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Monitoring ART in resource-limited settings: option or necessity ? Public Health Approach

Monitoring ART in resource-limited settings: option or necessity ? Public Health Approach. Prof Charlie Gilks UNAIDS Country Coordinator, India 5th IAS conference on Pathogenesis, Cape Town, 21 July 2009. Outline. The Public Health Approach and what it means in terms of lab monitoring

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Monitoring ART in resource-limited settings: option or necessity ? Public Health Approach

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  1. Monitoring ART in resource-limited settings: option or necessity ?Public Health Approach Prof Charlie Gilks UNAIDS Country Coordinator, India 5th IAS conference on Pathogenesis, Cape Town, 21 July 2009

  2. Outline • The Public Health Approach and what it means in terms of lab monitoring • Evidence of the impact of different ART monitoring strategies • Options for resource-limited settings

  3. “Three by Five” Initiative started in 2003 The target: three million people on treatment by the end of 2005 The goal : universal access to anti-retroviral therapy (ART) as a human right to health

  4. Key elements for public sector ART First-line then second-line regimens Simple recommendations for when to start, toxicity substitutions & switch Tiered laboratory support for clinical decision-making Standard population-based HIVDR monitoring and surveillance Population-based Pharmacovigilance and toxicity monitoring Integrated and decentralised care with task shifting Chronic disease management Public Health ART Strategy

  5. Harmonised ART Policy Guidance

  6. Different guidelines for different populations and ART approaches • Public sector ART • First then second line regimens • Limited number of ARVs used • Limited human resources • Limited laboratory services • Physician/specialist-led ART • Initial regimen then multiple options • All ARVs available for use • Sophisticated labs to tailor regimen choice • Any detectable vl triggers regime change • Few cost constraints Consider guidelines in their context

  7. Core elements of ART monitoring • ARV toxicity and SAEs • ART efficacy • HIV drug resistance • Clinical monitoring • Laboratory monitoring • Individual and/or population level

  8. Evidence base on laboratory monitoring strategies in PHA Clinical end-point trials including cost-effectiveness • DART trial: preliminary data, IAS Cape Town ART toxicity and efficacy Clinically driven monitoring versus clinical + CD4 monitoring • Modelling study: Phillips et al. Lancet 2008: 371 1443-51 • HBAC trial: presented but as yet unpublished data ART efficacy Clinical monitoring; clinical + CD4; clinical and CD4 and/or + VL • No end-point data on ART switch with detectable vl Targeted viral loads: July 2009 CID paper & editorial

  9. DART routine toxicity monitoring LCM CDM 1.0 SAE p=0.20 0.8 ART- modifying AE p=0.85 0.6 Grade 4 AE p=0.18 Proportion event-free 0.4 Grade 3/4 AE p=0.52 0.2 0.0 0 1 2 3 4 5 Years from randomisation (ART initiation) 10 IAS July 2009

  10. LCM CDM DART: first-line ART received • Median follow-up to 31 December 2008 4.9 years (IQR 4.5-5.3) • 98% and 99% of expected nurse and doctor visits attended 1.0 Second-line 0.8 0.6 Original first-line Proportion of patients alive on trial 0.4 0.2 Substituted first-line 0.0 0 1 2 3 4 5 Years from randomisation (ART initiation)

  11. Switch to second-line 0.5 HR(CDM:LCM) = 0.84 (95% CI 0.72-0.98), p=0.03 0.4 Proportion switched to second-line 0.3 LCM CDM 0.2 0.1 0.0 0 1 2 3 4 5 Years from randomisation (ART initiation) HR(CDM:LCM) 0.58 0.48 0.77 0.90 1.35 1.10 heterogeneity p=0.001 12 IAS July 2009 Note: Adjusted for competing risk of death before switch to second-line

  12. Survival (secondary endpoint) 0.95 0.94 0.92 0.90 0.90 0.87 1.0 LCM CDM 0.8 0.6 Proportion alive 0.4 0.2 HR(CDM:LCM) = 1.35 (1.10-1.65) p=0.004 Number needed to monitor = 130 0.0 0 1 2 3 4 5 Years from randomisation (ART initiation) HR(CDM:LCM) 1.08 2.05het p=0.004 (95% CI) (0.85-1.39) (1.43-2.93) LCM 1656 1552 1501 1468 1436 796 13 IAS July 2009 CDM 1660 1542 1494 1445 1395 749

