Liggins Institute, The University of Auckland, Auckland, New Zealand.
Health Systems, School of Population Health, University of Auckland, Auckland, New Zealand.
BMJ Open. 2020 Sep 16;10(9):e037324. doi: 10.1136/bmjopen-2020-037324.
Within cost-effectiveness models, prevalence figures can inform transition probabilities. The methodological quality of studies can inform the choice of prevalence figures but no single obvious candidate tool exists for assessing quality of the observational epidemiological studies for selecting prevalence estimates. We aimed to compare different tools to assess the risk of bias of studies reporting prevalence, and develop and compare possible numerical scoring systems using these tools to set a threshold for inclusion of reports of prevalence in an economic analysis of neonatal hypoglycaemia.
Assessments of bias using two tools (Joanna Briggs Institute (JBI) Checklist for Prevalence Studies and a modified version of Risk Of Bias In Non-randomised Studies-of Interventions (ROBINS-I)) were compared for 18 studies relevant to a single setting (neonatal hypoglycaemia). Inclusions of studies for use in a decision analysis model were considered based on summary scores derived from these tools.
Both tools were considered easy to use and produced dispersed scores for each of the 40 study-outcome combinations. The modified ROBINS-I scores were more skewed than the JBI scores, particularly at higher thresholds. The studies selected for inclusion are generally the same using either tool; if 50% was used as the cut-off threshold using the Applicable Score both tools would yield the same results. However, the JBI tool is shorter and may be easier to interpret and apply to studies that do not involve a control group, while the modified ROBINS-I tool assesses more methodological detail in studies that include a control group.
Both tools performed well for systematically assessing studies that report on outcome prevalence and provided similar discrimination between studies for risk of bias. This convergent validity supports use of both tools for the purpose of assessing risk of bias and selecting studies that report prevalence for inclusion in economic analyses.
在成本效益模型中，患病率数据可用于推断转移概率。研究方法的质量可以为选择患病率数据提供信息，但目前还没有一种单一的工具可以用于评估选择患病率估计值的观察性流行病学研究的质量。我们旨在比较不同的工具来评估报告患病率的研究的偏倚风险，并使用这些工具开发和比较可能的数值评分系统，为新生儿低血糖症的经济分析中纳入患病率报告设定一个纳入标准。
使用两种工具（ Joanna Briggs Institute （JBI）患病率研究检查表和改良版的非随机干预研究偏倚风险（ROBINS-I））评估了 18 项与单一环境（新生儿低血糖症）相关的研究的偏倚。根据这些工具得出的综合评分，考虑了纳入研究进行决策分析模型的情况。
两种工具都被认为易于使用，且对 40 种研究结果组合中的每一种都产生了分散的评分。改良版 ROBINS-I 评分的偏度大于 JBI 评分，尤其是在较高的阈值下。使用这两种工具选择纳入的研究通常是相同的；如果将 50%作为应用得分的截断阈值，两种工具将产生相同的结果。然而，JBI 工具更短，可能更容易解释和应用于不涉及对照组的研究，而改良版 ROBINS-I 工具则在包括对照组的研究中评估了更多的方法学细节。
这两种工具在系统评估报告结局患病率的研究方面表现良好，且在评估研究偏倚风险方面具有相似的区分能力。这种收敛有效性支持使用这两种工具来评估偏倚风险和选择报告患病率的研究，以纳入经济分析。
