Until recently, extensively treatment-experienced patients with advanced human immunodeficiency virus (HIV) infection had limited treatment options and poor outcomes.1 Prolonged treatment with antiretroviral drugs without full virologic suppression can lead to selective drug pressure and the emergence of resistant virus.2 Furthermore, many mutations confer cross-resistance to other HIV antiretroviral drugs in the same class.3 In a recent trial of treatment options for patients with advanced multidrug-resistant HIV, 35% of patients died over 4 years and 27% experienced at least 1 AIDS-defining event.4,5
Several antiretroviral drugs approved since 2005 have offered patients with advanced HIV additional treatment options, including new drugs within conventional classes, such as the nonnucleoside reverse transcriptase inhibitors etravirine and rilpivirine and the second-generation protease inhibitors darunavir and tipranavir as well as novel drug classes, such as maraviroc, an entry inhibitor, and raltegravir, an integrase inhibitor. In randomized controlled trials comparing regimens containing newer drugs (approved since 2005) with background regimens consisting of conventional drugs optimized through the use of resistance tests, the newer drug regimens more effectively suppressed viral load and increased CD4 counts.6–21 Newer drugs are particularly useful when used in combination. Epidemiological data from Western Europe in 2000 indicate that 32% of patients had exhausted all available drug options; in 2008, this proportion had decreased to 1%, in large part due to the availability of newer antiretroviral drugs.22
However, these newer antiretroviral drugs are also expensive. Because more than one newer drug is typically used when constructing a new regimen, the incremental costs of newer antiretroviral drug combinations are substantial. Furthermore, the health effects might be marginal in patients with multidrug-resistant virus. We used cost-effectiveness analysis to assess whether this increased cost was associated with a commensurate gain in health. We focused on evaluating strategies (composed of many different regimens) rather than individual drugs or specific regimens because treatment for patients with advanced HIV disease must be person-specific to account for resistance patterns and individual experiences with adverse events.
We evaluated the use of regimens that included both newer antiretroviral drugs in combination with conventional antiretroviral drugs compared with regimens that used only conventional antiretroviral drugs. We modified a previously published state-transition model of HIV infection to simulate the clinical course of individuals with advanced HIV infection who are heavily treatment experienced.23,24 We used the perspective of the ideal insurer and thus included all direct health-care costs. We used US costs. We discounted costs and outcomes at 3% per annum, in accord with guidelines on the conduct of cost-effectiveness analyses.25 We present a brief description of the model with further details available in the Supplemental Material (see Additional Methods and Results, Supplemental Digital Content, http://links.lww.com/QAI/A466).
We evaluated 2 treatment strategies. In the first strategy, which we labeled “conventional” therapy, patients were treated with 3 antiretroviral agents, including enfuvirtide, that were released before 2005. In the second strategy, “newer” antiretroviral drugs (etravirine, darunavir, tipranavir, maraviroc, and raltegravir) were used. In our base case, we assumed that 2 newer antiretroviral drugs were used in combination with 1 conventional antiretroviral, in accordance with the treatment principle that more than 1 active antiretroviral should be used when changing regimens.26 We estimated the efficacy of newer antiretroviral drugs from a review of the literature and a pooled analysis of relevant studies (see Figure S1, Supplemental Digital Content, http://links.lww.com/QAI/A466). To be conservative, we included only the effect of newer antiretroviral drugs on initial virologic suppression (and adverse event rates) in the base case analysis. We assumed that this benefit was obtained by using 2 newer drugs with at least 1 conventional drug. We assumed that discontinuation of older drugs was not associated with worse virologic outcomes because randomized trials have demonstrated no benefit from continuing multiple conventional antiretroviral drugs.4,27 We assumed that new regimens might contain some older drugs for 2 reasons. First, they might have residual antiretroviral activity. Second, they might select for mutations that increase susceptibility to other drugs in the regimen. We assumed that antiretroviral selection is optimal within the constraints of available drugs and is guided by the results of resistance testing.
