Rate of accumulation of TAMS slow in patients continuing on failing AZT or d4T containing regimens
30 December 2009. Related: Drug resistance.
Polly Clayden, HIV i-Base
First line regimens in resource limited settings (RLS) as currently recommended by WHO – are usually two nucleosides, 3TC plus a thymidine analogue (TA) either d4T or AZT, and one NNRTI.
Most programmes have limited access to virological monitoring and genotype resistance testing. Because of this most treatment switches are based on clinical or immunological failure.
A considerable number of patients are expected to receive failing TA containing regimens for extended periods before switching to second line. Since the nucleoside drugs in second line regimens may be compromised by presence of TAMS there is concern over the consequences of accumulation of TAMS before switching.
Alessandro Cozzi-Lepri and investigators for the EuroSIDA Study Group used European cohort data to estimate the rate and predictors of accumulation of TA mutations (TAMS) in patients who continue to receive failing regimens. In an article published in the 1 September 2009 issue of the Journal of Infectious Diseases they report lower than anticipated accumulation of TAMs in patients experiencing virological failure.
The investigators analysed data from patients in the EuroSIDA study who experienced virological failure (defined as first viral load >=500 copies/mL after >=6 months), with >= 2 genotype resistance tests (GRTs) while receiving the same TA-containing regimen, with a viral load of >500 copies at both. The time of the first genotype test results in a pair was defined as t0, the date of the very first genotype used in the analysis as baseline-t0.
In this analysis, the majority (87%) of genotype results were obtained retrospectively from stored samples.
The rate of TAM accumulation was calculated as the number of TAMs detected at t1 that were not present at t0 divided by the interval between t0 and t1. The investigators used a multivariate Poisson regression model to identify independent predictors of TAM accumulation.
They also simulated a scenario in which all patients studied were switched to a WHO recommended second line nucleosides (eg AZT+ddI or ABC+ddI) after the extended period on failing TA-containing HAART. This was used to estimate the decrease in susceptibility of subsequent regimens due the accumulation of TAMs.
The study population of 339 patients provided 603 pairs of GRTs. At t0 their median age was 39 years and 14% were female. Of this group 67% had one pair of GRTs; 18% had two; 6% had 3 and 9% more than three pairs of GRTs. Their median viral load was 4.11 log copies/mL and CD4 244 cells/mm3. They were very treatment experienced, 53% had failed 1-3 drugs before baseline t-0 and the remainder 4 or more drugs; 35% had failed an NNRTI and 72% a PI.
During the interval t0-t1 (median 6 months, range 1-89 months) the investigators reported the patients having very stable viral loads (mean absolute change +0.03 log copies/mL, 95% CI -0.3 to +0.09, p=0.29) and CD4 counts (mean absolute change -5.74 cells/mm3, 95% CI -2.52 to +14, p=0.17).
Over t0-t1 all patients were receiving either AZT or d4T, which they received for a median of 9 and 15 months duration respectively from virological failure to t1. Twenty-nine percent received an AZT-containing regimen (176 pairs) and 71% a d4T-containing regimen (427 pairs). Besides the TA, the majority (70%) of patients were receiving 3TC at t0. Other frequently used nucleosides were ddI (25%) and abacavir (18%). The most common NNRTIs were NVP (34%), EFV (18%), but some patients were also receiving PIs, NFV (19%), IDV (26%) and LPV (9%). The investigators noted frequent switching in the drugs besides the TA between t0 and t1. In 478 (79%) patients, more than 1 drug used at t0 was no longer used at t1.
At t0, 90% of the study population had at least one TAM and a median of 3 (range 0-6). Of these 81% had TAM profile 1 (TAM1) 41L, 210W and 215F mutations, and 62% TAM profile 2 (TAM2) 67N, 70R and 219EQ; 65% had 41L and 68% 215Y TAM1 mutations and 52% 67N TAM2 mutations.
At t1 93% had at least one new TAM. The investigators noted that he rate of accumulation of TAM1 mutations was twice as fast as that of TAM2.
