When does economic model type become a decisive factor in health technology appraisals? Learning from the expanding treatment options for relapsing–remitting multiple sclerosis

<b>Objectives:</b> Specific economic model types often become <i>de facto</i> standard for health technology appraisal over time. Markov and discrete event simulation (DES) models were compared to investigate the impact of innovative modeling on the cost-effectiveness of disease-modifying therapies (DMTs) in relapsing–remitting multiple sclerosis (RRMS). Fingolimod was compared to dimethyl fumarate (DMF; in highly active [HA] RRMS), alemtuzumab (in HA RRMS) and natalizumab (in rapidly evolving severe RRMS). Comparator DMTs were chosen to reflect different dosing regimens. <b>Materials and methods:</b> Markov and DES models used have been published previously. Inputs were aligned in all relevant respects, with differences in the modeling of event-triggered attributes, such as relapse-related retreatment, which is inherently difficult with a memoryless Markov approach. Outcomes were compared, with and without different attributes. <b>Results:</b> All results used list prices. For fingolimod and DMF, incremental cost-effectiveness ratios (ICERs) were comparable (Markov: £4206/quality-adjusted life year [QALY] gained versus DES: £3910/QALY gained). Deviations were observed when long-term adverse events (AEs) were incorporated in the DES (Markov: £25,412 saved/QALY lost, versus DES: £34,209 saved/QALY lost, fingolimod versus natalizumab; higher ICERs indicate greater cost-effectiveness). For fingolimod versus alemtuzumab, when relapse-triggered retreatment was included in the DES, large cost differences were observed (difference between incremental cost is £35,410 and QALY is 0.10). <b>Limitations:</b> UK payer perspective, therefore societal approach was not considered. Resource utilization and utilities for both models were not derived from the subpopulations; as the focus is on model type, input limitations that apply to both models are less relevant. <b>Conclusions:</b> Whilst no model can fully represent a disease, a DES allows an opportunity to include features excluded in a Markov structure. A DES may be more suitable for modeling in RRMS for health technology assessment purposes given the complexity of some DMTs. This analysis highlights the capabilities of different model structures to model event-triggered attributes.

**研究目标**：随着时间推移，特定的经济学模型类型往往会成为卫生技术评估（Health Technology Appraisal）的事实上标准。本研究对比了Markov模型（Markov）与离散事件模拟（Discrete Event Simulation, DES）模型，以探究创新建模方式对复发缓解型多发性硬化（relapsing–remitting multiple sclerosis, RRMS）患者的疾病修正治疗（disease-modifying therapies, DMTs）成本效果的影响。研究对比了芬戈莫德（Fingolimod）与富马酸二甲酯（dimethyl fumarate, DMF；针对高活动度复发缓解型多发性硬化[HA RRMS]）、阿仑单抗（alemtuzumab；针对HA RRMS）以及那他珠单抗（natalizumab；针对快速进展型重症RRMS）。所选对照DMTs均覆盖不同的给药方案。
**材料与方法**：本次研究使用的Markov模型与DES模型均已在既往研究中发表。所有相关维度的输入参数均保持一致，仅在事件触发属性的建模方式上存在差异，例如与复发相关的再治疗建模——无记忆性的Markov方法天生难以处理此类场景。研究对比了纳入与不纳入不同事件触发属性时的模型结局。
**研究结果**：所有结果均采用挂牌价格计算。针对芬戈莫德与DMF，二者的增量成本效果比（incremental cost-effectiveness ratios, ICERs）较为接近（Markov模型：每获得1个质量调整生命年（quality-adjusted life year, QALY）需花费4206英镑；DES模型：每获得1个QALY需花费3910英镑）。当在DES模型中纳入长期不良事件（adverse events, AEs）时，二者结果出现偏差：芬戈莫德对比那他珠单抗的情况下，Markov模型显示每丢失1个QALY可节省25412英镑，而DES模型显示每丢失1个QALY可节省34209英镑；需注意，ICERs数值越高代表成本效果越好。针对芬戈莫德对比阿仑单抗的场景，当在DES模型中纳入复发触发的再治疗环节时，二者出现了显著的成本差异（增量成本差额为35410英镑，QALY差额为0.10）。
**研究局限性**：本研究采用英国支付方视角，因此未考虑社会层面的成本与收益。两种模型的资源利用与效用值均未基于亚人群数据推导；由于本研究的核心聚焦于模型类型本身，因此对两种模型均适用的输入参数局限性影响有限。
**研究结论**：尽管没有任何模型能够完全复刻某一疾病的病理进程，但DES模型能够纳入Markov结构无法涵盖的特征。鉴于部分DMTs的治疗复杂性，在卫生技术评估场景下，DES模型或许更适用于RRMS的建模研究。本分析也凸显了不同模型结构在处理事件触发属性建模时的各自优势。