Top

Published in:

01-08-2021 | Human Immunodeficiency Virus | Behavioral-Bio-Medical Interface (RJ DiClemente and JL Brown, Section Editors)

The Value of Assessing Self-Reported and Biological Indicators of Outcomes in Evaluating HIV Programs

Authors: Rick S. Zimmerman, Purnima Mehrotra, Tessa Madden, Rachel Paul

Published in: Current HIV/AIDS Reports | Issue 4/2021

Abstract

Purpose of Review

In this manuscript, we present recent findings concerning concordance and discrepancy between biological measures and self-reports of these three outcomes of HIV programs: HIV status, adherence to antiretroviral medications (ARVs) and use of and adherence to pre-exposure prophylaxis medication (PrEP), and condom use/unprotected sex.

Recent Findings

Recent studies suggest that three successive rapid HIV tests (for those whose first test in positive) might be reasonably inexpensive and valid biological data to collect to combine with self-reports of HIV status, dried blood spots sufficiently affordable to combine with self-reports of adherence to ARVs and use of or adherence to PrEP, and that the discrepancy between self-reports of condom use and biomarkers of unprotected sex may be relatively small in high-income countries. Additional work on assessment of incorrect condom usage and breakage, standardized self-report measures of condom use, and more private data collection methodologies in low-income settings might reduce the recent observed discrepancies even further.

Summary

Concordance between self-reports of HIV and biomarkers indicating HIV positive status has varied considerably, with much lower rates in low-income countries, where the stigma of HIV is still very high. Recommendation is for combining self-report data with the results of three successive rapid tests for those testing positive. For adherence, again agreement between self-reports and a variety of more objective and/or biological measures is only moderate. Dried blood spots (DBS) may be sufficiently inexpensive in low-resource settings that this may be the best biological method to combine with self-reports. In publications over the last 8 years, the discrepancy between self-reports of condom use and biomarkers for unprotected sex may be even lower than 20% after controlling for other features of the study, particularly in high-income countries. Our results suggest that more careful assessment of incorrect condom use and breakage as reasons other than intentional misreporting should be investigated more carefully and that more private data collection methods such as audio, computer-assisted self-interviewing (ACASI) might be employed more often in low-resource settings to reduce this discrepancy in those settings further. In addition, further analysis of the discrepancy between self-reports of condom use and biomarkers should be conducted of published studies using the correct calculation methods to be more certain of these findings.

Zimmerman RS, Langer LM. Improving prevalence estimates of sensitive behaviors: the randomized lists technique and self-reported honesty. J Sex Res. 2002;32:107–17.CrossRef

Zenilman JM, Yuenger J, Galai N, Turner CF, Rogers SM. Polymerase chain reaction detection of Y chromosome sequences in vaginal fluid: preliminary studies of a potential biomarker for sexual behavior. Sex Transm Dis. 2005;32(2):90–4.PubMedCrossRef

Zimmerman RS, Morisky DE, Harrison L, Hayley M. Validity of behavioral measures as proxies for HIV-related outcomes. J Acquir Immune Defic Syndr. 2014;66(3):S285–92.PubMedPubMedCentralCrossRef

Gallo MF, Steiner MJ, Hobbs MM, Warner L, Jamieson DJ, Macaluso M. Biological markers of sexual activity: tools for improving measurement in HIV/sexually transmitted infection prevention research. Sex Transm Dis. 2013;40(6):112–9.CrossRef

UNAIDS. 90–90–90: an ambitious treatment target to help end the AIDS epidemic. Geneva: Joint United Nations Programme on HIV/AIDS (UNAIDS); 2014.

Rentsch CT, Reniers G, Machemba R, Slaymaker E, Marston M, Wringe A, et al. Nondisclosure of HIV testing history in population-based surveys: implications for estimating a UNAIDS 90–90-90 target. Glob Health Action. 2018;11:1553470.PubMedCentralCrossRef

UNAIDS. UNAIDS data 2019. Retrieved from https://www.unaids.org/sites/default/files/media_asset/2019-UNAIDS-data_en.pdf on February 8, 2021.

