Julia Hanevelt MD, Richard M. Brohet PhD, Leon M. G. Moons MD, PhD, Miangela M. Laclé MD, PhD, Frank P. Vleggaar MD, PhD, Henderik L. van Westreenen MD, PhD, Wouter H. de Vos Tot Nederveen Cappel MD, PhD
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Four machine learning models were evaluated to predict LNM.</p><h3>Results</h3><p>LNMs were found in 1877/9803 patients (19.1%). Independent risk factors included (younger) age (odds ratio [OR] 0.98, 95% confidence interval [CI] 0.979–0.990), left-sided CC (OR 1.5, 95% CI 1.4–1.7), poor differentiation (OR 1.7, 95% CI 1.4–2.2), and lymphovascular invasion (LVI; OR 4.1, 95% CI 3.6–4.7). A deficient mismatch repair (MMR) status significantly lowered the risk of LNM (OR 0.3, 95% CI 0.2–0.5). The general linear model demonstrated the highest prediction accuracy, achieving area under the receiver operating characteristic curves of 0.67 and 0.68, with good calibration. In the absence of risk factors, elderly patients (≥74 years of age) had a predicted risk of LNM of 10.7%, yet up to 30% experienced postoperative complications, with mortality rates reaching up to 3.5%. 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引用次数: 0
摘要
背景:与T1结肠癌(CC)类似,危险分层可以指导T2 CC的治疗,减少不必要的大手术。在本研究中,建立了预测模型,可以识别淋巴结转移(LNM)风险较低的T2 CC患者,可以考虑在局部治疗后进行(强化)随访。方法:一项涉及2012年至2020年间接受手术的pT2 CC患者的全国性队列研究,使用荷兰结直肠审计的数据,该数据与全国病理数据库相关联。评估了四种机器学习模型来预测LNM。结果:1877/9803例患者中有LNMs,占19.1%。独立危险因素包括(年轻)年龄(优势比[OR] 0.98, 95%可信区间[CI] 0.979-0.990),左侧CC (OR 1.5, 95% CI 1.4-1.7),分化差(OR 1.7, 95% CI 1.4-2.2)和淋巴血管侵犯(LVI;或4.1,95% ci 3.6-4.7)。缺陷错配修复(MMR)状态显著降低LNM的风险(OR 0.3, 95% CI 0.2-0.5)。一般线性模型预测精度最高,在接收机工作特性曲线下的面积分别为0.67和0.68,具有良好的定标性。在没有危险因素的情况下,老年患者(≥74岁)发生LNM的预测风险为10.7%,但高达30%的患者出现术后并发症,死亡率高达3.5%。如果LVI缺失且肿瘤分化良好,MMR状态不足的患者预测LNM的风险为6.1%。结论:应权衡LNM的风险与手术风险。这项研究的发现将使临床医生在做出共同的决定之前,对这些相互竞争的风险做出更深思熟虑的考虑。
Risk of Lymph Node Metastasis in T2 Colon Cancer: A Nationwide Population-Based Cohort Study
Background
Similar to T1 colon cancer (CC), risk stratification may guide T2 CC treatment and reduce unnecessary major surgery. In this study, prediction models were developed that could identify T2 CC patients with a lower risk of lymph node metastasis (LNM) for whom (intensive) follow-up after local treatment could be considered.
Methods
A nationwide cohort study was performed involving pT2 CC patients who underwent surgery between 2012 and 2020, using data from the Dutch ColoRectal Audit, which were linked to the Nationwide Pathology Databank. Four machine learning models were evaluated to predict LNM.
Results
LNMs were found in 1877/9803 patients (19.1%). Independent risk factors included (younger) age (odds ratio [OR] 0.98, 95% confidence interval [CI] 0.979–0.990), left-sided CC (OR 1.5, 95% CI 1.4–1.7), poor differentiation (OR 1.7, 95% CI 1.4–2.2), and lymphovascular invasion (LVI; OR 4.1, 95% CI 3.6–4.7). A deficient mismatch repair (MMR) status significantly lowered the risk of LNM (OR 0.3, 95% CI 0.2–0.5). The general linear model demonstrated the highest prediction accuracy, achieving area under the receiver operating characteristic curves of 0.67 and 0.68, with good calibration. In the absence of risk factors, elderly patients (≥74 years of age) had a predicted risk of LNM of 10.7%, yet up to 30% experienced postoperative complications, with mortality rates reaching up to 3.5%. Patients with a deficient MMR status had a predicted risk of LNM of 6.1% if LVI was absent and the tumor was well-differentiated.
Conclusions
The risk of LNM should be weighed against surgical risks. The findings of this study will enable clinicians to make more deliberate considerations about these competing risks before making a shared decision.
期刊介绍:
The Annals of Surgical Oncology is the official journal of The Society of Surgical Oncology and is published for the Society by Springer. The Annals publishes original and educational manuscripts about oncology for surgeons from all specialities in academic and community settings.