PLoS MEDICINE
Cost-Effectiveness of Treating
Multidrug-Resistant Tuberculosis
Stephen C. Resch1*, Joshua A. Salomon2,3, Megan Murray4,5, Milton C. Weinstein1,5
1 Department of Health Policy and Management, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America, 2 Department of
Population and International Health, Harvard School of Public Health, Harvard University, Boston, Massachusetts, United States of America, 3 Harvard Initiative for Global
Health, Harvard University, Cambridge, Massachusetts, United States of America, 4 Department of Epidemiology, Harvard School of Public Health, Harvard University, Boston,
Massachusetts, United States of America, 5 Division of Social Medicine and Health Inequalities, Brigham and Women’s Hospital, Boston, Massachusetts, United States of
America
Funding: This study was supported
by grants from the Bill and Melinda
Gates Foundation through the
foundation’s grant to the
Department of Social Medicine at
Harvard Medical School and to
Partners In Health, and from the
National Institute for Allergy and
Infectious Diseases (T32 AI07433–
12). The funders had no role in study
design, data collection and analysis,
decision to publish, or preparation
of the manuscript.
Competing Interests: The authors
have declared that no competing
interests exist.
Academic Editor: Keith Klugman,
Emory University, United States of
America
Citation: Resch SC, Salomon JA,
Murray M, Weinstein MC (2006) Costeffectiveness of treating multidrugresistant tuberculosis. PLoS Med
3(7): e241. DOI: 10.1371/journal.
pmed.0030241
Received: July 6, 2005
Accepted: March 24, 2006
Published: July 4, 2006
DOI:
10.1371/journal.pmed.0030241
Copyright: Ó 2006 Resch et al. This
is an open-access article distributed
under the terms of the Creative
Commons Attribution License, which
permits unrestricted use,
distribution, and reproduction in any
medium, provided the original
author and source are credited.
Abbreviations: DALY, disabilityadjusted life year; DST, drug
susceptibility testing; GDP, gross
domestic product; MDR, multidrugresistant; QALY, quality-adjusted life
year; TB, tuberculosis; WHO, World
Health Organization
* To whom correspondence should
be addressed. E-mail: resch@fas.
harvard.edu
ABSTRACT
Background
Despite the existence of effective drug treatments, tuberculosis (TB) causes 2 million deaths
annually worldwide. Effective treatment is complicated by multidrug-resistant TB (MDR TB)
strains that respond only to second-line drugs. We projected the health benefits and costeffectiveness of using drug susceptibility testing and second-line drugs in a lower-middleincome setting with high levels of MDR TB.
Methods and Findings
We developed a dynamic state-transition model of TB. In a base case analysis, the model was
calibrated to approximate the TB epidemic in Peru, a setting with a smear-positive TB incidence
of 120 per 100,000 and 4.5% MDR TB among prevalent cases. Secondary analyses considered
other settings. The following strategies were evaluated: first-line drugs administered under
directly observed therapy (DOTS), locally standardized second-line drugs for previously treated
cases (STR1), locally standardized second-line drugs for previously treated cases with testconfirmed MDR TB (STR2), comprehensive drug susceptibility testing and individualized
treatment for previously treated cases (ITR1), and comprehensive drug susceptibility testing
and individualized treatment for all cases (ITR2). Outcomes were costs per TB death averted and
costs per quality-adjusted life year (QALY) gained. We found that strategies incorporating the
use of second-line drug regimens following first-line treatment failure were highly costeffective compared to strategies using first-line drugs only. In our base case, standardized
second-line treatment for confirmed MDR TB cases (STR2) had an incremental costeffectiveness ratio of $720 per QALY ($8,700 per averted death) compared to DOTS.
Individualized second-line drug treatment for MDR TB following first-line failure (ITR1) provided
more benefit at an incremental cost of $990 per QALY ($12,000 per averted death) compared to
STR2. A more aggressive version of the individualized treatment strategy (ITR2), in which both
new and previously treated cases are tested for MDR TB, had an incremental cost-effectiveness
ratio of $11,000 per QALY ($160,000 per averted death) compared to ITR1. The STR2 and ITR1
strategies remained cost-effective under a wide range of alternative assumptions about
treatment costs, effectiveness, MDR TB prevalence, and transmission.
Conclusions
Treatment of MDR TB using second-line drugs is highly cost-effective in Peru. In other
settings, the attractiveness of strategies using second-line drugs will depend on TB incidence,
MDR burden, and the available budget, but simulation results suggest that individualized
regimens would be cost-effective in a wide range of situations.
The Editors’ Summary of this article follows the references.
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Cost-Effectiveness of MDR TB Treatment
epidemic in Peru. Co-infection with HIV was not explicitly
considered because only 2% of TB cases in Peru have HIV coinfection [10]. The time horizon for the analysis was 30 y, and
the perspective was that of a public health-care system.
Introduction
Mycobacterium tuberculosis infects nearly one-third of the
world’s population, and 8 to 10 million infected persons
progress to active tuberculosis (TB) each year [1]. Despite the
existence of effective drug treatment, TB causes approximately 2 million deaths annually [1]. Efforts to treat patients
with active disease and to control the spread of TB are
complicated by resource constraints, co-infection with HIV,
and the emergence of drug-resistant TB strains.
Multidrug-resistant TB (MDR TB), defined by resistance to
the two most potent first-line anti-TB agents (isoniazid and
rifampicin), arises initially as a result of poorly implemented
treatment. Subsequent transmission of MDR TB strains gives
rise to cases of ‘‘primary’’ resistance. Among 77 settings
surveyed by the World Health Organization (WHO), the
estimated fraction of prevalent TB cases that are MDR ranged
from 0% to 27% (median 1.7%) [2].
