Skip to main content

Advertisement

Log in

Outcomes of Antiretroviral Therapy in the Swiss HIV Cohort Study: Latent Class Analysis

  • Original Paper
  • Published:
AIDS and Behavior Aims and scope Submit manuscript

Abstract

An in-depth understanding of the different groups that make up the HIV-infected population should inform prevention and care. Using latent class analysis (LCA) we identified seven groups with similar socio-demographic and behavioral characteristics at enrolment in the Swiss HIV Cohort Study: older gay men, younger gay men, older heterosexual men, injection drug users, single migrants, migrant women in partnerships and heterosexual men and women. Outcomes of combination antiretroviral therapy (ART) were analyzed in 1,633 patients starting ART. Compared to older gay men, the probability of a virologic response to ART was reduced in single migrants, in older heterosexual men and in IDUs. Loss to follow-up was higher in single migrants and IDUs, and mortality was increased in older heterosexual men and IDUs. Socio-behavioral groups identified by LCA allow insights above what can be gleaned from traditional transmission groups, and may identify patients who could benefit from targeted interventions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. May MT, Sterne JA, Costagliola D, et al. HIV treatment response and prognosis in Europe and North America in the first decade of highly active antiretroviral therapy: a collaborative analysis. Lancet. 2006;368(9534):451–8.

    Article  PubMed  Google Scholar 

  2. Keiser O, Taffe P, Zwahlen M, et al. All cause mortality in the Swiss HIV Cohort Study from 1990 to 2001 in comparison with the Swiss population. AIDS. 2004;18(13):1835–43.

    Article  PubMed  Google Scholar 

  3. Zwahlen M, Harris R, May M, et al. Mortality of HIV-infected patients starting potent antiretroviral therapy: comparison with the general population in nine industrialized countries. Int J Epidemiol. 2009;38(6):1624–33.

    Article  PubMed  Google Scholar 

  4. Ledergerber B, Egger M, Opravil M, et al. Clinical progression and virological failure on highly active antiretroviral therapy in HIV-1 patients: a prospective cohort study. Lancet. 1999;353(9156):863–8.

    Article  PubMed  CAS  Google Scholar 

  5. Pellmar TC, Brandt EN Jr, Baird MA. Health and behavior: the interplay of biological, behavioral, and social influences: summary of an institute of medicine report. Am J Health Promot. 2002;16(4):206–19.

    Article  PubMed  Google Scholar 

  6. Wood E, Hogg RS, Lima VD, et al. Highly active antiretroviral therapy and survival in HIV-infected injection drug users. JAMA. 2008;300(5):550–4.

    Article  PubMed  CAS  Google Scholar 

  7. Hinkin CH, Hardy DJ, Mason KI, et al. Medication adherence in HIV-infected adults: effect of patient age, cognitive status, and substance abuse. AIDS. 2004;18(Suppl 1):S19–25.

    PubMed  Google Scholar 

  8. Appay V, Sauce D. Immune activation and inflammation in HIV-1 infection: causes and consequences. J Pathol. 2008;214(2):231–41.

    Article  PubMed  CAS  Google Scholar 

  9. Brenchley JM, Price DA, Schacker TW, et al. Microbial translocation is a cause of systemic immune activation in chronic HIV infection. Nat Med. 2006;12(12):1365–71.

    Article  PubMed  CAS  Google Scholar 

  10. McMahon J, Wanke CA, Terrin N, Skinner S, Knox T. Poverty, hunger, education, and residential status impact survival in HIV. Aids Behavior. 2010. (in press).

  11. Hogg R, Strathdee SA, Craib KJ, O’Shaughnessy MV, Montaner JS, Schechter MT. Lower socioeconomic status and shorter survival following HIV infection. Lancet. 1994;344(8939):1100–1.

    Google Scholar 

  12. Chaisson RE, Keruly JC, Moore RD. Race, sex, drug use, and progression of human immunodeficiency virus disease. N Engl J Med. 1995;333(12):751–6.

    Article  PubMed  CAS  Google Scholar 

  13. Oramasionwu CU, Brown CM, Lawson KA, Ryan L, Frei CR. Evaluating HIV/AIDS disparities for blacks in the United States: a review of antiretroviral and mortality studies. J Natl Med Assoc. 2009;101(12):122–9.

