TY - JOUR
T1 - Genomic Classifiers in Personalized Prostate Cancer Radiation Therapy Approaches
T2 - A Systematic Review and Future Perspectives Based on International Consensus
AU - Spohn, Simon K.B.
AU - Draulans, Cédric
AU - Kishan, Amar U.
AU - Spratt, Daniel
AU - Ross, Ashley
AU - Maurer, Tobias
AU - Tilki, Derya
AU - Berlin, Alejandro
AU - Blanchard, Pierre
AU - Collins, Sean
AU - Bronsert, Peter
AU - Chen, Ronald
AU - Pra, Alan Dal
AU - de Meerleer, Gert
AU - Eade, Thomas
AU - Haustermans, Karin
AU - Hölscher, Tobias
AU - Höcht, Stefan
AU - Ghadjar, Pirus
AU - Davicioni, Elai
AU - Heck, Matthias
AU - Kerkmeijer, Linda G.W.
AU - Kirste, Simon
AU - Tselis, Nikolaos
AU - Tran, Phuoc T.
AU - Pinkawa, Michael
AU - Pommier, Pascal
AU - Deltas, Constantinos
AU - Schmidt-Hegemann, Nina Sophie
AU - Wiegel, Thomas
AU - Zilli, Thomas
AU - Tree, Alison C.
AU - Qiu, Xuefeng
AU - Murthy, Vedang
AU - Epstein, Jonathan I.
AU - Graztke, Christian
AU - Gao, Xin
AU - Grosu, Anca L.
AU - Kamran, Sophia C.
AU - Zamboglou, Constantinos
N1 - Publisher Copyright:
© 2022 The Author(s)
PY - 2023/7/1
Y1 - 2023/7/1
N2 - 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 exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) 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. 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. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa.
AB - 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 exist for patients treated with definitive radiation therapy (RT) or RT in oligo-/metastatic disease stages. To guide future perspectives of GCs for RT, we conducted (1) a systematic review on the evidence of GCs for patients treated with RT and (2) 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. 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. Thirty-one and 30 experts answered round 1 and round 2, respectively. Questions with ≥75% agreement were considered relevant and included in the qualitative synthesis. Evidence for GCs as predictive biomarkers is mainly available to the postoperative RT setting. Validation of GCs as prognostic markers in the definitive RT setting is emerging. Experts used GCs in patients with PCa with extensive metastases (30%), in postoperative settings (27%), and in newly diagnosed PCa (23%). Forty-seven percent of experts do not currently use GCs in clinical practice. Expert consensus demonstrates that GCs are promising tools to improve risk-stratification in primary and oligo-/metastatic patients in addition to existing classifications. Experts were convinced that GCs might guide treatment decisions in terms of RT-field definition and intensification/deintensification in various disease stages. This work confirms the value of GCs and the promising evidence of GC utility in the setting of RT. Additional studies of GCs as prognostic biomarkers are anticipated and form the basis for future studies addressing predictive capabilities of GCs to optimize RT and systemic therapy. The expert consensus points out future directions for GC research in the management of PCa.
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U2 - 10.1016/j.ijrobp.2022.12.038
DO - 10.1016/j.ijrobp.2022.12.038
M3 - Review article
C2 - 36596346
AN - SCOPUS:85147803881
SN - 0360-3016
VL - 116
SP - 503
EP - 520
JO - International Journal of Radiation Oncology Biology Physics
JF - International Journal of Radiation Oncology Biology Physics
IS - 3
ER -