Conceived and designed the experiments: CFG P. Mugyenyi JH AR JD DMG AGB AML ASW P. Munderi. Performed the experiments: P. Mugyenyi HG EK CK P. Munderi RK FS JH AR DMG CFG AGB ASW AML REMM JK JA LM BNW. Analyzed the data: AML REMM. Wrote the paper: AML CFG ASW DMG JK JA LM REMM BNW RK FS AR HG AGB CK EK P. Munderi P. Mugyenyi JH JD.
GlaxoSmithKline, Gilead Sciences, Boehringer-Ingelheim and Abbott Laboratories donated drugs for DART. There are no patents, products in development or marketed products to declare. This does not alter the authors’ adherence to all the PLoS ONE policies on sharing data and materials, as detailed online in the guide for authors.
Despite funding constraints for treatment programmes in Africa, the costs and economic consequences of routine laboratory monitoring for efficacy and toxicity of antiretroviral therapy (ART) have rarely been evaluated.
Cost-effectiveness analysis was conducted in the DART trial (ISRCTN13968779). Adults in Uganda/Zimbabwe starting ART were randomised to clinically-driven monitoring (CDM) or laboratory and clinical monitoring (LCM); individual patient data on healthcare resource utilisation and outcomes were valued with primary economic costs and utilities. Total costs of first/second-line ART, routine 12-weekly CD4 and biochemistry/haematology tests, additional diagnostic investigations, clinic visits, concomitant medications and hospitalisations were considered from the public healthcare sector perspective. A Markov model was used to extrapolate costs and benefits 20 years beyond the trial.
3316 (1660LCM;1656CDM) symptomatic, immunosuppressed ART-naive adults (median (IQR) age 37 (32,42); CD4 86 (31,139) cells/mm3) were followed for median 4.9 years. LCM had a mean 0.112 year (41 days) survival benefit at an additional mean cost of $765 [95%CI:685,845], translating into an adjusted incremental cost of $7386 [3277,dominated] per life-year gained and $7793 [4442,39179] per quality-adjusted life year gained. Routine toxicity tests were prominent cost-drivers and had no benefit. With 12-weekly CD4 monitoring from year 2 on ART, low-cost second-line ART, but without toxicity monitoring, CD4 test costs need to fall below $3.78 to become cost-effective (<3xper-capita GDP, following WHO benchmarks). CD4 monitoring at current costs as undertaken in DART was not cost-effective in the long-term.
There is no rationale for routine toxicity monitoring, which did not affect outcomes and was costly. Even though beneficial, there is little justification for routine 12-weekly CD4 monitoring of ART at current test costs in low-income African countries. CD4 monitoring, restricted to the second year on ART onwards, could be cost-effective with lower cost second-line therapy and development of a cheaper, ideally point-of-care, CD4 test.
It is essential to evaluate the economic impact of antiretroviral therapy (ART) programmes using a public health approach
Several studies have evaluated the clinical benefit
Here we present a cost-effectiveness analysis, from the public healthcare perspective, of Laboratory and Clinical Monitoring (LCM) compared with Clinically-Driven Monitoring (CDM) of ART alongside a randomised controlled trial conducted in Uganda and Zimbabwe
The DART trial was approved by Research Ethics Committees in Uganda, Zimbabwe and the UK, and all enrolled participants gave individual informed consent.
