Treatment interruptions affect biochemical failure rates in prostate cancer patients treated with proton beam therapy: Report from the multi-institutional proton collaborative group registry

James E Han; John Chang; Lane Rosen; William Hartsell; Henry Tsai; Jonathan Chen; Mark V Mishra; Daniel Krauss; J Isabelle Choi; Charles B Simone 2nd; Shaakir Hasan

doi:10.1016/j.ctro.2020.10.003

Treatment interruptions affect biochemical failure rates in prostate cancer patients treated with proton beam therapy: Report from the multi-institutional proton collaborative group registry

Clin Transl Radiat Oncol. 2020 Oct 22:25:94-101. doi: 10.1016/j.ctro.2020.10.003. eCollection 2020 Nov.

Authors

James E Han¹, John Chang², Lane Rosen³, William Hartsell⁴, Henry Tsai⁵, Jonathan Chen⁶, Mark V Mishra⁷, Daniel Krauss⁸, J Isabelle Choi⁹, Charles B Simone 2nd⁹, Shaakir Hasan⁹

Affiliations

¹ Department of Radiation Oncology, University of California Los Angeles, Los Angeles, CA, USA.
² Department of Radiation Oncology, Oklahoma Proton Center, Oklahoma City, OK, USA.
³ Department of Radiation Oncology, Willis Knighton Medical Center, Shreveport, LA, USA.
⁴ Department of Radiation Oncology, Northwestern University, Chicago, IL, USA.
⁵ ProCure Proton Therapy Center, Somerset, NJ, USA.
⁶ Department of Radiation Oncology, University of Washington, Seattle, WA, USA.
⁷ Department of Radiation Oncology, University of Maryland School of Medicine, MD, USA.
⁸ Department of Radiation Oncology, Beaumont Hospital, Royal Oak, MI, USA.
⁹ Department of Radiation Oncology, New York Proton Center, New York, NY, USA.

Abstract

Introduction: To date, no studies examining the effect of treatment interruptions (TI) with proton beam therapy (PBT) have been published. The goal of our study was to determine the predictors of TI amongst patients with prostate cancer (PCa) treated with PBT and to determine whether TI are associated with biochemical failure (BF). We hypothesized that any correlation between TI and biochemical control would be more pronounced in high risk groups.

Methods: Data for 4278 patients with PCa was obtained from the prospectively collected Proton Collaborative Group (PCG) data registry. Univariate and multivariate logistic regression analysis (MVA) was used to model possible predictors of BF. A subset analysis was performed for high risk patients treated with ADT and PBT. Finally, propensity score (PS) analysis was performed to account for any indication bias caused by lack of randomization.

Results: Total treatment duration (OR, 1.05 [1.04-1.06]; p < 0.001) increased the likelihood of TI on MVA. TI did not have a statistically significant correlation with BF (OR, 1.44 [0.86-2.39]; p = 0.162) amongst PS matched patients. However, on subset analyses of high risk group patients with PS matching, there was a trend towards worse BF in patients with TI (OR 3.85; 95%CI (0.96-15.44); p = 0.057).

Conclusion: In the first analysis of its kind, the results suggest that TI in high risk PCa patients treated with PBT and ADT have worse BF rates. Interventions such as increased patient education, proper maintenance of proton facilities, and decreasing total treatment duration with alternative fractionation schedules may help avoid the unintended negative effects on tumor control due to TI. However, future analyses on a larger patient population is needed.

Keywords: Prostate cancer; Proton beam therapy; Treatment interruptions.