不适合移植的大 B 细胞淋巴瘤二线使用 axicabtagene ciloleucel:ALYCANTE 最终分析
Second-line axicabtagene ciloleucel in large B-cell lymphoma ineligible for transplantation: ALYCANTE final analysis.
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.
Chemotherapy-Sparing Strategies in Follicular Lymphoma: Emerging Targeted and Immune-Based Approaches.
分数与星级只用于站内排序 —— 不代表疗效、安全性或个人适用性。
滤泡性淋巴瘤(FL)传统上被视为惰性但无法治愈的恶性肿瘤。随着无化疗治疗策略出现,其治疗格局正经历重大变化。这些新方法挑战了传统的化疗范式,为初诊及复发/难治性(RR)FL患者提供了有前景的替代方案。在这些创新疗法中,双特异性抗体(BsAb)显示出令人瞩目的疗效,并具有门诊给药、总体安全性易于管理等实际优势。嵌合抗原受体(CAR)T细胞疗法进一步扩充了治疗选择,在经多线治疗及高危人群中取得前所未有的缓解率,但其应用仍受流程复杂和成本高昂限制。其他靶向药物,如zeste同源物2增强子(EZH2)抑制剂、来那度胺和布鲁顿酪氨酸激酶(BTK)抑制剂,也为无化疗治疗作出重要贡献,尤其是在可能增强临床获益的联合方案中。尽管取得这些进展,仍存在若干挑战。早期疾病进展(POD24)仍是FL最有力的预后决定因素之一。整合机器学习风险分层的FLIPI-C模型,在识别最可能从创新疗法中获益的高危患者方面显示出潜力。将无化疗疗法更早纳入治疗路径,可能改善这些患者的结局,同时减轻传统化疗的长期毒性。仍需通过前瞻性临床试验和真实世界证据持续验证,以确定这些疗法的最佳整合方式。
总体而言,这一不断演变的治疗范式凸显了持续创新、多学科协作和公平可及的迫切需求,从而使这类复杂疾病患者充分获益于无化疗策略。
Follicular lymphoma (FL), traditionally considered an indolent yet incurable malignancy, is experiencing a substantial evolution in its therapeutic landscape with the emergence of chemo-free treatment strategies. These novel approaches challenge conventional chemotherapy-based paradigms and offer promising alternatives for both newly diagnosed and relapsed/refractory (RR) FL patients. Among these innovations, bispecific antibodies (BsAbs) have demonstrated compelling efficacy while providing practical advantages, including outpatient administration and generally manageable safety profiles. Chimeric antigen receptor (CAR) T-cell therapies have further expanded the therapeutic armamentarium, achieving unprecedented response rates in heavily pretreated and high-risk populations, although their implementation remains limited by logistical complexity and high associated costs.
Additional targeted agents-such as Enhancer of zeste homolog 2 (EZH2) inhibitors, lenalidomide, and Bruton tyrosine kinase (BTK) inhibitors-also contribute meaningfully to chemo-free treatment options, particularly within combination regimens that may enhance clinical benefit. Despite these advances, several challenges persist. Early disease progression (POD24) remains one of the most powerful prognostic determinants in FL.
The FLIPI-C model, incorporating machine-learning-derived risk stratification, has shown promise in identifying high-risk patients who may benefit most from innovative approaches. Introducing chemo-free therapies earlier in the treatment algorithm may improve outcomes for these patients while mitigating the long-term toxicities associated with conventional chemotherapy. Ongoing validation through prospective clinical trials and real-world evidence will be essential to define the optimal integration of these therapies.
Overall, this evolving paradigm highlights the urgent need for continued innovation, multidisciplinary collaboration, and equitable access to ensure that the full potential of chemo-free strategies can be realized for patients with this complex disease.
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