Effectiveness and resource utilisation data were collected in the Development of Antiretroviral Therapy (DART) trial, conducted from 2003–2008 at 3 centres in Africa: Entebbe and Kampala (plus satellite), Uganda; Harare, Zimbabwe. The trial compared LCM (routine 12-weekly laboratory monitoring: CD4 counts for efficacy; haematology and biochemistry for toxicity) with CDM (CD4 counts never available to clinicians) in ART-naïve adults (≥18 years) starting therapy with symptomatic HIV disease and CD4<200 cells/mm3. Additional diagnostic investigations and monitoring tests (except CD4 in CDM) could be requested according to clinical judgement at routine visits, patient-initiated visits or hospital admission. Concomitant medicines were provided. The trial demonstrated no impact of routine toxicity tests on any adverse event outcome; and a small, statistically significant benefit of CD4 monitoring on HIV disease progression and death from the second year onwards
Mean total cost per patient by group was estimated using intention-to-treat. Research component costs were separated from those for ART delivery/monitoring and excluded from analysis. Individual patient data on healthcare resource utilisation and health outcomes of all DART participants were analysed, except for concomitant medications which were analysed by group. Because of the large number of different medications used over the 6 year trial, only those used by >30% of patients, or where there was difference of >3% in the proportion using a medication between the two randomised groups were accounted for. Healthcare utilisation outside of the trial (health clinic visits, hospitalisations and concomitant medications) were elicited at every 4-weekly visit and included. Unit costs of CD4 counts, biochemistry, haematology, clinic and health centre visits were estimated in primary economic costing analyses
All local prices were converted to 2008 US$ using exchange rates over the trial period (e.g. $1US$ = 1,900 Uganda Shillings; 1US$ = 777,500,000 Zimbabwean dollars in 2008) and the US Consumer Price Index
Survival benefits were estimated from the difference in the area under the Kaplan-Meier
Incremental cost effectiveness ratios (ICERs) defined as the ratio of incremental mean cost to mean survival or QALY gained, were estimated. Costs and health benefits occurring after 12 months were discounted at 3% per annum, and adjusted for censoring due to drop-out using the method of Li
A Markov model of transitions between discrete CD4 states and death was used to extrapolate outcomes post-DART, from 6 to 25 years after ART initiation. An individual alive at trial closure would be in one of three states, defined by CD4 <100, 100–200, and >200 cells/mm3, qualified by first-line or second-line ART due to expected differences in costs and benefits. After every 12-week period, the participant would have moved to a different state, remained in the initial state or died. Overall 97.7% of expected CD4 counts before end of trial/death/loss to follow-up were available. For routine CD4 tests, clinic visits and ART use, full compliance with the DART follow-up schedule was assumed. Other costs and QALYs were analysed as random events, divided into 12-week periods and matched to latest CD4 count range to derive estimates of cost and benefit (‘pay-offs’) for Markov states as a function of latest CD4 count and group. In this extrapolation, only cotrimoxazole prophylaxis and treatment and antimalarial drugs, were included as concomitant medications; the former were the only concomitant medications whose use varied significantly over years on ART and the latter were the only medications whose use varied significantly across centres. The analysis accounted for background mortality risks derived from counterfactual life tables for Uganda that exclude the effect of HIV/AIDS (see Supporting
ICERs <3x per capita GDP were used as an indication of cost-effectiveness, following benchmarks suggested by WHO
In DART, 3316 (1660 LCM; 1656 CDM) HIV-infected, treatment-naïve, symptomatic African adults started ART (65% female; median (IQR) age 37 (32–42); CD4 86 (31–139) cells/mm3) and were followed for median 4.9 (4.5–5.3) years. Unit costs are presented in
Item | Observed | Source and Date | Sensitivity Analysis | Source and Date | ||
First line therapy annual cost |
||||||
ZDV+3TC+TDF | $349.12 | Midpoint of MSF prices, 2009 |
$290.72 | Generic prices (from WHO)2008 |
||
ZDV+3TC+NVP | $308.79 | $165.64 | ||||
ZDV+3TC+ABC | $585.46 | $441.80 | ||||
Second-line therapy annual cost |
||||||
ddI+EFV+KAL | $1032.59 | Midpoint of MSF prices, 2009 |
$874.18 | Lower bound of MSF prices,2009 |
||
ddI+NVP+KAL | $967.98 | $763.22 | ||||
ddI+ABC+KAL | $1244.65 | $1062.52 | ||||
CD4 cell counts | $15.79 | Entebbe | Micro-costing– centre specific, 2008 | $8.82 | Rosen, Long and Sane,2008 |
|
$10.07 | JCRC | |||||
$18.82 | UZCRC | |||||
Haematology panel tests | $6.46 | Entebbe | $5.30 | National Referral Laboratories, 2008 | ||
$7.13 | JCRC | |||||
$12.32 | UZCRC | |||||
Biochemistry panel tests | $11.66 | Entebbe | $29.50 | |||
$10.67 | JCRC | |||||
$12.23 | UZCRC | |||||
DART visits | $4.08 | Entebbe | N/A | N/A | ||
$3.30 | JCRC | |||||
$8.38 | UZCRC | |||||
Health Centre visits | $3.26 | Entebbe | N/A | N/A | ||
$8.84 | JCRC | |||||
$8.73 | UZCRC | |||||
Per diem hospital cost |
$25.57 | Adam, Evans & Murray, 2003 |
N/A | N/A | ||
Other diagnostic investigations and tests |
$6.26 | National Referral Laboratories, 2008 | N/A | N/A |
Annual drug costs of keeping a patient on this specific combination of drugs continuously for 365 days.
