Evidence map›Paper›PMID 29446343›Full record

ArticleEpidemiology and infection2018

Cost-utility analysis of antiviral use under pandemic influenza using a novel approach - linking pharmacology, epidemiology and heath economics.

D B C Wu, N Chaiyakunapruk, C Pratoomsoot, K K C Lee, H Y Chong, R E Nelson, P F Smith, C M Kirkpatrick, M A Kamal, K Nieforth and 5 more

Open access · bronzeAbstract read
In one paragraph

Article in Epidemiology and infection, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 22% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it, 11 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Valuing COVID-19 Morbidity Risk Reductions.Journal of benefit-cost analysis · 2022
    Article
  5. Review
  6. Article
  7. Article
  8. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 8 institutions in 4 countries.

D B C WuSchool of Pharmacy, Monash University Malaysia,Bandar Sunway,Malaysia.
N ChaiyakunaprukSchool of Pharmacy, Monash University Malaysia,Bandar Sunway,Malaysia.
C PratoomsootFaculty of Public Health,Naresuan University,Phitsanulok,Thailand.
K K C LeeSchool of Pharmacy, Monash University Malaysia,Bandar Sunway,Malaysia.
H Y ChongSchool of Pharmacy, Monash University Malaysia,Bandar Sunway,Malaysia.
R E NelsonUniversity of Utah,Salt Lake City, UT,USA.
P F Smithd3 Medicine, a Certara Company,Parsippany, New Jersey,USA.
C M KirkpatrickCentre for Medicine Use and Safety,Faculty of Pharmacy and Pharmaceutical Sciences,Monash University,Melbourne,Australia.
M A KamalDepartment of Clinical Pharmacology,Regeneron Pharmaceuticals,Tarrytown, NY,USA.
K Nieforthd3 Medicine, a Certara Company,Parsippany, New Jersey,USA.
G Dalld3 Medicine, a Certara Company,Parsippany, New Jersey,USA.
S TooveyPegasus Research,Basel,Switzerland.
D C M KongCentre for Medicine Use and Safety,Faculty of Pharmacy and Pharmaceutical Sciences,Monash University,Melbourne,Australia.
A KamauuAnonlinx LLC,Salt Lake City,USA.
C R Raynerd3 Medicine, a Certara Company,Parsippany, New Jersey,USA.
Monash University Malaysia · MYCertara (United States) · USMonash University · AUIntegra LifeSciences (United States) · USNaresuan University · THRegeneron (United States) · USVA Salt Lake City Healthcare System · USXilinx (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simulation models are used widely in pharmacology, epidemiology and health economics (HEs). However, there have been no attempts to incorporate models from these disciplines into a single integrated model. Accordingly, we explored this linkage to evaluate the epidemiological and economic impact of oseltamivir dose optimisation in supporting pandemic influenza planning in the USA. An HE decision analytic model was linked to a pharmacokinetic/pharmacodynamics (PK/PD) - dynamic transmission model simulating the impact of pandemic influenza with low virulence and low transmissibility and, high virulence and high transmissibility. The cost-utility analysis was from the payer and societal perspectives, comparing oseltamivir 75 and 150 mg twice daily (BID) to no treatment over a 1-year time horizon. Model parameters were derived from published studies. Outcomes were measured as cost per quality-adjusted life year (QALY) gained. Sensitivity analyses were performed to examine the integrated model's robustness. Under both pandemic scenarios, compared to no treatment, the use of oseltamivir 75 or 150 mg BID led to a significant reduction of influenza episodes and influenza-related deaths, translating to substantial savings of QALYs. Overall drug costs were offset by the reduction of both direct and indirect costs, making these two interventions cost-saving from both perspectives. The results were sensitive to the proportion of inpatient presentation at the emergency visit and patients' quality of life. Integrating PK/PD-EPI/HE models is achievable. Whilst further refinement of this novel linkage model to more closely mimic the reality is needed, the current study has generated useful insights to support influenza pandemic planning.

Indexed as

Cost-Benefit AnalysisModels, EconomicModels, TheoreticalAdolescentAdultAgedAntiviral AgentsChildChild, PreschoolDrug CostsFemaleHumansInfantInfluenza, HumanMaleMiddle AgedAntiviral AgentsOseltamivirClinical pharmacologycost-effectiveness analysiscost-utility analysisepidemiologyhealth economicsoseltamivir

Identifiers

PMID29446343
PMCPMC9134563
OpenAlexW2788805987

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.