| Literature DB >> 32461226 |
Philip Erick Wikman-Jorgensen1,2, Jara Llenas-Garcia3,4, Jad Shedrawy5, Joaquim Gascon6, Jose Muñoz6, Zeno Bisoffi7,8, Ana Requena-Mendez9,10.
Abstract
BACKGROUND: The best strategy for controlling morbidity due to imported strongyloidiasis in migrants is unclear. We evaluate the cost-effectiveness of six possible interventions.Entities:
Keywords: Strongyloides stercoralis infection; health economics; infections, diseases, disorders, injuries; public health; screening
Mesh:
Year: 2020 PMID: 32461226 PMCID: PMC7254101 DOI: 10.1136/bmjgh-2020-002321
Source DB: PubMed Journal: BMJ Glob Health ISSN: 2059-7908
Figure 1Compartmental Markov model for strongyloidiasis. No arrows to "death other cause" because patients from all states (except from death due to strongyloidiasis) can transition into this state; e1 is divided as patients that transition back from e2 cannot be treated or screened again; e4 is also divided as patients getting cured (ie, not infected) would not be tested or treated again.
Base-case scenario probabilities
| Probabilities | Value and OWSA range | PSA distribution | Source |
| Probability of seeking outpatient consultation | Baseline: 0.001 | Beta (mean 0.001, SE 0.001) | Valerio |
| Probability of being diagnosed and treated | Baseline: 0.92 | Beta (mean 0.92, SE 0.03) | Bissofi |
| Probability of clearing infection | Baseline: 0.84 | Beta (mean 0.84, SE 0.066) | Henriquez-Camacho |
| Probability of seeking inpatient consultation due to severe disease | Baseline: 0.000423 | Beta (mean 0.000423, SE 0.0001) | Salvador |
| Probability of being diagnosed and treated for severe disease | Baseline: 0.92 | Beta (mean 0.92, SE 0.03) | Bissofi |
| Probability of curing and clearing infection in severe disease | 1-CFR | CFR is estimated below | |
| Probability of dying due to severe disease (CFR) | Baseline: 0.47 | Beta (mean 0.47, SE 0.01) | Buonfrate |
| Probability of misdiagnosis and treatment for | Baseline: 0.001 | Beta (mean 0.001, SE 0.001) | Bissofi |
| Probability of death due to other causes | Mortality tables | Spanish National Statistical Institute |
CFR, case fatality ratio; OWSA, one-way sensitivity analysis; PSA, probabilistic sensitivity analysis.
Figure 2Cost-effectiveness plane representing the incremental costs in 2016 € Versus incremental effects in life-years gained (LYG). Hosp PresTr, hospital-based presumptive treatment; Hosp SerTr, hospital-based serology screening and treatment; HospPresTrImmuneSup, hospital-based presumptive treatment of immunosuppressed patients; HospSerTrImmuneSup, hospital-based serology screening and treatment of immunosuppressed patients; PC PresTr, presumptive treatment at a primary care setting; PCSerTr, serology screening and treatment at a primary care setting.
Summary of the analysis results
| LYG | Lifetime costs | Incremental LYG | Incremental cost | ICER | |
| Baseline | 2,486,708.24 | 3,238,393 | Baseline | Baseline | Baseline |
| HospSerTr | 2,488,024.33 | 207,734,073 | 1316.08 | 204 495 681 | Dominated |
| HospPresTr | 2,488,046.17 | 14,559,575 | 1337.92 | 11 321 182 | Dominated |
| HospSerTrIm | 2,488,073.8 | 4,274,239 | 1365.55 | 1 035 846 | Dominated |
| PCSerTr | 2,488,085.82 | 207,679,077 | 1377.57 | 204 440 684 | Dominated |
| HospPresTrIm | 2,488,093.93 | 1,105,483 | 1385.68 | −2,132,910* | −1,539* |
| PCPresTr | 2,488,095.47 | 8,194,563 | 1387.23 | 4 956 170 | 4,582,463.62 |
Dominated: the strategy is less effective and more costly.
*Cost saving.
HospPresTr, hospital-based presumptive treatment; HospPresTrIm, hospital-based presumptive treatment of immunosuppressed migrants; HospSerTr, hospital-based serology screening and treatment; HospSerTrIm, hospital-based serology screening and treatment of Immunosuppressed migrants; PCPresTr, presumptive treatment at a primary care setting; PCSerTr, serology screening and treatment at a primary care setting.
Figure 3Tornado plots of the one-way sensitivity analysis for each strategy evaluated. Red vertical line represents the deterministic value of the ACER. The black vertical line represents the cost-effectiveness threshold. ACER, average cost-effectiveness rate; CFR, case fatality ratio; LYG, life-years gained.
Figure 4Probabilistic sensitivity analysis. (A) The cost-effectiveness plane is represented. (B) Cost-effectiveness plane removing the two least cost-effective strategies. (C) Cost-effectiveness probability curves. Hosp PresTr, hospital-based presumptive treatment; Hosp SerTr, hospital-based serology screening and treatment; HospPresTrImmuneSup, hospital-based presumptive treatment of immunosuppressed patients; HospSerTrImmuneSup, hospital-based serology screening and treatment of immunosuppressed patients; PC PresTr, presumptive treatment at a primary care setting; PCSerTr, serology screening andtreatment at a primary care setting.