    Google Scholar 

  14. McDavid Harrison K, Ling Q, Song R, Hall HI. County-level socioeconomic status and survival after HIV diagnosis, United States. Ann Epidemiol. 2008;18(12):919–27.

    Article  PubMed  Google Scholar 

  15. Katz MH, Hsu L, Lingo M, Woelffer G, Schwarcz SK. Impact of socioeconomic status on survival with AIDS. Am J Epidemiol. 1998;148(3):282–91.

    PubMed  CAS  Google Scholar 

  16. Lazarsfeld R, Henry NW. Latent structure analysis. Latent structure analysis. Boston: Houghton Mifflin; 1968.

    Google Scholar 

  17. Spycher BD, Silverman M, Brooke AM, Minder CE, Kuehni CE. Distinguishing phenotypes of childhood wheeze and cough using latent class analysis. Eur Respir J. 2008;31(5):974–81.

    Article  PubMed  CAS  Google Scholar 

  18. Ganesalingam J, Stahl D, Wijesekera L, et al. Latent cluster analysis of ALS phenotypes identifies prognostically differing groups. PLoS One. 2009;4(9):e7107.

    Article  PubMed  Google Scholar 

  19. Girardi E, Angeletti C, Puro V, et al. Estimating diagnostic accuracy of tests for latent tuberculosis infection without a gold standard among healthcare workers. Euro Surveill. 2009;14(43):1–9.

    Google Scholar 

  20. Schoeni-Affolter F, Ledergerber B, Rickenbach M, et al. Cohort profile: the Swiss HIV Cohort study. Int J Epidemiol. 2010;39(5):1179–89.

    Article  PubMed  Google Scholar 

  21. Weber R, Huber M, Rickenbach M, et al. Uptake of and virological response to antiretroviral therapy among HIV-infected former and current injecting drug users and persons in an opiate substitution treatment programme: the Swiss HIV Cohort Study. HIV Med. 2009;10(7):407–16.

    Article  PubMed  CAS  Google Scholar 

  22. Centers for Disease Control. 1993 revised classification system for HIV infection and expanded surveillance case definition for AIDS among adolescents and adults. MMWR. 1992;41:1–20.

    Google Scholar 

  23. McLachlan G, Peel D. Finite mixture models. New York: John Wiley & Sons; 2000.

    Book  Google Scholar 

  24. Rubin D. Multiple imputation for nonresponse in surveys. New York: Wiley; 1987.

    Book  Google Scholar 

  25. Gebhardt M, Rickenbach M, Egger M. Impact of antiretroviral combination therapies on AIDS surveillance reports in Switzerland. Swiss HIV Cohort Study. AIDS. 1998;12(10):1195–201.

    Article  PubMed  CAS  Google Scholar 

  26. Simoni JM, Kurth AE, Pearson CR, Pantalone DW, Merrill JO, Frick PA. Self-report measures of antiretroviral therapy adherence: a review with recommendations for HIV research and clinical management. AIDS Behav. 2006;10(3):227–45.

    Article  PubMed  Google Scholar 

  27. Glass TR, Battegay M, Cavassini M, et al. Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study. J Acquir Immune Defic Syndr. 2010;54(2):197–203.

    PubMed  Google Scholar 

  28. Greenland S, Gago-Dominguez M, Castelao JE. The value of risk-factor (“black-box”) epidemiology. Epidemiology. 2004;15(5):529–35.

    Article  PubMed  Google Scholar 

  29. Sterne JA, May M, Costagliola D, et al. Timing of initiation of antiretroviral therapy in AIDS-free HIV-1-infected patients: a collaborative analysis of 18 HIV cohort studies. Lancet. 2009;373(9672):1352–63.

    Article  PubMed  Google Scholar 

  30. Kitahata MM, Gange SJ, Abraham AG, et al. Effect of early versus deferred antiretroviral therapy for HIV on survival. N Engl J Med. 2009;360(18):1815–26.

    Article  PubMed  CAS  Google Scholar 

  31. Egger M, May M, Chene G, et al. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet. 2002;360(9327):119–29.

    Article  PubMed  Google Scholar 

  32. Braude HD. Clinical intuition versus statistics: different modes of tacit knowledge in clinical epidemiology and evidence-based medicine. Theor Med Bioeth. 2009;30(3):181–98.