Most parameters describing the clinical course, costs, and utility of treatment-experienced patients treated with conventional (but not newer) antiretroviral drugs were estimated from the Options in Management with Antiretrovirals (OPTIMA) trial, the largest randomized controlled trial in patients with multidrug-resistant HIV infection (Table 1).4 We estimated parameters that were not available within OPTIMA from the literature (see Additional Methods and Results, Supplemental Digital Content, http://links.lww.com/QAI/A466).
The analysis represented patients who had extensive past experience with antiretroviral therapy and harbored multidrug-resistant virus. Our base case analysis was for a 48-year-old man with a CD4 count of 127 cells/mm3, a viral load of 89,000 (4.95 log10) copies/mL, and no active AIDS illnesses at baseline, which was similar to the typical patient included in our secondary analysis of trial data. We did not consider patients co-infected with hepatitis B or C.
We constructed a Markov cohort simulation model, which characterizes the health of HIV-positive individuals by defining distinct health states, transitions between these states, and transient events that occur during a model cycle (see Figure S2, Supplemental Digital Content, http://links.lww.com/QAI/A466). The model tracks the proportion of a hypothetical cohort in each health state at 1-month time intervals over the entire lifetime of the cohort. Health states were defined according to regimen, viral load, CD4 count, adverse event history, and intercurrent AIDS illness. Transitions between states occurred due to failure to decrease viral load to undetectable levels from baseline levels (lack of virologic response), rebound from a suppressed to a detectable viral load level (loss of virologic response), treatment discontinuation due to a treatment-limiting serious adverse event, successful virologic control, changes in CD4 count, development of a new AIDS-defining condition, resolution of an AIDS-defining condition, or death.
We defined regimens by distinguishing between active and nonsuppressive antiretroviral therapy. Active therapy was defined as treatment that was able to achieve virologic response (defined as virologic suppression below 50 copies/mL) in some proportion of the cohort, whereas nonsuppressive therapy was defined as treatment that reduced, but never suppressed, viral load. We assumed that if patients did not experience a treatment-limiting adverse event, active therapies were continued as long as viral load was suppressed. Thus, treatment changes could result from either inefficacy (lack of initial viral suppression or initial suppression with subsequent rebound) or intolerance (experiencing a serious adverse event). We assumed that, from the time of entry into the model, patients in both newer and conventional treatment strategies used 2 active regimens before starting nonsuppressive therapy. We further assumed that the first and second active regimens in each strategy were equally effective at suppressing viral load, associated with similar risks of rebound, and had the same rate of discontinuation due to adverse events, based on observations in the randomized controlled trial. We assumed that nonsuppressive therapy was continued until death.
We estimated the cost associated with each health state and with transient adverse events based on data from the Department of Veterans Affairs, where 78% of trial participants were enrolled.28,29 We used the prevalence of resistant virus (for etravirine, darunavir, and tipranavir) or the prevalence of CXCR4 tropism (for maraviroc) to estimate the frequency with which individual antiretroviral drugs would be prescribed in regimens containing newer antiretroviral drugs.30–33 This analysis indicated that drugs associated with less frequent resistance on a population level also tended to be less expensive. Accordingly, the average incremental cost of each newer antiretroviral drug in a new regimen is slightly more than the last one. We varied the costs of newer antiretroviral drugs widely in sensitivity analyses, recognizing that factors other than genetic susceptibility—including dosing, adverse effects, and patient preference—influence this choice.
Quality of Life
We estimated quality-of-life weights for the model from trial participants' responses to the Health Utilities Index (Mark 3).34,35 We modeled a further transient decrease in quality of life for patients who experienced a serious adverse event at the time of the event.5
We calibrated the conventional therapy strategy in the model to empirically observed data in the OPTIMA trial, including overall survival, time to development of a first AIDS-defining illness, cumulative costs, and cumulative quality-adjusted life-years (QALYs). We manually adjusted input parameters that were uncertain (examples include the proportion of individuals using nonsuppressive therapy who experience side effects and the proportion who recover from an AIDS illness) to yield survival curves and summary estimates that corresponded to observed values. Adequate fit of model outputs to observed data was assessed subjectively for survival curves and was judged acceptable if values were within 10% of observed values for cumulative costs and QALYs.