The optimal strategy for detecting and treating MDR TB in
resource-poor countries is unclear. Directly observed therapy
using a standard short course of first-line antibiotics (DOTS),
as developed and promoted by WHO, is widely endorsed by
national TB programs. Several studies report high cure rates
using DOTS for drug-sensitive TB [1,3–6]. However, DOTS
has been shown to be much less effective against MDR TB,
with cure rates in six countries ranging from 6% to 59% [6].
Treatment strategies that include the use of second-line
drugs in the directly observed treatment of MDR TB (DOTSPlus) can achieve cure rates nearly as high as those for drugsensitive TB treated with first-line drugs [7,8]. Strategies for
using second-line drugs fall into two broad categories: those
using standardized regimens formulated for particular geographic areas based on drug resistance profiles of a sample of
cases, and those using individualized regimens selected on the
basis of individual drug susceptibility testing (DST).
Although second-line therapy yields higher cure rates for
MDR TB, it is more expensive than first-line therapy and
requires longer treatment durations. Policy-makers have
questioned the wisdom of allocating resources to second-line
therapy, particularly where DOTS programs are not fully
implemented [9].
Our objective was to assess the health benefits and costeffectiveness of identifying and treating patients with MDR
TB in lower-middle-income settings using the example of
Peru, where an estimated 4.5% of all TB cases are MDR TB
[10,11]. Our analysis differs from previously published costeffectiveness analyses [12,13] in that it uses more recent data
on the efficacy of DOTS-Plus and uses a dynamic model to
simulate the reduction of TB transmission in the community
as a benefit of treatment.
Treatment Strategies
The following strategies were considered.
DOTS. New cases are treated with a 6-mo course of firstline drugs, and previously treated patients who are not cured
are retreated with a second course of first-line drugs.
STR1. New cases are treated with first-line drugs, and
previously treated patients who are not cured receive an 18mo standardized regimen of three second-line drugs and two
first-line drugs.
STR2. New cases are treated with first-line drugs, and
previously treated patients are tested for MDR TB. Confirmed
cases receive an 18-mo standardized regimen of three secondline drugs and two first-line drugs.
ITR1. New cases are treated with first-line drugs, and
previously treated patients who are not cured receive
comprehensive DST; those with confirmed MDR TB receive
an individualized regimen of second-line drugs.
ITR2. New and previously treated patients receive DST,
and those with MDR TB receive an individualized regimen;
those not cured are given a repeat DST and another
individualized treatment regimen.
In all strategies, patients who are not cured by two courses
of treatment continue to receive treatment, which is assumed
to reduce their mortality risk but confer no added probability
of cure.
Model Structure and Simulation
The model (Figure 1) begins with a population of 100,000
people, distributed across health states to distinguish uninfected from infected persons, latent infection from active
disease, non-MDR from MDR infection, and various treatment histories (see Text S1 and Tables S1–S3 for technical
details). In each monthly cycle persons may transition from
one state to another, reflecting the processes of infection,
progression, treatment initiation and completion, and mortality. Active disease is limited to smear-positive pulmonary
cases, since they are the primary target of DOTS-based TB
control strategies.
Natural History
Transmission of TB infection from persons with active
disease to those who are uninfected or latently infected
increases proportionally with the number of infectious
persons in the population at any specific time. In the base
case we assumed that MDR TB is as transmissible as drugsusceptible TB [14–16]. In the model, a proportion of new
infections progress directly to the active disease state, and the
remainder enter a latent state and are subject to subsequent
activation at a constant rate [17,18]. Without treatment,
patients may cure spontaneously, remain actively infected, or
die. Natural history assumptions (Table 1) were derived from
epidemiologic studies [14,17–24] and by calibrating the model
to produce estimates consistent with epidemiologic data from
Peru (see Text S1 and Table S4). Since more than one
combination of model parameters could generate an epidemic consistent with available data, several sets of parameter
combinations were considered in sensitivity analysis.
Methods
We used a state-transition model to evaluate the costeffectiveness of five alternative treatment strategies for TB.
Strategies were evaluated in terms of incremental costs per
averted TB death and incremental costs per quality-adjusted
life year (QALY) saved. The model is similar to a Markov
cohort model, but allows the incidence of drug-susceptible
TB and MDR TB infection to depend on the current
prevalence of infectious cases in the population. Model
parameters were calibrated to represent the current TB
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Cost-Effectiveness of MDR TB Treatment
Figure 1. Structure of the TB Treatment Model
Boxes represent health states, arrows represent population flow between health states, red arrows represent infection and re-infection. kd is the force of
non-MDR infection, km is the force of MDR TB infection, q is the proportion of new infections that break down rapidly, v is the immunity factor, c is the
rate of delayed progression from latent to active disease, ui is the case detection rate, di is the treatment dropout rate, s is the treatment failure rate,
and a is the fraction of uncured patients acquiring MDR. Death can occur from any state (not shown). Cure can occur from any diseased state. Cured
patients transition to the latent infection health state (not shown).
DOI: 10.1371/journal.pmed.0030241.g001
Diagnosis and Treatment
acquired MDR TB for patients in treatment; thus, the model
allows for 40% of treatment failures and uncured defaulters
to acquire MDR TB. In the model, cured cases remain latently
infected, and can reactivate or be reinfected.
New TB cases are detected when patients present with
pulmonary symptoms and are diagnosed by sputum smear
microscopy. Consistent with the high rates of case detection
achieved in Peru, we assumed that a new TB case had an 80%
annual probability of being detected and entering treatment
[3]. However, WHO estimates that, on average, in settings
with fully implemented DOTS programs, only about half of
incident TB cases are detected annually using passive case
detection [25]. Therefore, in sensitivity analysis we examined
the impact of the case-finding rate on outcomes.