Maheu-Giroux M, Marsh K, Doyle CM, Godin A, Laniece Delaunay C, Johnson LF, et al. National HIV testing and diagnosis coverage in sub-Saharan Africa: a new modeling tool for estimating the ‘first 90’ from program and survey data. AIDS. 2019;33(Suppl 3):S255–69.PubMedCrossRef

• Soni Nirali, Giguère Katia, Boily Marie-Claude, Fogel Jessica M, Maheu-Giroux Mathieu, Dimitrov Dobromir, Eshleman Susan, Mitchell Kate M. Under-reporting of known HIV-positive status among people living with HIV: a systematic review and meta-analysis. 2020. Available at SSRN: https://ssrn.com/abstract=3690926 or https://doi.org/10.2139/ssrn.3690926. This article conducted a meta-analysis of under-reporting of HIV-positive status in self-reports as compared to biological or clinical markers. Results indicated about 20% under-reporting on average, with somewhat higher levels in North American MSM.

10.

Fishel JD, Barrere B, Kishor S. Validity of data on self-reported HIV status in Malawi and Uganda and implications for measurement of ARV coverage. Rockville, Maryland: DHS Methodological Reports No. 10; 2014. Retrieved from http://dhsprogram.com/pubs/pdf/MR10/MR10.pdf. Accessed 23 Jan 2021.

11.

McCusker J, Stoddard AM, McDonald M, Zapka JG, Mayer KH. Maintenance of behavioral change in a cohort of homosexually active men. AIDS. 1992;6:861–8.PubMedCrossRef

12.

Rohr JK, Manne-Goehler J, Gomez-Olive FX, Wagner RG, Rosenberg M, Geldsetzer P, et al. HIV 490 treatment cascade for older adults in rural South Africa. Sex Transm Infect. 2019;491(96):271–6. https://doi.org/10.1136/sextrans-2018-053925.CrossRef

13.

Rodger A, Cambiano V, Bruun T, et al. Sexual activity without condoms and risk of HIV transmission 419 in serodifferent couples when the HIV-positive partner is using suppressive antiretroviral therapy. 420. JAMA. 2016;316:171 421 5.PubMedCrossRef

14.

Hall HI, Holtgrave DR, Maulsby C. HIV transmission rates from persons living with HIV who are 422 aware and unaware of their infection. AIDS. 2012;26(7):893–6. 423. https://doi.org/10.1097/QAD.0b013e328351f73f.CrossRefPubMed

15.

Johnston LG, Sabin ML, Prybylski D, Sabin K, McFarland W, Baral S, et al. The importance of assessing self-reported HIV status in bio-behavioural surveys. Bull World Health Organ. 2016;94(8):605–12. https://doi.org/10.2471/BLT.15.162933.CrossRefPubMedPubMedCentral

16.

Xia Y, Milwid RM, Godin A, Boily MC, Johnson LF, Marsh K, et al. Accuracy of self-reported HIV-testing history and awareness of HIV-positive status in four sub-Saharan African countries. AIDS. 2021;35(3):503–10. https://doi.org/10.1097/QAD.0000000000002759.CrossRefPubMed

17.

Origer A, Schmit JC. Prevalence of hepatitis B and C and HIV infections among problem drug users in Luxembourg: self-report versus serological evidence. J Epidemiol Community Health. 2012;66(1):64–8. https://doi.org/10.1136/jech.2009.101378.CrossRefPubMed

18.

Salani Mota RM, Sansigolo Kerr LR, Kendall C, Pinho A, de Mello MB, Dourado I, et al. Reliability of self-report of HIV status among men who have sex with men in Brazil. J Acquir Immune Defic Syndr. 2011;57(Suppl 3):S153–6. https://doi.org/10.1097/QAI.0b013e31821e9c10.CrossRefPubMed

19.

Ng’ang’a A, Waruiru W, Ngare C, et al. The status of HIV testing and counselling in Kenya: results from a nationally representative population-based survey. J Acquir Immune Defic Syndr. 2014;66(suppl 1):S27–36.PubMedPubMedCentralCrossRef

20.

Mooney AC, Campbell CK, Rathagana M-J, Grignon J, Mazibuko, et al. Beyond social desirability bias: investigating inconsistencies in self-reported HIV testing and treatment behaviors among HIV-positive adults in north West Province, South Africa. AIDS Behav. 2018;22:2368–79.PubMedCrossRef

21.

WHO. Consolidated strategic information guidelines for HIV in the health sector. Geneva: World Health Organization; 2015.

22.

CDC. 2020. Types of HIV Tests. https://www.cdc.gov/hiv/basics/hiv-testing/test-types.html#:~:text=There%20are%20three%20types%20of, drawing%20blood%20from%20a%20vein. February 19, 2021.

