作者投稿
专家审稿
编辑办公
邮件订阅
RSS
Development and Validation of A Prognosis Prediction Model for Esophageal Squamous Cell Carcinoma Patients Treated with Esophagectomy: A Multicenter Real-world Cohort Study
-
摘要:
目的 建立并验证食管鳞状细胞癌患者根治术后生存预后预测模型与风险分级标准，为术后最优辅助治疗方案的确定提供真实世界证据。 方法 分别收集2011年5月31日至2018年7月31日在河南省安阳市肿瘤医院(安阳中心)和2009年8月1日至2018年12月31日在广东省汕头大学医学院附属肿瘤医院(汕头中心)连续就诊的食管鳞状细胞癌患者的临床数据和生存随访数据。以安阳中心数据集为建模集，采用基于多因素Cox比例风险回归逐步后退法和AIC准则(Akaike information criterion)的“两步法”构建总生存预测模型。通过Bootstrap重抽样1 000次对模型进行内部统计验证，在汕头中心数据集进行外部验证。根据列线图得分构建预后风险分级标准。 结果 建模队列和验证队列分别纳入4 171例和1 895例食管鳞状细胞癌患者。模型由年龄、性别、肿瘤原发位置、T分期、N分期、淋巴结清扫数、肿瘤大小、辅助治疗方案和术前血红蛋白水平9个变量组成。其中，N分期与辅助治疗方案存在显著交互作用(P＜0.001)，即与单纯手术相比，N+期患者可能从辅助治疗中获益，但辅助治疗无法改善N0期患者的预后。建模队列的模型一致性指数(C-index)为0.728 (95% CI: 0.713~0.742)，经Bootstrap内部验证后为0.722 (95% CI: 0.711~0.739)，验证队列的模型C-index为0.679 (95% CI: 0.662~0.697)。校准图提示模型预测生存率与观测生存率一致性良好。在两个队列中模型准确性均显著高于第7版AJCC(American Joint Committee on Cancer)TNM分期系统(P＜0.05)。此外，在各TNM分期内部，该模型仍可实现理想的预后风险分层效果。 结论 本研究为我国食管鳞状细胞癌患者根治术后总生存提供了个体化预测模型，并揭示N分期可能是制订食管鳞状细胞癌患者术后辅助治疗方案的重要决定因素。 Abstract:Objective To construct and validate a prognosis prediction model and a risk stratification tool for more precise and individualized evaluation of prognosis for patients following resection of esophageal squamous cell carcinoma (ESCC), and provide real-world evidence for informing optimal decision-making about adjuvant therapy. Methods The comprehensive clinical data and follow-up data were collected from consecutive patients with ESCC in the Anyang Cancer Hospital (Anyang center) from May 31, 2011 to July 31, 2018, and in the Cancer Hospital of Shantou University Medical College (Shantou center) from August 1, 2009 to December 31, 2018. Patients from the Anyang center formed the training cohort, and a two-phase selection based on backward stepwise multivariable Cox proportional hazard regression and minimization of AIC was used to construct prediction model for overall survival (OS). Bootstrap with 1 000 resamples was used for internal validation, and cohort from the Shantou center was used for external validation. Furthermore, a risk stratification tool was constructed according to the tertiles of the total points derived from nomogram in the training cohort. Results A total of 4 171 eligible patients were included in the training cohort, and 1 895 patients were included in the validation cohort. The final model incorporated nine variables: age, sex, primary tumor location, T stage, N stage, number of lymph nodes harvested, tumor size, adjuvant treatment, and preoperative hemoglobin level. A