Division of Surgical Oncology, Department of Surgery, Mayo Clinic Arizona, Phoenix, AZ.
Surgical Outcomes Program, Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic Arizona, Phoenix, AZ.
Ann Surg. 2021 Jul 1;274(1):155-161. doi: 10.1097/SLA.0000000000003501.
Histologic subtypes of appendiceal cancer vary in their propensity for metastases to regional lymph nodes (LN). A predictive model would help direct subsequent surgical therapy.
The National Cancer Database was queried for patients with appendiceal cancer undergoing surgery between 1998 and 2012. Multivariable logistic regression was used to develop a predictive model of LN metastases which was internally validated using Brier score and Area under the Curve (AUC).
A total of 21,647 patients were identified, of whom 9079 (41.9%) had node negative disease, 4575 (21.1%) node positive disease, and 7993 (36.9%) unknown LN status. The strongest predictors of LN positivity were histology (carcinoid tumors OR 12.78, 95% CI 9.01-18.12), increasing T Stage (T3 OR 3.36, 95% CI 2.52-4.50, T4 OR 6.30, 95% CI 4.71-8.42), and tumor grade (G3 OR 5.55, 95% CI 4.78-6.45, G4 OR 5.98, 95% CI 4.30-8.31). The coefficients from the regression analysis were used to construct a calculator that generated predicted probabilities of LN metastases given certain inputs. Internal validation of the overall model showed an AUC of 0.75 (95% CI 0.74-0.76) and Brier score of 0.188. Histology-specific predictive models were also constructed with an AUC that varied from 0.669 for signet cell to 0.75 for goblet cell tumors.
The risk for nodal metastases in patients with appendiceal cancers can be quantified with reasonable accuracy using a predictive model incorporating patient age, sex, tumor histology, T-stage, and grade. This can help inform clinical decision making regarding the need for a right hemicolectomy following appendectomy.
阑尾癌的组织学亚型在向区域淋巴结（LN）转移的倾向方面存在差异。预测模型将有助于指导后续的手术治疗。
从 1998 年至 2012 年期间接受手术治疗的阑尾癌患者的国家癌症数据库中查询了数据。多变量逻辑回归用于建立 LN 转移的预测模型，并用 Brier 评分和曲线下面积（AUC）进行内部验证。
共确定了 21647 例患者，其中 9079 例（41.9%）为淋巴结阴性疾病，4575 例（21.1%）为淋巴结阳性疾病，7993 例（36.9%）为淋巴结状态未知。LN 阳性的最强预测因素是组织学（类癌肿瘤 OR 12.78，95%CI 9.01-18.12），T 分期增加（T3 OR 3.36，95%CI 2.52-4.50，T4 OR 6.30，95%CI 4.71-8.42）和肿瘤分级（G3 OR 5.55，95%CI 4.78-6.45，G4 OR 5.98，95%CI 4.30-8.31）。回归分析的系数用于构建一个计算器，该计算器根据特定输入生成 LN 转移的预测概率。对整个模型的内部验证显示 AUC 为 0.75（95%CI 0.74-0.76），Brier 评分为 0.188。还构建了组织学特异性预测模型，其 AUC 范围从印戒细胞癌的 0.669 到杯状细胞癌的 0.75。
使用包含患者年龄、性别、肿瘤组织学、T 分期和分级的预测模型，可以合理准确地量化阑尾癌患者的淋巴结转移风险。这有助于为阑尾切除术后是否需要右半结肠切除术提供决策依据。
