ARTEMIS:经独立验证的乳腺癌预后预测模型,其中包含具有主效应和基因-基因相互作用的表观遗传生物标志物。

Maojie Xue, Ziang Xu, Xiang Wang, Jiajin Chen, Xinxin Kong, Shenxuan Zhou, Jiamin Wu, Yuhao Zhang, Yi Li, David C Christiani, Feng Chen, Yang Zhao, Ruyang Zhang
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ARTEMIS was evaluated for discrimination ability using area under the receiver operating characteristics curve (AUC), and calibration using expected and observed (E/O) ratio. Additionally, we conducted decision curve analysis to evaluate its clinical efficacy by net benefit (NB) and net reduction (NR). Furthermore, we conducted a systematic review to compare its performance with existing models.</p><p><strong>Results: </strong>ARTEMIS exhibited excellent risk stratification ability in identifying patients at high risk of mortality. Compared to those below the 25th percentile of ARTEMIS scores, patients with above the 90th percentile had significantly lower overall survival time (HR = 15.43, 95% CI: 9.57-24.88, P = 3.06 × 10<sup>-29</sup>). ARTEMIS demonstrated satisfactory discrimination ability across four independent populations, with pooled AUC<sub>3-year</sub> = 0.844 (95% CI: 0.805-0.883), AUC<sub>5-year</sub> = 0.816 (95% CI: 0.775-0.857), and C-index = 0.803 (95% CI: 0.776-0.830). Meanwhile, ARTEMIS had well calibration performance with pooled E/O ratio 1.060 (95% CI: 1.038-1.083) and 1.090 (95% CI: 1.057-1.122) for 3- and 5-year survival prediction, respectively. Additionally, ARTEMIS is a clinical instrument with acceptable cost-effectiveness for detecting breast cancer patients at high risk of mortality (P<sub>t</sub> = 0.4: NB<sub>3-year</sub> = 19‰, NB<sub>5-year</sub> = 62‰; NR<sub>3-year</sub> = 69.21%, NR<sub>5-year</sub> = 56.01%). ARTEMIS has superior performance compared to existing models in terms of accuracy, extrapolation, and sample size, as indicated by the systematic review. 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引用次数: 0

摘要

简介乳腺癌是一种异质性疾病,受多种遗传和表观遗传因素的影响。大多数乳腺癌预后模型仅关注预测因素的主要影响,而忽视了基因与基因之间的相互作用对预后的重要影响:利用九个独立乳腺癌队列中的 DNA 甲基化数据,我们开发了一个经过独立验证的乳腺癌预后预测模型(ARTEMIS),该模型结合了具有主效应和基因-基因相互作用的表观遗传生物标志物,并采用了创新的三维建模策略。ARTEMIS 采用接收者操作特征曲线下面积 (AUC) 进行判别能力评估,并采用预期和观察 (E/O) 比率进行校准。此外,我们还进行了决策曲线分析,通过净获益(NB)和净减少(NR)来评估其临床疗效。此外,我们还进行了系统回顾,将其性能与现有模型进行了比较:结果:ARTEMIS在识别高死亡风险患者方面表现出卓越的风险分层能力。与 ARTEMIS 评分低于第 25 百分位数的患者相比,高于第 90 百分位数的患者总生存时间明显较短(HR=15.43,95 % CI:9.57-24.88,P=3.06 × 10-29)。ARTEMIS 在四个独立人群中表现出令人满意的分辨能力,汇总 AUC3-year = 0.844 (95 % CI: 0.805-0.883), AUC5-year = 0.816 (95 % CI: 0.775-0.857), C-index = 0.803 (95 % CI: 0.776-0.830).同时,ARTEMIS具有良好的校准性能,其3年和5年生存预测的汇总E/O比分别为1.060(95 % CI:1.038-1.083)和1.090(95 % CI:1.057-1.122)。此外,ARTEMIS 是一种临床工具,在检测高死亡风险乳腺癌患者方面具有可接受的成本效益(Pt = 0.4:NB3 年 = 0.019,NB5 年 = 0.062;NR3 年 = 69.21 %,NR5 年 = 56.01 %)。如系统综述所示,与现有模型相比,ARTEMIS 在准确性、外推和样本量方面都具有更优越的性能。ARTEMIS 是一个交互式在线工具,可通过 http://bigdata.njmu.edu.cn/ARTEMIS/.Conclusion 获取:ARTEMIS 是一种高效实用的乳腺癌预后预测工具。
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ARTEMIS: An independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions.

Introduction: Breast cancer, a heterogeneous disease, is influenced by multiple genetic and epigenetic factors. The majority of prognostic models for breast cancer focus merely on the main effects of predictors, disregarding the crucial impacts of gene-gene interactions on prognosis.

Objectives: Using DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy. ARTEMIS was evaluated for discrimination ability using area under the receiver operating characteristics curve (AUC), and calibration using expected and observed (E/O) ratio. Additionally, we conducted decision curve analysis to evaluate its clinical efficacy by net benefit (NB) and net reduction (NR). Furthermore, we conducted a systematic review to compare its performance with existing models.

Results: ARTEMIS exhibited excellent risk stratification ability in identifying patients at high risk of mortality. Compared to those below the 25th percentile of ARTEMIS scores, patients with above the 90th percentile had significantly lower overall survival time (HR = 15.43, 95% CI: 9.57-24.88, P = 3.06 × 10-29). ARTEMIS demonstrated satisfactory discrimination ability across four independent populations, with pooled AUC3-year = 0.844 (95% CI: 0.805-0.883), AUC5-year = 0.816 (95% CI: 0.775-0.857), and C-index = 0.803 (95% CI: 0.776-0.830). Meanwhile, ARTEMIS had well calibration performance with pooled E/O ratio 1.060 (95% CI: 1.038-1.083) and 1.090 (95% CI: 1.057-1.122) for 3- and 5-year survival prediction, respectively. Additionally, ARTEMIS is a clinical instrument with acceptable cost-effectiveness for detecting breast cancer patients at high risk of mortality (Pt = 0.4: NB3-year = 19‰, NB5-year = 62‰; NR3-year = 69.21%, NR5-year = 56.01%). ARTEMIS has superior performance compared to existing models in terms of accuracy, extrapolation, and sample size, as indicated by the systematic review. ARTEMIS is implemented as an interactive online tool available at http://bigdata.njmu.edu.cn/ARTEMIS/.

Conclusion: ARTEMIS is an efficient and practical tool for breast cancer prognostic prediction.

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