Personalized Cotesting Policies for Cervical Cancer Screening: A POMDP Approach

Malek Ebadi,Raha Akhavan-Tabatabaei

doi:10.3390/math9060679

Abstract

Screening for cervical cancer is a critical policy that requires clinical and managerial vigilance because of its serious health consequences. Recently the practice of conducting simultaneous tests of cytology and Human Papillomavirus (HPV)-DNA testing (known as cotesting) has been included in the public health policies and guidelines with a fixed frequency. On the other hand, personalizing medical interventions by incorporating patient characteristics into the decision making process has gained considerable attention in recent years. We develop a personalized partially observable Markov decision process (POMDP) model for cervical cancer screening decisions by cotesting. In addition to the merits offered by the guidelines, by availing the possibility of including patient-specific risks and other attributes, our POMDP model provides a patient-tailored screening plan. Our results show that the policy generated by the POMDP model outperforms the static guidelines in terms of quality-adjusted life years (QALY) gain, while performing comparatively equal in lifetime risk reduction.

Highlights

Cervical cancer is the fourth most common cancer type among women worldwide [1].Every year, more than half a million women are diagnosed with cervical cancer and over300,000 cases result in death worldwide [2]
Over a certain period in a patient’s lifetime, the decision maker aims to choose an optimal action from the feasible set of actions such that the expected total reward is maximized. We model this problem as a discrete-time finite horizon partially observable Markov decision process (POMDP) while at any point in time, the state of the patient evolves according to the underlying Markov chain
We begin with an example that helps to illustrate how the optimal policy is generated for any patient

Summary

Introduction

Cervical cancer is the fourth most common cancer type among women worldwide [1].Every year, more than half a million women are diagnosed with cervical cancer and over300,000 cases result in death worldwide [2]. Cervical cancer is the fourth most common cancer type among women worldwide [1]. In most of the cervical cancer cases an infection by Human Papillomavirus (HPV) is identified [3,4]. Two specific strains of HPV namely 16 and 18 are persistent in the body while the majority of the other strains are acute (non-persistent), harmless and cleaned from the body without medical interventions [6]. In this regard, spontaneous regression is a unique characteristic of the disease distinguishing it from most of the other cancer types

Objectives

Methods

Results