23.

Siedner MJ, Baisley K, Koole O, Mpofana I, Ording-Jespersen G, Matthews P, et al. Does antiretroviral therapy use affect the accuracy of HIV rapid diagnostic assays? Experience from a demographic health and surveillance site in rural South Africa. Diagn Microbiol Infect Dis. 2020;97(2):115031.PubMedPubMedCentralCrossRef

24.

Robbins RN, Spector AY, Mellins CA, Remien RH. Optimizing ART adherence: update for HIV treatment and prevention. Curr HIV/AIDS Rep. 2014;11(4):423–33.PubMedPubMedCentralCrossRef

25.

Haberer JE. Current concepts for PrEP adherence in the PrEP revolution: from clinical trials to routine practice. Curr Opin HIV AIDS. 2016;11(1):10–7.PubMedPubMedCentralCrossRef

26.

Haas AD, Zaniewski E, Anderegg N, Ford N, Fox MP, Vinikoor M, et al. Retention and mortality on antiretroviral therapy in subSaharan Africa: collaborative analyses of HIV treatment programmes. J Int AIDS Soc. 2018;21(2). https://doi.org/10.1002/jia2.25084.

27.

Castillo-Mancilla JR, Brown TT, Erlandson KM, Palella FJ Jr, Gardner EM, Macatangay BJ, et al. Suboptimal adherence to combination antiretroviral therapy is associated with higher levels of inflammation despite HIV suppression. Clin Infect Dis. 2016;63(12):1661–7. https://doi.org/10.1093/cid/ciw650.CrossRefPubMedPubMedCentral

28.

Rhead R, Masimirembwa C, Cooke G, Takaruza A, Nyamukapa C, Mutsimhi C, et al. Might ART Adherence Estimates Be Improved by Combining Biomarker and Self-Report Data? PLoS One. 2016;11(12):e0167852. https://doi.org/10.1371/journal.pone.0167852.CrossRefPubMedPubMedCentral

29.

Grant RM, Lama JR, Anderson PL, McMahan V, Liu AY, Vargas L, et al. Preexposure chemoprophylaxis for HIV prevention in men who have sex with men. N Engl J Med. 2010;363:2587–99. https://doi.org/10.1056/NEJMoa1011205.CrossRefPubMedPubMedCentral

30.

Baeten JM, Donnell D, Ndase P, Mugo NR, Campbell JD, Wangisi J, et al. Antiretroviral prophylaxis for HIV prevention in heterosexual men and women. N Engl J Med. 2012;367:399–410. https://doi.org/10.1056/NEJMoa1108524.CrossRefPubMedPubMedCentral

31.

Anderson PL, Glidden DV, Liu A, Buchbinder S, Lama JR, Guanira JV, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4:151ra25. https://doi.org/10.1126/scitranslmed.3004006.CrossRef

32.

Desai M, Field N, Grant R, McCormack S. Recent advances in preexposure prophylaxis for HIV. BMJ. 2017;359:j5011. https://doi.org/10.1136/bmj.j5011.CrossRefPubMed

33.

Liu AY, Cohen SE, Vittinghoff E, Anderson PL, Doblecki-Lewis S, Bacon O, et al. Preexposure prophylaxis for HIV infection integrated with municipal and community-based sexual health services. JAMA Intern Med. 2016;176:75–84. https://doi.org/10.1001/jamainternmed.2015.4683.CrossRefPubMedPubMedCentral

34.

McCormack S, Dunn DT, Desai M, Dalling D, Gafos M, et al. Pre-exposure prophylaxis to prevent the acquisition of HIV-1 infection (PROUD): effectiveness results from the pilot phase of a pragmatic open-label randomized trial. Lancet. 2016;387:53–60.PubMedPubMedCentralCrossRef

35.

Hojilla JC, Vlahov D, Glidden DV, Amico KR, Mehrotra M, Hance R, et al. Skating on thin ice: stimulant use and sub-optimal adherence to HIV pre-exposure prophylaxis. J Int AIDS Soc. 2018;21:e25103. https://doi.org/10.1002/jia2.25103.CrossRefPubMedPubMedCentral

36.

Simoni JM, Huh D, Wang Y, Wilson IB, Reynolds NR, Remien RH, et al. The validity of self-reported medication adherence as an outcome in clinical trials of adherence-promotion interventions: findings from the MACH14 Study. AIDS Behav. 2014;18:2285–90. https://doi.org/10.1007/s10461-014-0905-x.CrossRefPubMedPubMedCentral

37.