We calculated incremental cost-effectiveness ratios (ICERs) based on the comparison of the 2 treatment strategies. We conducted extensive sensitivity analyses to assess the robustness of our model to underlying assumptions and to identify priorities for further research. To assess parameter uncertainty, we conducted both deterministic sensitivity analysis on each model parameter as well as probabilistic sensitivity analyses with 10,000 simulations. Detailed results of the probabilistic sensitivity analyses are in the Supplemental Digital Content (see Additional Methods and Results, Supplemental Digital Content, http://links.lww.com/QAI/A466).
We assessed structural uncertainty by examining assumptions about the number of antiretroviral drugs used in conventional and newer regimens. In our base case, we assumed that 2 newer antiretroviral drugs were used in a new combination regimen. In sensitivity analyses, we assessed how our results would change if the number of newer drugs were 1 or 3. We assumed that 1 to 2 conventional antiretroviral drugs would be continued, with the constraint that a regimen always consisted of at least 3 antiretroviral drugs.
We initially assumed that efficacy was equivalent for all combinations incorporating newer antiretroviral drugs; this is effectively a sensitivity analysis on the cost of newer antiretroviral drug combinations. Next, we relaxed the assumption that efficacy was not related to the number of newer drugs and instead assumed that 3 newer antiretroviral drugs were more effective than 2 newer antiretroviral drugs. Based on our systematic review and other data,36,37 we assumed that the odds ratio for suppression was further increased 2-fold with the addition of a third newer antiretroviral drug (see Figure S3, Supplemental Digital Content, http://links.lww.com/QAI/A466). Furthermore, we assumed that if only 1 newer antiretroviral drug was used, the odds ratio for suppression was decreased by half.
Finally, we conducted analyses in which we evaluated the cost-effectiveness of newer antiretroviral drugs for patient subgroups. We evaluated patients with worse-than-average expected outcomes based on CD4 count (75 cells/mm3), viral load level (500,000 copies/mL), and low likelihood of success with conventional therapy (20%), an indicator of drug experience. We also evaluated patients with a better-than-average expected outcome with a higher-than-baseline CD4 count (250 cells/mm3), a lower viral load level (30,000 copies/mL), and a higher probability of suppression (60%).
We used Decision Maker version 2011.01.30b and Stata version 11.2.
Role of the Funding Source
The US Department of Veterans Affairs, the UK Medical Research Council, and the Canadian Institutes for Health Research approved the design and conduct of the OPTIMA clinical trial but had no role in the writing of this report.
The conventional therapy outcomes were well calibrated to OPTIMA data. At 1 year of follow-up, the observed survival was 93.1% and the predicted survival by the model was 92.2% (Fig. 1). The model was well calibrated to the time to first AIDS illness. At 1 year of follow-up, the observed proportion having experienced an AIDS illness was 8.9% and that predicted by the model was 9.5%. Further calibration results are reported in the Supplemental Material (see Additional Methods and Results, Supplemental Digital Content, http://links.lww.com/QAI/A466).
Effectiveness and Cost-effectiveness of Newer Antiretroviral Drugs
We estimated a pooled odds ratio of 3.80 (95% confidence interval: 2.76 to 5.23; see Figure S1, Supplemental Digital Content, http://links.lww.com/QAI/A466) for suppression with a regimen containing newer drugs relative to a regimen containing only conventional drugs. This corresponds to an increase in the probability of initial suppression from 35% with conventional therapy to 67% with newer therapy. Similar rates have been seen in a recent trial of treatment-experienced patients treated with multiple newer drugs.27 The model yielded an estimated survival gain of 3.9 years (2.6 QALYs) and 2.3 discounted life-years (1.6 discounted QALYs). After discounting, the ICER was $52,781/life-year gained. With quality-of-life adjustment, the ICER was $75,556/QALY gained (Table 2).
