The high biological and clinic heterogeneity of the disease has fostered efforts to improve patients’ selection: choosing the right treatment for the right patient is the ultimate goal of all HR PCa research. During the last years, new tools became available, allowing for better selection and counseling of patients potentially curable with a single-modality primary treatment, but also useful to choose who is more likely to benefit from multimodality treatment, after a primary intervention.
A multicenter group (EMPaCT) 12 has taken into consideration a NCCN high risk population and further stratified RP outcomes in three clusters: a good prognosis subgroup (one single high-risk defining factor), an intermediate prognosis subgroup (PSA > 20 …show more content…
A gene panel model, developed in a Mayo Clinic research study, showed is role as a predictive outcome tool in men with high risk features at RP 16. Karnes et al 17 utilized a similar case-control study in high-risk men after RP and investigated tumor protein levels of MIB-1 (Ki-67;proliferation index), TOP2a (DNA topoisomerase 2) and the ERG or fusion status (transcription factor of TMPRSS2-ETS fusion), finding associations between these markers and cancer-specific …show more content…
Decision curves showed that the genomic classifier net benefit exceeded that of clinical-only models, being the predominant predictor of metastasis on multivariable analysis 19.
A 2013 study by Schubert et al 20 has taken into consideration the role of distinct micro-RNA expression profiles in HR PCa progression, finding that let-7b, a tumor suppressor miRNA, has an impact as an independent prognostic marker for biochemical relapse and clinical failure identified let-7b as prognostic biomarker in high-risk PCa, with a potential role in improving individual therapy for high-risk PCa patients.
These finding underscore the potential role of biomarkers in improving PCa decision-making. To be useful in clinical practice, however, a biomarker study should address a population with precise clinical needs: in the post-surgical setting, in particular, the aim is to improve our ability to identify prognostic and predictive factors in order to provide tailored treatment to our
A multicenter group (EMPaCT) 12 has taken into consideration a NCCN high risk population and further stratified RP outcomes in three clusters: a good prognosis subgroup (one single high-risk defining factor), an intermediate prognosis subgroup (PSA > 20 …show more content…
A gene panel model, developed in a Mayo Clinic research study, showed is role as a predictive outcome tool in men with high risk features at RP 16. Karnes et al 17 utilized a similar case-control study in high-risk men after RP and investigated tumor protein levels of MIB-1 (Ki-67;proliferation index), TOP2a (DNA topoisomerase 2) and the ERG or fusion status (transcription factor of TMPRSS2-ETS fusion), finding associations between these markers and cancer-specific …show more content…
Decision curves showed that the genomic classifier net benefit exceeded that of clinical-only models, being the predominant predictor of metastasis on multivariable analysis 19.
A 2013 study by Schubert et al 20 has taken into consideration the role of distinct micro-RNA expression profiles in HR PCa progression, finding that let-7b, a tumor suppressor miRNA, has an impact as an independent prognostic marker for biochemical relapse and clinical failure identified let-7b as prognostic biomarker in high-risk PCa, with a potential role in improving individual therapy for high-risk PCa patients.
These finding underscore the potential role of biomarkers in improving PCa decision-making. To be useful in clinical practice, however, a biomarker study should address a population with precise clinical needs: in the post-surgical setting, in particular, the aim is to improve our ability to identify prognostic and predictive factors in order to provide tailored treatment to our