Centre for Health Economics and Medicines Evaluation, Institute of Medical and Social Care Research, Bangor University, Bangor, UK.
Pharmacoeconomics. 2012 Sep 1;30(9):779-94. doi: 10.2165/11591530-000000000-00000.
There have been several explorations of factors influencing the reimbursement decisions of the National Institute for Health and Clinical Excellence (NICE) but not of other UK-based health technology assessment (HTA) organizations.
This study aimed to explore the factors influencing the recommendations of the All Wales Medicines Strategy Group (AWMSG) on the use of new medicines in Wales.
Based on public data, logistic regression models were developed to evaluate the influence of cost effectiveness, the quality and quantity of clinical evidence, disease characteristics (including rarity), budget impact, and a range of other factors on the recommendations of AWMSG and its subcommittee, the New Medicines Group (NMG).
Multivariate analyses of 47 AWMSG appraisals between 2007-9 correctly predicted 87% of decisions. The results are suggestive of a positive influence on recommendations of the presence of probabilistic sensitivity analyses (PSAs) but, counter-intuitively, a statistically significant negative influence of evidence from high-quality randomized controlled trials (RCTs) [odds ratio 0.059; 95% CI 0.005, 0.699]. This latter observation may be attributed to our strict definition of high quality, which excluded the use of surrogate endpoints. Putative explanatory variables, including cost effectiveness, budget impact, underlying disease characteristics and 'ultra'-orphan drug status were not statistically significant predictors of final AWMSG decisions based on our dataset. Univariate analyses indicate that medicines with negative recommendations had significantly higher incremental cost-effectiveness ratios than those with positive recommendations, consistent with the pursuit of economic efficiency. There is also evidence that AWMSG considers equity issues via an ultra-orphan drugs policy.
Consideration of decision uncertainty via PSA appears to positively influence the reimbursement decisions of AWMSG. The significant negative impact of the presence of high-quality RCTs, and the lack of a significant positive impact of other expected factors, may reflect issues in the plausibility of supporting evidence for medicines that received negative recommendations. Furthermore, it serves to emphasize the difficulties in applying the usual hierarchies of evidence to the HTA process, and in particular to the appraisal of high-cost specialist medicines close to market launch.
已经有一些研究探索了影响英国国家卫生与临床优化研究所（NICE）报销决策的因素，但没有研究其他基于英国的卫生技术评估（HTA）组织的影响因素。
本研究旨在探讨影响全威尔士药品策略组（AWMSG）在威尔士使用新药建议的因素。
基于公开数据，建立逻辑回归模型，评估成本效益、临床证据的质量和数量、疾病特征（包括罕见病）、预算影响以及其他一系列因素对 AWMSG 及其下属委员会新药小组（NMG）建议的影响。
对 2007-2009 年期间 47 项 AWMSG 评估的多变量分析正确预测了 87%的决策。结果表明，存在概率敏感性分析（PSA）对建议有积极影响，但出人意料的是，高质量随机对照试验（RCT）证据具有统计学上显著的负面影响[比值比 0.059；95%置信区间 0.005，0.699]。这一观察结果可能归因于我们对高质量的严格定义，该定义排除了替代终点的使用。根据我们的数据集，成本效益、预算影响、潜在疾病特征和“超孤儿”药物状态等推测性解释变量不是 AWMSG 最终决策的统计学显著预测因素。单变量分析表明，具有负面推荐的药物的增量成本效益比显著高于具有正面推荐的药物，这与对经济效率的追求一致。还有证据表明，AWMSG 通过超孤儿药物政策考虑公平问题。
通过 PSA 考虑决策不确定性似乎对 AWMSG 的报销决策产生积极影响。高质量 RCT 存在的显著负面影响，以及其他预期因素没有显著积极影响，可能反映了对获得负面推荐的药物的支持证据的合理性问题。此外，这进一步强调了在 HTA 过程中，特别是在接近市场推出的高成本专科药物评估中，应用证据等级通常存在困难。