  13. Sensitivity Analysis: Minimal Monitoring • Modifications from Adjusted and Discounted Costs and Benefits: • 12-weekly CD4 cell count routinely performed after the 1st year on ART • No routine (12-weekly) Haematology and Biochemistry tests * 95% CI estimated with bootstrapping percentile method. ** Estimated through the area under the Kaplan-Meier survival curve, with censoring applied at the longest observed time of the arm whose maximum observed time occurs first. IAS July 2009 14

  14. Although survival was slightly longer with viral load monitoring, this strategy was not the most cost-effective. The benefits of Vl or CD4 over clinical monitoring are modest. Development of cheap and robust assays is important; meanwhile widening access to ARVs is the highest priority

  15. Interim HBAC Conclusions • Adding CD4 to clinical monitoring ($831 - $838 per DALY averted) is about as cost-effective as putting another person on ART in Tororo ($600 per DALY). • Adding viral load to CD4/clinical monitoring has a cost per DALY averted ($3,600 - $11,900) that is 4 to 20 times higher. • HBAC analysis suggests that CD4 monitoring or starting a patient on ART are economicallypreferable to viral load monitoring …

  16. Sensitivity Analysis: CD4 count costs At current costs ($7.06 - $8.82), CD4 testing is not cost effective We sought to establish the cost per test at which CD4 monitoring would be cost effective (ICER of $1200 ~3 times GDP per capita; WHO Commission on Macroeconomics and Health) CD4 count would have to cost $3.8 or less for ART management with 12-weekly CD4 monitoring after 1st year to be cost effective IAS July 2009 17

  17. Targeted viral loads at failure • 3 failure domains which are not the same: • clinical; immunological and virological • 20% of clinical failures had high CD4 in DART • 15 – 40% switches with clinical/immunological failure unnecessary: viral suppression or low-level replication • Targeted viral load testing as “tie-break” to conserve use of second-line and reduce costs: policy in India • Caveat: are “failing” patients not benefiting from early switch? • Does not mean that routine viral load monitoring is a necessary or will be cost-effective in resource-limited settings in public sector: • What threshold for viral failure to trigger switch? • Maximal suppression likely to be far too early

  18. DART Survival using PHA 0.95 0.94 0.55 0.92 0.90 0.18 0.90 0.87 0.08 1.0 LCM CDM 0.8 0.6 Proportion alive Entebbe Cohort: pre-ART, median CD4 75 at start 0.4 0.2 0.0 0 1 2 3 4 5 Years from randomisation (ART initiation) What more could VL monitoring add, and at what cost? CTXp – 50% reduction first 72 weeks of ART (MOPEB020) 19 IAS July 2009

  19. HIV drug resistance: population-based monitoring and surveillance No scope in PHA for different first-line ART according to baseline resistance pattern Cohort DR monitoring for programme effectiveness Population DR monitoring for extent of transmitted HIV DR Articles reporting results from HIVDR transmission surveys in 7 countries; all had <5% DR in incident cases No need to change ARVs provided in public sector for first-line ART

  20. Summary and conclusions • PHA is an extremely effective tool for ART scale-up and delivery of effective ART in resource-constrained settings • (Quality) clinically-driven monitoring can deliver excellent outcomes for the individual • Small outcome benefit from routine CD4 monitoring • Likely only small additional outcome benefit from routine VL in addition to CD4 monitoring • Neither laboratory-based strategies are cost-effective; getting people in need on to ART remains the priority • Drug resistance monitoring and SAE/toxicity monitoring are best done at a population level to inform PHA ARV choices

  21. Future directions • Drive for Quality clinical monitoring • CD4 testing for eligibility to start/thresholds • Targeted CD4 ART monitoring with much cheaper and ideally POC tests • VL testing for Early Infant Diagnosis • Targeted vl as cost-saving tie-break for patients with clinical or immunological failure • Drug resistance and pharmacovigilance at population level or in cohort studies

  22. THANK YOU

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