Evidence map›Paper›PMID 32249396›Full record

ArticlePharmacoEconomics2020

Estimating the Value of New Antimicrobials in the Context of Antimicrobial Resistance: Development and Application of a Dynamic Disease Transmission Model.

Jason Gordon, Oliver Darlington, Phil McEwan, Matthew Lumley, Amer Taie, Meagen Hicks, Claudie Charbonneau, Angela Blake, Neil Hawkins, Simon Goldenberg and 2 more

Open access · hybridAbstract readValidation Study
PubMed Publisher
In one paragraph

Article in PharmacoEconomics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 10% 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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 25 citations in OpenAlex.

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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

12 authors at 6 institutions in 1 country.

Jason GordonHealth Economics and Outcomes Research Limited, Birmingham, UK. jason.gordon@heor.co.uk.
Oliver DarlingtonHealth Economics and Outcomes Research Limited, Cardiff, UK.
Phil McEwanHealth Economics and Outcomes Research Limited, Cardiff, UK.
Matthew LumleyPfizer, Tadworth, UK.
Amer TaiePfizer, Tadworth, UK.
Meagen HicksPfizer, Tadworth, UK.
Claudie CharbonneauPfizer, Tadworth, UK.
Angela BlakePfizer, Tadworth, UK.
Neil HawkinsUniversity of Glasgow, Glasgow, UK.
Simon GoldenbergGuy's and St Thomas' NHS Foundation Trust, London, UK.
Jonathan OtterImperial College London, London, UK.
Mark WilcoxUniversity of Leeds, Leeds, UK.
Pfizer (United Kingdom) · GBHealth Economics and Outcomes Research (United Kingdom) · GBGuy's and St Thomas' NHS Foundation Trust · GBImperial College London · GBUniversity of Glasgow · GBUniversity of Leeds · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesAntimicrobial resistance (AMR) represents a significant threat to patient and population health. The study aim was to develop and validate a model of AMR that defines and quantifies the value of new antibiotics.

methodsA dynamic disease transmission and cost-effectiveness model of AMR consisting of three components (disease transmission, treatment pathway and optimisation) was developed to evaluate the health economic value of new antibiotics. The model is based on the relationship between AMR, antimicrobial availability and consumption. Model analysis explored the impact of different antibiotic treatment strategies on the development of AMR, patient and population estimates of health benefit, across three common treatment indications and pathogens in the UK.

resultsPopulation-level resistance to existing antimicrobials was estimated to increase from 10.3 to 16.1% over 10 years based on current antibiotic availability and consumption. In comparison, the diversified use of a new antibiotic was associated with significant reduction in AMR (12.8% vs. 16.1%) and quality-adjusted life year (QALY) gains at a patient (7.7-10.3, dependent on antimicrobial efficacy) and population level (3657-8197, dependent on antimicrobial efficacy and the prevalence of AMR). Validation across several real-world data sources showed that the model output does not tend to systematically under- or over-estimate observed data.

conclusionsThe development of new antibiotics and the appropriate use of existing antibiotics are key to addressing the threat of AMR. This study presents a validated model that quantifies the value of new antibiotics through clinical and economic outcomes of relevance, and accounts for disease transmission of infection and development of AMR. In this context, the model may be a useful tool that could contribute to the decision-making process alongside other potential models and expert advice.

Indexed as

Models, EconomicQuality-Adjusted Life YearsAnti-Bacterial AgentsBacterial InfectionsCost-Benefit AnalysisDrug DevelopmentDrug Resistance, BacterialHumansUnited KingdomAnti-Bacterial Agents

Identifiers

PMID32249396
OpenAlexW3014421200

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.