The relevance of cancer type specific scenarios in predicting primary radiotherapy use in non-metastatic cancer patients in the Netherlands towards 2032

Aim: To predict primary radiotherapy (RT) use in the Netherlands for patients with non-metastatic cancer. Additionally, we explore its associations with predefined scenarios for five types of cancers.
Methods: Cancer incidences in 2032 were predicted based on data from Netherlands Cancer Registry and Statistics Netherlands according to an Age-Period-Cohort model. In the prediction of the number of patients to receive primary RT, a random forest model was used. First, primary RT-use towards 2032 was predicted for all non-metastatic cancers assuming historical trends to be representative for the future (the base prediction). Next, primary RT-use was predicted for five types of cancer by applying predefined scenarios.
Results; According to the base prediction overall primary RT-use in non-metastatic cancers increased by 23% in 2032. Increased RT-use was predicted in NSCLC stage I (+55%) and II (+230%); DCIS grade I-II (+64%) and grade III (+22%); breast cancer stage I-III (+10%); localized intermediate-risk prostate cancer (EBRT-use +22%), brachytherapy-use (+10%); locally advanced prostate cancer (EBRT-use +29%), brachytherapy-use (+15%). Decreased RT-use was predicted in NSCLC stage III (-13%) as well as in localized high-risk prostate cancer (-19%) and remained unaltered in localized low-risk prostate cancer. Compared to the base prediction, predefined cancer type specific scenarios showed: RT-use in NSCLC stage I and III to increase further (+18%) and to decrease further (-7%), respectively; a decreased RT-use in low-risk DCIS (-61%) and in low-risk breast cancer (-15%); a decreased as well as an increased RT-use in prostate cancer. For rectal cancer a decreased RT-use is foreseen.
Conclusion: The magnitude of the predicted use of primary RT towards 2032 varies substantially by cancer type and depends strongly on cancer type specific scenarios. This underscores the importance of incorporating such scenarios to generate more accurate estimates of future workload for radiotherapy departments.