关键词: abiraterone androgen receptor pathway inhibitors darolutamide docetaxel metastatic castrate sensitive prostate cancer triplet therapy

Mesh : Male Humans Prostatic Neoplasms / therapy Docetaxel / therapeutic use Androgen Antagonists / therapeutic use Standard of Care Abiraterone Acetate / therapeutic use

来  源:   DOI:10.3390/curroncol30040332   PDF(Pubmed)

Abstract:
The treatment paradigm for metastatic castrate-sensitive prostate cancer (mCSPC) has evolved rapidly in the past decade with the approval of several life-prolonging therapies including docetaxel chemotherapy and multiple androgen receptor pathway inhibitors (ARPI) in combination with androgen deprivation therapy (ADT). Recently reported phase-three trials have demonstrated a survival benefit of upfront triplet therapy with ADT, docetaxel plus either abiraterone acetate or darolutamide when compared to ADT plus docetaxel alone. However, multiple questions including the incremental benefit of docetaxel to a combination of ADT and ARPI, the timing of ARPI, optimal patient selection for triplet therapy and clinical and genomic biomarkers still remain to be answered. Moreover, real-world data suggest suboptimal treatment intensification with many patients treated with ADT alone highlighting challenges in implementation. In this article, we review the phase-three data associated with triplet therapy in mCSPC. We also discuss the knowledge gaps that exist despite the completion of these studies and how ongoing studies are likely to change the paradigm in the near future. Finally, we provide a simple algorithm based on current data that clinicians can use in daily practice to select patients for appropriate treatment strategies.
摘要:
转移性去势敏感性前列腺癌(mCSPC)的治疗模式在过去十年中迅速发展,并获得了几种延长寿命的疗法的批准,包括多西他赛化疗和多种雄激素受体途径抑制剂(ARPI)与雄激素剥夺疗法(ADT)。最近报道的第三阶段试验已经证明了ADT前期三联疗法的生存益处,与单独的ADT加多西他赛相比,多西他赛加醋酸阿比特龙或达鲁他胺。然而,多个问题,包括多西他赛对ADT和ARPI组合的增量益处,ARPI的时机,三联疗法以及临床和基因组生物标志物的最佳患者选择仍有待回答.此外,现实世界的数据表明,许多患者仅接受ADT治疗,强化治疗效果欠佳,突出了实施过程中的挑战.在这篇文章中,我们回顾了mCSPC中与三联疗法相关的第三阶段数据.我们还讨论了尽管完成了这些研究,但仍存在的知识差距,以及正在进行的研究如何可能在不久的将来改变范式。最后,我们提供了一种基于当前数据的简单算法,临床医生可以在日常实践中使用该算法来选择患者采取适当的治疗策略.
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