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Treatment Access Cascades: Effects of viral load, resistance tes7ng and safety in pregnancy on access to Dolutegravir in Low and Middle income countries
Dr Jacob Levi1, Polly Clayden2 and Dr Andrew Hill2
1-‐Imperial College London, School of Public Health, London, United Kingdom, 2-‐HIV i-‐Base London, 3-‐Liverpool University, Transla7onal Medicine, Liverpool, United Kingdom,
Correspondence to: Dr Andrew Hill PhD Department of Translational Medicine, 1st Floor Block H, 70 Pembroke Place, Liverpool, L69 3GF Tel:+44 7834 364 608 Email: [email protected]
Objec7ves: Generic an*retroviral treatment with tenofovir disoproxil fumarate/lamivudine/dolutegravir (TDF/3TC/DTG; TLD) is available in eligible countries for $75/person-‐year. There are big plans to transi*on millions of HIV+ people to TLD in 2018–2019. However, the Phase 3 trial programme for Dolutegravir excluded many important pa*ent groups. Pregnant women, ART-‐naïve HIV+ people with transmiYed drug resistance, and ART experienced HIV+ People without genotypic resistance tes*ng were all not included in safety and feasibility studies. The DAWNING study also excluded ART-‐experienced HIV+ people with no ac*ve NRTIs. Furthermore, recent reports of neural tube defects (NTDs) a\er use of DTG at concep*on could limit use in women of child-‐bearing poten*al. We wanted to model how realis*c it is to start and switch diagnosed HIV+ people to TLD in low and middle income countries (LMIC) given these limita*ons. Method: Using UNAIDS 2016 data we made 4 separate cascades for each LMIC with available data. LMICS were categorised into low income <$1000 GDP/capita, lower-‐middle income ($1000-‐3955 GDP/capita) and upper-‐middle income (3956-‐$12,235 GDP/Capita). We excluded countries with <100,000 HIV+ people. Cascade 1 shows all diagnosed HIV+ people, split into three categories; those diagnosed but not on ART (red), those on ART and HIV-‐RNA suppressed (pink) and those on ART but unsuppressed (green). We subsequently modeled the impact on access to TLD if pa*ents could not be started or switched due to various factors. Cascade 2 models the impact of the lack of access to viral load tes*ng: HIV + people on ART cannot be switched to TLD without a viral load test in the last year – as they may actually be unsuppressed either due to low adherence or drug resistance. Viral load tes*ng access data was collected from the UNAIDS Spectrum model. Cascade 3 models the impact that lack of access to resistance tes*ng has on the number of people on ART that can be safely switched to TLD. We assumed 50% of PLWHIV on ART can access resistance tes*ng before switching due to a lack of available na*onal data. Cascade 4 shows the impact that the lack of safety data in pregnant women has on the number of HIV+ people that can be switched or started on TLD. We defined HIV+ women of childbearing poten*al as all of those aged 15-‐49. Results: All of the data is displayed in the 19 na*onal cascades below, [key in top le\ corner]. Each graph is in order of the percentage of diagnosed PLWHIV that are eligible to start on or switch to TLD, in the final stage -‐ cascade 4. Access to Viral Load in the upper-‐middle income countries was good. It was 100% in Brazil, 99% in Mexico, 82% in Thailand, 80% in Malaysia, 60% in South Africa and 38% in Botswana. Therefore the effects on access to TLD a\er excluding pa*ents without a HIV-‐RNA test in the last 12 months (Cascade 2) was minimal for richer countries. The lowest-‐income countries had much worse access to viral load tes*ng: 64% in Malawi, 31% in Hai*, 27% in Ethiopia, 16% in Togo and just 14% in Zimbabwe. Therefore, many more HIV+ people on ART are being excluded from switching to TLD due to lack of access to viral load tes*ng in poorer countries. There is a lack of data in access to resistance tes*ng for LMICs, so it is not clear exactly how many people in each country will be excluded from taking TLD. We assumed that only those HIV+ people on ART who are found to be not HIV-‐RNA virally suppressed would need a resistance test before switching to TLD. As the majority of people on ART are es*mated to be successfully HIV-‐RNA suppressed in all countries, our assump*on that 