Abstract IA03: Requirements for a statistical prediction model to receive AJCC endorsement

M. Kattan
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Abstract

The American Joint Committee on Cancer (AJCC) has recognizes the need for more personalized predictions than those delivered by cancer staging systems. In particular, the use of accurate risk models or calculators is seen as valuable. However, judging the quality and acceptability of a risk model is difficult. The AJCC Precision Medicine Core formed a committee to establish inclusion and exclusion criteria necessary for a risk model to potentially be endorsed by the AJCC. They identified 13 inclusion and 3 exclusion criteria for AJCC risk model endorsement. The criteria centered on performance metrics, implementation clarity, and clinical relevance. These criteria will be described. Citation Format: Michael W. Kattan. Requirements for a statistical prediction model to receive AJCC endorsement. [abstract]. In: Proceedings of the AACR Special Conference: Improving Cancer Risk Prediction for Prevention and Early Detection; Nov 16-19, 2016; Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2017;26(5 Suppl):Abstract nr IA03.
IA03:统计预测模型获得AJCC认可的要求
美国癌症联合委员会(AJCC)已经认识到需要比癌症分期系统更个性化的预测。特别是,使用准确的风险模型或计算器被认为是有价值的。然而,判断风险模型的质量和可接受性是困难的。AJCC精准医学核心成立了一个委员会,以建立风险模型可能得到AJCC认可所需的纳入和排除标准。他们确定了AJCC风险模型认可的13个纳入标准和3个排除标准。标准集中于绩效指标、实施清晰度和临床相关性。下面将描述这些标准。引文格式:Michael W. Kattan。获得AJCC认可的统计预测模型的要求。[摘要]。摘自:AACR特别会议论文集:改进癌症风险预测以预防和早期发现;2016年11月16日至19日;费城(PA): AACR;Cancer epidemiology Biomarkers pre2017;26(5增刊):摘要nr IA03。
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