CAR-T(CAR-T)细胞疗法在非肿瘤性疾病中的应用
Chimeric antigen receptor T (CAR-T) cell therapy in non-oncological diseases.
CAR-T(CAR-T)细胞在血液系统恶性肿瘤中的应用推动了这种免疫治疗形式的显著进展。
CELL INTELLIGENCE · 肿瘤细胞治疗研究
肿瘤细胞治疗研究
英文原题:The effect of centralising novel cell therapies for solid cancers - a health systems planning model for Europe.
The effect of centralising novel cell therapies for solid cancers - a health systems planning model for Europe.
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实体癌细胞治疗服务在欧洲的本地化需要在可及性、公平性和临床安全性之间取得平衡。这种建模方法可应用于所有欧洲卫生系统,以了解集中化实施前的影响,从而为优化服务设计和缓解措施提供信息。
将细胞疗法整合用于实体癌需要集中服务以确保高质量,并给所有医疗系统带来独特挑战。在这项基于全国人群的研究中,我们以英国 NHS 为原型,模拟了不同集中化情景对出行时间、公平性和医院容量的影响,为欧洲的规划提供参考。
我们在2016年至2018年间,在139家NHS医院中确定了10,050名接受全身治疗的转移性结直肠癌患者。七个假设情景A-G将细胞治疗服务集中到15至51个中心。例如,A)51个综合癌症中心;或D)15个CAR-T 中心。对于每个情景,根据患者偏好使用条件逻辑回归模型将患者重新分配到指定的专科中心;使用地理信息系统计算旅行时间;多变量线性回归模型估计了不同人口特征下旅行负担的变化。
对于每种集中化情景,预测旅行时间均增加3倍。将服务集中至综合性癌症中心(情景A)对旅行时间的影响最小(额外增加40.9分钟);72%的患者仍可在1小时内到达专科服务。集中至现有CAR-T 中心(情景D)导致44%的患者无法在1小时内到达相关设施。在5种情景中,额外的旅行负担对低社会经济群体的影响尤为严重。
Integrating cell therapies for solid cancers requires centralising services to ensure high quality and poses unique challenges for all healthcare systems. In this national population-based study, we modelled the effect of different centralisation scenarios in the English NHS on travel times, equity and hospital capacity as an archetype to inform European planning.
We identified 10,050 patients treated with systemic therapy for metastatic colorectal cancer in 139 NHS hospitals between 2016 and 2018. Seven hypothetical scenarios A-G centralised cell therapy services to between 15 and 51 centres. For example to A) 51 comprehensive cancer centres; or D) 15 CAR-T centres. For each scenario reallocation of patients to the designated specialist centre was based on patient preferences using conditional logistic regression models; travel times were calculated using a geographic information system; multivariable linear regression models estimated the variation in travel burden across demographic characteristics. KEY FINDINGS: For each centralisation scenario there was a 3 times increase in predicted travel time. Centralising services to comprehensive cancer centres (scenario A) had the smallest impact on travel time (additional 40.9 min); 72 % of patients remained within 1 h of specialist services. Centralisation to existing CAR-T centres (scenario D) resulted in 44 % of patients not having access to a facility within 1 h. For 5 scenarios additional travel burden disproportionately affected low socioeconomic groups.
Localisation of solid cancer cell therapy services in Europe requires a balance between access, equity, and clinical safety. This modelling approach can be used in all European health systems, to understand the pre-implementation impact of centralisation to inform optimum service design and mitigations.
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