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Pretherapy dental decisions in patients with head and neck cancer. A proposed model for dental decision support.

机译:头颈癌患者的治疗前牙科决策。牙科决策支持的建议模型。

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OBJECTIVE: The proposed model was designed to function as a tool for the development and testing of evidence-based clinical guidelines for the pretherapy oral screening and dental management of patients with head and neck cancer. STUDY DESIGN: Methods of clinical decision analysis were used to analyze the decision dilemma and construct a decision algorithm and decision tree. The robustness of the model was tested by means of a probabilistic sensitivity analysis with second-order Monte Carlo simulations (n = 10.000). RESULTS: Clinical criteria for evaluating dental pathologic conditions and malignancy- and patient-related conditions were transformed in probability estimates. The tradeoffs between the benefits and drawbacks of the dental intervention were integrated into the model to identify the optimal option for dental intervention. The calculation process of "folding back and averaging out" the decision tree enabled the identification of the optimal options for dental intervention in four different pretherapy risk conditions. CONCLUSIONS: A priori testing of the proposed model with 95% confidence intervals suggests that it has a great potential for solving clinical dilemmas associated with pretherapy dental decision-making. In addition, it seems a useful tool for the development of evidence-based clinical guidelines. A posteriori clinical testing should further validate the model before its assimilation into clinical practice takes place.
机译:目的:该模型旨在用作开发和测试基于证据的临床指南的工具,以用于头颈癌患者的治疗前口腔筛查和牙科管理。研究设计:采用临床决策分析方法分析决策困境,构建决策算法和决策树。通过概率敏感性分析和二阶蒙特卡洛模拟(n = 10.000)来测试模型的鲁棒性。结果:用于评估牙齿病理状况以及恶性和患者相关状况的临床标准已转化为概率估计。牙科干预的利弊之间的权衡被整合到模型中,以确定牙科干预的最佳选择。决策树“折回并平均化”的计算过程可以确定在四种不同的治疗前风险条件下进行牙科干预的最佳选择。结论:以95%置信区间对提议的模型进行的先验测试表明,它具有很大的潜力,可以解决与治疗前牙科决策相关的临床难题。此外,它似乎是开发循证临床指南的有用工具。后验临床测试应在将模型纳入临床实践之前进一步验证模型。

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