Effect of Treatment Strategy
The cost-effectiveness of newer antiretroviral drugs depends on the number of antiretrovirals started and the number discontinued. In the base case, we assumed that 2 newer antiretroviral drugs were started and 2 conventional antiretroviral drugs were discontinued for patients changing to a new regimen. The odds ratio for initial suppression in our model is based on trials that used 1 or 2 newer drugs; thus, our base case may overestimate the cost by assuming that 2 newer drugs were always started. Alternatively, if we assumed that the same virologic suppression could be obtained by starting just 1 newer antiretroviral and discontinuing 1 conventional antiretroviral, the ICER was $54,559/QALY. Conversely, assuming that this level of virologic suppression was obtained when 2 newer antiretroviral drugs were added to the preexisting regimen with no discontinuation of antiretroviral drugs yielded an ICER of $122,804/QALY. Finally, assuming this level of suppression from a regimen consisting solely of 3 newer antiretroviral drugs and discontinuing all conventional antiretroviral drugs yielded an ICER of $105,956/QALY.
The preceding analysis assumed that the number of newer antiretroviral drugs changed the cost of antiretroviral therapy but not the efficacy. We tested this assumption by repeating the analyses, but now assuming that each newer drug was associated with a doubling of the odds ratio of suppression. We compared the incremental cost-effectiveness of substituting successive numbers of conventional drugs in a 3-drug regimen under these assumptions. Substituting 1, 2, or 3 newer antiretroviral drugs was associated with ICERs of $68,732, $80,775, and $117,477 per QALY, respectively (Fig. 2).
The model was also sensitive to assumptions about the efficacy and tolerability of newer antiretroviral drugs. Some newer antiretroviral drugs, such as raltegravir, have demonstrated favorable toxicity profiles. If we changed the base case estimate regarding the tolerability of newer antiretroviral drugs to assume that they were half as likely to cause serious adverse events resulting in discontinuation of drugs, the ICER was consistently below $70,000/QALY throughout the 95% confidence interval estimate of the odds ratio for newer antiretroviral drug efficacy (Fig. 3).
Cost of Newer Antiretroviral Drugs
The model was also sensitive to several other parameter assumptions, most notably the cost of newer antiretroviral drugs. If the annual cost of each newer antiretroviral drug was less than $6206, the ICER was less than $50,000/QALY. In the United States, the annual cost to Medicare of most newer antiretroviral drugs ranges from approximately $6000 to $7500, with maraviroc costing $16,270 annually.
Patient heterogeneity is an important determinant of cost-effectiveness, particularly with respect to the starting CD4 count and viral load. To simulate very advanced patients with extensive multi-drug resistance, we analyzed the cost-effectiveness when there was a low probability of suppression with conventional drugs (20%), a low CD4 count (75 cells/mm3), and a high viral load level (500,000 copies/mL). For such patients, newer antiretroviral drugs cost $69,028/QALY. In contrast, in a comparatively healthier cohort with a higher probability of suppression (60%), a higher CD4 count (250 cells/mm3), and a viral load level of 30,000 copies/mL, use of newer drugs cost $121,492/QALY.
Probabilistic Sensitivity Analysis
Probabilistic sensitivity analysis indicated that the mean discounted incremental cost was $111,750 [95% credible interval (95% CrI): $27,183 to $196,675] and the mean discounted QALY gain was 1.46 (95% CrI: 0.33 to 2.50). The mean ICER was $76,910/QALY. The probability that the ICER was less than $50,000, $75,000, and $100,000/QALY was 0%, 37%, and 99%, respectively (see Figure S4, Supplemental Digital Content, http://links.lww.com/QAI/A466).
We evaluated the cost-effectiveness of newer antiretroviral drugs (those approved for marketing since 2005) for the treatment of patients with advanced HIV infection who were extensively treatment experienced. Treatment options based on newer drugs, when used in combination, are projected to yield significant health gains of about 3.9 additional years of life or 2.6 QALYs, reflecting the poor health of this population. These health gains require expenditures in the range of $54,559/QALY to $75,556/QALY gained, depending on whether we assumed that 1 or 2 newer drugs were required to achieve the rates of initial viral suppression seen in clinical trials of newer drugs.
