Modelling of lung cancer survival data for critical illness insurances

TL;DR

This paper develops a comprehensive multi-state model for critical illness insurance, accounting for disease duration and stage, and applies it to lung cancer data to improve risk assessment and pricing strategies.

Contribution

It introduces a novel multi-state model that incorporates disease duration and stage, applied specifically to lung cancer insurance analysis.

Findings

Transition matrix estimated from real data

Model applicable to insurance and viatical contracts

Enhanced risk modeling for critical illnesses

Abstract

We derive a general multiple state model for critical illness insurances. In contrast to the classical model, we take into account that the probability of death for a dread disease sufferer may depend on the duration of the disease, and the payment of benefits associated with a severe disease depends not only on the diagnosis but also on the disease stage. We apply the introduced model to the analysis of a critical illness insurance against the risk of lung cancer. Based on the real data for the Lower Silesian Voivodship in Poland, we estimate the transition matrix, related to the discrete-time Markov model. The obtained probabilistic structure of the model can be directly used to cost not only critical illness insurances and life insurances with accelerated death benefits option, but also to viatical settlement contracts.