Probabilities of cure, default (dropout), and death in each
treatment strategy listed in Table 2 are based on published
studies of treatment cohorts [3–7,13,26–33]. First-line DOTS
regimens cure approximately 90% of new drug-susceptible
cases, and reduce mortality to less than 5% [3–6]. Default
rates vary, but usually fall below 10% in well-administered
programs [3–6]. In contrast to the high cure rates among new
cases, between 57% and 88% of non-MDR cases are cured by
retreatment regimens [6,31,32]; we assumed a cure probability of 68% in our base case. First-line drugs are even less
effective against MDR TB [6,31]; for our base case, we
assumed a cure probability of 58% for new MDR TB cases
treated with a first-line regimen and 35% for retreatment.
Studies of standardized second-line drug regimens have
reported cure probabilities ranging from 44% to 72% [13,26–
28]. For our base case, we assumed a 63% probability of cure,
based on an average of these results. Studies of individualized
treatment have reported success rates of 75% in the United
States [30], 77% in Turkey [29], and 73%–79% in Peru [7,33].
We assumed 75%, 70%, and 60% probabilities of cure for
previously untreated patients, patients for whom a first-line
regimen had failed, and patients for whom a second-line
regimen had failed, respectively.
Poor adherence and other factors introduce a risk of
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Costs
Regimen costs include the cost of drugs, laboratory tests,
and personnel (Table 3) [13,34]. Patient time and transportation costs are excluded. Base case drug costs for secondline regimens and DST are based on unpublished information
obtained from Partners In Health, a Boston-based nongovernmental organization delivering TB treatment in Peru
(see Text S1 and Table S5 for details). Non-drug costs for
second-line regimens are based on a previously published
cost-effectiveness analysis [13]. Published estimates of firstline regimen costs are available for several settings. [4,13,34–
36]. For consistency, we used the estimates of Suarez et al. [13]
in our base case. We assumed that patients who default or die
during treatment incur half the costs of those completing
treatment [13]. All costs are reported in 2004 US dollars.
Health State Utilities
For calculation of QALYs, we use a utility weight of 0.58 for
active TB, based on a WHO study [37]. Other health states are
assigned a weight of 0.85, based on age-specific health state
values of Peruvian adults weighted by the current age
distribution [38,39].
Cost-Effectiveness Analysis
Future costs and health outcomes are discounted to
present value at an annual rate of 3% [40,41]. Strategies are
ranked in order of increasing cost, and any strategy that is
more costly and less beneficial than another strategy is
considered dominated. The incremental cost-effectiveness
ratio for each remaining strategy is calculated by dividing the
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Cost-Effectiveness of MDR TB Treatment
(DALY) averted may be considered good value [42]. (One
DALY averted is analogous to one QALY gained.) This
benchmark is endorsed by WHO [43]. In our evaluation, we
considered an incremental cost per QALY that was less than
the per capita GDP to be highly cost-effective, and we
considered three times the per capita GDP to be a threshold
beyond which an intervention would be considered too
expensive. The per capita GDP in Peru is $2,360 [24].
Table 1. Natural History Assumptions
Description
Valuea
Source
Contacts per infectious case
per year leading to infectionb
Relative fitness of MDR strain
for transmission
Proportion developing TB soon
after infection
Annual rate of progression from
latent infection to active TB
Partial immunity to reinfection
if latent or cured
Annual mortality rate for
untreated TB
Annual mortality rate from
non-TB causes
Spontaneous cure rate
Probability of acquiring MDR
given dropout or failure from a
single round of treatment
6.5
[19]
1
[14]
8%
[17–20]
0.0009
[20,21]
61%
[20,22]
0.3
[21]
0.015
[24]c
0.2
0.4
[23]
Text S1d
Sensitivity Analyses
Because there is variation in and uncertainty about the
effectiveness and cost of MDR TB treatment, we performed
several sensitivity analyses to determine the stability of our
base case findings. Parameter values for these analyses are
reported in Table S4. The MDR TB cure probabilities
associated with each regimen were varied, with probabilities
of other treatment outcomes adjusted proportionately. We
also explored the sensitivity of our results to uncertainty in
regimen cost. To characterize the tradeoffs between STR2
and ITR1, we simultaneously varied the differential MDR TB
cure probability and the differential cost between standardized and individualized regimens.
The underlying biology and epidemiological characteristics
of MDR TB are also uncertain. In sensitivity analyses we
considered alternative assumptions about TB transmission
and progression, including an assumption that MDR TB
strains are only half as transmissible as non-MDR strains. We
also considered alternative settings that differ from Peru in
terms of the magnitude of the overall TB epidemic in the
population, the fraction of prevalent TB cases that are MDR,
and the efficacy of case-finding.
We performed another sensitivity analysis that excluded
reductions in transmission associated with successful treatment of TB or MDR TB in order to distinguish the direct
benefit of treatment to patients from the indirect benefit to
the community through transmission reduction. In this
analysis, both the incidence of infection and the fraction of
a
All annual rates were assumed to be constant and were converted to monthly transition
probabilities using the exponential model.
Persons with active disease were considered infectious. Persons in treatment who died
or defaulted uncured were also considered infectious for the time they were in treatment.
Only infections capable of leading to smear-positive disease are reflected in this
parameter.
c
Currently, life expectancy at birth is approximately 70 y in Peru [24]. The mortality rate
was calculated to be approximately one divided by life expectancy.
d
This parameter value was selected so that, in combination with other parameter values,
the model yielded outputs consistent with observed epidemiological data from Peru (see
Text S1).
DOI: 10.1371/journal.pmed.0030241.t001
b
additional cost compared to the next most costly strategy by
the additional benefit (QALYs gained or TB deaths averted).