significant interaction was observed between N stage and adjuvant treatment (P < 0.001), which means that N+ stage patients were likely to benefit from addition of adjuvant therapy as opposed to surgery alone, but adjuvant therapy did not improve OS for N0 stage patients. The C-index of the model was 0.728 (95% CI: 0.713-0.742) in the training cohort, 0.722 (95% CI: 0.711-0.739) after bootstrapping, and 0.679 (95% CI: 0.662-0.697) in the external validation cohort. Calibration plots demonstrated favorable agreement between model prediction and actual observation for 1-, 3- and 5-year OS. In both training and validation cohorts, this model outperformed the seventh edition of the AJCC TNM (tumor, lymph node, and metastasis) staging system in terms of the accuracy of prognostic prediction (P < 0.05). Moreover, within each TNM staging group, this model achieved ideal risk stratification. Conclusions The prediction model constructed in this study may provide individualized survival prediction for patients with resected ESCC in China. This study also demonstrated that the N stage may be a fundamental determinant in planning postoperative adjuvant therapy for ESCC patients. 作者贡献：柯杨、何忠虎负责研究设计与论文修订；何忠虎、杨文蕾、刘芳芳、何煜、刘震负责数据整理、统计分析、论文撰写；徐瑞平、杨伟、周福有、张立新、陈蕾负责数据获取；徐瑞平、杨伟、周福有、张立新、陈蕾、侯波林、张凡、蔡奋、许铧文、林妙萍、衡反修、刘萌飞、潘雅琪、刘英、胡喆、陈环宇负责数据集建立与质量控制。利益冲突：所有作者均声明不存在利益冲突 -
图 3 食管鳞状细胞癌患者根治术后生存预后预测模型在建模队列和验证队列的1年、3年、5年生存率预测校准图
A.建模队列填补数据集；B.验证队列填补数据集；C.建模队列完整数据集；D.验证队列完整数据集
表 1 建模队列与验证队列患者特征比较
特征 建模队列(n=4171) 验证队列(n=1895) P值† 例数(%)* 死亡例数(%)# 例数(%)* 死亡例数(%)# 年龄(岁) ＜0.001 ＜60 966(23.2) 232(24.0) 889(46.9) 373(42.0) 60~64 1168(28.0) 294(25.2) 511(27.0) 225(44.0) 65~69 1136(27.2) 326(28.7) 272(14.4) 120(44.1) 70~74 626(15.0) 199(31.8) 168(8.9) 87(51.8) ≥75 275(6.6) 95(34.5) 55(2.9) 38(69.1) 性别 ＜0.001 女 1656(39.7) 403(24.3) 475(25.1) 185(38.9) 男 2515(60.3) 743(29.5) 1420(74.9) 658(46.3) 共病‡ ＜0.001 否 2426(58.2) 627(25.8) 1437(75.8) 629(43.8) 是 1745(41.8) 519(29.7) 458(24.2) 214(46.7) 食管癌家族史§ ＜0.001 否 3013(72.2) 847(28.1) 1643(87.5) 737(44.9) 是 1158(27.8) 299(25.8) 235(12.5) 100(42.6) 原发位置 0.235 食管下段 781(18.7) 212(27.1) 373(19.7) 179(48.0) 食管中段 2745(65.8) 708(25.8) 1259(66.4) 547(43.4) 食管上段 645(15.5) 226(35.0) 263(13.9) 117(44.5) T分期 ＜0.001 T0~T1 959(23.0) 87(9.1) 221(11.7) 38(17.2) T2 1019(24.4) 257(25.2) 296(15.6) 121(40.9) T3 2037(48.8) 719(35.3) 697(36.8) 311(44.6) T4 156(3.7) 83(53.2) 681(35.9) 373(54.8) N分期 ＜0.001 N0 2576(61.8) 473(18.4) 969(51.1) 306(31.6) N1 1041(25.0) 389(37.4) 484(25.5) 233(48.1) N2~N3 554(13.3) 284(51.3) 442(23.3) 304(68.8) 淋巴结清扫数(个) ＜0.001 0~9 617(14.8) 