Implementation of a rapid learning platform: Predicting 2-year survival in laryngeal carcinoma patients in a clinical setting.
Implementation of a rapid learning platform: Predicting 2-year survival in laryngeal carcinoma patients in a clinical setting.
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DOI：
10.18632/oncotarget.8755
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发表时间：
2016-06-14
期刊：
影响因子：
--
通讯作者：
Dekker A
中科院分区：
文献类型：
--
作者：
Lustberg T;Bailey M;Thwaites DI;Miller A;Carolan M;Holloway L;Rios Velazquez E;Hoebers F;Dekker A
为了提高肿瘤医疗保健的质量和个性化，需要决策辅助工具来为医生和患者提供建议。这项工作的目的是证明生存预测模型的临床相关性，作为多机构快速学习的第一步，并将其与临床试验数据集进行比较。使用数据提取和挖掘工具从Illawarra癌症护理中心（临床队列）肿瘤学信息系统收集未经策划的输入参数。将先前根据马斯特里赫特放射肿瘤学（训练队列）数据集建立的预后类别应用于RTOG-9111的临床队列和仅放射治疗组（试验队列）。数据挖掘确定了125名喉癌患者，最终临床队列中有52名患者有资格通过模型进行评估，以预测2年生存率，试验队列中有177名患者。该模型能够对患者进行分类并预测临床队列的生存率，但对于试验队列，它未能做到这一点。该技术基础设施和模型能够支持临床队列中喉癌患者的预后预测。该模型对于试验队列中高度选择性的患者人群表现不佳。
To improve quality and personalization of oncology health care, decision aid tools are needed to advise physicians and patients. The aim of this work is to demonstrate the clinical relevance of a survival prediction model as a first step to multi institutional rapid learning and compare this to a clinical trial dataset. Data extraction and mining tools were used to collect uncurated input parameters from Illawarra Cancer Care Centre's (clinical cohort) oncology information system. Prognosis categories previously established from the Maastricht Radiation Oncology (training cohort) dataset, were applied to the clinical cohort and the radiotherapy only arm of the RTOG-9111 (trial cohort). Data mining identified 125 laryngeal carcinoma patients, ending up with 52 patients in the clinical cohort who were eligible to be evaluated by the model to predict 2-year survival and 177 for the trial cohort. The model was able to classify patients and predict survival in the clinical cohort, but for the trial cohort it failed to do so. The technical infrastructure and model is able to support the prognosis prediction of laryngeal carcinoma patients in a clinical cohort. The model does not perform well for the highly selective patient population in the trial cohort.
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影响因子：
5.7
作者：
Lambin, Philippe;Roelofs, Erik;Dekker, Andre
通讯作者：
Dekker, Andre
影响因子：
158.5
作者：
WOLF, GT
通讯作者：
WOLF, GT
影响因子：
8.4
作者：
Cho, Jae-Keun;Lee, Gil-Joon;Ahn, Yong Chan
通讯作者：
Ahn, Yong Chan
DOI：
10.1038/nrclinonc.2012.196
发表时间：
2013-01
期刊：
Nature reviews. Clinical oncology
影响因子：
--
作者：
Lambin P;van Stiphout RG;Starmans MH;Rios-Velazquez E;Nalbantov G;Aerts HJ;Roelofs E;van Elmpt W;Boutros PC;Granone P;Valentini V;Begg AC;De Ruysscher D;Dekker A
通讯作者：
Dekker A
影响因子：
3.8
作者：
Jayasurya, K.;Fung, G.;Dekker, A. L. A. J.
通讯作者：
Dekker, A. L. A. J.