证据综合中宽泛与狭窄研究问题的对比：与估计目标的相似性及呼吁
Broad versus narrow research questions in evidence synthesis: a parallel to (and plea for) estimands
AI总结：
本文探讨了网络荟萃分析中研究问题从宽泛转向具体的趋势，指出这与个体注册试验引入估计目标框架的趋同，并呼吁将估计目标语言应用于NMA以应对卫生技术评估的狭窄视角。
摘要：
在网络荟萃分析（NMA）实践中，研究问题已从宽泛转向更具体。在近期引入估计目标框架后，这种趋同也发生在个体注册试验中，该框架正影响临床试验的设计、数据收集策略、分析和解释。估计目标的语言对NMA大有裨益，特别是在卫生技术评估对治疗和目标人群采取“狭窄”视角的情况下。
英文摘要：
There has been a transition from broad to more specific research questions in the practice of network meta-analysis (NMA). Such convergence is also taking place in the context of individual registrational trials, following the recent introduction of the estimand framework, which is impacting the design, data collection strategy, analysis and interpretation of clinical trials. The language of estimands has much to offer to NMA, particularly given the "narrow" perspective of treatments and target populations taken in health technology assessment.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