The Commission on Macroeconomics and Health suggests
that interventions costing less than three times the gross
domestic product (GDP) per disability-adjusted life year
Table 2. TB Treatment Outcome Parameters
Type of Case
New cases
Previously treated cases
Strategy
Non-MDR
MDR
Percent
Fail
Percent
Dead
Percent
Default
Percent
Cure
DOTS
STR1
STR2
ITR1
ITR2
3
3
3
3
3
6
6
6
6
6
88
88
88
88
88
3
3
3
3
3
DOTS
STR1
STR2
ITR1
ITR2
5
5
5
5
5
6
6
6
6
6
68
68
68
68
68
21
21
21
21
21
Type
Primary
Acquired
Primary
Acquired
Percent
Dead
Percent
Default
Percent
Cure
Percent
Fail
10
10
10
10
6
NAb
13
10
10
8
12
8
8
8
8
8
8
NA
11
12
12
9
10
9
58a
58a
58a
58a
75a
NA
35a
63a
63a
70a
60a
70a
24
24
24
24
11
NA
41
15
15
11
18
11
Derived from [3–7,13,26–33] (see text). Regimen outcome probabilities were converted to corresponding rates adjusting for treatment regimen duration (6 mo for first-line drug regimens,
18 mo for standardized second-line drug regimens, and 24 mo for individualized second-line drug regimens). These rates were then converted to monthly transition probabilities.
a
In one sensitivity analysis, the cure probabilities of first-line drugs against MDR were reduced by 20%. In another sensitivity analysis, the cure probabilities of second-line drugs against
MDR were reduced by 20%.
b
Of new cases, none entered treatment with acquired MDR TB (by definition).
NA, not applicable.
DOI: 10.1371/journal.pmed.0030241.t002
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Table 3. Treatment Costs
Description
Base Case
Sensitivity
Analysis
Peru Ministry
of Health [34]a
Partners In
Health (Peru)
Suarez et al. [13]
One
One
One
One
One
$350
$530
$150
$4,400c
$6,100c
$60
$100
—
$1,000–$4,400
$2,000–$10,000
$58
$98
—
$1,200
—
—
—
$50–$150b
$2,700d
$3,200–$4,000d,e
$350
$530
—
$2,600
—
round of first-line treatment
round of first-line retreatment
drug susceptibility test
round of standardized second-line treatment (18 mo)
round of individualized second-line treatment (18–24 mo)
Reported in 2004 US dollars.
a
Includes drugs, supplies, laboratory costs, and personnel.
b
Low estimate assumes local laboratory and staff; high estimate assumes testing performed remotely (e.g., supranational laboratory).
c
Base case regimen costs calculated by combining the averaged drug cost estimates from Partners In Health with the non-drug costs reported for the cohort in Suarez et al. [13]. Non-drug
costs for the Suarez et al. [13] cohort averaged approximately $1,700. In the base case, the non-drug non-DST costs for individualized regimens were assumed to be 25% higher than for
standardized regimens (i.e., $2,100), because individualized regimens are administered for approximately 6 mo longer than standardized regimens [7].
d
Includes drug costs only. Itemization shown in Table S5.
e
Low value represents an 18-mo individualized regimen; high value represents a 24-mo regimen.
DOI: 10.1371/journal.pmed.0030241.t003
QALY ($8,700 per averted death) compared to the DOTS
strategy. The strategy incorporating comprehensive DST for
previously treated cases and individualized second-line treatment for MDR TB (ITR1) saved an additonal 12 QALYs (0.9
deaths) per 100,000 persons compared to STR2, at an
incremental cost of $990 per QALY gained ($12,000 per
averted death). A more aggressive strategy that extended DST
to new TB cases as well (ITR2) saved an additional 16 QALYs
(1.2 deaths) compared to ITR1, for an incremental costeffectiveness of $11,000 per QALY ($160,000 per averted
death). Figure S2 shows the efficiency frontier for the base
case strategies.
In Peru, with a population of 27 million, DOTS-Plus with
standardized regimens (STR2) would avert 2,010 (undiscounted) deaths and individualized regimens (ITR1) would
avert 2,400 deaths as compared to DOTS alone over a 30-y
period at an (undiscounted) cost of $17 million and $21
million dollars, respectively.
primary MDR TB among new cases were held constant during
the intervention period.
Lastly, we considered a multivariable ‘‘worst-case scenario’’
in which several parameter values were biased against secondline treatment strategies: the cost of first-line regimens were
reduced to $60 for new cases and $100 for retreatment, the
effectiveness of second-line regimens against MDR TB was
20% lower, the relative transmissibility (fitness) of MDR TB
was 50%, and the time horizon was only 10 y.
Results
Base Case
The discounted costs, discounted benefits, and incremental
cost-effectiveness ratios for the alternative strategies are
shown in Table 4. Incidence trends are reported in Figure S1.
Over the 30-y time horizon, both standardized treatment
strategies (STR1 and STR2) averted 4.8 deaths and gained 59
QALYs per 100,000 persons compared to the DOTS strategy.
STR2, which utilized a test for MDR TB to screen out false
positives, provided this incremental benefit at lower cost than
STR1, and had an incremental cost-effectiveness of $720 per
Sensitivity Analyses
Table 5 reports the results of several sensitivity analyses.
Additional sensitivity analysis results are presented in Table
Table 4. Incremental Cost-Effectiveness of Second-Line Treatment Strategies for MDR TB: Base Case Results for Peru
Strategya
DOTS
STR1f
STR2g
ITR1
ITR2
Costb
$185,970
$272,340
$228,123
$239,755
$423,554
QALYsc
2,019,813
2,019,872
2,019,872
2,019,884
2,019,900
TB Deathsd
307.3
302.5
302.5
301.6
300.4
Incremental Cost per QALYe
Incremental Cost per Averted Deathe
—
Dominated
$720
$990
$11,000
—
Dominated
$8,700
$12,000
$160,000
a
DOTS is directly observed therapy with first-line drugs, followed by retreatment of failures with first-line drugs; STR1 is locally standardized second-line drug regimen for previously
treated cases; STR2 is locally standardized second-line drug regimen for previously treated cases test-confirmed to have MDR TB; ITR1 is comprehensive DST and individualized treatment
for previously treated cases; and ITR2 is immediate DST and individualized treatment.
b
US dollars, discounted at 3% annually over a 30-y horizon in a population of 100,000.
c
QALYs, discounted at 3% annually over a 30-y horizon in a population of 100,000.
d
TB deaths, discounted at 3% annually over a 30-y horizon in a population of 100,000.
e
Incremental cost-effectiveness ratios are computed relative to the next best non-dominated strategy. (Thus, STR2 is compared to DOTS, ITR1 is compared to STR2, and ITR2 is compared
to ITR1).
f
The STR1 strategy is dominated because it is more costly and confers less benefit than STR2. It has an incremental cost of $1,500 per QALY and $18,000 per averted death as compared to
DOTS.
g
Incremental costs and effectiveness are computed relative to DOTS because STR1 is dominated.
