Monitoring strategies.

<p>ART, antiretroviral therapy; VL, viral load; tVL, targeted viral load; m, monthly; POC, point-of-care; Lab, laboratory-based</p><p>POC VL tests are assumed to be qualitative with a detection limit of 5000 copies/ml; lab-VL tests are assumed to be fully quantitative</p><p>2x = second confirmatory measurement 3 months after first observation needed</p><p>* The information from these visits/tests is not used to decide about switching to second-line</p><p>** The probability of having a test is 50%</p><p>Monitoring strategies.</p

Model outcomes: main analysis assuming that treatment failure rate is twice as high in strategies without routine viral load monitoring (1.1 to 3.5) as in strategies with routine viral load monitoring due to improved adherence.

<p>Please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119299#pone.0119299.t002" target="_blank">Table 2</a> for a detailed description of all monitoring strategies. All costs are given in US$and cost-effectiveness ratios in US$ per DALY averted.</p><p>POC-VL, point-of-care viral load; lab-VL, laboratory-based viral load; ART, antiretroviral therapy; DALY, disability-adjusted life-year; CER, cost-effectiveness ratio; ICER, incremental cost-effectiveness ratio; l/e, least expensive and least effective strategy; w/d, weakly dominated; s/d, strongly dominated.</p><p>Model outcomes: main analysis assuming that treatment failure rate is twice as high in strategies without routine viral load monitoring (1.1 to 3.5) as in strategies with routine viral load monitoring due to improved adherence.</p

Cost-effectiveness of different monitoring strategies for antiretroviral therapy.

<p>Panel A presents Scenario A (failure rate identical in all monitoring strategies). Panel B presents Scenario B (failure rate twice as high in strategies without compared to strategies with routine viral load monitoring). Cost and DALYs averted are presented per one patient for the duration of ART. Please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119299#pone.0119299.t002" target="_blank">Table 2</a> for a detailed description of the monitoring strategies.</p

Input parameters that can be varied using the Excel tool.

<p>ART, antiretroviral therapy; US$, US dollar; M, male; F, female; GBD, Global Burden of Disease study; ASSA2008, ASSA2008 model</p><p>* Every simulated patient dies at the age of 75 if the effect of HIV is not accounted for</p><p>** This analysis is presented as the second main analysis, not a sensitivity analysis</p><p>Input parameters that can be varied using the Excel tool.</p

Progression of patients in the mathematical model.

<p>Panel A shows the progression of the patient’s treatment regimen and observed failure status. Within each compartment of panel A, the patient will proceed according to the underlying treatment progression shown in Panel B. The type of failure that can be detected depends on the monitoring strategy. After switching to second-line therapy, the patient will start either in the successful ART compartment (if he/she had no or concordant immunological/clinical failure) or in the clinical and/or immunological failure compartment (if he/she had a discordant failure of the corresponding type). See the main text for definitions of concordant and discordant failures.</p

Key parameters related to disease progression.

<p>The hazard of virological failure (1a) is applied for first-line ART as such, and for second-line ART together with a resistance penalty factor (1b) which depends on the time spent on failing first-line ART. Immunological failure can happen through two independent hazard functions: the other is applied only to patients on virologically failing first- or second-line ART (2a), the other for all patients irrespective of the virological status or ART regimen (2b). For clinical failure, the hazard function (3a) is used as such for patients without virological and immunological failures, and the hazard ratios (3b, 3c) are applied for patients with the corresponding failures. HIV-related mortality is calculated from a competing risk analysis of observed mortality (4a) and loss to follow-up (4b) as well as the expected mortality among lost patients (4c). The parametric hazard function for mortality (4d) is used as such for patients without virological, immunological or clinical treatment failure, and the hazard ratios (4e, 4f, 4g) are applied to patients with the corresponding failures.</p><p>CI, confidence interval; ART, antiretroviral therapy; HR, hazard ratio; LTFU, loss to follow-up; n/a, not applicable</p><p>* Relative decrease in second-line efficacy per year spent on failing first-line ART</p><p>** Observed mortality and LTFU rates on successful first-line ART were calculated from the data and used, together with background mortality and expected mortality among patients LTFU, to calculate the corrected HIV-related mortality for the cohort</p><p>*** Weighted sum of two Weibull distributions</p><p>Key parameters related to disease progression.</p

Model outcomes: main analysis assuming the treatment failure rate to be identical in all strategies.

<p>Please see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0119299#pone.0119299.t002" target="_blank">Table 2</a> for a detailed description of all monitoring strategies. All costs are given in US$and cost-effectiveness ratios in US$ per DALY averted.</p><p>POC-VL, point-of-care viral load; lab-VL, laboratory-based viral load; ART, antiretroviral therapy; DALY, disability-adjusted life-year; CER, cost-effectiveness ratio; ICER, incremental cost-effectiveness ratio; l/e, least expensive and least effective strategy; w/d, weakly dominated; s/d, strongly dominated.</p><p>Model outcomes: main analysis assuming the treatment failure rate to be identical in all strategies.</p