Between t0 and t1, 126 additional TAMs were accumulated during 548 patient years of follow up (PYFU), which the investigators estimated to give a rate of 0.23 per year (95% CI 0.20-0.27) or, in other words, 1 in 4.3 years (95% CI 3.7-5.0).
The rate was faster (0.3 per year) in the subset (330 pairs) with 0-3 TAMs at t0 and was slower, with a rate of 0.11 per year in the patients who already had 4-5 TAMs at baseline (245 pairs).
Using the Rega IS and the ANRS systems the investigators predicted the response to subsequent WHO recommended nucleoside pairs. Both systems appeared to show that regimens containing tenofovir (particularly with 3TC) were likely to have the greatest activity at t0 and the least reduction in activity t0-t1. These predictions however depend on the accuracy of current expert knowledge regarding which mutations may reduce susceptibility to tenofovir.
When they looked at predictors of TAM accumulation, they found that also greater susceptibility to non thymidine analogues in the failing regimen was associated with faster accumulation of TAMs (50% faster per additional active drug, RR 1.5 [95% CI,1.05-2.14], p=0.02).
Other predictive factors were acquisition of HIV through heterosexual contact (vs homosexual almost 2-fold difference in rate RR1.89 [95%CI 1.01-3.57] p=0.05) and TAM2 profiles at t0 (vs TAM1, 87% faster, RR 1.87 [95% CI 1.06-3.27], p=0.03). NNRTI+PI or PI based regimens at t0 were associated with slower accumulation of TAMs (RR 0.32 [95% CI, 0.12-0.84], p=0.02).
The investigators concluded that their data suggest, In patients who continue to receive TA-based, virologically failing regimens, the rate of accumulation of TAMS is relatively slow, on average, though the higher the initial predicted activity of the regimen, the faster the rate at which TAMs accumulate. Nucleoside pairs including tenofovir, although expensive, seem more likely to be active against viruses harbouring TAMs and also to experience the highest drop of activity in the face of TAM accumulation. Additional research in this area is needed to inform programme planning in RLS.
COMMENT
That two distinct pathways of TAMs can emerge under pressure of TA-containing HAART that is not fully suppressive is well described. TAM 1 has been associated with high-level resistance to AZT and most other NRTIs, including tenofovir and abacavir and TAM2 with lower levels of resistance to TDF and other NRTIs.
The finding that the rate of emergence of TAMs was slower than expected in this estimation by Cozzi-Lepri and colleagues is reassuring for programmes with limited access to monitoring and, alongside DART results, will make a big contribution to ongoing discussions about What to measure? How often? and What are the consequences?
The authors note that only 9% of their patients had non-B subtypes and that 24% were receiving WHO recommended first line regimens, which could limit the extent to which their results might be generalisable to patients in RLS. However, they suggest that the similarities between their estimation and that observed in RLS may make this bias negligible. They also were not able to establish an explanation why patients in EuroSIDA were left on failing regimens from these data, and so could not rule out selection bias.
While the average rate accumulation of TAMs is relatively slow and suggests a public health approach would be good, there still needs to be work on identifying why some patients do fail fast. Is it a function of the virus? The drug selection? Genes? What monitoring is needed to catch the small percentage of patients that dont respond?
While the average rate accumulation of TAMs is relatively slow and suggests a public health approach would be good, there still needs to be work on identifying why some patients fail more rapidly and what monitoring is needed to catch the small percentage of patients that dont respond?
One of the main predictors of faster accumulation suggested by this analysis (and others) was a function of the virus and drug selection. For example, the greater the amount of resistance already accumulated at the time of failure the slower the rate of accumulation of additional mutations.
And, as the authors stress all possible efforts should be continued to increase the availability of drug options in RLS.
Ref: Cozzi-Lepri A et al. Rate of accumulation of thymidine analogue mutations in patients continuing to receive virologically failing regimens containing zidovudine or stavudine: implications for antiretroviral therapy programs in resource limited settings. J Infectious Dis 200: 687-97, 1 September 2009.