Abstract
Background
Up to 90% of men with metastatic castration-resistant prostate cancer (mCRPC) will have a distribution of disease that includes bone metastases demonstrated on a Technetium-99m (99mTc-MDP) bone scan. The Prostate Cancer Working Group 2 and 3 Consensus Criteria standardized the criteria for assessing progression based on the development of new lesions. These criteria have been recognized by regulatory authorities for drug approval. The bone scan index (BSI) is a method to quantitatively measure the burden of bony disease, and can assess both disease progression and regression. The automated BSI (aBSI) is a method of computer analysis to assess BSI, and is being qualified as a clinical trials endpoint.
Methods
Manual searching was used to identify the literature on BSI and aBSI. We summarize the most relevant aspects of the retrospective and prospective studies evaluating aBSI measurements, and provide a critical discussion on the potential advantages and caveats of aBSI.
Results
The development of neural artificial networks (EXINI boneBSI) to automatically determine the BSI reduces the turnaround time for assessing BSI with high reproducibility and accuracy. Several studies showed that the concordance between aBSI and BSI, as well as the interobserver concordance of aBSI, was >0.95. In a phase 3 assessment of aBSI, a doubling value increased the risk of death in 20%, pre-treatment aBSI values independently correlated with overall survival (OS) and time to symptomatic progression. Retrospective studies suggest that a decrease in aBSI after treatment may correlate with higher survival when compared with increasing aBSI.
Conclusions
aBSI provides a quantitative measurement that is feasible, reproducible, and in analyses to date correlates with OS and symptomatic progression. These findings support the aBSI to risk-stratify men with mCRPC for clinical trial enrollment. Future studies quantifying aBSI change over time as an intermediate endpoint for evaluating new systemic therapies are needed.
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We declare the following conflicts of interest. Dr. Mota: none relevant to this manuscript. Dr. Armstrong: none relevant to this manuscript. Dr. Larson reports receiving commercial research grants from Genentech, Inc., WILEX AG, Telix Pharmaceuticals Limited, and Regeneron Pharmaceuticals, Inc.; holding ownership interest/equity in Voreyda Theranostics Inc. and Elucida Oncology Inc., and holding stock in ImaginAb, Inc. SML is the inventor and owner of issued patents both currently unlicensed and licensed by MSK to Samus Therapeutics, Inc. and Elucida Oncology, Inc. SML is or has served as a consultant to Cynvec LLC, Eli Lilly & Co., Prescient Therapeutics Limited, Advanced Innovative Partners, LLC, Gerson Lehrman Group, Progenics Pharmaceuticals, Inc., and Janssen Pharmaceuticals, Inc. Dr. Fox: None relevant to this manuscript. Dr. Morris reports unpaid consultant for Bayer, Endocyte, Progenics, Janssen; paid consultant for Oric Pharmaceuticals and Advance Acclerator Applications; research funding: Genentech/Roch, Endocyte, Bayer, Progenics, Astellas, Corcept.
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Mota, J.M., Armstrong, A.J., Larson, S.M. et al. Measuring the unmeasurable: automated bone scan index as a quantitative endpoint in prostate cancer clinical trials. Prostate Cancer Prostatic Dis 22, 522–530 (2019). https://doi.org/10.1038/s41391-019-0151-4
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DOI: https://doi.org/10.1038/s41391-019-0151-4
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