OBJECTIVES The rarity of atypical carcinoid (AC) of lung and the lack of prospective clinical trials lead to limited knowledge of its biology, treatment information and prognosis. The current study analyzed AC patients from the Surveillance, Epidemiology, and End Results (SEER) database to better understand the clinical characteristics of this disease and build a prognostic nomogram for clinical practice. MATERIALS AND METHODS A total of 507 AC patients with pathological confirmation from SEER database were performed with univariate Cox regression analyses for both overall survival (OS) and lung cancer specific survival (LCSS) analyses. Of the 507 observations, 464 were used in the multivariable Cox proportional hazards model as training cohort of new nomogram. A new nomogram was constructed based on the training cohort and validated by an external validation cohort to predict the 3-, 5- and 10-year OS of ACs. The accuracy and clinical practicability were separately tested by Harrell's C-indexes, calibration plots and decision curve analyses (DCA). RESULTS Lobectomy and segmental resection were found to be protective factors for AC patients. Age, primary tumor size, N stage, M stage, surgery and regional lymph nodes examination were shown as significant prognostic factors in Cox regression analyses and included in the nomogram as predictors. The C-index in the training cohort for 3-, 5-, and 10-year OS were 0.722, 0.737 and 0.712, respectively. The internal and external calibration plots for predictions of the 3-, 5-, and 10-year OS were in excellent agreement. An online webserver was built based on the proposed nomogram for convenient clinical use. CONCLUSION AC patients with lobectomy or segmental resection tended to have better OS and LCSS. A nomogram was constructed and validated to predict the OS for AC patients and to provide accurate and individualized survival predictions.

中文翻译：

---

外科手术对非典型性支气管肺类癌的作用：基于监测，流行病学和最终结果（SEER）数据库的模型的开发和验证。

目的罕见的非典型类癌（AC）和缺乏前瞻性临床试验导致对其生物学，治疗信息和预后的了解有限。本研究从监测，流行病学和最终结果（SEER）数据库中分析了AC患者，以更好地了解该疾病的临床特征并为临床实践建立预后列线图。材料与方法总共507名从SEER数据库中获得病理证实的AC患者使用单变量Cox回归分析进行了总生存期（OS）和肺癌特异性生存期（LCSS）分析。在507个观测值中，有464个在多变量Cox比例风险模型中用作新列线图的训练队列。基于培训队列构建了新的列线图，并通过外部验证队列进行了验证，以预测AC的3年，5年和10年OS。通过Harrell的C指数，校准图和决策曲线分析（DCA）分别测试了准确性和临床实用性。结果发现肺叶切除和节段切除是AC患者的保护因素。年龄，原发肿瘤大小，N期，M期，手术和局部淋巴结检查在Cox回归分析中显示为重要的预后因素，并在诺模图中作为预测因素。3年，5年和10年OS训练队列中的C指数分别为0.722、0.737和0.712。用于预测3年，5年和10年OS的内部和外部校准图非常吻合。基于提议的列线图构建了一个在线Web服务器，以方便临床使用。结论AC肺叶切除术或节段性切除术患者倾向于有更好的OS和LCSS。构建并验证了诺模图以预测AC患者的OS，并提供准确和个性化的生存预测。