205(33.2) 74(3.9) 42(56.8) 10~19 2358(56.5) 661(28.0) 498(26.3) 226(45.4) 20~29 963(23.1) 240(24.9) 724(38.2) 306(42.3) ≥30 233(5.6) 40(17.2) 599(31.6) 269(44.9) 治疗方案 ＜0.001 单纯手术 2774(66.5) 656(23.6) 1063(56.1) 424(39.9) 手术+术后化疗 1158(27.8) 376(32.5) 272(14.4) 114(41.9) 手术+术后放疗 107(2.6) 50(46.7) 362(19.1) 183(50.6) 手术+术后放化疗 132(3.2) 64(48.5) 198(10.4) 122(61.6) 手术方式 ＜0.001 OE 2929(70.2) 858(29.3) 1382(72.9) 682(49.3) MIE 1242(29.8) 288(23.2) 513(27.1) 161(31.4) 肿瘤大小(cm) ＜0.001 M(P25, P75) 4.0(3.0，5.0) 5.0(4.0，6.0) 红细胞(×1012/L) ＜0.001 ≥4.3 2859(68.5) 739(25.8) 1594(84.1) 678(42.5) ＜4.3 1312(31.5) 407(31.0) 301(15.9) 165(54.8) 血红蛋白(g/L) ＜0.001 ≥130(男)/115(女) 3105(74.4) 833(26.8) 1567(82.7) 692(44.2) ＜130(男)/115(女) 1066(25.6) 313(29.4) 328(17.3) 151(46.0) 嗜酸性粒细胞(×109/L) ＜0.001 ≥0.02 3387(81.2) 935(27.6) 1828(96.5) 811(44.4) ＜0.02 784(18.8) 211(26.9) 67(3.5) 32(47.8) 系统性免疫炎症指数 ＜0.001 ≤650 1905(45.7) 502(26.4) 1203(63.5) 540(44.9) ＞650 2266(54.3) 644(28.4) 692(36.5) 303(43.8) 白蛋白/球蛋白比值 ＜0.001 ≥1.2 2757(66.1) 706(25.6) 1803(95.1) 802(44.5) ＜1.2 1414(33.9) 440(31.1) 92(4.9) 41(44.6) OE：开放食管切除术；MIE：微创食管切除术；*变量中各亚组占总人数的比例; #各亚组内死亡人数占该组人数的比例；†采用χ2检验、t检验；‡患有高血压、糖尿病或心脏病中的任何一种疾病；§验证队列有17例患者食管癌家族史信息缺失 
下载: 导出CSV
表 2 建模队列预后预测变量的单因素和多因素Cox回归模型分析结果
预测变量 n(%) 单因素分析 多因素Cox回归模型分析 HR(95% CI) P值 HR(95% CI) P值 年龄(岁) ＜60 966(23.2) 1.00 1.00 60~64 1168(28.0) 1.16(0.98~1.38) 0.085 1.18(0.99~1.41) 0.061 65~69 1136(27.2) 1.45(1.23~1.72) ＜0.001 1.50(1.26~1.78) ＜0.001 70~74 626(15.0) 1.74(1.44~2.10) ＜0.001 1.62(1.33~1.96) ＜0.001 ≥75 275(6.6) 1.99(1.57~2.53) ＜0.001 1.90(1.49~2.42) ＜0.001 性别 女 1656(39.7) 1.00 1.00 男 2515(60.3) 1.25(1.10~1.41) ＜0.001 1.09(0.97~1.24) 0.157 原发位置 食管下段 781(18.7) 1.00 1.00 食管中段 2745(65.8) 0.95(0.81~1.10) 0.492 1.08(0.93~1.27) 0.304 食管上段 645(15.5) 1.28(1.06~1.54) 0.011 1.59(1.31~1.93) ＜0.001 T分期 T0~T1 959(23.0) 1.00 1.00 T2 1019(24.4) 2.89(2.26~3.68) ＜0.001 2.07(1.61~2.66) ＜0.001 T3 2037(48.8) 4.61(3.69~5.76) ＜0.001 3.00(2.37~3.80) ＜0.001 T4 156(3.7) 9.64(7.13~13.02) ＜0.001 5.10(3.69~7.06) ＜0.001 淋巴结清扫数(个) 0~9 617(14.8) 1.00 1.00 10~19 2358(56.5) 0.95(0.81~1.11) 0.512 0.81(0.69~0.95) 0.009 20~29 963(23.1) 1.04(0.86~1.25) 0.687 0.73(0.61~0.89) 0.001 ≥30 233(5.6) 0.87(0.62~1.23) 0.430 0.52(0.37~0.73) ＜0.001 肿瘤大小(cm) M(P25, P75) 4.0(3.0，5.0) 1.17(1.14~1.21) ＜0.001 1.04(1.00~1.08) 0.070 血红蛋白(g/L) ≥130(男)/115(女) 3105(74.4) 1.00 1.00 ＜130(男)/115(女) 1066(25.6) 1.39(1.22~1.58) ＜0.001 1.33(1.16~1.52) ＜0.001 治疗方案根据N分期分层* N0 单纯手术 2040(79.2) 1.00 1.00 手术+术后化疗 462(17.9) 1.54(1.24~1.90) ＜0.001 1.25(1.00~1.55) 0.047 手术+术后放疗 37(1.4) 2.33(1.39~3.91) 0.001 