Background: Chimeric antigen receptor T-cell (CAR-T) therapies have been approved by the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA) for the treatment of diffuse large B-cell lymphoma (DLBCL), primarily based on single-arm trials or indirect comparisons with stem cell transplantation. However, no direct head-to-head comparisons of CAR-T therapies have been conducted, largely due to their high cost. To assess their true value, indirect treatment comparisons (ITCs) are essential. These comparisons, however, are prone to confounding biases, which necessitate careful adjustments through the identification and measurement of relevant variables.Materials and Methods: This study aims to identify the variables used for adjustment in ITCs of CAR-T therapies for DLBCL and examine the methodologies employed to select them. A rapid literature review was conducted in PubMed in September 2023, focusing on ITCs involving CAR-T therapies for DLBCL. The search was based on keywords categorized into three groups: techniques (ITCs and related terms), drugs (CAR-T therapies), and indication (DLBCL).Results: The rapid literature review identified 21 articles, of which 11 were selected for analysis. Exclusions were made for articles that did not identify confounders, were letters to editors, or addressed conditions other than DLBCL. Among the 11 selected publications, 10 did not clearly specify the methodology used to identify adjustment variables. A total of 25 potential confounders were identified across the studies, with substantial variability in the set of variables used, reflecting a lack of standardization in confounder selection. Commonly identified confounders included the number of prior treatment lines and Eastern Cooperative Oncology Group Performance Status (ECOG PS), although their inclusion as adjustment variables in ITCs was inconsistent, often due to missing data.Conclusions: While the identified confounders are clinically relevant, the methodologies for selecting them remain unclear, resulting in significant variability across studies. Additionally, key variables commonly considered in health technology assessments (HTAs), such as age, sex, and disease severity, were inconsistently incorporated into ITCs. To improve the reliability and consistency of ITC outcomes, there is a pressing need for standardized methodologies for identifying and adjusting for confounders.
背景：嵌合抗原受体T细胞（CAR-T）疗法已获美国食品药品监督管理局（FDA）和欧洲药品管理局（EMA）批准用于治疗弥漫性大B细胞淋巴瘤（DLBCL），其批准主要基于单臂试验或与干细胞移植的间接比较。然而，由于CAR-T疗法成本高昂，目前尚未开展其直接头对头比较研究。为评估其真实价值，间接治疗比较（ITC）至关重要。但此类比较易受混杂偏倚影响，需通过识别和测量相关变量进行审慎调整。 材料与方法：本研究旨在识别DLBCL的CAR-T疗法ITC中用于调整的变量，并考察其选择方法。我们于2023年9月在PubMed进行了快速文献综述，聚焦于涉及DLBCL的CAR-T疗法ITC研究。检索关键词分为三类：技术（ITC及相关术语）、药物（CAR-T疗法）和适应症（DLBCL）。 结果：快速文献综述共识别21篇文献，其中11篇纳入分析。排除标准包括未识别混杂因素的文章、致编辑信函以及涉及非DLBCL适应症的文章。在11篇入选文献中，有10篇未明确说明识别调整变量的方法。各研究共识别出25个潜在混杂因素，所用变量集存在显著差异，反映出混杂因素选择缺乏标准化。常见识别出的混杂因素包括既往治疗线数和东部肿瘤协作组体能状态评分（ECOG PS），但由于数据缺失，这些因素在ITC中作为调整变量的纳入情况并不一致。 结论：尽管识别出的混杂因素具有临床相关性，但其选择方法仍不明确，导致研究间存在显著差异。此外，卫生技术评估（HTA）中通常考虑的关键变量（如年龄、性别和疾病严重程度）在ITC中的纳入情况也不一致。为提高ITC结果的可靠性和一致性，亟需建立识别和调整混杂因素的标准化方法。
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