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  5. Development and Validation of Nomograms to Predict Outcome Following LuPSMA Radionuclide Treatment for Metastatic Castration-Resistant Prostate Cancer: A Multicenter International Study

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Article
en
2021

Development and Validation of Nomograms to Predict Outcome Following LuPSMA Radionuclide Treatment for Metastatic Castration-Resistant Prostate Cancer: A Multicenter International Study

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en
2021
DOI: 10.2139/ssrn.3798566

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Shahneen Sandhu
Shahneen Sandhu

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Andrei Gafita
Jérémie Calais
Tristan Grogan
+22 more

Abstract

Background: 177 Lu-prostate-specific membrane antigen (LuPSMA) is a novel targeted treatment with activity and safety in men with mCRPC. We aimed to develop prognostic models to assist in identifying men with mCRPC who are most likely to benefit from undergoing LuPSMA and hence improve clinical implementation.Methods: Data from 270 men with mCRPC treated with LuPSMA under phase II clinical trials or compassionate use access programs in Europe, USA, and Australia were used. The outcome for prognostication was overall survival (OS) and prostate-specific antigen progression-free survival (PSA-PFS). Patients were divided into development (n=196) and validation (n=74) cohort. Putative parameters included 17 predefined clinicopathologic and screening PSMA PET/CT derived variables. Adapted least absolute shrinkage and selection operator (LASSO) was used to select prognostic variables in the final models. Models discrimination was measured on the validation cohort by the concordance index and calibration plots.Results: Patient characteristics and outcomes were well balanced between development and validation sets. Prognostic markers selected in the models by LASSO included time since diagnosis of prostate cancer, docetaxel status, alkaline phosphatase, hemoglobin levels, and 68 Ga-PSMA-11 PET/CT parameters (miTNM classification: pelvic nodal, distant nodal, bone involvement and liver involvement status; and tumor expression by SUVmean). The concordance index of the models for OS and PSA-PFS was 0·73 and 0·68, respectively. Models were well calibrated and predictions correlated with the observed outcome. Low- and high-risk patients divided by median nomogram-predicted risk scores had significantly different OS (21·3 vs. 6·5 months; p<0·001) and PSA-PFS (6·5 vs. 2·1 months; p=0·006).Conclusion: Using an international multicenter database, we developed and externally validated models that predict outcome from LuPSMA from mCRPC. An online risk calculator is available at www.uclahealth.org/nuc/nomograms. Funding: This study was partially funded by the Prostate Cancer Foundation (17CHAL02) and the UCLA SPORE in Prostate Cancer (P50 CA092131). AG is the recipient of the Jonsson Comprehensive Cancer Center fellowship award and Dr. Christiaan Schiepers postdoctoral fellowship award. JCa is supported by the Prostate Cancer Foundation (2020 Young Investigator Award 20YOUN05, 2019 Challenge Award 19CHAL02) and the Society of Nuclear Medicine and Molecular Imaging (2019 Molecular Imaging Research Grant for Junior Academic Faculty). WPF received financial support from the German Research Foundation (Deutsche Forschungsgemeinschaft, DFG, grant FE1573/3-1 / 659216), Mercator Research Center Ruhr (MERCUR, An-2019-0001), IFORES (D/107-81260, D/107-30240), Doktor Robert Pfleger-Stiftung, and Wiedenfeld-Stiftung/Stiftung Krebsforschung Duisburg. HW received financial support from the China Scholarship Council (CSC).Declaration of Interest: JCa reports prior consulting activities outside of the submitted work for Advanced Accelerator Applications, Blue Earth Diagnostics, Curium Pharma, GE Healthcare, Janssen Pharmaceuticals, Progenics Pharmaceuticals, Radiomedix and Telix Pharmaceuticals. ME reports prior consulting activities for Blue Earth Diagnostics, Progenics Pharmaceuticals and Point Biopharma and a patent application for rhPSMA outside of the submitted work. BH reports personal fees from ABX, Bayer, Lightpoint Medical, Inc., Janssen R&D, Bristol-Myers-Squibb and Astellas and travel from AstraZeneca, Janssen R&D and Astellas, all outside the submitted work. JCz is a founder, board member, and holds equity in Sofie biosciences and Trethera Therapeutics. Intellectual property is patented by the University of California and licensed to Sofie Biosciences and Trethera Therapeutics. JCz was a consultant for Endocyte Inc. (VISION trial steering committee), Actinium Pharmaceuticals and Point Biopharma outside of the submitted work. KH reports personal fees from Bayer, personal fees and other from Sofie Biosciences, personal fees from SIRTEX, non-financial support from ABX, personal fees from Adacap, personal fees from Curium, personal fees from Endocyte, grants and personal fees from BTG, personal fees from IPSEN, personal fees from Siemens Healthineers, personal fees from GE Healthcare, personal fees from Amgen, personal fees from Novartis, personal fees from ymabs, personal fees from Bain Capital, personal fees from MPM Capital outside the submitted work. WPF was a consultant for Endocyte and BTG, and he received fees from RadioMedix and Bayer outside of the submitted work. No other potential conflict of interest relevant to this article was reported.Ethical Approval: This study was approved by the institutional review board of the University of California, Los Angeles (IRB# 19- 000896).

How to cite this publication

Andrei Gafita, Jérémie Calais, Tristan Grogan, Anna Zeldin, Boris Hadaschik, Hui Wang, Manuel Weber, Shahneen Sandhu, Clemens Kratochwil, Rouzbeh Esfandiari, Robert Tauber, Hendrik Rathke, Wesley R. Armstrong, Andrew Robertson, Pan Thin, Calogero D’Alessandria, Matthew B. Rettig, Ebrahim S. Delpassand, Uwe Haberkorn, David Elashoff, Ken Herrmann, Johannes Czernin, Prof Michael S. Hofman, Wolfgang P. Fendler, Matthias Eiber (2021). Development and Validation of Nomograms to Predict Outcome Following LuPSMA Radionuclide Treatment for Metastatic Castration-Resistant Prostate Cancer: A Multicenter International Study. , DOI: https://doi.org/10.2139/ssrn.3798566.

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Publication Details

Type

Article

Year

2021

Authors

25

Datasets

0

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Language

en

DOI

https://doi.org/10.2139/ssrn.3798566

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