BERKELEY, CA (UroToday.com) - This work aimed at developing and evaluating an automated method for the detection of two imaging biomarkers, both of which are assumed to reflect skeletal tumor burden: the bone scan index (BSI) and lesion count. Bone scan is the method used most commonly to confirm presence or absence of bone metastases in patients with advanced prostate cancer. The method also allows for quantitative assessments which might be useful for the monitoring of disease progression or pharmacological effects. However, manual image reading and interpretation of the intensity and size of metastatic lesions in such a quantitative manner can be both tedious and subjective (reader dependent) - aspects that are overcome by the automated method.
In high-risk and metastatic prostate cancer, BSI has been found to be associated with patient survival and to correlate with other biomarkers of disease burden while adding independent prognostic information.[1, 2, 3, 4] Further, patients stratified by BSI have been observed to differ significantly in disease severity, disease progression rate, and survival.[4, 5, 6] From this follows that BSI could act as a valuable prognostic tool in patients with advanced prostate cancer and be useful for stratifying such patients entering treatment protocols. Moreover, changes in BSI induced by immuno- or chemotherapy seem to be associated with overall survival in patients with metastatic castration-resistant prostate cancer[3, 5, 7] – findings that were further supported by this study.
The favorable current situation in metastatic castration-resistant prostate cancer (mCRPC) with several newly approved therapies, and yet other therapies in development, has generated the option for personalized patient care. However, due to the lack of validated predictive biomarkers, selecting a priori “the right drug for the right patient” is not (yet) feasible. Instead, personalized patient care is accomplished by disease progression-controlled therapy switches. The management approach requires frequent clinical monitoring over sufficiently long periods of treatment to allow for the therapeutic effects to set in and become detectable. In this context, it is envisaged that BSI and lesion count could make valuable contributions to the array of biomarkers needed for treatment response monitoring in mCRPC.
The need for structured validation processes that no longer rely on long and resource-intense clinical trials in order to ensure effective introduction of imaging biomarkers into routine care to the benefit of patients was identified recently by the European Alliance for Personalised Medicine. This insight is in line with currently adopted views on quantitative imaging biomarkers which could improve routine clinical care and speed the development of new therapies for unmet medical needs. The emergence of new validated imaging biomarkers suffers, however, from complex regulatory pathways and unclear requirements on which data need to be collected to support the different pathways most efficiently, given the time and cost-intensive nature of doing so.
In summary, it is hoped that this work on two imaging biomarkers will contribute to improved future management of patients with mCRPC so as for them to gain maximal clinical benefit out of established as well as new therapies.
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Prof. Anders Bjartell, MD, PhD and Prof. Lars Edenbrandt, MD, PhD, et al. as part of Beyond the Abstract on UroToday.com. This initiative offers a method of publishing for the professional urology community. Authors are given an opportunity to expand on the circumstances, limitations etc... of their research by referencing the published abstract.
Department of Molecular and Clinical Medicine, Sahlgrenska Academy at the University of Gothenburg, Gothenburg SE 413 45, Sweden
Department of Clinical Sciences, Lund University, Malmö, Sweden
EXINI Diagnostics AB, Lund, Sweden
Progression of bone metastases in patients with prostate cancer - Automated detection of new lesions and calculation of bone scan index - Abstract
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