Department of Oncology, Mayo Clinic, Rochester, Minnesota.
Department of Medicine, University of South Carolina School of Medicine, Columbia, South Carolina.
J Natl Compr Canc Netw. 2020 Feb;18(2):151-159. doi: 10.6004/jnccn.2019.7357.
Current staging systems for gallbladder cancer (GBC) are primarily based on surgical pathology and therefore are not relevant for unresectable patients and those undergoing neoadjuvant chemotherapy.
Patients with a confirmed diagnosis of GBC managed at a tertiary referral center (2000-2016) were included. Independent predictors of overall survival (OS) were identified using multivariable analysis (MVA). A combination of these variables was then assessed to identify a set of factors that provided maximal accuracy in predicting OS, and a nomogram and a new staging system were created based on these factors. Harrell's C-statistic was calculated to evaluate the predictive accuracy of the nomogram and staging system.
A total of 528 patients were included in the final analysis. On MVA, factors predictive of poor OS were older age, ECOG performance status, hemoglobin level <9 g/dL, presence of metastases, and alkaline phosphatase (ALP) level >200 U/L. A nomogram and a 4-tier staging system predictive of OS were created using age at diagnosis, ECOG status, tumor size, presence or absence of metastasis, and ALP level. The C-statistic for this novel staging system was 0.71 compared with 0.69 for the TNM staging system (P=.08). In patients who did not undergo surgery, the C-statistics of the novel and TNM staging systems were 0.60 and 0.51, respectively (P<.001).
We created a novel, clinically based staging system for GBC based on nonoperative information at the time of diagnosis that was superior to the TNM staging system in predicting OS in patients who did not undergo surgery, and that performed on par with TNM staging in surgical patients.
目前的胆囊癌（GBC）分期系统主要基于手术病理学，因此对于不可切除的患者和接受新辅助化疗的患者并不相关。
纳入在三级转诊中心确诊为 GBC 并接受治疗的患者（2000-2016 年）。使用多变量分析（MVA）确定总生存期（OS）的独立预测因素。然后评估这些变量的组合，以确定一组可最大程度准确预测 OS 的因素，并基于这些因素创建一个列线图和一个新的分期系统。计算 Harrell 的 C 统计量来评估列线图和分期系统的预测准确性。
共有 528 例患者纳入最终分析。在 MVA 中，与较差 OS 相关的因素为年龄较大、ECOG 表现状态、血红蛋白水平<9g/dL、存在转移以及碱性磷酸酶（ALP）水平>200U/L。使用诊断时的年龄、ECOG 状态、肿瘤大小、是否存在转移以及 ALP 水平创建了一个预测 OS 的列线图和 4 级分期系统。该新型分期系统的 C 统计量为 0.71，而 TNM 分期系统为 0.69（P=0.08）。在未接受手术的患者中，新型和 TNM 分期系统的 C 统计量分别为 0.60 和 0.51（P<0.001）。
我们基于诊断时非手术信息创建了一个新的基于临床的 GBC 分期系统，该系统在预测未接受手术的患者的 OS 方面优于 TNM 分期系统，在接受手术的患者中与 TNM 分期系统相当。
