用于风险-收益分析的综合疗效和安全性结果的Chauhan加权轨迹分析。

IF 1.3 4区 医学 Q4 PHARMACOLOGY & PHARMACY
Utkarsh Chauhan, Daylen Mackey, John R Mackey
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引用次数: 0

摘要

分析和有效沟通治疗的疗效和毒性是风险-效益分析(RBA)的基础。需要更有效和客观的工具。我们采用Chauhan加权轨迹分析(CWTA)来进行RBA,具有较好的客观性、有效性和沟通便利性。我们使用CWTA对随机对照试验进行了1000倍的模拟,使用顺序终点来捕捉治疗疗效和治疗毒性。随机对照试验随机生成,按规定的样本量和风险比按1:1分配。我们首先研究了毒性和功效各3个级别的最简单案例模拟(3 × 3矩阵)。然后,我们模拟了晚期癌症试验的一般情况,用5种RECIST 1.1健康状态对疗效进行分级,用6点CTCAE量表对毒性进行分级,以创建6 × 5矩阵。最后,6 × 5矩阵模型应用于实际的晚期癌症剂量递增I期试验。在3 × 3最简单病例矩阵和6 × 5晚期癌症矩阵中的模拟证实了我们的假设,即具有优越疗效和毒性特征的药物与CWTA RBA的协同作用比单独使用任何一种信号具有更大的统计效力。CWTA RBA 6 × 5矩阵在仅分析CWTA有效性方面显著减少了样本量需求。尽管样本量很小,但将矩阵应用于剂量寻找I期临床试验的七个队列中的每一个队列,为试验人员主观选择的剂量提供了客观和统计上显着的验证。CWTA RBA结合了药物疗效和药物毒性的轨迹,提供了一个单一的试验统计和总结图,分析、可视化并有效地传达了临床试验的风险-收益评估。当实验药物更有效且毒性更小时,CWTA RBA比CWTA仅进行疗效分析所需的患者更少。我们的研究结果表明,CWTA RBA具有在整个药物开发途径中帮助客观有效地评估新疗法的潜力。此外,与竞争测试相比,它在可视化和传达风险-收益方面的独特优势将有助于监管审查、临床采用以及临床医生和患者对治疗风险和收益的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Chauhan Weighted Trajectory Analysis of Combined Efficacy and Safety Outcomes for Risk-Benefit Analysis.

Analyzing and effectively communicating the efficacy and toxicity of treatment is the fundamental basis of risk-benefit analysis (RBA). There is a need for more efficient and objective tools. We apply Chauhan Weighted Trajectory Analysis (CWTA) to perform RBA with superior objectivity, power, and ease of communication. We used CWTA to perform 1000-fold simulations of RCTs using ordinal endpoints that captured both treatment efficacy and treatment toxicity. RCTs were stochastically generated with 1:1 allocation at defined sample sizes and hazard ratios. We first studied the simplest case simulation of 3 levels each of toxicity and efficacy (a 3 × 3 matrix). We then simulated the general case of the advanced cancer trial, with efficacy graded by five RECIST 1.1 health statuses and toxicity graded by the six-point CTCAE scale to create a 6 × 5 matrix. Finally, the 6 × 5 matrix model was applied to a real-world dose escalation phase I trial in advanced cancer. Simulations in both the 3 × 3 simplest case matrix and the 6 × 5 advanced cancer matrix confirmed our hypothesis that drugs with both superior efficacy and toxicity profiles synergize for greater statistical power with CWTA RBA than either signal alone. The CWTA RBA 6 × 5 matrix meaningfully reduced sample size requirements over CWTA efficacy-only analysis. Despite a small sample size, application of the matrix to each of the seven cohorts of the dose finding phase I clinical trial provided objective and statistically significant validation for the dose subjectively selected by the trialists. CWTA RBA, by incorporating both drug efficacy and the trajectory of drug toxicity, provides a single test statistic and summary plot that analyzes, visualizes, and effectively communicates the risk-benefit assessment of a clinical trial. CWTA RBA requires fewer patients than CWTA efficacy-only analysis when the experimental drug is both more effective and less toxic. Our results show CWTA RBA has the potential to aid the objective and efficient assessment of new therapies throughout the drug development pathway. Furthermore, its distinct advantages over competing tests in visualizing and communicating risk-benefit will assist regulatory review, clinical adoption, and understanding of therapeutic risks and benefits by clinicians and patients alike.

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来源期刊
Pharmaceutical Statistics
Pharmaceutical Statistics 医学-统计学与概率论
CiteScore
2.70
自引率
6.70%
发文量
90
审稿时长
6-12 weeks
期刊介绍: Pharmaceutical Statistics is an industry-led initiative, tackling real problems in statistical applications. The Journal publishes papers that share experiences in the practical application of statistics within the pharmaceutical industry. It covers all aspects of pharmaceutical statistical applications from discovery, through pre-clinical development, clinical development, post-marketing surveillance, consumer health, production, epidemiology, and health economics. The Journal is both international and multidisciplinary. It includes high quality practical papers, case studies and review papers.
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