[Other] The prognostic role of next-generation imaging-driven upstaging in newly diagnosed prostate cancer patients Copy

Phase III evidence showed that next-generation imaging (NGI), such as prostate-specific membrane antigen positron emission tomography/computed tomography (PSMA PET/CT), provides higher diagnostic accuracy than bone scan and contrast-enhanced computed tomography (conventional imaging, CI) in the primary staging of intermediate-to-high-risk prostate cancer (PCa) patients. However, due to the lack of outcome data, the introduction of NGI in routine clinical practice is still debated. Analysing the oncological outcome of patients upstaged by NGI (though managed according to CI) might shed light on this issue, supporting the design of randomised trials comparing the effects of treatments delivered based on NGI vs. CI.

We prospectively enrolled a cohort of 100 biopsy-proven intermediate-to-high-risk PCa patients staged with CI and PSMA PET/CT (though managed according to the CI stage), to assess the frequency of the stage migration phenomenon. Stage migration was then assessed as biochemical recurrence—free survival (bRFS) predictor.

Three patients were lost at follow-up after imaging. PSMA PET/CT upstaged 26.8% of patients compared to CI, while it downstaged 6.1% of patients. Notably, 50% of patients excluded from surgery due to the presence of bone metastases at CI would have been treated with radical-intent approaches if PSMA PET/CT had guided the treatment choice. After a median follow-up of 6 months of surgically treated patients, 22/83 (26.5%) had biochemical recurrence (BCR). PSMA PET/CT-driven upstaging determined a significant risk increase for BCR (HR:3.41, 95%CI:1.21–9.56, p = 0.019). Including stage migration in a univariable and multivariable model identified PSMA PET/CT-upstaging as an independent predictor of bRFS.

In conclusion, implementing NGI for staging purposes improves the prediction of bRFS. Although phase III evidence is still needed, this advancement suggests that NGI may better identify patients who would benefit from local treatments than those who may achieve better oncological outcomes through systemic treatment.