MRI provides long-term prognosis of patients with biochemical recurrence after prostatectomy

Use of prostatectomy bed magnetic resonance imaging (MRI) can give out long-term prognostic information for assessing patients with biochemical recurrence following prostatectomy, reveals a recent study.

Postprostatectomy patients with recurrent lesions on imaging have longer progression-free survival but shorter prostate cancer-specific survival than those without lesions. Patients with larger lesions are also more likely to have poorer cancer-specific survival.

This study retrospectively assessed men with biochemical recurrence after radical prostatectomy who were evaluated by prostatectomy bed MRI for suspected local recurrence. The authors observed and measured locally recurrent tumours from imaging reports. Patients with nodal/bone lesions at the time of imaging were not included in the analysis.

Finally, the authors assessed systemic progression-free and prostate cancer-specific survival using Kaplan-Meier and Cox regression analyses.

Of the 896 men enrolled, 441 and 455 were in the MRI imaging positive and negative groups for local recurrent tumour, respectively.

Univariate analysis revealed significant between-group difference in preoperative prostate specific antigen (p=0.02), clinical tumour stage (p=0.006), pathological Gleason score from prostatectomy (p=0.02), subsequent salvage radiotherapy (p<0.001), biochemical recurrence to magnetic resonance imaging time interval (p<0.001), age at magnetic resonance imaging (p=0.047) and prostate specific antigen at magnetic resonance imaging (p<0.001).

Patients with negative MRI results had worse systemic progression-free survival rates (p=0.025) but better prostate cancer-specific survival (p=0.016) than those with recurrence. Moreover, patients with larger lesion size had a significantly higher risk of prostate cancer mortality (hazard ratio, 1.07; p<0.001).

Multivariate analysis revealed that pathological Gleason scores ≥7 independently predicted systemic progression (p<0.05).