Abstract
Although personalization of cancer care is recommended, current follow‐up after the curative treatment of breast cancer is consensus‐based and not differentiated for base‐line risk. Every patient receives annual follow‐up for 5 years without taking into account the individual risk of recurrence. The aim of this study was to introduce personalized follow‐up schemes by stratifying for age. Using data from the Netherlands Cancer Registry of 37 230 patients with early breast cancer between 2003 and 2006, the risk of recurrence was determined for four age groups (<50, 50‐59, 60‐69, >70). Follow‐up was modeled with a discrete‐time partially observable Markov decision process. The decision to test for recurrences was made two times per year. Recurrences could be detected by mammography as well as by self‐detection. For all age groups, it was optimal to have more intensive follow‐up around the peak in recurrence risk in the second year after diagnosis. For the first age group (<50) with the highest risk, a slightly more intensive follow‐up with one extra visit was proposed compared to the current guideline recommendation. The other age groups were recommended less visits: four for ages 50‐59, three for 60‐69, and three for ≥70. With this model for risk‐based follow‐up, clinicians can make informed decisions and focus resources on patients with higher risk, while avoiding unnecessary and potentially harmful follow‐up visits for women with very low risks. The model can easily be extended to take into account more risk factors and provide even more personalized follow‐up schedules.
Highlights
The incidence of breast cancer is rising.[1]
Of the patients treated for primary invasive breast cancer, 4% will develop a locoregional recurrence (LRR) and almost 5% will be diagnosed with a second primary (SP) breast cancer in the 10 years following the primary diagnosis.[2]
The aim of this study was to provide a comprehensive model of the breast cancer follow-up setting with a clinical focus that takes into account the different methods of detection and uncertainty of the true health state and maximizes the total expected quality-adjusted life years (QALYs)
Summary
The incidence of breast cancer is rising.[1]. The number of new invasive breast cancer cases in the Netherlands is currently more than 14 000 per year, which accounts for over 28% of all cancer cases in women.[2]. A more personalized follow-u p, targeting intensive follow-u p to those at high risk for recurrence is a necessary approach to allocate scarce resources and to optimize detection
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