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Zamboglou C, Peeken JC, Janbain A, Katsahian S, Strouthos I, Ferentinos K, Farolfi A, Koerber SA, Debus J, Vogel ME, Combs SE, Vrachimis A, Morganti AG, Spohn SKB, Shelan M, Aebersold DM, Grosu AL, Ceci F, Henkenberens C, Kroeze SGC, Guckenberger M, Fanti S, Belka C, Bartenstein P, Hruby G, Scharl S, Wiegel T, Emmett L, Arnoux A, Schmidt-Hegemann NS. Development and Validation of a Multi-institutional Nomogram of Outcomes for PSMA-PET-Based Salvage Radiotherapy for Recurrent Prostate Cancer. JAMA Netw Open 2023; 6:e2314748. [PMID: 37219907 DOI: 10.1001/jamanetworkopen.2023.14748] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/24/2023] Open
Abstract
Importance Prostate-specific antigen membrane positron-emission tomography (PSMA-PET) is increasingly used to guide salvage radiotherapy (sRT) after radical prostatectomy for patients with recurrent or persistent prostate cancer. Objective To develop and validate a nomogram for prediction of freedom from biochemical failure (FFBF) after PSMA-PET-based sRT. Design, Setting, and Participants This retrospective cohort study included 1029 patients with prostate cancer treated between July 1, 2013, and June 30, 2020, at 11 centers from 5 countries. The initial database consisted of 1221 patients. All patients had a PSMA-PET scan prior to sRT. Data were analyzed in November 2022. Exposures Patients with a detectable post-radical prostatectomy prostate-specific antigen (PSA) level treated with sRT to the prostatic fossa with or without additional sRT to pelvic lymphatics or concurrent androgen deprivation therapy (ADT) were eligible. Main Outcomes and Measures The FFBF rate was estimated, and a predictive nomogram was generated and validated. Biochemical relapse was defined as a PSA nadir of 0.2 ng/mL after sRT. Results In the nomogram creation and validation process, 1029 patients (median age at sRT, 70 years [IQR, 64-74 years]) were included and further divided into a training set (n = 708), internal validation set (n = 271), and external outlier validation set (n = 50). The median follow-up was 32 months (IQR, 21-45 months). Based on the PSMA-PET scan prior to sRT, 437 patients (42.5%) had local recurrences and 313 patients (30.4%) had nodal recurrences. Pelvic lymphatics were electively irradiated for 395 patients (38.4%). All patients received sRT to the prostatic fossa: 103 (10.0%) received a dose of less than 66 Gy, 551 (53.5%) received a dose of 66 to 70 Gy, and 375 (36.5%) received a dose of more than 70 Gy. Androgen deprivation therapy was given to 325 (31.6%) patients. On multivariable Cox proportional hazards regression analysis, pre-sRT PSA level (hazard ratio [HR], 1.80 [95% CI, 1.41-2.31]), International Society of Urological Pathology grade in surgery specimen (grade 5 vs 1+2: HR, 2.39 [95% CI, 1.63-3.50], pT stage (pT3b+pT4 vs pT2: HR, 1.91 [95% CI, 1.39-2.67]), surgical margins (R0 vs R1+R2+Rx: HR, 0.60 [95% CI, 0.48-0.78]), ADT use (HR, 0.49 [95% CI, 0.37-0.65]), sRT dose (>70 vs ≤66 Gy: HR, 0.44 [95% CI, 0.29-0.67]), and nodal recurrence detected on PSMA-PET scans (HR, 1.42 [95% CI, 1.09-1.85]) were associated with FFBF. The mean (SD) nomogram concordance index for FFBF was 0.72 (0.06) for the internal validation cohort and 0.67 (0.11) in the external outlier validation cohort. Conclusions and Relevance This cohort study of patients with prostate cancer presents an internally and externally validated nomogram that estimated individual patient outcomes after PSMA-PET-guided sRT.
