Trade-offs between cost and accuracy in active case finding for tuberculosis: A dynamic modelling analysis.
Antitubercular Agents
/ economics
Cost-Benefit Analysis
Diagnostic Screening Programs
/ economics
Drug Costs
Drug Resistance, Bacterial
Health Care Costs
Humans
India
Microbial Sensitivity Tests
/ economics
Microscopy
/ economics
Models, Economic
Molecular Diagnostic Techniques
/ economics
Predictive Value of Tests
Reproducibility of Results
Time Factors
Tuberculosis
/ diagnosis
Journal
PLoS medicine
ISSN: 1549-1676
Titre abrégé: PLoS Med
Pays: United States
ID NLM: 101231360
Informations de publication
Date de publication:
12 2020
12 2020
Historique:
received:
12
09
2019
accepted:
02
11
2020
entrez:
2
12
2020
pubmed:
3
12
2020
medline:
2
2
2021
Statut:
epublish
Résumé
Active case finding (ACF) may be valuable in tuberculosis (TB) control, but questions remain about its optimum implementation in different settings. For example, smear microscopy misses up to half of TB cases, yet is cheap and detects the most infectious TB cases. What, then, is the incremental value of using more sensitive and specific, yet more costly, tests such as Xpert MTB/RIF in ACF in a high-burden setting? We constructed a dynamic transmission model of TB, calibrated to be consistent with an urban slum population in India. We applied this model to compare the potential cost and impact of 2 hypothetical approaches following initial symptom screening: (i) 'moderate accuracy' testing employing a microscopy-like test (i.e., lower cost but also lower accuracy) for bacteriological confirmation and (ii) 'high accuracy' testing employing an Xpert-like test (higher cost but also higher accuracy, while also detecting rifampicin resistance). Results suggest that ACF using a moderate-accuracy test could in fact cost more overall than using a high-accuracy test. Under an illustrative budget of US$20 million in a slum population of 2 million, high-accuracy testing would avert 1.14 (95% credible interval 0.75-1.99, with p = 0.28) cases relative to each case averted by moderate-accuracy testing. Test specificity is a key driver: High-accuracy testing would be significantly more impactful at the 5% significance level, as long as the high-accuracy test has specificity at least 3 percentage points greater than the moderate-accuracy test. Additional factors promoting the impact of high-accuracy testing are that (i) its ability to detect rifampicin resistance can lead to long-term cost savings in second-line treatment and (ii) its higher sensitivity contributes to the overall cases averted by ACF. Amongst the limitations of this study, our cost model has a narrow focus on the commodity costs of testing and treatment; our estimates should not be taken as indicative of the overall cost of ACF. There remains uncertainty about the true specificity of tests such as smear and Xpert-like tests in ACF, relating to the accuracy of the reference standard under such conditions. Our results suggest that cheaper diagnostics do not necessarily translate to less costly ACF, as any savings from the test cost can be strongly outweighed by factors including false-positive TB treatment, reduced sensitivity, and foregone savings in second-line treatment. In resource-limited settings, it is therefore important to take all of these factors into account when designing cost-effective strategies for ACF.
Sections du résumé
BACKGROUND
Active case finding (ACF) may be valuable in tuberculosis (TB) control, but questions remain about its optimum implementation in different settings. For example, smear microscopy misses up to half of TB cases, yet is cheap and detects the most infectious TB cases. What, then, is the incremental value of using more sensitive and specific, yet more costly, tests such as Xpert MTB/RIF in ACF in a high-burden setting?
METHODS AND FINDINGS
We constructed a dynamic transmission model of TB, calibrated to be consistent with an urban slum population in India. We applied this model to compare the potential cost and impact of 2 hypothetical approaches following initial symptom screening: (i) 'moderate accuracy' testing employing a microscopy-like test (i.e., lower cost but also lower accuracy) for bacteriological confirmation and (ii) 'high accuracy' testing employing an Xpert-like test (higher cost but also higher accuracy, while also detecting rifampicin resistance). Results suggest that ACF using a moderate-accuracy test could in fact cost more overall than using a high-accuracy test. Under an illustrative budget of US$20 million in a slum population of 2 million, high-accuracy testing would avert 1.14 (95% credible interval 0.75-1.99, with p = 0.28) cases relative to each case averted by moderate-accuracy testing. Test specificity is a key driver: High-accuracy testing would be significantly more impactful at the 5% significance level, as long as the high-accuracy test has specificity at least 3 percentage points greater than the moderate-accuracy test. Additional factors promoting the impact of high-accuracy testing are that (i) its ability to detect rifampicin resistance can lead to long-term cost savings in second-line treatment and (ii) its higher sensitivity contributes to the overall cases averted by ACF. Amongst the limitations of this study, our cost model has a narrow focus on the commodity costs of testing and treatment; our estimates should not be taken as indicative of the overall cost of ACF. There remains uncertainty about the true specificity of tests such as smear and Xpert-like tests in ACF, relating to the accuracy of the reference standard under such conditions.