50% of people can get resistance tes*ng in all countries did not have a big impact on the number of people able to switch to TLD in any country. The largest exclusion factor was unknown safety for HIV+ women of childbearing age (Cascade 4). In sub-‐Saharan African countries there is a high percentage of HIV+ women of childbearing poten*al. In total Zimbabwe (9%) and Nigeria (11%) had the lowest number of people who could be safely started on or switched to TLD. Conclusions: The clinical development programme for DTG excluded pregnant women, and with low access to contracep*on and abor*on in LMICs, along with the dangerous ideologically driven “Global Gag Rule” limi*ng PEPFAR, serious changes are needed to improve op*ons for HIV+ women. Access to TLD is par*cularly low for low-‐income sub-‐Saharn African countries. Further analysis of DTG pre-‐concep*on is needed to determine whether the adverse safety signal is maintained across cohorts. The lack of data in key popula*ons limits the poten*al to transi*on large numbers of pa*ents to TLD. We highlight the need for improved access to viral-‐load and genotype tes*ng in LMICs. New trials are needed to evaluate TLD in treatment-‐experienced pa*ents with limited or no NRTI op*ons.
Presented at HIV DRUG THERAPY GLASGOW 2018
How many people can safely start on or be switched to TDF/3TC/DTG (TLD)? Data from 19 Na7onal Cascades
0
50,000
100,000
150,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
DR Congo Total PLWHIV = 370,000 Lower-‐Middle Income
Total = 37,176 Total 18,541 Total = 35,656 Total = 133,200
14%
Cascade 3 Cascade 4 Cascade 2
28% 27%
0
200,000
400,000
600,000
800,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4****
Kenya Total PLWHIV = 1,600,000 Lower-‐Middle Income
Total = 374,381 Total = 188,339 Total = 369,291 Total = 816,000
23%
Cascade 4
45% 46%
0
200,000
400,000
600,000
800,000
1,000,000
1,200,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Nigeria Total PLWHIV = 3,200,000 Lower-‐Middle Income
Total = 212,992 Total = 114,791 Total = 208,712 Total =1,024,000
11%
Cascade 3 Cascade 2 Cascade 4
20% 21%
0
50,000
100,000
150,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Ukraine Total PLWHIV = 240,000 Lower-‐Middle Income
Total = 115,772 Total = 70,583 Total = 108,589 Total = 134,400
53%
Cascade 3 Cascade 4 Cascade 2
86% 81%
0
50,000
100,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Hai7 Total PLWHIV = 150,000
Low Income
Total = 31,099 Total = 15,867 Total = 29,938 Total = 88,500
18%
Cascade 2 Cascade 3 Cascade 4
34% 35%
0
50,000
100,000
150,000
200,000
250,000
300,000
350,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Cameroon Total PLWHIV = 560,000 Lower-‐Middle Income
Total = 148,823 Total = 69,785 Total = 145,386 Total = 324,800
22%
Cascade 3 Cascade 3 Cascade 4
Cascade 2
46% 45%
Cascade 2
0
200,000
400,000
600,000
800,000
1,000,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Malawi Total PLWHIV = 1,100,000
Low-‐Income
Total = 618,596 Total = 325,689 Total = 603,127
Total = 935,000
35%
65% 66%
0
100,000
200,000
300,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Botswana Total PLWHIV = 360,000 Upper-‐Middle Income
Total = 114,138 Total = 61,960 Total = 112,655 Total = 306,000
20%
Cascade 2 Cascade 3 Cascade 4
37% 37%
0
100,000
200,000
300,000
400,000
500,000
600,000
700,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Ethiopia Total PLWHIV = 710,000 Low-‐Income countries
Total = 170,110 Total = 93,046 Total = 166,154 Total = 475,700
20%
Cascade 2 Cascade 3 Cascade 4
36% 35%
0
10,000
20,000
30,000
40,000
50,000
60,000
70,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Togo Total PLWHIV = 100,000
Low Income
Total = 20,135 Total = 10,674 Total = 19,767 Total = 63,000
17%
Cascade 3 Cascade 4 Cascade 2
32% 31%
0
200,000
400,000
600,000
800,000
1,000,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Zimbabwe Total PLWHIV = 1,300,000
Low Income
Total = 187,425 Total = 89,578 Total = 172,265 Total = 975,000
9%
Cascade 3 Cascade 4 Cascade 2
19% 18%
On ART but not Virally Supressed
Star7ng ART
On ART and Virally
Supressed
Cascade 1
Cascade 2
Cascade 3
Cascade 4
The second cascade
removes all of those diagnosed PLWHIV that
were not able to access a viral load test in the last 12 months.
