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HIV & TB Drug Interactions University of Liverpool

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Presentation on theme: "HIV & TB Drug Interactions University of Liverpool"— Presentation transcript:

1 HIV & TB Drug Interactions University of Liverpool
Research Priorities THE UNIVERSITY of LIVERPOOL S. H. Khoo University of Liverpool

2 Interactions between HIV and TB Drugs
Pharmacology Effects of TB drugs on HIV treatment Effects of ARVs on TB treatment Therapeutics Drug toxicities & overlapping syndromes Effect on mortality Adherence

3 Anti-retroviral therapy
NRTI zidovudine lamivudine didanosine zalcitabine stavudine abacavir emtricitabine tenofovir NNRTI nevirapine efavirenz delavirdine PI saquinavir ritonavir indinavir nelfinavir lopinavir amprenavir atazanavir fosamprenavir (tipranavir) Toxicity Adherence Prescribing issues for developing countries

4 How much adherence is enough ?
After median 6 months This is a famous early adherence study. It really established the importance of adherence for long term treatment success. To this point the focus of treatment was maximising potency; with the publication of these results the focus shifted almost overnight to ease of adherence. This was good for NNRTIs, bad for PIis, and has been the basis for wide acceptance of combination products. The results of the study have never really been questioned. It used MEMS caps recording as the measure of adherence. Patients and doctors are likely to instinctively believe that once-a-day regimens are easier to adhere to than bid. This is a perception that should be capitalised on: paint a picture of how patients can easily ensure that they take their once-a-day regimen as part of their daily routine; ask what sort of treatment patients are requesting; or ask what kind of regimen the doctor might prefer. You may wish to emphasise that we are now at the point that clinicians don’t have to compromise potency in order to achieve an easy to adhere to once-a-day combination. Viread, 3TC and EFV has demonstrated great results over 96 weeks of treatment, including patients with high viral load and CD4. How Much Adherence is Enough? A Prospective Study of Adherence to Protease Inhibitor Therapy Using MEMSCaps Methods: Adherence to protease inhibitors (PIs) was assessed electronically in 99 subjects at two sites using MEMScaps. Demographics, medications, CD4 cell counts, viral load measurements, psychiatric morbidity, alcohol/substance abuse, health beliefs, physician adherence assessment and patient self-report were collected. Baseline CD4 counts ranged from <50 cells/mm3 (12%) to >500 (25%) and baseline viral load from <400 copies/ml (22%) to >100,000 (18%). 20% were taking two PIs. Results: At 3 months, a highly significant association was found between adherence and virologic suppression (p= ). 81% of subjects with >95% adherence had complete viral suppression compared to 64% with 90-95% adherence, 50% with 80-90% adherence, 25% with 70-80% adherence and 6% with <70% adherence. Physicians perception of adherence was poor: 21% of subjects judged nonadherent had >95% adherence, and 32% judged adherent took <80% of doses. Patient self-report also proved unreliable: of those who denied nonadherence, 45% had 80-95% adherence and 29% had <80% adherence. No PI was associated with better adherence, although median adherence was slightly better with one PI (91%) than two (74%)(p=0.15). Mean adherence was 73% (median 84%) for BID and 71% (median 92%) for TID regimens (p=0.42). Modifiable variables associated with poor adherence included active depression (p=0.02) and active alcoholism (p=0.069). Other variables associated with poor adherence were African American race (p=0.008), lower educational level (p=0.01), and higher baseline viral load (p=0.04). Conclusions: >95% adherence to PI therapy is associated with virologic success, and failure rates increase sharply with decreasing levels of adherence. Patient self-report and physician judgement are unreliable measures of adherence. Efforts to improve adherence should focus on untreated depression and alcohol abuse. Paterson 2000

5 Prescribing issues for developing countries
Effect of gender, body weight, ethnicity Interactions with other medications (TB, antibiotics, OCP, herbals, etc) Need to be dosed with food Once-daily for DOTS Pediatric formulations of FDCs Drug quality Shelf life & storage Monitoring The need for second line ARVs – role for protease inhibitors ? Access to information / knowledge

6 PK of ARVs Large intra-individual variability
Significant proportion of individuals with low / high levels

7 PK of ARVs Effect of ethnicity, gender and body weight Ethnicity
 EFV in Africans (? 2B6 polymorphism) () NVP in Africans  IDV peaks in Thais Different toxicity profile (lipo, hypersensitivity) Gender  Levels in women (NVP/ EFV/ ?LPV) ZDV/3TC triphosphates in women Toxicity (lipo, hepatitis) Body weight Differences for PIs & NNRTIs ?