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Affiliation(s)
- Constantinos Zamboglou
- Department of Radiation Oncology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
- Berta-Ottenstein-Programme, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Oncology Center, University Hospital of the European University, Limassol, Cyprus
| | - Jan C Peeken
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Zentrum, München, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Ali Janbain
- Cité University, AP-HP, European Hospital Georges-Pompidou, Clinical research unit, Clinical Investigation Center 1418 Clinical Epidemiology, INSERM, INRIA, HeKA, Paris, France
| | - Sandrine Katsahian
- Cité University, AP-HP, European Hospital Georges-Pompidou, Clinical research unit, Clinical Investigation Center 1418 Clinical Epidemiology, INSERM, INRIA, HeKA, Paris, France
| | - Iosif Strouthos
- Department of Radiation Oncology, German Oncology Center, University Hospital of the European University, Limassol, Cyprus
| | - Konstantinos Ferentinos
- Department of Radiation Oncology, German Oncology Center, University Hospital of the European University, Limassol, Cyprus
| | - Andrea Farolfi
- Division of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Stefan A Koerber
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Juergen Debus
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
- Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center, Heidelberg, Germany
| | - Marco E Vogel
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Zentrum, München, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Stephanie E Combs
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
- Institute of Radiation Medicine (IRM), Department of Radiation Sciences (DRS), Helmholtz Zentrum, München, Germany
- Deutsches Konsortium für Translationale Krebsforschung (DKTK), Partner Site Munich, Munich, Germany
| | - Alexis Vrachimis
- Department of Nuclear Medicine, German Oncology Center, University Hospital of the European University, Limassol, Cyprus
- C.A.R.I.C. Cancer Research & Innovation Center, Limassol, Cyprus
| | | | - Simon K B Spohn
- Department of Radiation Oncology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
- Berta-Ottenstein-Programme, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Mohamed Shelan
- Department of Radiation Oncology, Inselspital Bern, University of Bern, Bern, Switzerland
| | - Daniel M Aebersold
- Department of Radiation Oncology, Inselspital Bern, University of Bern, Bern, Switzerland
| | - Anca-Ligia Grosu
- Department of Radiation Oncology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
- German Cancer Consortium (DKTK), Partner Site Freiburg, Freiburg, Germany
| | - Francesco Ceci
- Division of Nuclear Medicine, IEO European Institute of Oncology IRCCS, Milan, Italy
- Department of Oncology and Hemato-Oncology, University of Milan, Milan, Italy
| | - Christoph Henkenberens
- Department of Radiotherapy and Special Oncology, Medical School Hannover, Hannover, Germany
| | - Stephanie G C Kroeze
- Department of Radiation Oncology, University Hospital Zürich, University of Zurich, Zurich, Switzerland
- Department of Radiation Oncology KSA-KSB, Cantonal Hospital Aarau, Aarau, Switzerland
| | - Matthias Guckenberger
- Department of Radiation Oncology, University Hospital Zürich, University of Zurich, Zurich, Switzerland
| | - Stefano Fanti
- Division of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Claus Belka
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Munich, Germany
| | - George Hruby
- Department of Radiation Oncology, Royal North Shore Hospital-University of Sydney, Sydney, Australia
| | - Sophia Scharl
- Department of Radiation Oncology, University of Ulm, Ulm, Germany
| | - Thomas Wiegel
- Department of Radiation Oncology, University of Ulm, Ulm, Germany
| | - Louise Emmett
- Department of Theranostics and Nuclear medicine, St Vincent's Hospital Sydney, Sydney, Australia
- St Vincent's Clinical School, University of New South Wales, Sydney, Australia
| | - Armelle Arnoux
- Cité University, AP-HP, European Hospital Georges-Pompidou, Clinical research unit, Clinical Investigation Center 1418 Clinical Epidemiology, INSERM, INRIA, HeKA, Paris, France
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Zamboglou C, Arnoux A, Janbain A, Strouthos I, Farolfi A, Koerber S, Peeken J, Vogel M, Ferentinos K, Shelan M, Grosu AL, Kroeze S, Guckenberger M, Fanti S, Hruby G, Scharl S, Wiegel T, Henkeberens C, Emmett L, Hegemann NS. Development and validation of a multi-institutional nomogram of outcomes for PSMA-PET–based salvage radiotherapy in recurrent prostate cancer. J Clin Oncol 2023. [DOI: 10.1200/jco.2023.41.6_suppl.355] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023] Open
Abstract
355 Background: We aimed to develop and to validate a multi-institutional nomogram of outcomes for PSMA-PET based salvage radiotherapy (sRT) following radical prostatectomy (RP) for patients with recurrent or persistent prostate cancer (PCa). Methods: Data from patients with a detectable post-RP prostate-specific antigen (PSA) treated with sRT with or without concurrent androgen-deprivation therapy (ADT) were obtained from 11 academic institutions from 5 countries. All patients had a PSMA-PET scan prior sRT and patients with distant metastases on PET were excluded from this analysis. The freedom from biochemical failure (FFBF) rate was estimated, and a predictive nomogram was generated and validated. Biochemical relapse (BR) was defined as PSA nadir +0.2 ng/ml after sRT. Results: Overall, 1029 patients (training set n=821, external validation set n=208) with a median follow-up of 33 months were included. On PSMA-PET, 427 (42%) and 313 (30%) patients had local and nodal recurrences, respectively. Elective pelvic lymphatics were irradiated in 368 (36%) patients. All patients received sRT to the prostatic fossa receiving a dose of <66 Gy, 66-70 Gy and >70 Gy in 103 (10%), 551 (54%) and 375 (36%) patients, respectively. Androgen deprivation therapy (ADT) was given in 325 (32%) patients. On multivariable Cox regression analysis, pre-SRT PSA, ISUP grade, pT stage, surgical margins, ADT use, sRT dose and nodal recurrence on PSMA PET were associated with FFBF. The nomogram concordance index was 0.7 for FFBF in external validation. Conclusions: We present an externally validated contemporary nomogram which can estimate individual patient outcomes after PSMA-PET guided sRT. Positive lymph nodes on PSMA-PET seem to be a new risk factor for BR after sRT.