Per diem hospital costs from Adam T, Evans DB and Murray CJL, 2003 were reflated to 2008 USD($).
Other unit costs for diagnostic investigations (including X rays, TB smears, CSF analysis etc) and non-routine biochemistry and haematology tests are not listed here but were obtained from National Referral Laboratories prices list.
Healthcare resources consumed by patients, overall costs of resource utilisation and cost differences between the groups are shown in
Healthcare resource utilisation | Observed total over trial period per patient (median 4.9 years) | Cost difference LCM – CDM |
|
LCM | CDM | ||
First-line therapyNumber of days Mean (SD)Costs Mean (SD) | 1464.96 (555)1451 (603) | 1481.90 (545)1470 (603) | −19 |
Second-line therapyNumber of days Mean (SD)Costs Mean (SD) | 152.99 (355)406 (964) | 102.89 (270)265 (718) | +141 |
CD4 monitoringNumber of CD4s Mean (SD)Costs Mean (SD) | 19.81 (6)288 (121) | 0 (0)0 (0) | +288 |
Routine 12-weekly haematology toxicity monitoringNumber of haematology tests Mean (SD)Costs Mean (SD) | 21.58 (7)183 (81) | 0 (0)0 (0) | +183 |
Routine 12-weekly biochemistry toxicity monitoringNumber of CD4s biochemistry tests Mean (SD)Costs Mean (SD) | 20.93 (6)227 (69) | 0 (0)0 (0) | +227 |
Clinically indicated diagnostic investigations, other tests outsideroutine visits (both groups) or monitoring tests (except CD4)requested for clinical reasons at routine visits (CDM)Number of diagnostic investigationsCost Mean (SD) | 6.56 (11)41 (81) | 10.49 (18) |
−25 |
DART clinic visitsNumber of visits Mean (SD)Costs Mean (SD) | 61.18 (19)414 (195) | 60.12 (20)405 (197) | +9 |
Health centre visitsNumber of visits Mean (SD)Costs Mean (SD) | 7.73 (7)53 (56) | 7.88 (8)55 (64) | +2 |
Nights in hospitalNumber of visits Mean (SD)Costs Mean (SD) | 5.51 (13)141 (347) | 6.77 (16)177 (444) | −36 |
Concomitant medications | 46 | 48 | −2 |
Overall mean total costs (SD)[95% confidence interval] | 3249 (1246) | 2485 (1095) | 765[685,845] |
Discrepancies in totals and differences are due to rounding.
1.47 (3) and 0.86 (3) of the total were standard haematology or biochemistry tests respectively performed at routine doctor visits as part of the trial for CDM but requested for clinical management.
95% CIs were estimated with bootstrapping percentile method.
