There are many ongoing randomised trials of promising therapies for metastatic hormone-sensitive prostate cancer (mHSPC), but standard systematic reviews may not synthesise these in a timely or reliable way. We demonstrate how a novel approach to evidence synthesis is being used to speed up and improve treatment evaluations for mHSPC. This more prospective, dynamic, and collaborative approach to systematic reviews of both trial results and individual participant data (IPD) is helping in establishing quickly and reliably which treatments are most effective and for which men. However, mHSPC is a complex disease and trials can be lengthy. Thus, parallel efforts will synthesise further IPD to identify early surrogate endpoints for overall survival and prognostic factors, to reduce the duration and improve the design of future trials. The STOPCAP M1 repository of IPD will be made available to other researchers for tackling new questions that might arise. The associated global, collaborative forum will aid strategic and harmonised development of the next generation of mHSPC trials (STOPCAP M1; http://www.stopcapm1.org). PATIENT SUMMARY: We report how a worldwide research effort will review results and anonymised data from advanced prostate cancer trials in new and different ways. We will work out, as quickly as possible, which advanced prostate cancer treatments are best and for which men. We will also find which measures of prostate cancer control and which cancer and patient characteristics can be used to shorten and improve trials of newer treatments. Finally, we describe how the data will help answer new questions about advanced prostate cancer and its treatments.
European urology focus. 2019 Jan 31 [Epub ahead of print]
Jayne F Tierney, Claire L Vale, Wendy R Parelukar, Larysa Rydzewska, Susan Halabi
MRC Clinical Trials Unit at University College London, London, UK. Electronic address: ., MRC Clinical Trials Unit at University College London, London, UK., Canadian Cancer Trials Group, Queen's University, Kingston, ON, Canada., Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA.