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Accurate prediction of long-term risk of biochemical failure after salvage radiotherapy including the impact of pelvic node irradiation

      Highlights

      • 795 pts treated with early salvage RT for prostate cancer were investigated.
      • Median follow-up was 8.5 years; PSA = 0.43 ng/ml,EQD2: 71.3 Gy. 331 pts received PNI.
      • Biochemical failure data were fitted with a radiobiology based formula on the training cohort.
      • Fit was successful and prediction performances were confirmed in the validation cohort.
      • The model can individually assess failure risk based on Dose, PSA, ISUP grouping and PNI.

      Abstract

      Background and purpose

      Explainable models of long-term risk of biochemical failure (BF) after post-prostatectomy salvage radiotherapy (SRT) are lacking. A previously introduced radiobiology-based formula was adapted to incorporate the impact of pelvic nodes irradiation (PNI).

      Materials and methods

      The risk of post-SRT BF may be expressed by a Poisson-based equation including pre-SRT PSA, the radiosensitivity α, the clonogen density C, the prescribed dose (in terms of EQD2, α/β = 1.5 Gy) and a factor (1-BxλxPSA) accounting for clonogens outside the irradiated volume, being λ the recovery due to PNI. Data of 795 pT2-pT3, pN0/pN1/pNx (n = 627/94/74) patients with follow-up ≥ 5 years and pre-RT PSA ≤ 2 ng/mL were randomly split into training (n = 528) and validation (n = 267) cohorts; the training cohort data were fitted by the least square method. Separate fits were performed for different risk groups. Model performances were assessed by calibration plots and tested in the validation group.

      Results

      The median follow-up was 8.5y, median pre-SRT PSA and EQD2 were 0.43 ng/mL and 71.3 Gy respectively; 331/795 pts received PNI. The most clinically significant prognostic grouping was pT3b and/or ISUP4-5 versus pT2/3a and ISUP1-3. Best-fit parameters were αeff = 0.26/0.23 Gy−1, C = 107/107, B = 0.40/0.97, λ = 0.87/0.41 for low/high-risk group. Performances were confirmed in the validation group (slope = 0.89,R2 = 0.85). Results suggested optimal SRT dose at 70–74 Gy. The estimated reduction of post-SRT BF due to PNI at these dose values was > 5 % for PSA > 1/>0.15 ng/mL for low/high-risk patients, being > 10 % for high-risk patients with pre-SRT PSA > 0.25 ng/mL.

      Conclusion

      An explainable one-size-fits-all equation satisfactorily predicts long-term risk of post-SRT BF. The model was independently validated. A calculator tool was made available.

      Keywords

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