Mean survival benefit with LCM was 0.112 life-years (41 days). The unadjusted incremental cost per life year gained (LYG) was US$6819, with 95% CI from US$3282 to the dominated outcome where it produces lower survival benefits alongside higher costs than CDM (
LCMN = 1656 | CDMN = 1660 | DifferenceLCM – CDM | |
|
|||
Overall survival days |
2000 | 1959 | +41 [−15,+95] |
Overall survival years |
5.48 | 5.36 | +0.112 [−0.04,+0.26] |
Overall mean total costs in US$ [95% CI] (unadjusted) | 3249 | 2485 | +765 [685,845] |
Overall QALYs – patients’ values | 3.351 | 3.255 | +0.096 |
Overall QALYs – general population’s values | 2.714 | 2.636 | +0.078 |
Overall mean total costs in US$ [95% CI] | 3146 | 2398 | +748 [+679,+818] |
Incremental Cost per Year Gained in US$ (unadjusted) [95% CI] | 6819 [3282, Dominated] | ||
Incremental Cost per Life Year Gained in US$ [95% CI] | 7386 [3277, Dominated] | ||
Incremental Cost per QALY Gained in US$ – patients’ values [95% CI] | 7793 [4442,39179] | ||
Incremental Cost per QALY Gained – in US$ general population’s values [95% CI] | 9621 [5484,48359] | ||
|
|||
|
|||
Mean second-line therapy costs in US$ (SD) | 357 (845) | 236 (637) | +121 |
Overall mean total costs in US$ (unadjusted) [95% CI] | 3194 | 2449 | +745 [669,821] |
Incremental Cost per Life Year Gained in US$ (unadjusted) [95% CI] | 6643 [3307, Dominated] | ||
Incremental Cost per Life Year Gained in US$ [95% CI] | 6443 [2891, Dominated] | ||
Incremental Cost per QALY Gained in US$ – patients’ values [95% CI] | 6798 [3917, 30501] | ||
Incremental Cost per QALY Gained in US$ – general population’s values [95% CI] | 8392 [4836,37656] | ||
|
|||
Mean CD4 monitoring costs in US$ (SD) | 175 (57) | 0 (0) | +175 |
Standard 12-weekly haematology biochemistry toxicity monitoring (SD) | 699 (216) | 23 (65) | +676 |
Overall mean total costs in US$ (unadjusted) [95% CI] | 3425 | 2493 | +932 [+851,+1013] |
Incremental Cost per Life Year Gained in US$ (unadjusted) [95% CI] | 8318 [3876, Dominated] | ||
Incremental Cost per Life Year Gained in US$ [95% CI] | 8990 [4160, Dominated] | ||
Incremental Cost per QALY Gained in US$ – patients’ values [95% CI] | 9485 [5334, 47957] | ||
Incremental Cost per QALY Gained in US$ – general population’s values [95% CI] | 11710 [6586, 59206] |
See column sensitivity analysis in
In sensitivity analyses with prices for low-cost second-line drugs, ICERs reduced: the adjusted incremental cost per LYG was $6443 [2891, Dominated]; and per QALY was $6798 [3917,30501] using patients’ values and $8392 [4836,37656] using general population values (
Scenario analyses were undertaken to explore the cost-effectiveness of monitoring strategies not directly evaluated in DART. In a limited CD4 monitoring scenario without routine toxicity monitoring, 12-weekly CD4 monitoring was restricted to the second year on ART onwards (as outcomes between groups differed only from the third year on ART following differences in rates of switching to second-line ART from the second year
ART outcomes were extrapolated long-term by applying predicted transition probabilities corresponding to the last two years of DART (see Supporting
The ICER per QALY gained over time is shown for the limited laboratory monitoring (CD4 from the second year on ART only) scenario in
Here we report the costs and economic outcomes associated with routine laboratory monitoring of ART using individual patient data from Uganda and Zimbabwe in the DART trial. Routine toxicity monitoring had no additional benefits on any adverse event outcome and was more costly than clinically driven toxicity monitoring. While effective, routine (12-weekly) laboratory CD4 count monitoring was more costly than monitoring without CD4 counts. Even ignoring routine toxicity monitoring, based on the ICERs derived for life-years or QALYs gained, the CD4 monitoring strategy used in DART is beyond the cost-effective threshold of <3x per capita GDP, which is the WHO benchmark used for assessing cost-effectiveness of interventions in low-income sub-Saharan African countries
Since DART publication, three other randomised trials comparing different ways to monitor adults on ART in low and middle income countries have been presented or published: the HBAC trial in Uganda
According to our primary costing studies and models, we estimated that the current costs of CD4 tests need to drop to below USD$3.78 for 12-weekly CD4 monitoring to be cost-effective. Extrapolating over the longer-term under the fixed budget rule (instead of the arbitrary, conventional threshold used to approximate the value of a life year in optimal health or without disability
The long-term economic value of routine CD4 monitoring is inversely related to the costs of second-line therapy: the lower the costs of second-line therapy, the greater the likelihood of CD4 monitoring being cost-effective. Of the three other trials of ART monitoring strategies,only the Uganda HBAC study so far has conducted cost-effectiveness analysis
DART and HBAC used different clinical thresholds to determine first-line failure and thus trigger switch to second-line ART. The most important difference is the inclusion of single WHO 3 events in the HBAC clinical criteria for switch (weight loss, unexplained fever, diarrhoea, oral candidiasis), which were not included in WHO guidelines
Furthermore, the median of only 3 years of follow-up in HBAC, compared to 5 years in DART, inevitably has implications for the accuracy of longer term predictions based on observed data. Although our model did not adjust for the effect of past or ongoing opportunistic infections on the risk of death over and above that captured by current CD4 count, any resulting bias favouring clinical monitoring is likely to be reversed by the assumption of higher switch rates with CDM to second-line therapy at high CD4 counts throughout the period after DART.
