SEMI-MARKOVIAN ANALYSIS OF THE PROGNOSIS OF BREAST CANCER BETWEEN DIAGNOSIS AND TREATMENT INITIATION IN KENYA: A CASE STUDY OF TWO COUNTIES

Abstract

Breast cancer is a major health burden not only globally. It is the most commonly diagnosed type of cancer globally and in Kenya. In 2022, 7,243 new cases of breast cancer were reported accounting for approximately 16.2% of all cancer cases diagnosed with a mortality rate of 11.6% which translates to 3,398 deaths. This study aimed to determine the prevalence and analyze female breast cancer (FBC) prognosis between diagnosis and treatment, taking a case study of two counties in Kenya. Data for this study was obtained from two cancer registries in two county hospitals with a sample of 300 health records. After data cleaning, 150 records were eligible for analysis. Key variables of interest in the study were staging information of FBC at diagnosis and treatment, time taken between diagnosis and treatment, as well as the waiting time before transiting to the subsequent stage. One of the approaches that can be used to gain insight into how breast cancer progresses over time is the application of semi-Markov analysis which was used to analyze the prognosis of breast cancer in two counties in Kenya. This was obtained by determining the prevalence of FBC at diagnosis and at treatment and finding the transitional probabilities between different cancer states. The results of the analysis showed that FBC stage III was the most prevalent at diagnosis and treatment initiation with a prevalence of 36% and 34.7% respectively. The probability of remaining at stage II or stage III after diagnosis was found to decrease with the increase in the waiting time before treatment initiation. The results outline the necessity of timely diagnosis and initiation of interventions, which may help in clinical decision-making, resource allocation and inform public health policies.