Sasaki Kazunari, Margonis Georgios A, Andreatos Nikolaos, Zhang Xu-Feng, Buettner Stefan, Wang Jaeyun, Deshwar Amar, He Jin, Wolfgang Christopher L, Weiss Matthew, Pawlik Timothy M
Department of Surgery, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, Ohio.
J Surg Oncol. 2017 Sep;116(4):515-523. doi: 10.1002/jso.24678. Epub 2017 May 25.
Recently, a tumor-burden "metro ticket" score (TBS) based on final pathology was proposed to predict outcome following resection of colorectal liver metastasis (CRLM). We sought to validate the TBS prognostic tool using preoperative radiologic cross-sectional imaging.
Imaging TBS was defined on a Cartesian plane that incorporated both maximum tumor size (x-axis) and lesion number (y-axis) assessed by pre-operative imaging. The discriminatory power (area under the curve [AUC]) and goodness-of-fit (Harrel's C statistic and Somer's D statistics) of the imaging TBS model was assessed.
Imaging and pathologic TBS correlated strongly (r = 0.76, P < 0.01). Among patients treated with neoadjuvant therapy, the correlation was strongest among patients with progressive disease/stable disease (PD/SD) (r = 0.81). Discriminatory power of the imaging-based versus pathology-based TBS models were comparable (AUC 0.64 vs. 0.67, respectively P > 0.05). An incremental worsening of long-term survival was noted as the imaging TBS increased (5-year OS: Zone1, Zone2, and Zone3-61.3%, 46.7%, and 38.5%, respectively; P = 0.03). The imaging-based TBS model outperformed the "classic" pathology-based Fong score (Harrel's C-index: imaging TBS-0.56 vs. Fong score-0.53; Somers'D-index: imaging TBS-012 vs. Fong score-0.06).
Imaging-based TBS was superior to traditional tumor size and number and was comparable to pathology-based TBS. Imaging-based TBS may have the potential to facilitate improved preoperative risk stratification of patients with CRLM.
最近,有人提出基于最终病理结果的肿瘤负荷“地铁票”评分(TBS)来预测结直肠癌肝转移(CRLM)切除术后的预后。我们试图使用术前放射学横断面成像来验证TBS预后工具。
成像TBS在笛卡尔平面上定义,该平面结合了术前成像评估的最大肿瘤大小(x轴)和病灶数量(y轴)。评估成像TBS模型的鉴别力(曲线下面积[AUC])和拟合优度(Harrel's C统计量和Somer's D统计量)。
成像TBS与病理TBS高度相关(r = 0.76,P < 0.01)。在接受新辅助治疗的患者中,疾病进展/稳定(PD/SD)患者之间的相关性最强(r = 0.81)。基于成像的TBS模型与基于病理的TBS模型的鉴别力相当(AUC分别为0.64和0.67,P > 0.05)。随着成像TBS增加,长期生存率逐渐恶化(5年总生存率:1区、2区和3 - 6区分别为61.3%、46.7%和38.5%;P = 0.03)。基于成像的TBS模型优于“经典”的基于病理的Fong评分(Harrel's C指数:成像TBS为0.56,Fong评分为0.53;Somer's D指数:成像TBS为0.12,Fong评分为0.06)。
基于成像的TBS优于传统的肿瘤大小和数量,与基于病理的TBS相当。基于成像的TBS可能有潜力促进改善CRLM患者的术前风险分层。