Evidence map›Paper›PMID 37525183›Full record

ArticleCost effectiveness and resource allocation : C/E2023

INES: Interactive tool for construction and extrapolation of partitioned survival models.

Vicente Gimeno-Ballester, Daniel Perez-Troncoso, Antonio Olry-Labry, David Epstein

Abstract read
In one paragraph

Article in Cost effectiveness and resource allocation : C/E, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. 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

4 authors.

Vicente Gimeno-BallesterServicio de Farmacia, Hospital Universitario Miguel Servet, Zaragoza, Spain.
Daniel Perez-TroncosoAgència De Qualitat I Avaluació Sanitàries De Catalunya, Barcelona, Spain.
Antonio Olry-LabryEscuela Andaluza de Salud Pública, Granada, Spain.
David EpsteinMinistry of Health, Madrid, Spain. davidepstein@ugr.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundINES (INteractive model for Extrapolation of Survival and cost) provides an open-access tool powered by R that implements three-state partitioned survival models (PSM). This article describes the properties of the tool, and the situations where INES may or may not be suitable.

methodsINES is designed to be used by investigators or healthcare professionals who have a good grasp of the principles of economic evaluation and understand the strengths and weaknesses of partitioned survival models, but are not sufficiently familiar with a statistical package such as Excel or R to be able to construct and test a de-novo PSM themselves. INES is delivered to the user via a batch file. Once downloaded to the user's hard drive, it interacts with the user via a portable version of R with web interactivity built in Shiny. INES requires absolutely no knowledge of R and the user does not need to have R or any of its dependences installed. Hence the user will deal with a standalone Shiny app. Inputs (digitalized survival curves, unit costs, posology, hazard ratios, discount rate) can be uploaded from a template spreadsheet.

resultsThe INES application provides a seamlessly integrated package for estimating a set of parametric hazard functions for progression free and overall survival, selecting an appropriate function from this menu, and applying this as an input to a PSM to calculate mean costs and quality-adjusted life years. Examples are given that may serve as a tutorial.

conclusionINES offers a rapid, flexible, robust and transparent tool for parametric survival analysis and calculating a PSM that can be used in many different contexts.

Indexed as

Cost-effectiveness analysisEconomic evaluationExtrapolationPartitioned survival modelSurvival analysis

Identifiers

PMID37525183
PMCPMC10391963

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.