8 Nevirapine Efavirenz Dutch TDM Liverpool TDM LaPorte et al, 2003
LHPG data, 2004

9 STOP Study 10 patients stopping therapy (EFV-containing regimen)
EFV concentrations measured over 3 w Nucleoside backbone continued 1w after stopping EFV 5 had EFV T½ h 5 had EFV T½ >100 h 4 / 5 Black African women 3 had EFV levels in the ‘therapeutic’ range at 2 w

10 Clearance of HIV Drugs PI / NNRTI Rif Chronic Hepatitis Alcohol
Hepatoxicity Chronic Hepatitis Alcohol Other toxins

11 TB / HIV drug Interactions
Rifampicin lowers HIV NNRTI levels NVP – % EFV – % Rifampicin lowers HIV PIs by ~ 90% partially restored by high dose RTV - cost, toxicity, pill burden HIV drugs may affect rifamycins increase RBT dose with NNRTIs decrease RBT dose with Pis

12 IDV SQV LPV Grub EJCP 2001 Jutesen CID 2004
La Porte et al. Antimicrob Agents Chemother. 2004;48:

13 Distribution of plasma EFV levels between EFV 600 and 800 mg groups
Manosuthi et al. XV AIDS Conference Bangkok 2004

14 START Study Prospective pilot HAART + TB (DOT) n = 20
19 remained in study; ddI+3TC+EFV Jack et al. JAIDS 2004;36:929-35 EFV TB treatment post-TB treatment Repeatedly high (4/4 normalised) Repeatedly low (4/6 normalised) Low / normal (4/5 normalised) Consistently normal

15 Complex Clinical Syndromes
Liver toxicity Liver toxicity of HIV drugs 8-13% [2NN 2003] Liver toxicity of TB drugs 2- 4% [Aquinas BMJ 1972] Liver toxicity TB + HIV drugs > TB drugs [Patel JAIDS 2004] Background chronic hepatitis B Immune reconstitution with ARVs Paradoxical reactions TB (7%) vs TB / HIV (36%) [Narita AJRCCM 1998] Impact on Mortality

16 Outcomes in a “smear negative” cohort treated for TB
mortality in smear-positives ~23% [Harries IJTLD 2001] higher mortality in smear-negative, HIV-positive can early introduction of ARVs modulate this ? Hargreaves N, et al, INT J TUBERC LUNG DIS (9):847–854

17 Alternatives to RIF ? Sterilising phase
RH (95%) > EH (87.4%) IUTLD Study A Jindani Paris 2003 What other (short course) regimens would allow ARVs ? induction: rifampicin > rifapentine > rifabutin Study 22: Rifapentine + INAH once weekly Rifamycin monoresistance in 4/30 (13%) TB+HIV patients Vernon et al Lancet 1999;353:1843 Study 23: Rifabutin + INAH twice weekly Rifamycin monoresistance in 5/147 (3.4%) TB+HIV patients MMWR March / 51 (10);214 Quinolones ?

18 Disseminating ‘Knowledge’ to support prescribing
Dosing Interactions Identifying toxicities Gender, ethnicity, weight Adherence interventions etc Need to : Gather & synthesise existing information identify gaps in knowledge Address these in a co-ordinated manner Access and training

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22 Research Priorities Problem with rifampicin RPT / RBT/ quinolones
When / how to give ARVs ? effect of ARVs on early mortality use of rifampicin in sterilising phase lead-in dosing for NVP dose modifications vs FDC Toxicity & resistance pharmacovigilance networks surveillance networks

23 Research Priorities How to support adherence ? What are the barriers?
DOTs alternatives ? How do we disseminate knowledge ? Co-ordinate research activities Gather available evidence Enable access Support training

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25 Patients with EFV level < 1 mg/L
Number of patients 25 20 Plasma EFV 15 10 กราฟนี้ไม่แน่ใจ ถ้า wee จะใช้ ช่วย label ให้ด้วยนะ ว่าเป็น graph ของอะไร 5 p = 0.274 EFV 600 mg EFV 800 mg

26 Inadequate drug levels may result in resistance
Periodically inadequate drug levels Mutant selected with reduced susceptibility Rebound with highly resistant organism

27 Rifabutin & Ritonavir Cato et al, 1998
Mean Rifabutin Plasma Concentrations Mean 25-O-Desacetylrifabutin Plasma Concentrations AUC (ng.h.ml-1) 1843 ± 392 8362 ± 2229 AUC (ng.h.ml-1) 165 ± 79 6289 ± 840 Cato et al, 1998

28 La Ribera et al. JAIDS 2001

29 Adherence - resistance relationship
Unboosted PI Boosted PI NNRTI Risk of resistance Adherence (%) Bangsberg, Moss & Deeks. JAC 2004


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