Agot K, Taylor D, Corneli AL, Wang M, Ambia J, Kashuba AD, et al. Accuracy of self-report and pill-count measures of adherence in the FEM-PrEP clinical trial: implications for future HIV-prevention trials. AIDS Behav. 2015;19:743–51. https://doi.org/10.1007/s10461-014-0859-z.CrossRefPubMed

38.

Mills EJ, Nachega JB, Buchan I, Orbinski J, Attaran A, Singh S, et al. Adherence to antiretroviral therapy in sub-Saharan Africa and North America: a meta-analysis. JAMA. 2006;296:679–90. https://doi.org/10.1001/jama.296.6.679.CrossRefPubMed

39.

Okatch H, Beiter K, Eby J, Chapman J, Marukutira T, Tshume O, et al. Brief report: apparent antiretroviral overadherence by pill count is associated with HIV treatment failure in adolescents. J Acquir Immune Defic Syndr. 2016;72(5):542–5. https://doi.org/10.1097/QAI.0000000000000994.34.CrossRefPubMedPubMedCentral

40.

Bisson GP, Gross R, Bellamy S, Chittams J, Hislop M, Regensberg L, et al. Pharmacy refill adherence compared with CD4 count changes for monitoring HIV-infected adults on antiretroviral therapy. PLoS Med. 2008;5(5):e109. https://doi.org/10.1371/journal.pmed.0050109.CrossRefPubMedPubMedCentral

41.

Winchester NE, Maldarelli F, Mejia Y, Dee N, Dewar R, Laidlaw E, et al. 8-day inpatient directly observed therapy for ART failure: a tool for preventing unnecessary ART changes and optimizing adherence support. Clin Infect Dis. 2019. https://doi.org/10.1093/cid/ciz590.

42.

Golin CE, Liu H, Hays RD, Miller LG, Beck CK, Ickovics J, et al. A prospective study of predictors of adherence to combination antiretroviral medication. J Gen Intern Med. 2002;17:756–65. https://doi.org/10.1046/j.1525-1497.2002.11214.x.CrossRefPubMedPubMedCentral

43.

Arnsten JH, Demas PA, Farzadegan H, Grant RW, Gourevitch MN, Chang C-J, et al. Antiretroviral therapy adherence and viral suppression in HIV-infected drug users: comparison of self-report and electronic monitoring. Clin Infect Dis Off Publ Infect Dis Soc Am. 2001;33:1417–23.CrossRef

44.

Yamada E, Takagi R, Sudo K, Kato S. Determination of abacavir, tenofovir, darunavir, and raltegravir in human plasma and saliva using liquid chromatography coupled with tandem mass spectrometry. J Pharm Biomed Anal. 2015;114:390–7 10.PubMedCrossRef

45.

Derissen EJ, Hillebrand MJ, Rosing H, Otten HM, Laille E, Schellens JH, et al. Quantitative determination of azacitidine triphosphate in peripheral blood mononuclear cells using liquid chromatography coupled with high-resolution mass spectrometry. J Pharm Biomed Anal. 2014;90:7–14 11.PubMedCrossRef

46.

Koal T, Burhenne H, Romling R, Svoboda M, Resch K, Kaever V. Quantifcation of antiretroviral drugs in dried blood spot samples by means of liquid chromatography/tandem mass spectrometry. Rapid Commun Mass Spectrom. 2005;19(21):2995–3001 12.PubMedCrossRef

47.

Wu Y, Yang J, Duan C, Chu L, Chen S, Qiao S, et al. Simultaneous determination of antiretroviral drugs in human hair with liquid chromatography-electrospray ionization-tandem mass spectrometry. J Chromatogr B Anal Technol Biomed Life Sci. 2018;1083:209–21.CrossRef

48.

Kumar AK, Ramachandran G, Kumar P, Kumaraswami V, Swaminathan S. Can urine lamivudine be used to monitor antiretroviral treatment adherence? MedGenMed. 2006;8(4):53. Published 2006 Dec 13. https://doi.org/10.1186/1758-2652-8-4-53.CrossRefPubMedPubMedCentral

49.

