Department of Conservative Dentistry, Faculty of Dental Medicine, Medical University of Tirana, Tirana, Albania.
Oral Dis. 2018 Mar;24(1-2):115-119. doi: 10.1111/odi.12753.
We investigated methods and risk of bias, focusing on research design, aim, prognostic factors, outcome, and statistical analysis in molecular marker prognosis studies of oral squamous cell carcinoma.
We used a database search strategy to indentify relevant articles published in English in 2016. We developed a data extraction form to assess and extract information on methods of molecular marker prognosis studies in oral squamous cell carcinoma, based on methodological recommendations for prognosis studies. We used the Quality in Prognosis Studies tool to assess the risk of bias in six domains.
Thirty-six papers were retrieved for full text review: 35 were replication prognosis factor studies and one was a model development based only on molecular markers to stratify patient's risk. Retrospective cohort was the design used in most studies (91%). Despite recommendations against dichotomizing continuous prognostic variables, this was observed in the majority of cases. A substantial number of studies (60%) conducted survival analysis, COX regression, and Kaplan-Meier. Prognostic variables included in the multivariate model were often preselected based on the results of univariable analysis. Risk of bias was assessed high for confounding, statistical analysis and reporting domains in 46% and 49% of studies, respectively.
The prognosis studies analyzed here can be considered phase II explanatory studies. The next step is to construct and validate models, which can be applied for use in the clinical practice, to guide patient management or build explanatory models that can help better understand the causative role in the disease process of these markers.
我们调查了方法和偏倚风险,重点关注口腔鳞状细胞癌分子标志物预后研究的研究设计、目的、预后因素、结局和统计分析。
我们使用数据库搜索策略,确定了 2016 年以英文发表的相关文章。我们根据预后研究的方法学建议,制定了一个数据提取表格,以评估和提取口腔鳞状细胞癌分子标志物预后研究方法的信息。我们使用预后研究质量工具(Quality in Prognosis Studies tool)评估了六个领域的偏倚风险。
共检索到 36 篇全文进行评估:35 篇是复制预后因素的研究,1 篇是仅基于分子标志物的模型开发,用于分层患者的风险。大多数研究(91%)采用回顾性队列设计。尽管有建议反对将连续预后变量二分法,但在大多数情况下仍然存在这种情况。相当数量的研究(60%)进行了生存分析、COX 回归和 Kaplan-Meier 分析。多变量模型中包含的预后变量通常是基于单变量分析的结果预先选择的。在 46%和 49%的研究中,分别有 46%和 49%的研究存在混杂、统计分析和报告方面的偏倚风险。
本文分析的预后研究可以被认为是解释性 II 期研究。下一步是构建和验证模型,这些模型可以应用于临床实践,以指导患者管理或构建可以帮助更好地理解这些标志物在疾病过程中的因果作用的解释性模型。