Department of Gastroenterology and Hepatology, University Medical Center Utrecht, Utrecht, the Netherlands.
Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, the Netherlands.
Gastroenterology. 2018 May;154(6):1647-1659. doi: 10.1053/j.gastro.2018.01.023. Epub 2018 Jan 31.
BACKGROUND & AIMS: Most patients with pedunculated T1 colorectal tumors referred for surgery are not found to have lymph node metastases, and were therefore unnecessarily placed at risk for surgery-associated complications. We aimed to identify histologic factors associated with need for surgery in patients with pedunculated T1 colorectal tumors.
We performed a cohort-nested matched case-control study of 708 patients diagnosed with pedunculated T1 colorectal tumors at 13 hospitals in The Netherlands, from January 1, 2000 through December 31, 2014, followed for a median of 44 months (interquartile range, 20-80 months). We identified 37 patients (5.2%) who required surgery (due to lymph node, intramural, or distant metastases). These patients were matched with patients with pedunculated T1 colorectal tumors without a need for surgery (no metastases, controls, n = 111). Blinded pathologists analyzed specimens from each tumor, stained with H&E. We evaluated associations between histologic factors and patient need for surgery using univariable conditional logistic regression analysis. We used multivariable least absolute shrinkage and selection operator (LASSO; an online version of the LASSO model is available at: http://t1crc.com/calculator/) regression to develop models for identification of patients with tumors requiring surgery, and tested the accuracy of our model by projecting our case-control data toward the entire cohort (708 patients). We compared our model with previously developed strategies to identify high-risk tumors: conventional model 1 (based on poor differentiation, lymphovascular invasion, or Haggitt level 4) and conventional model 2 (based on poor differentiation, lymphovascular invasion, Haggitt level 4, or tumor budding).
We identified 5 histologic factors that differentiated cases from controls: lymphovascular invasion, Haggitt level 4 invasion, muscularis mucosae type B (incompletely or completely disrupted), poorly differentiated clusters and tumor budding, which identified patients who required surgery with an area under the curve (AUC) value of 0.83 (95% confidence interval, 0.76-0.90). When we used a clinically plausible predicted probability threshold of ≥4.0%, 67.5% (478 of 708) of patients were predicted to not need surgery. This threshold identified patients who required surgery with 83.8% sensitivity (95% confidence interval, 68.0%-93.8%) and 70.3% specificity (95% confidence interval, 60.9%-78.6%). Conventional models 1 and 2 identified patients who required surgery with lower AUC values (AUC, 0.67; 95% CI, 0.60-0.74; P = .002 and AUC, 0.64; 95% CI, 0.58-0.70; P < .001, respectively) than our LASSO model. When we applied our LASSO model with a predicted probability threshold of ≥4.0%, the percentage of missed cases (tumors mistakenly assigned as low risk) was comparable (6 of 478 [1.3%]) to that of conventional model 1 (4 of 307 [1.3%]) and conventional model 2 (3 of 244 [1.2%]). However, the percentage of patients referred for surgery based on our LASSO model was much lower (32.5%, n = 230) than that for conventional model 1 (56.6%, n = 401) or conventional model 2 (65.5%, n = 464).
In a cohort-nested matched case-control study of 708 patients with pedunculated T1 colorectal carcinomas, we developed a model based on histologic features of tumors that identifies patients who require surgery (due to high risk of metastasis) with greater accuracy than previous models. Our model might be used to identify patients most likely to benefit from adjuvant surgery.
大多数接受手术治疗的带蒂 T1 结直肠肿瘤患者未发现淋巴结转移,因此不必要地面临手术相关并发症的风险。我们旨在确定与带蒂 T1 结直肠肿瘤患者手术相关的组织学因素。
我们对荷兰 13 家医院 2000 年 1 月 1 日至 2014 年 12 月 31 日期间诊断为带蒂 T1 结直肠肿瘤的 708 例患者进行了队列嵌套匹配病例对照研究,中位随访时间为 44 个月(四分位距,20-80 个月)。我们发现 37 例(5.2%)患者需要手术(由于淋巴结、壁内或远处转移)。这些患者与无手术需求的带蒂 T1 结直肠肿瘤患者(无转移,对照组,n=111)相匹配。盲法病理学家分析了每个肿瘤的 H&E 染色标本。我们使用单变量条件逻辑回归分析评估了组织学因素与患者手术需求之间的关联。我们使用多变量最小绝对收缩和选择算子(LASSO;LASSO 模型的在线版本可在:http://t1crc.com/calculator/)回归来开发识别需要手术的肿瘤患者的模型,并通过将我们的病例对照数据投影到整个队列(708 例患者)来测试我们模型的准确性。我们将我们的模型与先前用于识别高危肿瘤的策略进行了比较:传统模型 1(基于低分化、血管淋巴管侵犯或 Haggitt 分级 4)和传统模型 2(基于低分化、血管淋巴管侵犯、Haggitt 分级 4 或肿瘤芽生)。
我们确定了 5 个可区分病例和对照组的组织学因素:血管淋巴管侵犯、Haggitt 分级 4 侵犯、黏膜下肌层 B 型(不完全或完全破坏)、低分化簇和肿瘤芽生,其 AUC 值为 0.83(95%置信区间,0.76-0.90)。当我们使用临床合理的预测概率阈值≥4.0%时,708 例患者中有 67.5%(478 例)被预测不需要手术。该阈值以 83.8%的敏感性(95%置信区间,68.0%-93.8%)和 70.3%的特异性(95%置信区间,60.9%-78.6%)识别出需要手术的患者。传统模型 1 和 2 识别出需要手术的患者的 AUC 值较低(AUC,0.67;95%CI,0.60-0.74;P=0.002 和 AUC,0.64;95%CI,0.58-0.70;P<0.001),低于我们的 LASSO 模型。当我们应用预测概率阈值≥4.0%的 LASSO 模型时,漏诊病例(肿瘤错误地被归类为低风险)的比例(478 例中有 6 例[1.3%])与传统模型 1(307 例中有 4 例[1.3%])和传统模型 2(244 例中有 3 例[1.2%])相当。然而,根据我们的 LASSO 模型转诊接受手术的患者比例(32.5%,n=230)远低于传统模型 1(56.6%,n=401)或传统模型 2(65.5%,n=464)。
在一项对 708 例带蒂 T1 结直肠癌患者的队列嵌套匹配病例对照研究中,我们基于肿瘤的组织学特征开发了一种模型,该模型可以更准确地识别出需要手术(由于转移风险高)的患者,优于以前的模型。我们的模型可用于识别最有可能受益于辅助手术的患者。