DOI: 10.1371/journal.pmed.0030241.t004
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TB. This figure is consistent with the outcome of a large
retrospective study of laboratory results in Peru that found
that 57% of previously treated patients reentering treatment
had MDR TB [44].
DOTS-Plus programs that use standardized regimens
typically do not use DST to determine each patient’s
resistance profile [26,27,45], but in a South African DOTSPlus program, patients suspected of having MDR TB are
tested for first-line drug resistance before standardized
second-line regimens are administered [46]. Although the
STR2 strategy, which mimics the South African program, is
an efficient strategy, we found that ITR1 conferred additional
benefit at an incremental cost of $990 per QALY, which is still
well below the per capita GDP of Peru. In Peru, the difference
in MDR TB cure probability between individualized and
standardized regimens must be less than 2%, and standardized regimens must be $3,200 less expensive, in order for
the incremental cost-effectiveness ratio of ITR1 to be
considered beyond the threshold of three times the GDP
($7,080).
The finding that individualized second-line treatment of
previously treated cases (ITR1) is highly cost-effective was
stable over a wide range of assumptions. The incremental cost
per QALY gained for ITR1 remained under $1,900 in all oneway sensitivity analyses. When considering a situation in
which several one-way sensitivity analyses were combined
into a ‘‘worst-case scenario’’ over a 10-y time horizon with
several parameter values simultaneously biased against
second-line treatment strategies, STR2 is dominated, but
ITR1 still appears quite favorable at $6,400 per QALY as
compared to DOTS alone. The incremental cost-effectiveness
ratio of the more aggressive individualized treatment strategy
(ITR2) compared to ITR1 exceeded the threshold of three
times the per capita GDP in the base case, but appeared more
favorable when the fraction of MDR TB among prevalent TB
cases was higher, and also under the plausible assumption
that the cure probability for first-line therapy against MDR
TB is 20% lower than assumed in the base case.
Interrupting transmission is a critical component of the
overall benefit of treatment. When these community-level
benefits were excluded, costs per QALY or per averted death
by STR2 and ITR1 approximately doubled. Nonetheless,
individualized treatment with second-line drugs remained
cost-effective by international standards even without accounting for transmission benefits.
A key uncertainty in our model is the relative fitness of
MDR TB strains for transmission. Recent models [15,16]
indicate that over very long time horizons, heterogeneous
fitness among MDR strains will lead to the eventual
dominance of MDR TB as long as some fraction of MDR
strains are as fit as drug-sensitive strains. We assumed that
MDR TB was equally transmissible as drug-susceptible TB in
our base case, but considered the possibility that it is up to
50% less transmissible. When MDR TB fitness was reduced,
DOTS-Plus strategies became somewhat less cost-effective,
but remained attractive.
We assumed that second-line therapies were no more
effective than DOTS in TB patients without MDR TB. This
assumption may underestimate the benefits of DOTS-Plus
strategies if second-line drugs confer additional benefits in
patients with non-MDR drug resistance.
The analysis reflects the perspective of a public health-care
S6. When outcomes are measured over a 30-y time horizon,
the incremental cost-effectiveness of both STR2 and ITR1
remains under $1,900 in all one-way sensitivity analyses. In
the worst-case scenario, STR2 is dominated and the costeffectiveness of ITR1 is $6,400 per QALY compared to DOTS.
Among the non-dominated strategies (DOTS, STR2, ITR1,
and ITR2), ITR1 would be selected for Peru using three times
the per capita GDP as a threshold for cost-effectiveness.
Although the relative performance of ITR1 compared to
STR2 was sensitive to assumptions about the MDR TB cure
probability and cost of each regimen, the ITR1 remained the
optimal choice within plausible ranges for these parameters.
If cure probabilities are 7% lower in standardized compared
to individualized regimens (as in our base case), the difference in cost between standardized and individualized
regimens would have to exceed $9,500 in order for STR2 to
be the preferred strategy. If cure probabilities for standardized regimens are just 2% lower than those for individualized regimens, STR2 would be preferred to ITR1 if the
difference in regimen costs exceeded $3,200.
The incremental cost-effectiveness of the ITR2 strategy
compared to ITR1 improves significantly when first-line
drugs are less effective against MDR TB and when the
fraction of MDR TB cases among all cases is increased to 10%.
Discussion
Our cost-effectiveness analysis of treatment strategies
provides evidence that DOTS-Plus strategies are likely to be
cost-effective in lower-middle-income settings with at least
1% MDR TB. Over a wide range of assumptions, a strategy of
testing previously treated patients for MDR TB and then
treating them with second-line regimens was found to be
cost-effective compared to first-line DOTS alone. In our base
case for Peru, we estimate that STR2 would avert 4.8 deaths
per 100,000 persons over 30 y, at an incremental cost of $720
per QALY compared to DOTS. A policy of comprehensive
DST and individualized treatment for first-line failures
(ITR1), the best performing strategy under the cost-effectiveness threshold of the per capita GDP, averted 0.9 additional
deaths per 100,000 at an incremental cost of $990 per QALY
compared to STR2. A clinical strategy that begins with
comprehensive DST for all cases upon diagnosis of TB may be
cost-effective in settings with high levels of MDR or where
first-line drugs perform especially poorly against MDR TB.
