Copenhagen, Denmark
Onsite/Online

ESTRO 2022

Session Item

Sunday
May 08
10:30 - 11:30
Room D5
Radiomics & modelling
Claudio Fiorino, Italy;
Marta Bogowicz, The Netherlands
Proffered Papers
Physics
10:50 - 11:00
Modeling outcome after salvage post-prostatectomy radiotherapy: impact of pelvic nodes irradiation
Claudio Fiorino, Italy
OC-0457

Abstract

Modeling outcome after salvage post-prostatectomy radiotherapy: impact of pelvic nodes irradiation
Authors:

Michela Olivieri1, Cesare Cozzarini2, Alessandro Magli3, Domenico Cante4, Barbara Noris Chiorda5, Fernando Munoz6, Adriana Faiella7, Elisa Olivetta8, Marco Andrea Signor3, Cristina Piva4, Barbara Avuzzi5, Letizia Ferella6, Alice Pastorino8, Elisabetta Garibaldi9, Marco Gatti9, Luciana Rago10, Teodora Statuto11, Sara Broggi12, Andrei Fodor13, Chiara Deantoni13, Tiziana Rancati14, Giuseppe Sanguineti7, Riccardo Valdagni5, Nadia Di Muzio13, Claudio Fiorino12

1San Raffaele Scientific Institute, Medical Physics, Milano, Italy; 2San Raffaele Scientific Instite, Radiotherapy, Milano, Italy; 3Azienda Ospedaliero Universitaria S. Maria della Misericordia, Radiotherapy, Udine, Italy; 4ASL TO4 Ospedale di Ivrea, Radiotherapy, Ivrea, Italy; 5Fondazione IRCCS Istituto Nazionale dei Tumori, Radiotherapy, Milano, Italy; 6Ospedale Regionale Parini-AUSL Valle d’Aosta, Radiotherapy, Aosta, Italy; 7IRCCS Istituto Nazionale dei Tumori “Regina Elena”, Radiotherapy, Roma, Italy; 8A.O.SS. Antonio e Biagio, Radiotherapy, Alessandria, Italy; 9IRCCS Ospedale di Candiolo, Radiotherapy, Torino, Italy; 10Centro di Riferimento Oncologico della Basilicata (IRCCS-CROB), Radiotherapy, Rionero in Vulture, Italy; 11Centro di Riferimento Oncologico della Basilicata (IRCCS-CROB) , Radiotherapy, Rionero in Vulture, Italy; 12San Raffaele Scientific Institute, Medical Physics, Milano, Italy; 13San Raffaele Scientific Institute, Radiotherapy, Milano, Italy; 14Fondazione IRCCS Istituto Nazionale dei Tumori, Medical Physics, Milano, Italy

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Purpose or Objective

Comprehensive predictive models of long-term biochemical-relapse-free survival (bRFS) after post-prostatectomy salvage radiotherapy (SRT) are lacking. A previously realized radiobiology-based formula was adapted to incorporate the impact of pelvic node irradiation (PNI) and was applied to a multi-Institute cohort treated with SRT to estimate the long-term impact of PNI.

Material and Methods

bRFS may be expressed by a Poisson-based equation ((K x (1- exp(-αeffD))CxPSA), including pre-SRT PSA, the radiosensitivity parameter αeff, the clonogen density C (assuming a pre-SRT PSA=1 ng/mL), the prescribed

2-Gy equivalent dose D, and a factor K=(1-BxλxPSA) representing the detrimental impact on post-SRT bRFS due to clonogens outside the irradiated volume at SRT, with λ being the recovery of bRFS obtainable with PNI. Data of 795 pT2-pT3a/pT3b, pN0/pN1/pNx patients (pts) treted in 8 Institutes with a 5-year minimum follow-up and a pre-RT PSA≤2 ng/mL were randomly split into training (n=528) and validation (n=267) cohorts; data of the training cohort were fitted by the least square method. Separate fits were performed on two class-risk groups, based on the most robust, clinically significant predictors resulting from a multi-variable Cox regression analysis. Model performances were compared against true data by calibration plots and tested in the validation group.

Results

The median follow-up was 8.5 years, median pre-SRT PSA 0.54 ng/mL, median SRT EQD2 dose 72.6 Gy; 336/795 pts received PNI. The most clinically significant prognostic grouping identifying the high-risk cohort was found to be “pT3b and/or ISUP 4-5 Class”, as opposed to pT2/pT3a and ISUP 1-3 (low-risk group). Fits on the training cohort were successful with consistent best-fit parameters of: αeff=0.26/0.23Gy-1, C=107, B=0.40/0.97, λ=0.87/0.41 for the low-risk (n=417) and high-risk (n=111) groups, respectively. The calibration was satisfactory (slope=0.79, R2=0.82). Performances were confirmed in the validation group (slope=0.91, R2=0.91). Results suggested an optimal SRT EQD2 dose in the range of 70 and 74 Gy for low- and high-risk groups, respectively. The estimated bRFS recovery obtainable with PNI corresponding to these dose levels is shown in the Figure: >5% for PSA>1 and 0.15 ng/mL in low-risk and high-risk pts, respectively, and >10% for high-risk pts with a pre-SRT PSA>0.25 ng/mL.



Conclusion

An explainable one-size-fits-all equation satisfactorily predicts long-term bRFS after SRT. Model parameters were obtained by fitting a large multi-centric cohort, and the model was independently validated. Results suggest that a significant (and rapidly increasing for rising pre-SRT PSA values) impact of PNI may be expected in patients with pT3b and/or ISUP4-5 disease at prostatectomy. The added value of PNI is, on the contrary, negligible in the low-risk cohort for pre-SRT values up to 1 ng/mL. A calculation tool for individual estimates is available.