This affects the number of
people on ART who could be
switched to TLD but not those in red who are
diagnosed and yet to start ART.
The third cascade removes those that are on ART, not suppressed
and need resistance
tes7ng.
We have assumed that 50% need a
resistance test.
The fourth cascade
removes all women of childbearing
poten7al due to lack of safety data for TLD in pregnancy
The first cascade shows all PLWHIV in the country that are already diagnosed that could safely
start TLD.
Those in red are diagnosed but not on ART so can start
TLD.
Those in pink are already on ART and virally suppressed. They can switch safely to TLD.
Those in orange are on ART but not yet virally suppressed. We assume that some may have resistance, so
roughly 50% will need resistance tes7ng, before
being switched to TLD.
0
1,000,000
2,000,000
3,000,000
4,000,000
5,000,000
6,000,000
7,000,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
South Africa Total PLWHIV = 7,100,000 Upper-‐Middle Income
Total = 4,518,440 Total = 6,106,000 Total = 4,405,326 Total = 2,246,716
37%
72% 74%
0
50,000
100,000
150,000
200,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Vietnam Total PLWHIV = 250,000 Lower-‐Middle Income
Total = 76,510 Total = 55,680 Total = 75,243 Total = 175,000
44%
32% 43%
0
50,000
100,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Angola Total PLWHIV = 280,000
Low Income
Total = 52,248 Total = 25,538 Total = 52,119 Total = 112,000
23%
47% 57%
0
50,000
100,000
150,000
200,000
250,000
300,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Cote D'Ivoire Total PLWHIV = 460,000 Lower-‐Middle Income
Total = 143,672 Total = 78,414 Total = 140,025 Total = 266,800
54%
30%
52%
0
100,000
200,000
300,000
400,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Thailand Total PLWHIV = 450,000 Upper-‐Middle Income
Total = 354,218 Total = 211,417 Total = 340,996 Total = 409,500
0
50,000
100,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Malaysia Total PLWHIV = 97,000 Upper-‐Middle Income
Total = 85,681 Total = 75,863 Total = 85,239 Total = 92,150
82% 93% 93%
0
50,000
100,000
150,000
Cascade 1 = (UNAIDS 2016 es7mates)*
Cascde 2 ** Cascade 3*** Cascade 4****
Mexico Total PLWHIV = 220,000 Upper-‐Middle Income
Total = 137,450 Total = 107,644 Total = 132,894 Total = 138,600
78%
96% 99%
0
200,000
400,000
600,000
800,000
Cascade 1 = (UNAIDS 2016 es7mates)
Cascde 2 Cascade 3 Cascade 4
Brazil Total PLWHIV = 830,000 Upper-‐Middle Income
Total = 713,800 Total = 499,500 Total = 703,521 Total = 713,800
70%
99% 100%
83%
52%
87%
[P026]