• Spinelli MA, Haberer JE, Chai PR, Castillo-Mancilla J, Anderson PL, Gandhi M. Approaches to objectively measure antiretroviral medication adherence and drive adherence interventions. Curr HIV/AIDS Rep. 2020;17(4):301–14. https://doi.org/10.1007/s11904-020-00502-5This paper reviews various objective measures of ARV and PrEP adherence. The authors conclude that some of the newest measures, including urine-based assays, “real-time electronic adherence monitors,” and ingestible electronic pills with sensors may be both valid measures and have an impact on adherence.CrossRefPubMedPubMedCentral

50.

Zhang Q, Qiao S, Yang X, Li X. Antiretroviral concentration in hair as a measure for antiretroviral medication adherence: a systematic review of global literature. AIDS Behav. 2020;24(1):311–30. https://doi.org/10.1007/s10461-019-02460-5.CrossRefPubMedPubMedCentral

51.

Hendrix CW, Andrade A, Bumpus NN, Kashuba AD, Marzinke MA, Moore A, et al. Dose frequency ranging pharmacokinetic study of tenofovir-emtricitabine after directly observed dosing in healthy volunteers to establish adherence benchmarks (HPTN 066). AIDS Res Hum Retrovir. 2016;32(1):32–43. https://doi.org/10.1089/AID.2015.0182.

52.

Castillo-Mancilla JR, Zheng JH, Rower JE, Meditz A, Gardner EM, Predhomme J, Fernandez C, Langness J, Kiser JJ, Bushman LR, Anderson PL Tenofovir, emtricitabine, and tenofovir diphosphate in dried blood spots for determining recent and Curr HIV/AIDS Rep (2020) 17:301–314 311 cumulative drug exposure. AIDS Res Hum Retrovir 2013;29(2): 384–390. https://doi.org/10.1089/AID.2012.0089.

53.

Gandhi M, Wang G, King R, Rodrigues WC, Vincent M, Glidden DV, et al. Development and validation of the first point-of-care assay to objectively monitor adherence to HIV treatment and prevention in real-time in routine settings. AIDS. 2020;34(2):255–60. https://doi.org/10.1097/QAD.0000000000002395.101.CrossRefPubMed

54.

Spinelli MA, Rodrigues WC, Wang G, Vincent M, Glidden DV, Okochi H, et al. High accuracy of a real-time urine antibody-based tenofovir point-of-care test compared to laboratory-based ELISA in diverse populations. JAIDS. 2020;84(2):149–2. https://doi.org/10.1097/QAI.0000000000002322.102.CrossRefPubMed

55.

Podsadecki TJ, Vrijens BC, Tousset EP, Rode RA, Hanna GJ. “White coat compliance” limits the reliability of therapeutic drug monitoring in HIV-1-infected patients. HIV Clin Trials. 2008;9(4):238–46.PubMedCrossRef

56.

Nettles RE, Kieffer TL, Parsons T, Johnson J, Cofrancesco J Jr, Gallant JE, et al. Marked intraindividual variability in antiretroviral concentrations may limit the utility of therapeutic drug monitoring. Clin Infect Dis. 2006;42(8):1189–96.PubMedCrossRef

57.

Anderson PL, Glidden DV, Liu A, Buchbinder S, Lama JR, Guanira JV, et al. Emtricitabine-tenofovir concentrations and pre-exposure prophylaxis efficacy in men who have sex with men. Sci Transl Med. 2012;4(151):151ra25. https://doi.org/10.1126/scitranslmed.3004006.CrossRef

58.

Anderson PL, Liu AY, Castillo-Mancilla JR, Gardner EM, Seifert SM, McHugh C, et al. Intracellular tenofovir-diphosphate and emtricitabine-triphosphate in dried blood spots following directly observed therapy. Antimicrob Agents Chemother. 2018;62(1). https://doi.org/10.1128/AAC.01710-17.

59.

Castillo-Mancilla J, Seifert S, Campbell K, Coleman S, McAllister K, Zheng JH, et al. Emtricitabine-triphosphate in dried blood spots as a marker of recent dosing. Antimicrob Agents Chemother. 2016;60(11):6692–7. https://doi.org/10.1128/AAC.01017-16.CrossRefPubMedPubMedCentral

60.

Morrow M, MaWhinney S, Coyle RP, Coleman SS, Gardner EM, Zheng JH, et al. Predictive value of tenofovir diphosphate in dried blood spots for future viremia in persons living with HIV. J Infect Dis. 2019;220(4):635–42. https://doi.org/10.1093/infdis/jiz144.CrossRefPubMedPubMedCentral

61.

