (plasma HIV RNA level >1000 copies/mL) seen from 1999 through 2005.
Demographic characteristics, clinical factors, GPT use, all-cause mortality, and crude and adjusted hazard ratios (HRs) for the association of GPT with survival.
Patients were followed for a median of 3.3 years; 915 (34%) had GPT. Patients who had GPT had lower mortality rates than those who did not (2.0 vs. 2.7 deaths per 100 person-years). In standard Cox models, GPT was associated with improved survival (adjusted HR, 0.69 [95% CI, 0.51 to 0.94]; PÂ = 0.017) after controlling for demographic characteristics, CD4+ cell count, HIV RNA level, and intensity of clinical follow-up. In subgroup analyses, GPT was associated with improved survival for the 2107 highly active antiretroviral therapy (HAART)â€“experienced patients (2.2 vs. 3.2 deaths per 100 person-years for patients who had GPT vs. those who did not have GPT; adjusted HR, 0.60 [CI, 0.43 to 0.82]; PÂ = 0.002) and for the 921 triple antiretroviral classâ€“experienced patients (2.1 vs. 3.1 deaths per 100 person-years; adjusted HR, 0.61 [CI 0.40 to 0.93]; PÂ = 0.022). Marginal structural models supported associations between GPT and improved survival in the overall cohort (adjusted HR, 0.54; PÂ = 0.001) and in the HAART-experienced group (adjusted HR, 0.56; PÂ = 0.003).
Use of GPT was not randomized. Residual confounding may exist.
Use of GPT was independently associated with improved survival among HAART-experienced patients.
Centers for Disease Control and Prevention.
Division of Infectious Diseases, AUSL Rimini, Italy
August 14, 2009
HIV SusceptibilityTesting With Survival Among HIV-Infected Patients Receiving Antiretroviral Therapy
To the Editor, In the Vol.151 n 2, 2009 of the Annals, Palella J.F and colleagues presented an analysis of the HOPS cohort in order to evaluate the effect of HIV susceptibility testing (GPT ) on survival among HIV-Infected patients. The conclusion of the authors is that the use of GPT is independently associated with improved survival among HAART-experienced patients.
Nevertheless, as underlined by authors, the lack of randomization is a great limitation of the study, highlighted by significant differences between patients receiving or not receiving GPT both at baseline, where patients in no-GPT group were more likely to be black, to have history of injection drug abuse and not provided of private medical insurance, and during follow-up where patients in GPT group were more likely to receive antiretroviral therapy, to be treated with HAART or more potent drugs ( PI or NNRTI) and to have an antiretroviral regimen change . RCTs designed to investigate the role of resistance testing in the management of antiretroviral therapy, have failed in demonstrating a long term virological response of routine access to the testing (1), or have demonstrated only for genotyping testing and in studies with short term follow-up, a benefit of relatively small amount, but differences in CD4+ cell count (2) and in clinical events have never been reported.
In the present study 16% and 33% of overall deaths occurred in the first 6 and 12 months respectively in the no-GPT group, compared with 0 and 3% in GPT group. The difference in early mortality is surprising and in our opinion hard to explain only with a presumable better choice of antiretroviral agents GPT-guided. The differences in baseline characteristics and in attending care during follow-up between the two groups are so evident that, in the context of this cohort, it seems more probable that the use of GPT might be a marker for improvement or advantages in other aspects of care. Although the lack of a clear relationship with a better long term virological and clinical response , the relatively large discordances between genotypic interpretation systems (3,4) and development of different mechanisms of drug resistance (5), genotyping testing are widely used, while the effect of care-related aspects has never been systematically measured.
In our opinion the present study well highlights as these aspects might be crucial so that the best choice of antiretroviral regimen might be really the choice with the best effect on long term outcome.
1) 1 Wegener SA, Wallace MR, Aronson NE, Tascher SA, Blazes DL, Tamminga C, et al. Long-Term Efficacy of Routine Access To Antiretroviral-Resistant Testing in HIV Type-1-Infected Patients: Results of the Clinical Efficacy of Resistant Testing Trial. Clin Infect Dis. 2004;38:723-30
2) Panidou ET, Trikalinos TA, Ioannidis JPA. Limited benefit of antiretroviral resistance testing in treatment-experienced patients: a meta-analysis. AIDS. 2004;18:2153-2161
3) Ravela J, Bradley JB, Brun-Vezinet F, Vandamme AM, Descamps D, Van Laethem K, et al. HIV-1 Protease and Reverse Transcriptase Mutation Patterns responsible for discordance between Genotypic drug resistance interpretation algorithms. JAIDS. 2003;33:8-14
4) Fox VZ, Geretti AM, Kiaer J, Dragsted UB, Phillips AN, Gerstoft J, et al. The ability of four genotypic interpretation systems to predict virological response to ritonavir-boosted protease inhibitors. AIDS. 2007;2033-2042
5) Nijhuis M, van Maarseveen NM, Lestere S, Schipper P, Coakley E, Glass B, et al. A novel substrate based HIV-1 protease inhibitor drug resistance mechanism. PLOS Medicine. 2007;4:152-163
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