Genomic classifiers in personalized prostate cancer radiotherapy approaches - a systematic review and future perspectives based on international consensus
Abstract
BACKGROUND
Current risk-stratification systems for prostate cancer (PCa) do not sufficiently reflect the disease heterogeneity. Genomic classifiers (GC) enable improved risk-stratification after surgery, but less data exists for patients treated with definitive radiotherapy (RT) or RT in oligo-/metastatic disease stages. In order to guide future perspectives of GCs for RT, we conducted (i) a systematic review on the evidence of GCs for patients treated with RT and (ii) a survey of experts using the DELPHI method, addressing the role of GCs in personalized treatments to identify relevant fields of future clinical and translational research.
METHODS
We performed a systematic review and screened ongoing clinical trials on "clinicaltrials.gov". Based on these results a multidisciplinary international team of experts received an adapted DELPHI method survey. 31 and 30 experts answered round 1 and round 2, respectively. Questions with ≥ 75% agreement were considered as relevant and included into the qualitative synthesis.
RESULTS
Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT settings is emerging. Experts used GCs in PCa patients with extensive metastases (30%), in postoperative settings (27%) and newly diagnosed PCa (23%). 47% of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification…
How strong is the evidence?
Evidence Hub reads this as a systematic review, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid.
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