The base case incremental cost per QALY gained with this
strategy (ITR2 compared to ITR1) was $11,000, but when the
prevalence of MDR TB among prevalent TB cases was 10%,
the cost per QALY gained for ITR2 dropped to $6,400.
Poorer performance of first-line drugs against MDR TB
increases the potential gains from immediate diagnosis and
treatment of MDR TB. When the effectiveness of a first-line
regimen was dropped 20% from the base case assumptions,
the ITR2 strategy had a cost per QALY of $5,500.
In our analysis, DOTS-Plus based on standardized secondline regimens administered to previously treated patients
presumed to have MDR TB (STR1) was consistently dominated because it provided the same benefit as STR2 at a
higher overall cost. This result is largely due to the costs of
treating non-MDR cases unnecessarily with second-line
therapy. In the base case calibration of our model, on average
54% of cases entering a second round of treatment had MDR
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Cost-Effectiveness of MDR TB Treatment
Table 5. Sensitivity Analyses
Scenario
Strategy Total Cost Total QALYs Total TB Deaths Incremental Cost Incremental Cost
per QALYa
per Averted Deatha
Base case
DOTS
STR1
STR2
ITR1
ITR2
DOTS
$185,970
$272,340
$228,124
$239,755
$423,554
$388,907
2,019,813
2,019,872
2,019,872
2,019,884
2,019,900
2,017,400
307.3
302.5
302.5
301.6
300.4
528.3
—
$1,467
$716
$987
$11,439
—
—
$17,871
$8,722
$12,441
$160,100
—
STR1
STR2
ITR1
ITR2
DOTS
$582,805
$493,658
$523,386
$988,490
$31,987
2,017,461
2,017,461
2,017,477
2,017,520
2,019,813
522.6
522.6
521.2
517.3
307.3
$3,172
$1,714
$1,934
$10,837
—
$33,937
$18,334
$20,703
$118,855
—
STR1
STR2
ITR1
ITR2
DOTS
$129,343
$80,127
$92,005
$279,944
$185,970
2,019,872
2,019,872
2,019,884
2,019,900
2,019,813
302.5
302.5
301.6
300.4
307.3
$1,654
$818
$1,008
$11,696
—
$20,144
$9,961
$12,704
$163,707
—
STR1
STR2
ITR1
ITR2
DOTS
$275,974
$237,040
$252,614
$464,757
$189,926
2,019,848
2,019,847
2,019,857
2,019,863
2,019,756
304.6
304.6
303.8
303.4
312.4
$2,580
$1,521
$1,541
$33,576
—
$32,445
$18,815
$19,635
$506,135
—
STR1
STR2
ITR1
ITR2
DOTS
$280,753
$236,567
$249,202
$423,554
$182,292
2,019,854
2,019,854
2,019,868
2,019,900
2,019,880
303.9
303.9
302.7
300.4
302.3
$929
$477
$880
$5,541
—
$10,727
$5,509
$10,883
$75,603
—
STR1
STR2
ITR1
ITR2
DOTS
$267,203
$221,610
$232,926
$391,215
$95,483
2,019,919
2,019,919
2,019,928
2,019,936
788,537
299.3
299.3
298.6
298.1
218.5
$2,160
$1,000
$1,277
$19,602
—
$28,199
$13,058
$16,923
$295,373
—
STR1
STR2
ITR1
ITR2
DOTS
STR1
STR2
ITR1
ITR2
DOTS
$140,209
$117,629
$123,528
$219,263
$176,787
$254,530
$215,011
$225,533
$401,431
$181,830
788,546
788,546
788,547
788,551
2,018,546
2,018,604
2,018,604
2,018,615
2,018,631
2,019,900
216.5
216.5
216
215.4
400
395.2
395.2
394.2
393.1
300.9
$5,513
$2,730
$3,422
$28,907
—
$1,347
$662
$923
$11,227
—
$21,969
$10,878
$13,762
$145,544
—
$16,022
$7,878
$11,349
$153,716
—
STR1
STR2
ITR1
ITR2
DOTS
$253,467
$193,476
$197,258
$345,409
$192,575
2,019,917
2,019,915
2,019,918
2,019,922
2,019,660
299.6
299.6
299.4
299.1
318.2
$4,201
$768
$1,247
$34,757
—
$53,826
$9,345
$15,700
$482,668
—
STR1
STR2
ITR1
ITR2
DOTS
$288,813
$283,499
$307,707
$545,062
$360,272
2,019,790
2,019,790
2,019,816
2,019,850
2,011,862
307.6
307.6
305.6
303.2
824.9
$743
$703
$934
$6,937
—
$9,103
$8,609
$11,838
$98,924
—
STR1
STR2
ITR1
ITR2
$520,650
$442,006
$464,032
$847,376
2,011,992
2,011,992
2,012,017
2,012,056
813.3
813.3
811.1
808.1
$1,237
$631
$884
$9,855
$13,753
$7,009
$10,305
$125,534
Treatment does not reduce transmission
(constant exogenous TB incidence rate)
First-line regimen costs reduced to $60 for
new cases, $100 for retreatment
Effectiveness of second-line regimen against
MDR TB reduced by 20%b
Effectiveness of first-line regimen against MDR
TB reduced by 20%
Relative fitness (transmissibility) of MDR TB
reduced to 50%
Time horizon reduced to 10 y (QALYs from
averted deaths that accrue beyond 10 y are ignored)
Case detection rate reduced to 50% per year
MDR TB represents 1% of all TB cases (probability
of acquiring MDR TB reduced)
MDR TB represents 10% of all TB cases
(probability of acquiring MDR TB increased)
Overall burden of smear-positive TB doubled
to 238 per 100,000
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Cost-Effectiveness of MDR TB Treatment
Table 5. Continued
Outcome
Strategy
Total Cost
Total QALYs
Total TB Deaths
Incremental Cost
per QALYa
Incremental Cost
per Averted Deatha
Worst-case scenarioc
DOTS
STR1
STR2
ITR1
ITR2
$16,267
$65,618
$42,913
$50,219
$139,820
788,550
788,555
788,554
788,555
788,556
215.9
214.9
215
214.7
214.5
—
$11,320
$6,772
$6,442
$91,431
—
$52,192
$30,505
$28,866
$571,776
Incremental cost-effectiveness ratios in bold fall below the threshold for Peru. Incremental cost-effectiveness ratios that are struck through are dominated.