Gandhi M, Yang Q, Bacchetti P, Huang Y. Short communication: a low-cost method for analyzing nevirapine levels in hair as a marker of adherence in resource-limited settings. AIDS Res Hum Retrovir. 2014;30(1):25–8. https://doi.org/10.1089/AID.2013.0239.CrossRefPubMedPubMedCentral

62.

Thaden JT, Gandhi M, Okochi H, Hurt CB, McKellar MS. Seroconversion on preexposure prophylaxis: a case report with segmental hair analysis for timed adherence determination. AIDS. 2018;32(9):F1–4. https://doi.org/10.1097/QAD.0000000000001825.CrossRefPubMed

63.

Blumenthal J, Pasipanodya EC, Jain S, et al. Comparing self-report pre-exposure prophylaxis adherence questions to pharmacologic measures of recent and cumulative pre-exposure prophylaxis exposure. Front Pharmacol. 2019;10:721. Published 2019 Jul 5. https://doi.org/10.3389/fphar.2019.00721.CrossRefPubMedPubMedCentral

64.

Ramsey S, Ames E, Uber J, Habib S, Clark S. A mobile health app to improve HIV medication adherence: protocol for a pilot randomized controlled trial. JMIR Res Protoc. 2019;8(11):e15356. https://doi.org/10.2196/15356.CrossRefPubMedPubMedCentral

65.

Coppock D, Zambo D, Moyo D, Tanthuma G, Chapman J, Re VL III, et al. Development and usability of a smartphone application for tracking antiretroviral medication refill data for human immunodeficiency virus. Methods Inf Med. 2017;56(5):351–9. https://doi.org/10.3414/ME17-01-0045.CrossRefPubMed

66.

Muchomba FM, Gearing RE, Simoni JM, El-Bassel N. State of the science of adherence in pre-exposure prophylaxis and microbicide trials. J Acquir Immune Defic Syndr. 2012;61:490–8. https://doi.org/10.1097/QAI.0b013e31826f9962.CrossRefPubMedPubMedCentral

67.

Amico KR, Mehrotra M, Avelino-Silva VI, McMahan V, Veloso VG, Anderson P, et al. Self-reported recent PrEP dosing and drug detection in an open label PrEP study. AIDS Behav. 2016;20:1535–40. https://doi.org/10.1007/s10461-016-1360-7.CrossRefPubMedPubMedCentral

68.

Musinguzi N, Muganzi CD, Boum Y 2nd, Ronald A, Marzinke MA, Hendrix CW, et al. Comparison of subjective and objective adherence measures for preexposure prophylaxis against HIV infection among serodiscordant couples in East Africa. AIDS. 2016;30:1121–9. https://doi.org/10.1097/QAD.0000000000001024.CrossRefPubMed

69.

Jadack RA, Yuenger J, Ghanem KG, Zenilman J. Polymerase chain reaction detecting of Y-chromosome sequences in vaginal fluid of women accessing a sexually transmitted disease clinic. Sex Transm Dis. 2006;33:22–5.PubMedCrossRef

70.

Gallo MF, Behets FM, Steiner MJ, et al. Prostate-specific antigen to ascertain reliability of self-reported coital exposure to semen. Sex Transm Dis. 2006;33:376–479.CrossRef

71.

Gallo MF, Behets FM, Steiner MJ, Thomsen SC, Ombidi W, Luchters S, et al. Validity of self-reported “safe sex” among female sex workers in Mombasa, Kenya—PSA analysis. Int J STD AIDS. 2007;18:33–8.PubMedCrossRef

72.

Thomsen SC, Gallo MF, Ombidi W, Omungo Z, Janowitz, et al. Randomised controlled trial on whether advance knowledge of prostate-specific antigen testing improves participant reporting of unprotected sex. Sex Transm Infect. 2007;83:419–20.PubMedCrossRef

73.

Minnis AM, Steiner MJ, Gallo MF, Warner L, Hobbs MM, van der Straten A, et al. Biomarker validation of reports of recent sexual activity: results of a randomized controlled study in Zibabwe. Am J Epidemiol. 2009;170:918–24.PubMedPubMedCentralCrossRef

74.

Rose E, Di Clemente RJ, Wingood GM, et al. The validity of teens’ and young adults’ self-reported condom use. Arch Pediatr Adolesc Med. 2009;63:61–4.CrossRef

75.

