INES (INteractive model for Extrapolation of Survival and cost)
INES is a user-friendly, open-access tool that helps healthcare professionals build and analyze survival models without needing programming skills. It uses real-world data to estimate how long patients live and stay disease-free, and calculates treatment costs and health benefits in terms of quality-adjusted life years.
At a glance
Use when
Conducting economic evaluations requiring survival extrapolation; when users lack programming skills; during early HTA or reimbursement submissions; when transparency and rapid modeling are priorities
Avoid when
Complex disease pathways requiring more than three health states; when advanced customization or integration with other models is needed; if non-parametric or microsimulation approaches are preferred
Inputs
Digitized survival curves, hazard ratios, unit costs, posology, discount rate (uploaded via template spreadsheet)
Outputs
Fitted parametric survival functions, selected best-fit models, mean survival times, mean costs, quality-adjusted life years (QALYs), and results from the partitioned survival model
How it works
INES implements a three-state partitioned survival model (PSM) using parametric hazard functions for progression-free and overall survival. Built on R Shiny, it provides a standalone interactive web application requiring no installation of R or coding knowledge. Users upload inputs (digitized survival curves, hazard ratios, unit costs, posology, discount rates) via a template spreadsheet. The tool fits multiple parametric survival distributions, enables visual and statistical comparison, selects best-fit functions, and propagates these into a PSM to estimate mean costs and QALYs. It supports transparent, reproducible economic modeling across diverse therapeutic areas.
- HTA domains
- Clinical Effectiveness, Costs & Economic Evaluation, Patient and Social Aspects
- Assumptions
- Survival times can be adequately modeled using parametric distributions; the proportional hazards assumption holds where applicable; costs and utilities are constant over time or follow predefined patterns; the three-state PSM (progression-free, progressed, death) sufficiently represents the disease course
- Strengths
- No coding required; standalone Shiny app with portable R; transparent and reproducible modeling; rapid model construction; supports multiple parametric distributions with visual and statistical fit assessment; integrates directly into economic evaluations; open-access and flexible for various contexts
- Limitations
- Limited to three-state partitioned survival models; relies on quality of digitized survival data; assumes parametric fit is appropriate; does not support more complex modeling structures like Markov or microsimulation without external adaptation
- Also known as
- INES, Interactive tool for construction and extrapolation of partitioned survival models
Questions this answers
- › What is the expected progression-free and overall survival time under different treatment strategies?
- › Which parametric survival distribution best fits the observed clinical trial data?
- › What are the mean costs and quality-adjusted life years (QALYs) associated with a treatment?
- › How can partitioned survival models be constructed transparently without coding expertise?
- › How do different extrapolations of survival curves impact cost-effectiveness results?
- › Can a robust and flexible survival model be built quickly for early health technology assessment?
References & sources
Similar by meaning
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