Estimating the risk of cancer with and without a screening history

This article presents an innovative probability modeling approach to estimate the risk of cancer from an individual's current age until the end of life, considering both scenarios with and without a screening history. The study uses a disease progression model with three states: disease-free, preclinical, and clinical, and incorporates parameters estimated from screening data. The article applies this method to estimate breast cancer risk using data from the Health Insurance Plan of Greater New York (HIP) study. It provides insights into the probability of cancer incidence and lifetime risk, demonstrating how these probabilities change with age and screening history. The findings reveal that cancer risk is relatively stable before age 40 and gradually decreases thereafter, with the highest probability density of breast cancer incidence occurring around ages 67 and 68. The article also discusses the impact of different screening intervals and durations on cancer risk assessment. This research offers a more personalized and dynamic approach to cancer risk estimation, which could potentially inform screening recommendations and improve patient care.