Incremental cost-effectiveness ratios are computed relative to the next-best non-dominated strategy. (Thus, when STR1 is dominated, ITR2 is compared to DOTS.)
b
Cure probability for first-line drugs reduced from 58% to 46% among new MDR TB cases and from 35% to 28% among previously treated MDR TB cases.
c
First-line regimen costs $60 for new cases and $100 for retreatment, effectiveness of second-line regimen against MDR TB reduced by 20%, relative fitness of MDR TB reduced to 50%,
and time horizon reduced to 10 y.
DOI: 10.1371/journal.pmed.0030241.t005
a
system and includes the costs of medical care only. An
analysis from the societal perspective would need to
incorporate costs for patient time, transportation, and
unpaid caregiver time, but such data were not available and
would be unlikely to alter the conclusions.
An analysis by Sterling et al. [12] found that a DOTS-Plus
strategy using DST and second-line drugs over a 10-y time
period had an incremental cost-effectiveness ratio of $68,860
per averted death compared to a DOTS strategy using firstline drugs only, suggesting that it would be relatively
expensive for low- to middle-income countries. However,
the study used estimates of the effectiveness of second-line
therapy that are lower than current data suggest [7,13,26–
30,33] and assumed that TB incidence and the fraction of
MDR TB among new cases would not decline in response to
treatment.
Suarez et al. [13] found that the use of second-line drugs in
patients failing other therapies had an incremental costeffectiveness ratio of about $200–$700 per DALY averted
(year 2000 US dollars). Our dynamic transmission modeling
results corroborate the finding of Suarez et al. [13] that
second-line therapy for MDR TB patients is highly costeffective in Peru.
Like Sterling et al. [12] and Suarez et al. [13], our study
suggests that DOTS-Plus is both more effective and more
costly than DOTS. Therefore, if DOTS has not been fully
implemented and can be expanded within the available
infrastructure, it would be more efficient to expand DOTS
coverage than to initiate DOTS-Plus. Similarly, an implementation of DOTS-Plus that uses non-surplus resources
from an existing DOTS program would also be inefficient.
Nevertheless, our results also show that fully implementing
DOTS and initiating DOTS-Plus would be a reasonable use of
resources in many settings.
We quantified the marginal gains of relatively more
aggressive strategies to control MDR TB and found that the
relatively high cost of second-line therapy (as compared to
first-line therapy) should not be perceived as a barrier to
implementation of DOTS-Plus programs. We did not account
for start-up costs (e.g., laboratory capacity) required for DST.
However, in lower-middle-income countries such as Peru,
with about 2,900 MDR TB cases each year [47], even if a lump
sum of $5.5 million for start-up costs were added in the first
time period to the costs of ITR1, that strategy would still have
a cost per QALY less than the per capita GDP.
PLoS Medicine | www.plosmedicine.org
We found that standardized regimens could be costeffective when a test for MDR TB is used before enrolling
previously treated patients into second-line therapy, suggesting the possible utility of an inexpensive rapid test for MDR
such as the Greiss method [48]. We also found that
comprehensive DST for previously treated patients followed
by individualized treatment for MDR TB cases will likely be
cost-effective in a variety of settings, even in countries with
severely constrained resources. Furthermore, immediate DST
for all detected TB cases and individualized second-line
treatment for MDR TB may be cost-effective in middleincome countries with high levels of MDR TB.
The feasibility of delivering effective individualized TB
care has been demonstrated in Peru and other countries. Our
study finds that the strategy of testing previously treated cases
with DST and treating MDR TB with individualized regimens
would be cost-effective in Peru under a wide range of
alternative assumptions about treatment costs, effectiveness,
MDR TB prevalence, and transmission, including a range of
assumptions regarding the relative performance of a similar
strategy based on standardized regimens. Our study contributes to a growing body of evidence that indicates that
national TB programs and nongovernmental organizations
should move quickly to implement DOTS-Plus in settings
where multiple drug resistance is prevalent.
Supporting Information
Figure S1. Incidence Trends
Annual non-MDR and MDR TB incidence per 100,000 persons under
the four non-dominated TB control strategies in the base case. MDR
TB is initially generated during the substandard treatment era that
precedes the 30-y intervention era. MDR TB incidence initially
declines under all four control strategies, but when only first-line
treatment is available, the decline reverses after a few years.
Found at DOI: 10.1371/journal.pmed.0030241.sg001 (10.1 MB TIF).
Figure S2. Efficiency Frontier for MDR TB Control Strategies
In the base case, in order of increasing effectiveness and cost, DOTS,
STR2, ITR1, and ITR2 lie along the efficiency frontier. STR1 is
dominated because it costs more than STR2 and provides no more
benefit.
Found at DOI: 10.1371/journal.pmed.0030241.sg002 (460 KB JPG).
Table S1. Treatment Outcome Parameters for Substandard Treatment Era
Found at DOI: 10.1371/journal.pmed.0030241.st001 (32 KB DOC).
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Table S2. Description of Model States
Found at DOI: 10.1371/journal.pmed.0030241.st002 (63 KB DOC).
