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Predictors of Relapse in Oligometastatic Prostate Patients Receiving Stereotactic Ablative Radiotherapy.
Saleh Sandoughdaran1, Veni Ezhil1, Christos Mikropoulos1
1Royal Surrey County Hospital, Guildford, UK.
The British Journal of Radiology
|July 3, 2026
Summary
Prostate cancer patients undergoing Stereotactic Ablative Radiotherapy (SABR) relapse risk is best predicted by PSA levels after treatment, not traditional markers. Early PSA reduction post-SABR indicates a significantly lower chance of recurrence.
Area of Science:
- Oncology
- Radiation Oncology
- Prostate Cancer Research
Background:
- Oligometastatic prostate cancer presents a treatment challenge, with limited understanding of relapse predictors post-SABR.
- Conventional prognostic factors may not adequately stratify relapse risk in this specific patient group.
Purpose of the Study:
- To identify predictors of disease relapse in patients with oligometastatic prostate cancer treated with Stereotactic Ablative Radiotherapy (SABR).
- To evaluate the efficacy of PSA kinetics as a prognostic biomarker compared to traditional factors.
Main Methods:
- Retrospective analysis of 57 oligometastatic prostate cancer patients treated with SABR (30 Gy in 3-5 fractions).
- Kaplan-Meier and Cox regression analyses were employed to identify prognostic factors for disease-free survival (DFS).
- Primary endpoint: DFS; Secondary endpoints: local relapse rates.
Main Results:
- Median follow-up was 34.5 months; 1-year and 2-year DFS rates were 64.5% and 24.3%.
- Local control was achieved in 87% of patients.
- Post-SABR PSA reduction was the sole significant predictor of relapse (HR=0.235, p=0.005), indicating a 76.5% lower recurrence risk. Traditional markers showed no significant correlation.
Conclusions:
- Post-SABR PSA kinetics are a more reliable predictor of relapse than conventional risk factors in oligometastatic prostate cancer.
- Early PSA reduction post-SABR is independently associated with reduced relapse risk, suggesting its utility in guiding follow-up intensity and identifying high-risk patients.
