Evidence mapPaperPMID 26792792Full record

SynthesisPharmacoEconomics2016

A Systematic Review of Cost-Effectiveness Models in Type 1 Diabetes Mellitus.

Martin Henriksson, Ramandeep Jindal, Catarina Sternhufvud, Klas Bergenheim, Elisabeth Sörstadius, Michael Willis

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in PharmacoEconomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 2 pooled it
3.7field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 2 syntheses or guidelines pooled it, 35 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
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  8. Review
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  13. How to Address Uncertainty in Health Economic Discrete-Event Simulation Models: An Illustration for Chronic Obstructive Pulmonary Disease.Medical decision making : an international journal of the Society for Medical Decision Making · 2020
    Article
  14. Article
  15. Assessing the economic value of maintained improvements in Type 1 diabetes management, in terms of HbADiabetic medicine : a journal of the British Diabetic Association · 2018
    Article
  16. Article
  17. Article
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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

6 authors at 4 institutions in 2 countries.

Martin HenrikssonPAREXEL International, Stockholm, Sweden.
Ramandeep JindalPAREXEL International, Chandigarh, India.
Catarina SternhufvudGlobal Medicines Development | Global Payer Evidence and Pricing, AstraZeneca, SE-431 83, Mölndal, Sweden. Catarina.Sternhufvud@astrazeneca.com.
Klas BergenheimGlobal Medicines Development | Global Payer Evidence and Pricing, AstraZeneca, SE-431 83, Mölndal, Sweden.
Elisabeth SörstadiusGlobal Medicines Development | Global Payer Evidence and Pricing, AstraZeneca, SE-431 83, Mölndal, Sweden.
Michael WillisThe Swedish Institute for Health Economics, IHE, Lund, Sweden.
AstraZeneca (Sweden) · SELinköping University · SEPAREXEL International (India) · INSwedish Institute for Health Economics · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCritiques of cost-effectiveness modelling in type 1 diabetes mellitus (T1DM) are scarce and are often undertaken in combination with type 2 diabetes mellitus (T2DM) models. However, T1DM is a separate disease, and it is therefore important to appraise modelling methods in T1DM.

objectivesThis review identified published economic models in T1DM and provided an overview of the characteristics and capabilities of available models, thus enabling a discussion of best-practice modelling approaches in T1DM.

methodsA systematic review of Embase(®), MEDLINE(®), MEDLINE(®) In-Process, and NHS EED was conducted to identify available models in T1DM. Key conferences and health technology assessment (HTA) websites were also reviewed. The characteristics of each model (e.g. model structure, simulation method, handling of uncertainty, incorporation of treatment effect, data for risk equations, and validation procedures, based on information in the primary publication) were extracted, with a focus on model capabilities.

resultsWe identified 13 unique models. Overall, the included studies varied greatly in scope as well as in the quality and quantity of information reported, but six of the models (Archimedes, CDM [Core Diabetes Model], CRC DES [Cardiff Research Consortium Discrete Event Simulation], DCCT [Diabetes Control and Complications Trial], Sheffield, and EAGLE [Economic Assessment of Glycaemic control and Long-term Effects of diabetes]) were the most rigorous and thoroughly reported. Most models were Markov based, and cohort and microsimulation methods were equally common. All of the more comprehensive models employed microsimulation methods. Model structure varied widely, with the more holistic models providing a comprehensive approach to microvascular and macrovascular events, as well as including adverse events. The majority of studies reported a lifetime horizon, used a payer perspective, and had the capability for sensitivity analysis.

conclusionsSeveral models have been developed that provide useful insight into T1DM modelling. Based on a review of the models identified in this study, we identified a set of 'best in class' methods for the different technical aspects of T1DM modelling.

Indexed as

Models, EconomicComputer SimulationCost-Benefit AnalysisDiabetes Mellitus, Type 1HumansHypoglycemic AgentsMarkov ChainsHypoglycemic Agents

Identifiers

PMID26792792
OpenAlexW2263588873

What Socratic 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 Socratic graph.