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Integrating population data in a computerized Decision Support System for Head and Neck Cancer

机译:将人群数据整合到头颈癌的计算机决策支持系统中

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Head and Neck Cancer, the seventh cancer in incidence worldwide, is a heterogeneous disease that encompasses different molecular entities and subgroups with variable risk and potential discriminative treatment options that influence disease outcome. Treatment choice depends mainly on a staging system that has limits on advances cases (Stages III and IV). Because of that, it is needed to find more prognostic factors that can enhance this current classification. Population data contribute on the identification of risk and prognostic factors. Therefore, in the era of precision medicine, the integration of population data with patient clinical data is expected to contribute to a better patient stratification. In this work, carried out in the context of the European Research project “Big Data to Decide” (BD2Decide), the use of publicly available data sources to improve decision making in Head and Neck Cancer, and their integration in a computerized decision support system have been studied with the contribution of oncologists, epidemiologists and bio-statisticians. The conceptual framework design presented in this paper pretends to support the discovery of prognostic factors, improving risk stratification in Head and Neck Cancer.
机译:头颈癌是全球第七大癌症,是一种异质性疾病,涵盖不同的分子实体和亚组,具有可变的风险和可能影响疾病结果的歧视性治疗选择。治疗的选择主要取决于分期系统,该系统对预诊病例(第三和第四阶段)有限制。因此,需要找到更多可以增强当前分类的预后因素。人口数据有助于识别风险和预后因素。因此,在精密医学时代,人口数据与患者临床数据的整合有望促进更好的患者分层。在这项工作中,是在欧洲研究项目“要决定的大数据”(BD2Decide),使用公开可用的数据源来改善头颈癌的决策以及将其集成到计算机决策支持系统中进行的。在肿瘤学家,流行病学家和生物统计学家的帮助下进行了研究。本文提出的概念框架设计假装支持发现预后因素,改善头颈癌的危险分层。

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