Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017, United States.
Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, 485 Lexington Avenue, New York, NY 10017, United States.
Lung Cancer. 2022 Dec;174:60-66. doi: 10.1016/j.lungcan.2022.10.004. Epub 2022 Oct 20.
Accurate lymph node (LN) staging is crucial for prognostication in NSCLC. Diagnosis of pN0 disease is based on the absence of positive LNs, irrespective of the number of LNs excised, and is thus susceptible to sampling error. Tumors that are assumed to be pN0 may in fact be understaged. We developed a tool to quantify the risk of occult nodal disease (OND) among patients with pN0 NSCLC in terms of the number of LNs examined.
Patients treated surgically for stage I-III primary NSCLC between 2004 and 2014 (n = 49,356) were extracted from the Surveillance, Epidemiology, and End Results database. The probability of missing a positive node in terms of the number of LNs examined was modeled using a beta-binomial model. A mathematical tool was then used to calculate the negative predictive value (NPV) corresponding to the number of LNs examined. Ranging from 0 to 100%, higher NPV reflects greater confidence in the pN0 diagnosis and a lower probability of OND.
The median number of LNs examined was 7 for N0, 10 for N1/N2, and 8 for N3 disease. The probability of missing a positive node decreased as LNs examined increased. Additionally, higher T stage required more LNs to confirm an N0 diagnosis. After accounting for false-negative diagnoses, the prevalence of node-positive disease was readjusted from 16% to 22% among patients with T1 disease. According to our tool, with 10 LNs examined, the NPV was 85% (15% probability of OND) for a patient with T3 disease, compared with 95% (5% probability of OND) for a patient with T1 disease.
Accurate pN0 diagnosis depends on the number of LNs examined. The proposed tool offers the ability to quantify, in a patient-specific manner, the confidence in a diagnosis of node-negative disease on the basis of the number of LNs examined.
准确的淋巴结(LN)分期对于非小细胞肺癌(NSCLC)的预后至关重要。pN0 疾病的诊断基于无阳性淋巴结,而不考虑切除的淋巴结数量,因此易受取样误差的影响。被认为是 pN0 的肿瘤实际上可能分期不足。我们开发了一种工具,用于根据检查的淋巴结数量来量化 pN0 NSCLC 患者隐匿性淋巴结疾病(OND)的风险。
从监测、流行病学和最终结果(SEER)数据库中提取 2004 年至 2014 年期间接受 I-III 期原发性 NSCLC 手术治疗的患者(n=49356)。使用贝塔二项式模型来模拟根据检查的淋巴结数量错过阳性节点的概率。然后使用一个数学工具来计算与检查的淋巴结数量相对应的阴性预测值(NPV)。NPV 从 0%到 100%,数值越高表明对 pN0 诊断的信心越大,发生 OND 的概率越低。
N0 的中位数为 7 个,N1/N2 的中位数为 10 个,N3 的中位数为 8 个。随着检查的淋巴结数量增加,错过阳性节点的概率降低。此外,较高的 T 分期需要更多的淋巴结来确认 N0 诊断。在考虑到假阴性诊断后,T1 疾病患者的阳性疾病患病率从 16%调整为 22%。根据我们的工具,对于 T3 疾病患者,检查 10 个淋巴结时,NPV 为 85%(发生 OND 的概率为 15%),而对于 T1 疾病患者,NPV 为 95%(发生 OND 的概率为 5%)。
准确的 pN0 诊断取决于检查的淋巴结数量。该工具提供了一种能力,可以根据检查的淋巴结数量,以患者特异性的方式,对淋巴结阴性疾病的诊断信心进行量化。