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Affiliation(s)
| | | | - Ali Janbain
- AP-HP Centre – Université Paris Cité, Paris, France
| | - Iosif Strouthos
- e)Department of Radiation Oncology, German Oncology Center, University Hospital of the European University, Limassol, Cyprus
| | - Andrea Farolfi
- Division of Nuclear Medicine, IRCCS Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy
| | - Stefan Koerber
- Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jan Peeken
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
| | - Marco Vogel
- l)Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Munich, Germany
| | - Konstantinos Ferentinos
- Department of Radiation Oncology, German Oncology Center, University Hospital of the European University, Limassol, Cyprus
| | - Mohamed Shelan
- Department of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Anca L. Grosu
- Department of Radiation Oncology, Medical Center – University of Freiburg, Faculty of Medicine, Freiburg, Germany
| | - Stephanie Kroeze
- Department of Radiation Oncology, University Hospital Zürich, University of Zurich, Zurich, Switzerland
| | | | - Stefano Fanti
- Nuclear Medicine, IRCCS, Azienda Ospedaliero-Universitaria Di Bologna, Bologna, Italy., Bologna, Italy
| | - George Hruby
- Royal North Shore Hospital, St Leonards, Australia
| | - Sophia Scharl
- Department of Radiation Oncology, University Hospital Ulm, Ulm, Germany
| | | | - Christoph Henkeberens
- Department of Radiotherapy and Special Oncology, Medical School Hannover, Hannover, Germany
| | - Louise Emmett
- Department of Theranostics and Nuclear Medicine, St Vincent's Hospital; Faculty of Medicine, UNSW, Sydney, NSW, Australia
| | - Nina-Sophie Hegemann
- Department of Radiation Oncology, Klinikum rechts der Isar, Technical University of Munich (TUM), Germany, Munich, Germany
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Janbain A, Reynès C, Assaghir Z, Zeineddine H, Sabatier R, Journot L. TopoFun: a machine learning method to improve the functional similarity of gene co-expression modules. NAR Genom Bioinform 2021; 3:lqab103. [PMID: 34761220 PMCID: PMC8573820 DOI: 10.1093/nargab/lqab103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 09/22/2021] [Accepted: 10/13/2021] [Indexed: 11/14/2022] Open
Abstract
A comprehensive, accurate functional annotation of genes is key to systems-level approaches. As functionally related genes tend to be co-expressed, one possible approach to identify functional modules or supplement existing gene annotations is to analyse gene co-expression. We describe TopoFun, a machine learning method that combines topological and functional information to improve the functional similarity of gene co-expression modules. Using LASSO, we selected topological descriptors that discriminated modules made of functionally related genes and random modules. Using the selected topological descriptors, we performed linear discriminant analysis to construct a topological score that predicted the type of a module, random-like or functional-like. We combined the topological score with a functional similarity score in a fitness function that we used in a genetic algorithm to explore the co-expression network. To illustrate the use of TopoFun, we started from a subset of the Gene Ontology Biological Processes (GO-BPs) and showed that TopoFun efficiently retrieved genes that we omitted, and aggregated a number of novel genes to the initial GO-BP while improving module topology and functional similarity. Using an independent protein-protein interaction database, we confirmed that the novel genes gathered by TopoFun were functionally related to the original gene set.
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Affiliation(s)
- Ali Janbain
- IGF, Univ Montpellier, CNRS, INSERM, Montpellier 34094, France
| | | | - Zainab Assaghir
- Applied Mathematics Department, Lebanese University, Beirut 1003, Lebanon
| | - Hassan Zeineddine
- Applied Mathematics Department, Lebanese University, Beirut 1003, Lebanon
| | - Robert Sabatier
- IGF, Univ Montpellier, CNRS, INSERM, Montpellier 34094, France
| | - Laurent Journot
- IGF, Univ Montpellier, CNRS, INSERM, Montpellier 34094, France
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