The cost-effectiveness of newer drugs depends on the number of drugs that are included and the number that are withdrawn to construct newer antiretroviral regimens. Some clinicians might advocate reusing or recycling drugs that have been well tolerated in the past because some virus strains might harbor residual sensitivity. However, we note that the OPTIMA trial demonstrated that a strategy of using multiple (5 or more) conventional antiretroviral drugs with minimal efficacy is not more beneficial than using 3 or 4 antiretroviral drugs.4 Thus, continuation of ineffective drugs is likely to represent poor value for money. Use of 3 newer drugs, even with an assumption of considerably improved efficacy, is relatively expensive, with a cost-effectiveness ratio of $117,477/QALY. Thus, newer antiretroviral drugs are most likely to be cost-effective when 2 newer drugs are added and 2 older drugs are withdrawn. Use of 3 newer antiretroviral drugs should be reserved for patients who have no other effective options.
The definition of advanced HIV disease is inconsistent throughout the medical literature. Classifications include low CD4 counts, uncontrolled high viral loads, experience with multiple antiretroviral drugs or classes of drugs, or harboring multidrug-resistant virus. Our scenario analyses suggest that such distinctions are important and careful selection of patients with advanced disease who are most likely to benefit is needed to maximize the efficient use of these drugs. Nevertheless, the complicated interactions between these factors, and the imprecision of predicting responses from the results of resistance tests, preclude the development of simple guidelines for limiting the use of these drugs. Patients with a history of intolerance or nonadherence to previous antiretroviral regimens might be at higher risk of such events with newer regimens and factors such as dosing and absorption might be important selection factors. Clinicians might continue antiretroviral drugs with activity against hepatitis B virus in co-infected patients despite the emergence of HIV resistance.
The cost of newer antiretroviral drugs varies considerably. In particular, the estimated annual cost to Medicare of maraviroc was $16,270, which is considerably more expensive than other newer antiretroviral drugs ($6115 to $7573). We focused on strategies and combinations that included any newer antiretroviral drugs (rather than specific agents) because individualization of therapy is required for patients with complex histories. Accordingly, it is not feasible to consider all possible therapeutic combinations for all subsets of resistance patterns. Nevertheless, our assumptions about the frequency with which individual drugs are used are uncertain. We addressed these uncertainties through examining a wide range of assumptions regarding which combinations of drugs are used together and the corresponding costs in sensitivity analyses.
Although previous studies have analyzed the cost-effectiveness of individual drugs, we are unaware of a previous analysis that has evaluated newer drugs used in combination because they are likely to be prescribed in clinical practice.38–49 Another strength of our study is the estimation of model parameters for patients treated with conventional antiretroviral drugs from the clinical and health economic data collected in the largest study of advanced multidrug-resistant HIV disease to date.
Our analysis also has some limitations. Our results were based on the cohort of patients recruited to participate in OPTIMA and might thus not be generalizable to all patients with advanced disease. OPTIMA patients were cared for in the Veterans Health Administration in the United States and under public health care programs in Canada and the United Kingdom. Costs might differ for patients with private insurance. Similarly, the effectiveness of drugs in practice might differ from that observed in the trials we used to estimate effectiveness due to selection biases. Although women were eligible for inclusion in OPTIMA, 98% of the cohort was male and there might be important differences related to discontinuation of antiretroviral drugs.50 Our model was well calibrated to known data but was not externally validated against another data source. Furthermore, the time horizon of the decision is considerably longer than that of the clinical trial. As such, we extrapolated effects over time. We also assumed that different strategies had similar effects as direct comparisons between individual strategies for patients with multiple options are lacking. Finally, we did not separately model non-AIDS events, which might be important if patients with experienced disease are at increased risk for such complications with newer antiretroviral drugs. However, we modeled all-cause mortality, including both AIDS-related and non–AIDS-related events, and our estimates of quality of life and costs appropriately capture the overall health and economic outcomes of the cohort.
In conclusion, our analysis indicates that newer drugs for the treatment of HIV infection yield very important health gains and compare favorably to interventions considered cost-effective in the United States. The most important way to ensure that newer antiretroviral drugs provide good value are to carefully select patients with advanced disease for whom less expensive options are clearly inferior and to encourage discontinuation of older drugs whose benefits are minimal.
The authors thank all the participants who joined the OPTIMA trial and the OPTIMA Trial Steering Committee members.
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