Multidisciplinary expert consensus on treatment intensification in metastatic androgen pathway modulation-sensitive prostate cancer: a case-based RAND/UCLA analysis.

Authors

Ángel Borque-Fernando, Teresa Alonso-Gordoa, María José Juan-Fita, Fernando Lopez Campos, Daniel Adolfo Pérez-Fentes, Antoni Vilaseca, Cristina Moretones Agut, Paola Usán, Pablo Maroto Rey

Published in

Drugs in context. Volume 15. Epub Sep 07, 2026.

Abstract

Metastatic androgen pathway modulation (mAPM)-sensitive prostate cancer, formerly termed metastatic hormone-sensitive prostate cancer, is a clinically heterogeneous disease in which treatment intensification decisions are guided by metastatic volume and timing of presentation. However, increasing use of advanced imaging and molecular profiling has revealed prognostic scenarios that are not adequately addressed by current algorithms. This study presents a structured multidisciplinary expert consensus exercise, rather than primary clinical research, applying the RAND/UCLA Appropriateness Method to evaluate systemic treatment intensification strategies in mAPM-sensitive prostate cancer. Four anonymized real-world clinical cases representing key prognostic constellations - metachronous/synchronous disease, low/high metastatic burden - were assessed. Panellists rated the appropriateness of doublet therapy versus triplet therapy, including tailored 'what-if' variations, through two rounds of anonymous voting with structured discussion. The resulting assessments reflect structured expert judgement integrating available evidence with clinical experience. The panel identified metastatic pattern, particularly the presence and type of visceral involvement, disease dynamics, patient fitness and imaging context as dominant drivers of treatment selection. These findings should be interpreted as consensus-based appropriateness assessments rather than evidence-based treatment recommendations. They support a personalized, multidisciplinary approach to mAPM-sensitive prostate cancer management, emphasizing expert integration of prognostic factors beyond volume-based classifications in clinical scenarios where high-level evidence is limited or not directly applicable.

PMID:
42741748
Bibliographic data and abstract were imported from PubMed on 15 Sep 2026.

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