Harvey Rebecca C
Tolley Health Economics Ltd, Unit 5, 11-13 Eagle Parade, Buxton, Derbyshire SK17 6EQ UK.
Oncol Ther. 2017;5(1):53-67. doi: 10.1007/s40487-017-0048-0. Epub 2017 Jun 6.
Advanced gastric cancer (AGC) is one of the most common forms of cancer and remains difficult to cure. There is currently no recommended therapy for second-line AGC in the UK despite the availability of various interventions. This paper aims to compare different interventions for treatment of second-line AGC using more complex methods to estimate relative efficacy, fitting various parametric models and to compare results to those published adopting conventional methods of synthesis.
Seven studies were identified in an existing literature review evaluating seven comparators, which formed a connected network of evidence. Citations were limited to randomised controlled trials in previously-treated AGC patients. Evidence quality was assessed using the Cochrane Collaboration's tool. Studies were assessed for the availability of Kaplan-Meier curves for overall survival. Individual patient data (IPD) were recreated using digitisation software along with a published algorithm in R. The data were analysed using multi-dimensional network meta-analysis (NMA) methods. A series of parametric models were fitted to the pseudo-IPD. Both fixed and random-effects models were fitted to explore long-term survival prospects based on extrapolation methods and estimated mean survival.
Relative efficacy estimates were compared to those previously reported, which utilised conventional NMA methods. Results presented were consistent within findings from other publications and identified ramucirumab plus paclitaxel as the best treatment; however, all the treatments assessed were associated with poor survival prospects with mean survival estimates ranging from 5.0 to 12.7 months.
Whilst the approach adopted in this paper does not adjust for differences in trial patient populations and is particularly data-intensive, use of such sophisticated methods of evidence synthesis may be more informative for subsequent cost-effectiveness modelling and may have greater impact when considering an indication where observed data is particularly immature or survival prospects are more positive, which may then lead to more informative decision-making for drug reimbursement.
进展期胃癌（AGC）是最常见的癌症形式之一，仍然难以治愈。尽管有多种干预措施，但目前在英国尚无推荐用于二线AGC的治疗方法。本文旨在使用更复杂的方法来估计相对疗效，拟合各种参数模型，比较二线AGC不同治疗干预措施，并将结果与采用传统综合方法发表的结果进行比较。
在现有文献综述中确定了7项研究，评估了7种对照治疗措施，形成了一个相互关联的证据网络。纳入文献限于既往接受过治疗的AGC患者的随机对照试验。使用Cochrane协作网的工具评估证据质量。评估研究中是否有总生存的Kaplan-Meier曲线。使用数字化软件和R语言中已发表的算法重新创建个体患者数据（IPD）。使用多维网络meta分析（NMA）方法对数据进行分析。对伪IPD拟合一系列参数模型。拟合固定效应模型和随机效应模型，基于外推法和估计的平均生存来探索长期生存前景。
将相对疗效估计值与先前报告的结果进行比较，先前报告采用的是传统NMA方法。呈现的结果与其他出版物的结果一致，并确定雷莫西尤单抗联合紫杉醇是最佳治疗方法；然而，所有评估的治疗方法均与较差的生存前景相关，平均生存估计值在5.0至12.7个月之间。
虽然本文采用的方法未对试验患者群体的差异进行调整，且数据量特别大，但使用这种复杂的证据综合方法可能会为后续的成本效益建模提供更多信息，并且在考虑观察数据特别不成熟或生存前景更乐观的适应症时可能会产生更大影响，进而可能导致在药物报销决策方面提供更多信息。