    Article  PubMed  Google Scholar 

  33. Staehelin C, Keiser O, Calmy A, et al. Response to antiretroviral therapy in HIV-positive migrants of Sub-Saharan African origin within the Swiss HIV Cohort Study (SHCS). AIDS conference, Mexico 2008. Available at http://www.aids2008.org/Pag/Abstracts.aspx?SID=229&AID=6062. Accessed 5 May 2010.

  34. Young J, De Geest S, Spirig R, et al. Stable partnership and progression to AIDS or death in HIV infected patients receiving highly active antiretroviral therapy: Swiss HIV Cohort Study. BMJ. 2004;328(7430):15.

    Article  PubMed  Google Scholar 

  35. Braitstein P, Brinkhof MWG, Dabis F, et al. Mortality of HIV-1-infected patients in the first year of antiretroviral therapy: comparison between low-income and high-income countries. Lancet. 2006;367:817–24.

    Article  PubMed  Google Scholar 

  36. Lanoy E, Mary-Krause M, Tattevin P, et al. Frequency, determinants and consequences of delayed access to care for HIV infection in France. Antivir Ther. 2007;12(1):89–96.

    PubMed  Google Scholar 

  37. Battegay M, Fluckiger U, Hirschel B, Furrer H. Late presentation of HIV-infected individuals. Antivir Ther. 2007;12(6):841–51.

    PubMed  Google Scholar 

  38. Wolbers M, Bucher HC, Furrer H, et al. Delayed diagnosis of HIV infection and late initiation of antiretroviral therapy in the Swiss HIV Cohort Study. HIV Med. 2008;9(6):397–405.

    Article  PubMed  CAS  Google Scholar 

  39. Nellen JF, Wit FW, de Wolf F, Jurriaans S, Lange JM, Prins JM. Virologic and immunologic response to highly active antiretroviral therapy in indigenous and nonindigenous HIV-1-infected patients in the Netherlands. J Acquir Immune Defic Syndr. 2004;36:943–50.

    Article  PubMed  Google Scholar 

  40. van den Berg JB, Hak E, Vervoort SC, et al. Increased risk of early virological failure in non-European HIV-1-infected patients in a Dutch cohort on highly active antiretroviral therapy. HIV Med. 2005;6(5):299–306.

    Article  PubMed  Google Scholar 

  41. World Health Organization. National AIDS programme management. Module 4. Targeted HIV prevention and care interventions. 2007.

  42. Staehelin C, Egloff N, Rickenbach M, Kopp C, Furrer H. Migrants from sub-Saharan Africa in the Swiss HIV Cohort Study: a single center study of epidemiologic migration-specific and clinical features. AIDS Patient Care STDS. 2004;18(11):665–75.

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

This study was funded in the framework of the Swiss HIV Cohort Study and a PROSPER fellowhip to O Keiser, both supported by the Swiss National Science Foundation. The members of the Swiss HIV Cohort Study are Barth J, Battegay M, Bernasconi E, Böni J, Bucher HC, Bürgisser P, Burton-Jeangros C, Calmy A, Cavassini M, Dubs R, Egger M, Elzi L, Fehr J, Fischer M, Flepp M, Francioli P (President of the SHCS), Furrer H (Chairman of the Clinical and Laboratory Committee), Fux CA, Gorgievski M, Günthard H (Chairman of the Scientific Board), Hasse B, Hirsch HH, Hirschel B, Hösli I, Kahlert C, Kaiser L, Keiser O, Kind C, Klimkait T, Kovari H, Ledergerber B, Martinetti G, Martinez de Tejada B, Müller N, Nadal D, Pantaleo G, Rauch A, Regenass S, Rickenbach M (Head of Data Center), Rudin C (Chairman of the Mother & Child Substudy), Schmid P,Schultze D, Schöni-Affolter F, Schüpbach J, Speck R, Taffé P, Telenti A, Trkola A, Vernazza P, von Wyl V, Weber R, Yerly S.

Author information

Authors and Affiliations

Authors

Consortia

Corresponding author

Correspondence to Olivia Keiser.

Additional information

Olivia Keiser and Ben Spycher contributed equally to this study.

The members of The Swiss HIV Cohort Study are given in the acknowledgement.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Keiser, O., Spycher, B., Rauch, A. et al. Outcomes of Antiretroviral Therapy in the Swiss HIV Cohort Study: Latent Class Analysis. AIDS Behav 16, 245–255 (2012). https://doi.org/10.1007/s10461-011-9971-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10461-011-9971-5

Keywords

Navigation