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Table S3. Description of Model Parameters
Found at DOI: 10.1371/journal.pmed.0030241.st003 (139 KB DOC).
Table S4. Calibration to Peru and Parameters Used in Sensitivity
Analysis
Found at DOI: 10.1371/journal.pmed.0030241.st004 (57 KB DOC).
Table S5. Itemized Cost Calculations for Regimens Using SecondLine Drugs
Found at DOI: 10.1371/journal.pmed.0030241.st005 (91 KB DOC).
Table S6. Sensitivity Analyses (Extended Version of Table 5)
Found at DOI: 10.1371/journal.pmed.0030241.st006 (191 KB DOC).
Text S1. Appendix
Found at DOI: 10.1371/journal.pmed.0030241.sd001 (1.2 MB DOC).
Acknowledgments
We gratefully acknowledge guidance, encouragement, and helpful
comments from Drs. Mercedes Becerra, Carole Mitnick, Howard
Hiatt, Edward Nardell, and Sonya Shin.
Author contributions. SCR, JAS, MM, and MCW designed the study.
JAS, MM, and MCW provided study supervision. SCR and MM
acquired data. SCR, JAS, MM, and MCW analyzed the data and
provided statistical expertise. MCW provided administrative, technical, and material support. SCR and MCW drafted the manuscript.
SCR, JAS, MM, and MCW critically revised the manuscript for
important intellectual content.
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Editors’ Summary
patients were given a personalized regimen of second-line drugs. The
fifth strategy, ITR2, tested all patients for drug susceptibility at the outset
of treatment, and those with MDR TB were given an individualized
course; those not cured were tested again and given another
individualized course.
Compared with DOTS, both the STR1 and STR2 strategies averted
4.8 deaths per 100,000 population, at a cost of $8,700 per averted
death—with STR2 being a better value for money since it treated only
confirmed MDR TB cases with the more expensive, second-line drugs. Of
the individualized treatments, ITR1 averted an extra 0.9 deaths at a cost
of $12,000 per averted death; ITR2 averted a further 1.2 deaths but at a
much higher $160,000 per saved life.
Background. Tuberculosis (TB) remains one of the most entrenched
diseases on the planet—an estimated one in three people worldwide are
infected with Mycobacterium tuberculosis, which causes the disease.
Although effective drugs exist, a major reason for the failure to stem the
spread of TB lies in the rise of drug-resistant strains of the bacterium.
Some strains are resistant to several drugs; patients with this sort of
infection are said to have multidrug-resistant (MDR) TB. The development of drug-resistant strains is fostered when health-care workers do
not follow treatment guidelines or fail to ensure that patients take the
whole treatment course. The World Health Organization recommends an
approach to TB control called ‘‘DOTS,’’ which has been adopted by many
countries. (See the link below for an explanation of what DOTS involves.)
The antibiotics that are used in DOTS are described as ‘‘first-line’’
treatment drugs. They are highly effective against non-resistant TB but
much less so against MDR TB. There are other, more expensive, ‘‘secondline’’ antibiotics that perform better against MDR TB.
What Do These Findings Mean? Despite the slightly higher cost of ITR1,
the extra number of lives it would save compared with STR2 makes it a
good approach for treatment in Peru. However, cost-effectiveness varies
with other factors. If the difference in cost between the two strategies
became higher than $9,500 per patient, STR would be preferable. And, if
MDR TB were present in 10% of all TB cases, ITR2—with comprehensive
drug susceptibility testing for all TB patients—would be best.
The findings are of interest not just in Peru but in other developing
countries where MDR TB is a growing problem. The researchers maintain
that, in areas where DOTS has not yet been fully implemented, it would
be more efficient to expand DOTS than to introduce DOTS-Plus. But they
add that it would be beneficial to expand DOTS as well as implement
DOTS-Plus. Individualized treatment after drug susceptibility testing is
likely to be cost-effective even in the poorest of countries, which should
give impetus to governments and organizations in those countries where
MDR TB is a growing concern to modify their approach to treatment.
Why Was This Study Done? Despite the worrying rise in MDR TB cases,
the much higher cost of using second-line drugs is prompting some
policy-makers to question the merits of introducing them in poor
countries with limited resources. However, with MDR TB accounting for
nearly a third of TB cases in some countries, first-line therapies seem
unlikely to be sufficient in the long term. Second-line strategies, or
‘‘DOTS-Plus’’ strategies, are either standardized for a particular region or
are chosen for individual patients on the basis of drug susceptibility
tests. The researchers wanted to investigate whether standardized or
individualized second-line regimens could save lives and be costeffective in poor countries.
What Did the Researchers Do and Find? The researchers used a
method called modeling. They took information already available about
TB in Peru, where for every 100,000 people there are 120 new TB
infections every year, and 4.5% of existing cases are MDR TB. The
researchers then calculated what might happen over the next 30 years,
comparing the likely effects of five alternative strategies. In four, new
cases were given first-line drugs for 6 months. Those who were not cured
were then treated in different ways. In DOTS, they were retreated with a
second course of the same drugs; in STR1 they were given an 18-month
standardized course of second-line and first-line drugs; in STR2, only
confirmed MDR TB patients were given an 18-month standardized
course of second-line and first-line drugs; and in ITR1, confirmed MDR TB
PLoS Medicine | www.plosmedicine.org
Additional Information. Please access these Web sites via the online
version of this summary at http://dx.doi.org/10.1371/journal.pmed.
0030241.
Basic information about tuberculosis can be found on the Web site of
the US National Institute of Allergy and Infectious Diseases
The Web site of the World Health Organization’s Stop TB department
outlines both the DOTS and DOTS-Plus strategies
TB Alert, a UK-based charity that promotes TB awareness worldwide,
has information on TB in several European, African, and Asian
languages
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July 2006 | Volume 3 | Issue 7 | e241