Aho J, Koushik A, Diakite SL, et al. Biological validation of self-reported condom use among sex workers in Guinea. AIDS Behav. 2010;14:1287–93.PubMedCrossRef

76.

Mensch BS, Hewett PC, Abbott S, Rankin J, Littlefield S, Ahmed K, et al. Assessing the reporting of adherence and sexual activity in a simulated microbicide trial in South Africa: an interview mode experiment using a placebo gel. AIDS Behav. 2011;15:407–21.PubMedCrossRef

77.

Evans JL, Couture M-C, Stein ES, Sansothy N, Maher L, Page K, et al. Biomarker validation of recent unprotected sexual intercourse in a prospective study of young men engaged in sex work in Phnom Penh, Cambodia. Sex Transm Dis. 2013;40:462–8.PubMedPubMedCentralCrossRef

78.

Mose F, Newman LP, Njunguna R, Tamooh H, John-Stewart G, Farquhar C, et al. Biomarker evaluation of self-reported condom use among women in HIV-serodiscordant couples. Int J STD AIDS. 2013;24(7):537–40.PubMedPubMedCentralCrossRef

79.

McCoy SI, Ralph LJ, Padian NS, MInnis AM. Are hormonal contraceptive users more likely to misreport unprotected sex? Evidence from a biomarker validation study in Zimbabwe. AIDS Behav. 2014;18:2259–64.PubMedPubMedCentralCrossRef

80.

Penrose KJ, Richardson BA, Besson G, Dezzrutti CS, Herold BC, et al. Y chromosome and HIV DNA detection in vaginal swabs as biomarkers of semen and HIV exposure in women. Sex Transm Dis. 2014;41(11):674–9.PubMedPubMedCentralCrossRef

81.

Rosenbaum JE, Zenilman J, Melendez J, Rose E, Wingood G, Diclemente R. Telling truth from Ys: An evaluation of whether the accuracy of self-reported semen exposure assessed by a semen Y-chromosome biomarker predicts pregnancy in a longitudinal cohort study of pregnancy. Sex Transm Infect. 2014;90(6):479–84.PubMedCrossRef

82.

Gallo MF, Warner L, Hobbs MM, Jamieson DJ, Hylton-Kong T, Steiner MJ. Differences in misreporting of sexual behavior over time: implications for HIV trials. Sex Transm Dis. 2015;42(3):160–1.PubMedPubMedCentralCrossRef

83.

An T, Carr RP, Snead MC, Fields K, Ervin M, Kourtis AP, et al. Recent biomarker-confirmed unprotected vaginal sex, but not self-reported unprotected sex, is associated with recurrent bacterial vaginosis. Sex Transm Dis. 2016;43(3):172–6.CrossRef

84.

Wilson KS, Deya R, Yuhas K, Simoni J, Stoep AV, Shafi J, et al. A prospective cohort study of intimate partner violence and unprotected sex in HIV-positive female sex workers in Mombasa, Kenya. AIDS Behav. 2016;20(9):2054–64.PubMedPubMedCentralCrossRef

85.

Heffron R, Parikh UM, Penrose KJ, Mugo N, Donnell D, et al. Objective measurement of inaccurate condom use reporting among women using depot Medroxyprogesterone acetate for contraception. AIDS Behav. 2017;21:2173–9.PubMedPubMedCentralCrossRef

86.

Zia Y, Davis N, Wiener J, Lapple D, Chinula L, et al. Factors associated with vaginal prostate-specific antigen detection and self-reported unprotected sex in a clinical trial in Malawi. Sex Transm Infect. 2017;93(suppl 2):A184.

87.

Malagon T, Burchell A, El-Zein M, Guenoun J, Tellier P-P, et al. Y chromosome DNA in women’s vaginal samples as a biomarker of recent vaginal sex and condom use with male partners in the HITCH cohort study. Sex Transm Dis. 2018;45(1):28–34.PubMedPubMedCentralCrossRef

88.

Fiore JR, Zoboli F, DiStefano M, Fasano M, et al. Inconsistent use of condom in Italian HIV-serodiscordant heterosexual couples as revealed by the detection of Y chromosomal (Y_c) DNA in vaginal swabs. Open AIDS J. 2019;13:31–5.CrossRef

89.