CONCLUSIONS
Our results suggest that cheaper diagnostics do not necessarily translate to less costly ACF, as any savings from the test cost can be strongly outweighed by factors including false-positive TB treatment, reduced sensitivity, and foregone savings in second-line treatment. In resource-limited settings, it is therefore important to take all of these factors into account when designing cost-effective strategies for ACF.
Identifiants
pubmed: 33264288
doi: 10.1371/journal.pmed.1003456
pii: PMEDICINE-D-19-03327
pmc: PMC7710036
doi:
Substances chimiques
Antitubercular Agents
0
Types de publication
Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1003456Subventions
Organisme : Medical Research Council
ID : MR/R008345/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R015600/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : 1645544
Pays : United Kingdom
Déclaration de conflit d'intérêts
The authors have declared that no competing interests exist.
Références
Bull World Health Organ. 2014 Feb 1;92(2):126-38
pubmed: 24623906
PLoS One. 2014 Feb 26;9(2):e89301
pubmed: 24586675
BMC Med. 2014 Oct 30;12:216
pubmed: 25358459
Glob Health Action. 2018;11(1):1477493
pubmed: 29902134
PLoS One. 2012;7(7):e38691
pubmed: 22792158
BMC Med. 2019 Aug 6;17(1):155
pubmed: 31382959
Public Health Action. 2019 Jun 21;9(2):58-62
pubmed: 31417854
PLoS One. 2015 Apr 23;10(4):e0124260
pubmed: 25905900
Pharmacoeconomics. 2015 Sep;33(9):939-55
pubmed: 25939501
PLoS One. 2015 May 21;10(5):e0126065
pubmed: 25996389
Eur Respir J. 2010 Mar;35(3):689-92
pubmed: 20190334
Cochrane Database Syst Rev. 2014 Jan 21;(1):CD009593
pubmed: 24448973
PLoS Med. 2016 Oct 25;13(10):e1002149
pubmed: 27780217
Epidemiol Infect. 2008 Oct;136(10):1342-9
pubmed: 18177518
N Engl J Med. 2010 Sep 9;363(11):1005-15
pubmed: 20825313
Lancet Glob Health. 2016 Nov;4(11):e816-e826
pubmed: 27720689
Clin Infect Dis. 2012 Mar;54(6):784-91
pubmed: 22267721
Eur Respir J. 2014 Jun;43(6):1763-75
pubmed: 24525439
J Clin Tuberc Other Mycobact Dis. 2018 Nov 12;13:22-27
pubmed: 31720408
Int J Tuberc Lung Dis. 2013 Apr;17(4):432-46
pubmed: 23485377
Int J Tuberc Lung Dis. 2013 Dec;17(12):1613-20
pubmed: 24200278
Indian J Tuberc. 2008 Jul;55(3):157-61
pubmed: 18807749
Lancet Infect Dis. 2016 Nov;16(11):1255-1260
pubmed: 27568356
PLoS One. 2017 Feb 2;12(2):e0171310
pubmed: 28152082
Lancet Glob Health. 2016 Nov;4(11):e806-e815
pubmed: 27720688
Trans R Soc Trop Med Hyg. 2020 Feb 7;114(3):185-192
pubmed: 31820812
BMC Public Health. 2019 Jan 22;19(1):99
pubmed: 30669990
PLoS One. 2013 Oct 16;8(10):e77517
pubmed: 24147015
Clin Infect Dis. 2008 Nov 1;47(9):1135-42
pubmed: 18823268
PLoS One. 2019 Jul 2;14(7):e0218890
pubmed: 31265470
BMC Infect Dis. 2014 Oct 19;14:532
pubmed: 25326816
PLoS One. 2019 Feb 22;14(2):e0212264
pubmed: 30794595
Semin Respir Infect. 1994 Jun;9(2):113-9
pubmed: 7973170
PLoS Med. 2011 Nov;8(11):e1001120
pubmed: 22087078
PLoS One. 2013;8(1):e51121
pubmed: 23349670
Lancet Infect Dis. 2018 Jan;18(1):76-84
pubmed: 29198911
Clin Infect Dis. 2019 Jan 1;68(1):150-156
pubmed: 29982375
PLoS One. 2019 Apr 1;14(4):e0214675
pubmed: 30933997
JAMA Netw Open. 2019 Feb 1;2(2):e187617
pubmed: 30735231
PLoS One. 2011 Apr 04;6(4):e17601
pubmed: 21483732
Indian J Med Res. 2013 Mar;137(3):442-4
pubmed: 23640550