To be eligible for DART, all potential participants underwent CD4 testing and needed to have CD4<200 cells/mm3 to enter the trial. Our analysis was therefore not able to consider the costs and benefits of CD4 testing for ART eligibility
Our study is unique in its prospective valuation of patient preferences for health states in a sub-sample of DART patients. Interestingly, applying utility weights to health states in DART defined according to performance status and any ongoing WHO stage 3 or 4 events, as assessed by a doctor, showed that the estimated survival difference (0.101 life years) was associated with an almost equal gain in asymptomatic survival (0.097 life years).
DART used a simple and easy to interpret switch criterion of CD4<100 cells/mm3 which does not require longitudinal measurement of CD4 counts, or pre-ART counts. More complex failure criteria based on prior values (CD4 fall <pre-ART, >50% decline from peak) may increase the proportions switching to second-line without necessarily improving outcomes, thus reducing the likelihood of CD4 monitoring being cost-effective; these criteria are also more challenging to implement. Interestingly the HBAC study used persistently declining CD4 cell counts on two consecutive measurements to indicate treatment failure: this has been demonstrated to have the lowest sensitivity of the three failure criteria
DART did not evaluate routine viral load testing. However, the difference between DART groups receiving and not receiving routine CD4 monitoring trial based was similar to one modelling study
A further limitation of the cost-effectiveness analysis presented here is that it has only considered the patients on ART, and in particular has not considered other possible impacts such as increased HIV transmission, including of drug resistant virus, from unsuppressed patients on ART or, in contrast, reduced transmission from having been able to put more patients on ART without providing routine laboratory monitoring for the same fixed budget. Modelling studies, when they have examined the evolution and transmission of drug resistance under a public health approach to ART, have been relatively reassuring
Our findings have implications for public sector ART programmes in Africa, given the unmet demand for treatment, the limited availability of laboratory services and stagnant or declining international funding for health. Strengthening laboratory services is a priority: CD4 testing should focus on ART initiation; toxicity testing can be clinically guided rather than routine; access to quality-controlled diagnostic testing must be widened. With fixed and constrained budgets, relative to no ART provision
Results from the DART trial and the cost-effectiveness analysis also raise challenging issues about how to act on research findings when effectiveness is demonstrated but cost-effectiveness is not, as profound underlying tensions between patients, healthcare workers, funders and policy makers are exposed
In conclusion, the DART trial has clearly shown that routine laboratory monitoring of ART is not currently cost-effective in low-income African countries. There is no rationale for toxicity monitoring which does not affect outcomes and is costly. Routine CD4 monitoring has small but measurable benefits on survival; for it to be cost-effective the costs of second-line ART and CD4 testing need to fall substantially. Laboratories will remain important for quality of care especially for the diagnosis of intercurrent events on ART. Realising the survival benefits of CD4 monitoring widely in Africa is likely to be dependent on the development of a cheap, ideally point-of-care CD4 test. In the meantime, given competing priorities, HIV programmes in Africa may best spend limited resources on increasing access to first and second-line ART.
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We thank all the patients and staff from all the centres participating in the DART trial.
Data were presented at the 5th IAS Conference on HIV Pathogenesis, Treatment and Prevention, 19–22 July 2009, Cape Town, South Africa.