Mariana Reza1, Manfred Wirth2, Teuvo Tammela3, Virgilio Cicalese4, Francisco Gomez Veiga5, Peter Mulders6, Kurt Miller7, Andrea Tubaro8, Frans Debruyne9, Anup Patel10, Christien Caris11, Wim Witjes11, Ola Thorsson1, Per Wollmer1, Lars Edenbrandt12, Mattias Ohlsson13, Elin Trägårdh1, Anders Bjartell14. 1. Department of Clinical Physiology, Translational Medicine, Malmö, Lund University, Malmö, Sweden. 2. Department of Urology, University Clinic Carl Gustav Carus, Dresden, Germany. 3. Department of Urology, Tampere University Hospital and University of Tampere, Tampere, Finland. 4. Department of Urology, Azienda Ospedaliera S. Giuseppe Moscati, Avellino, Italy. 5. Urology Department and Kidney Transplant Unit, Translational Research Group of Urology GITUR-IBSAL, Salamanca University Hospital, Salamanca, Spain. 6. Department of Urology, Radboud University, Nijmegen Medical Centre, Nijmegen, The Netherlands. 7. Department of Urology, Charité, Universitätsmedizin, Berlin, Germany. 8. Department of Urology, Sant'Andrea Hospital, Sapienza University of Rome, Rome, Italy. 9. Department of Urology, Andros Clinic, Arnhem, The Netherlands. 10. London, UK. 11. European Association of Urology, Research Foundation (EAU RF), Arnhem, The Netherlands. 12. Department of Clinical Physiology, Translational Medicine, Malmö, Lund University, Malmö, Sweden; Region Västra Götaland, Sahlgrenska University Hospital, Department of Clinical Physiology, Gothenburg, Sweden. 13. Department of Astronomy and Theoretical Physics, Lund University, Lund, Sweden. 14. Department of Urology, Skåne University Hospital, Malmö, Lund University, Sweden. Electronic address: anders.bjartell@med.lu.se.
Abstract
BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostate cancer, it would be of value to use objective tools to monitor the status of bone metastases during clinical trials. Automated Bone Scan Index (aBSI) based on artificial intelligence has been proposed as an imaging biomarker for the quantification of skeletal metastases from bone scintigraphy. OBJECTIVE: To investigate how an increase in aBSI during treatment may predict clinical outcome in a randomised controlled clinical trial including patients with high-risk prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively selected all patients from the Zometa European Study (ZEUS)/SPCG11 study with image data of sufficient quality to allow for aBSI assessment at baseline and at 48-mo follow-up. Data on aBSI were obtained using EXINIboneBSI software, blinded for clinical data and randomisation of zoledronic acid treatment. Data on age, overall survival (OS), and prostate-specific antigen (PSA) at baseline and upon follow-up were available from the study database. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Association between clinical parameters and aBSI increase during treatment was evaluated using Cox proportional-hazards regression models, Kaplan-Meier estimates, and log-rank test. Discrimination between prognostic variables was assessed using the concordance index (C-index). RESULTS AND LIMITATIONS: In this cohort, 176 patients with bone metastases and a change in aBSI from baseline to follow-up of ≤0.3 had a significantly longer median survival time than patients with an aBSI change of >0.3 (p<0.0001). The increase in aBSI was significantly associated with OS (p<0.01 and C-index=0.65), while age and PSA change were not. CONCLUSIONS: The aBSI used as an objective imaging biomarker predicted outcome in prostate cancer patients in the ZEUS/SPCG11 study. An analysis of the change in aBSI from baseline to 48-mo follow-up represents a valuable tool for prognostication and monitoring of prostate cancer patients with bone metastases. PATIENT SUMMARY: The increase in the burden of skeletal metastases, as measured by the automated Bone Scan Index (aBSI), during treatment was associated with overall survival in patients from the Zometa European Study/SPCG11 study. The aBSI may be a useful tool also in monitoring prostate cancer patients with newly developed bone metastases.
BACKGROUND: Owing to the large variation in treatment response among patients with high-risk prostate cancer, it would be of value to use objective tools to monitor the status of bone metastases during clinical trials. Automated Bone Scan Index (aBSI) based on artificial intelligence has been proposed as an imaging biomarker for the quantification of skeletal metastases from bone scintigraphy. OBJECTIVE: To investigate how an increase in aBSI during treatment may predict clinical outcome in a randomised controlled clinical trial including patients with high-risk prostate cancer. DESIGN, SETTING, AND PARTICIPANTS: We retrospectively selected all patients from the Zometa European Study (ZEUS)/SPCG11 study with image data of sufficient quality to allow for aBSI assessment at baseline and at 48-mo follow-up. Data on aBSI were obtained using EXINIboneBSI software, blinded for clinical data and randomisation of zoledronic acid treatment. Data on age, overall survival (OS), and prostate-specific antigen (PSA) at baseline and upon follow-up were available from the study database. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS: Association between clinical parameters and aBSI increase during treatment was evaluated using Cox proportional-hazards regression models, Kaplan-Meier estimates, and log-rank test. Discrimination between prognostic variables was assessed using the concordance index (C-index). RESULTS AND LIMITATIONS: In this cohort, 176 patients with bone metastases and a change in aBSI from baseline to follow-up of ≤0.3 had a significantly longer median survival time than patients with an aBSI change of >0.3 (p<0.0001). The increase in aBSI was significantly associated with OS (p<0.01 and C-index=0.65), while age and PSA change were not. CONCLUSIONS: The aBSI used as an objective imaging biomarker predicted outcome in prostate cancer patients in the ZEUS/SPCG11 study. An analysis of the change in aBSI from baseline to 48-mo follow-up represents a valuable tool for prognostication and monitoring of prostate cancer patients with bone metastases. PATIENT SUMMARY: The increase in the burden of skeletal metastases, as measured by the automated Bone Scan Index (aBSI), during treatment was associated with overall survival in patients from the Zometa European Study/SPCG11 study. The aBSI may be a useful tool also in monitoring prostate cancer patients with newly developed bone metastases.
Authors: Adnan Ali; Alex P Hoyle; Christopher C Parker; Christopher D Brawley; Adrian Cook; Claire Amos; Joanna Calvert; Hassan Douis; Malcolm D Mason; Gerhardt Attard; Mahesh K B Parmar; Matthew R Sydes; Nicholas D James; Noel W Clarke Journal: Eur Urol Oncol Date: 2020-06-24