# Radiobiological Meta-Analysis of the Response of Prostate Cancer to High-Dose-Rate Brachytherapy: Investigation of the Reduction in Control for Extreme Hypofractionation

## TL;DR

This study finds that prostate cancer treated with extreme hypofractionated HDR-BT shows poor tumor control, better explained by the LQL model than the traditional LQ model.

## Contribution

The study demonstrates that the LQL model better explains prostate cancer response to extreme HDR-BT hypofractionation compared to the LQ model.

## Key findings

- The LQ model cannot fit HDR-BT dose–response data without assuming an unrealistically high α/β ratio.
- The LQL model, which accounts for moderation of radiation damage at higher doses, provides a better fit to clinical data.
- The reoxygenation model does not match the results obtained with the LQL model.

## Abstract

Clinical studies have shown an important reduction in tumor control in prostate cancer when treated with radically hypofractionated high-dose-rate brachytherapy (HDR-BT). This poor response seems in contradiction with studies in external radiotherapy that showed that prostate cancer is very sensitive to fractionation (low α/β). The purpose of this study was to analyze the dose–response of prostate cancer treated with HDR-BT through biomathematical modelling, aiming at understanding the cause of the poor response for radically hypofractionated HDR-BT. We found that the LQ model cannot fit the dose–response curves and that models that include a moderation of the fractionation effect with increasing dose per fraction like the LQL provide a better fit to the experimental data. These results may assist in the design of radical HDR-BT treatments.

Background/Objectives: Clinical studies have shown a marked reduction in tumor control in prostate cancer treated with radically hypofractionated high-dose-rate brachytherapy (HDR-BT). The purpose of this study was to analyze the dose–response of prostate cancer treated with HDR-BT, specifically aiming at investigating the potential failure of the linear–quadratic (LQ) model to describe the response at large doses-per-fraction. Methods: We collated a dataset of dose–response to HDR-BT (3239 patients). The analysis was conducted separately for low and intermediate risk, resulting in 21 schedules (1633 patients) and 23 schedules (1606 patients), respectively. Data were fitted to tumor control probability models based on the LQ model, the linear–quadratic–linear (LQL), and a modification of the LQ model to include the effect of reoxygenation during treatment. Results: The LQ cannot fit the data unless the α/β is allowed to be high (∼[20, >100] Gy, 95% confidence interval). If the α/β is constrained to be low (≤8 Gy), the LQ model cannot reproduce the clinical results, and the LQL model, which includes a moderation of radiation damage with increasing dose, significantly improves the fitting. On the other hand, the reoxygenation model does not match the results obtained with the LQL. The clinically observed reduction in tumor control in prostate cancer treated with radical HDR-BT is better described by the LQL model. Using the best-fitting parameters, the BED for a 20 Gy × 1 treatment (128 Gyα/β) is far less than that of a conventional 2 Gy × 37 fractionation (196 Gyα/β). Conclusions: Our analysis showed that the substantial loss of tumor control observed in extremely hypofractionated HDR-BT trials can only be explained by the LQ model if the α/β is very large (≥100 Gy), in clear disagreement with the limits set in the analysis of external radiotherapy data. It seems more reasonable that there is a moderation of the LQ-predicted effect with increasing dose per fraction. These results may assist in the design of radical HDR-BT treatments.