Giguere K, Behanzin L, Guedou FA, Talbot D, Leblond FA, et al. PrEP use among female sex workers: no evidence for risk compensation. JAIDS. 2019;82(3):257–64.PubMed

90.

Giguere K, Behanzin L, Guedou FA, Leblond FA, Goma-Matsetse E, et al. Biological validation of self-reported unprotected sex and comparison of underreporting over two different recall periods among female sex workers in Benin. Open F Infect Dise. 2019;6(2):ofz010. https://doi.org/10.1093/ofid/ofz010.CrossRef

91.

Roberts DA, Hawes SE, Bao MDB, Ndiaye AJ, Gueye D, et al. Trends in reported sexual behavior and Y-chromosomal DNA detection among female sex workers in the Senegal preexposure prophylaxis demonstration project. Sex Transm Dis. 2020;47(5):314–20.PubMedPubMedCentralCrossRef

92.

Wilson KS, Wanje G, Masese L, Simoni J, Shafi J, et al. A prospective cohort study of fertility desire, unprotected sex, and detectable viral load in HIV-positive female sex workers in Mombasa, Kenya. J Acquir Immune Defic Syndr. 2018;78(3):276–82.PubMedPubMedCentralCrossRef

93.

Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42(2):377–81.CrossRefPubMed

94.

Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95:103208.PubMedPubMedCentralCrossRef

95.

Fishbein M, Pequegnat W. Evaluating AIDS prevention interventions using behavioral and biological outcome measures. Sex Transm Dis. 2000;27(2):101–10.PubMedCrossRef

96.

DiClemente RJ, Swartzendruber AL, Brown JL. Improving the validity of self-reported sexual behavior: No easy answers. Sex Transm Dis. 2013;40(2). https://doi.org/10.1097/OLQ.0b013e3182838474.

97.

DiClemente RJ. Validity of self-reported sexual behavior among adolescents: where do we go from here? AIDS Behav. 2016;20:S215–7.PubMedCrossRef

98.

Corno L, De Paula A. Risky sexual behaviours: biological markers and self-reported data. Economica. 2009;86:229–61.CrossRef

99.

Noar SM, Cole C, Carlyle K. Condom use measurement in 56 studies of sexual risk behavior: review and recommendations. Arch Sex Behav. 2006;35(3):327–45.PubMedCrossRef

100.

Fonner VA, Kennedy CE, O’Reilly KR, Sweat MD. Systematic assessment of condom use measurement in evaluation of HIV prevention interventions: need for standardization of measures. AIDS Behav. 2014;18:2374–86.PubMedPubMedCentralCrossRef

101.

Beauclair R, Meng F, Deprez N, Temmerman M, Welte A, Hens N, et al. Evaluating audio computer assisted self-interviews in urban south African communities: evidence for good suitability and reduced social desirability bias of a cross-sectional survey on sexual behaviour. BMC Med Resrch Method. 2013;13(1):11.23368888.

Title: The Value of Assessing Self-Reported and Biological Indicators of Outcomes in Evaluating HIV Programs
Authors: Rick S. Zimmerman
Purnima Mehrotra
Tessa Madden
Rachel Paul
Publication date: 01-08-2021
Publisher: Springer US
Keywords: Human Immunodeficiency Virus
Biomarkers
Published in: Current HIV/AIDS Reports / Issue 4/2021
Print ISSN: 1548-3568
Electronic ISSN: 1548-3576
DOI: https://doi.org/10.1007/s11904-021-00560-3

ACC 2024 Congress Coverage

Heart Failure Video

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

The Value of Assessing Self-Reported and Biological Indicators of Outcomes in Evaluating HIV Programs

Abstract

Purpose of Review

Recent Findings

Summary

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Purpose of Review

Recent Findings

Summary

Please log in to get access to this content

Other articles of this Issue 4/2021

Interventions Addressing Depression and HIV-Related Outcomes in People with HIV

Current Interventions for People Living with HIV Who Use Alcohol: Why Gender Matters

Application of the Consolidated Framework for Implementation Research to Facilitate Violence Screening in HIV Care Settings: a Review of the Literature

Assessing Cardiovascular Risk in People Living with HIV: Current Tools and Limitations

Approaches to Promoting Linkage to and Retention in HIV Care in the United States: a Scoping Review

The Intersection of HIV and Syphilis: Update on the Key Considerations in Testing and Management

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

Incentivised to exercise

New intervention for STEMI-related cardiogenic shock

» View more highlights on the ACC 2024 congress hub page