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非小细胞肺癌(NSCLC)疾病负担评估:基于生存模型的Meta分析研究

Assessment of NSCLC disease burden: A survival model-based meta-analysis study

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影响因子:4.1
分区:生物学3区 / 生化与分子生物学3区
发表日期:2024 Dec
作者: Nataliya Kudryashova, Boris Shulgin, Nikolai Katuninks, Victoria Kulesh, Gabriel Helmlinger, Kirill Zhudenkov, Kirill Peskov
DOI: 10.1016/j.csbj.2024.09.012

摘要

本文采用整合生存模型的Meta分析方法量化NSCLC的疾病负担。利用公共数据来源的汇总生存数据,参数化模型以涵盖早期及晚期NSCLC不同阶段,结合化疗、靶向治疗及免疫治疗。在多样化患者群体中,根据不同分层和初始条件预测总生存期(OS)。通过评估药物经济学指标(生存年数(LYG)和质量调整生命年(QALY))来量化专业治疗和早期检测改善带来的益处。模拟结果显示,针对晚期NSCLC的创新疗法的引入,使中位生存期增加了8.1个月(95%CI:5.9, 10.0),相应的LYG增加了2.9个月(95%CI:2.2, 3.6),QALY增加了1.65个月(95%CI:1.2, 2.0)。在整个患者群体中改善早期癌症检测的情景下,中位生存期最多增加17.6个月(95%CI:16.5, 19.0),LYG和QALY分别增加6.2个月(95%CI:5.9, 6.4)和6.6个月(95%CI:6.4, 6.7),传统与优化治疗方案的获益可达相应的15.7个月(95%CI:14.8, 16.6)和5.2个月(95%CI:4.9, 5.4)在LYG,以及相应的月数在QALY中体现。该整合模型平台旨在描绘癌症负担,能够精准量化引入专业治疗和早期检测的总效益,为临床决策和公共卫生策略提供科学依据。

Abstract

We present a meta-analytics approach to quantify NSCLC disease burden by integrative survival models. Aggregated survival data from public sources were used to parameterize the models for early as well as advanced NSCLC stages incorporating chemotherapies, targeted therapies, and immunotherapies. Overall survival (OS) was predicted in a heterogeneous patient cohort based on various stratifications and initial conditions. Pharmacoeconomic metrics (life years gained (LYG) and quality-adjusted life years (QALY) gained), were evaluated to quantify the benefits of specialized treatments and improved early detection of NSCLC. Simulations showed that the introduction of novel therapies for the advanced NSCLC sub-group increased median survival by 8.1 months (95 % CI: 5.9, 10.0), with corresponding gains of 2.9 months (95 % CI: 2.2, 3.6) in LYG and 1.65 months (95 % CI: 1.2, 2.0) in QALY. Scenarios representing improved detection of early cancer in the whole patient cohort, revealed up to 17.6 (95 % CI: 16.5, 19.0) and 15.7 months (95 % CI: 14.8, 16.6) increase in median survival, with respective gains of 6.2 months (95 % CI: 5.9, 6.4) and 5.2 months (95 % CI: 4.9, 5.4) in LYG and 6.6 months (95 % CI: 6.4, 6.7) and 6.0 months (95 % CI: 5.9, 6.2) in QALY for conventional and optimal treatment. This integrative modeling platform, aimed at characterizing cancer burden, allows to precisely quantify the cumulative benefits of introducing specialized therapies into the treatment schemes and survival prolongation upon early detection of the disease.