1.73(1.03~2.92) 0.040 手术+术后放化疗 37(1.4) 4.36(2.78~6.85) ＜0.001 2.87(1.82~4.53) ＜0.001 N1 单纯手术 506(48.6) 1.00 1.00 手术+术后化疗 434(41.7) 0.73(0.59~0.90) 0.003 0.81(0.65~1.00) 0.053 手术+术后放疗 48(4.6) 0.82(0.53~1.28) 0.392 0.79(0.51~1.24) 0.312 手术+术后放化疗 53(5.1) 1.13(0.72~1.78) 0.585 1.08(0.68~1.70) 0.752 N2~N3 单纯手术 228(41.2) 1.00 1.00 手术+术后化疗 262(47.3) 0.66(0.51~0.85) 0.001 0.77(0.60~0.99) 0.041 手术+术后放疗 22(4.0) 0.98(0.55~1.73) 0.941 0.87(0.49~1.55) 0.642 手术+术后放化疗 42(7.6) 0.83(0.53~1.29) 0.408 0.85(0.54~1.33) 0.481 HR：风险比；*根据N分期分层估计各辅助治疗相对于单纯手术的风险比
下载: 导出CSV
表 3 食管鳞状细胞癌患者根治术后预后风险分级标准在建模队列和验证队列的效果评估
风险组 截断值§ 建模队列(n=4171) 例数(%)* 死亡例数(%)# 生存率(%，95% CI) 1年 3年 5年 低风险 [0，11.72978) 1390(33.3) 139(10.0) 98.4(97.7~99.0) 90.3(88.5~92.2) 82.8(79.7~86.0) 中风险 [11.72978，16.60198) 1390(33.3) 347(25.0) 94.9(93.8~96.1) 73.5(70.9~76.3) 62.9(59.4~66.7) 高风险 [16.60198，∞) 1391(33.3) 660(47.4) 85.3(83.4~87.2) 47.4(44.4~50.7) 31.6(28.2~35.5) 风险组 验证队列(n=1895) 例数(%)* 死亡例数(%)# 生存率(%，95% CI) 1年 3年 5年 低风险 474(25.0) 101(21.3) 97.3(95.8~98.7) 87.1(84.1~90.2) 82.0(78.5~85.6) 中风险 517(27.3) 211(40.8) 93.2(91.1~95.4) 71.5(67.7~75.6) 62.9(58.8~67.3) 高风险 904(47.7) 531(58.7) 81.1(78.6~83.7) 51.6(48.4~55.0) 42.9(39.7~46.4) §截断值依据建模队列列线图总得分的三分位数确定；*同表 1；#同表 1
下载: 导出CSV
-
[1] Sung H, Ferlay J, Siegel RL, et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2021, 71: 209-249. doi: 10.3322/caac.21660 [2] Liang H, Fan JH, Qiao YL. Epidemiology, etiology, and prevention of esophageal squamous cell carcinoma in China[J]. Cancer Biol Med, 2017, 14: 33-41. doi: 10.20892/j.issn.2095-3941.2016.0093 [3] Allemani C, Matsuda T, Di Carlo V, et al. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries[J]. Lancet, 2018, 391: 1023-1075. doi: 10.1016/S0140-6736(17)33326-3 [4] Siegel RL, Miller KD, Fuchs HE, et al. Cancer statistics, 2022[J]. CA Cancer J Clin, 2022, 72: 7-33. doi: 10.3322/caac.21708 [5] Van Putten M, De Vos-Geelen J, Nieuwenhuijzen GaP, et al. Long-term survival improvement in oesophageal cancer in the Netherlands[J]. Eur J Cancer, 2018, 94: 138-147. doi: 10.1016/j.ejca.2018.02.025 [6] Zeng H, Chen W, Zheng R, et al. Changing cancer survival in China during 2003-15: a pooled analysis of 17 population-based cancer registries[J] Lancet Glob Health, 2018, 6: e555-e567. doi: 10.1016/S2214-109X(18)30127-X [7] Rice TW, Rusch VW, Apperson-Hansen C, et al. World-wide esophageal cancer collaboration[J]. Dis Esophagus, 2009, 22: 1-8. doi: 10.1111/j.1442-2050.2008.00901.x [8] Watanabe M, Tachimori Y, Oyama T, et al. Comprehensive registry of esophageal cancer in Japan, 2013[J]. Esophagus, 2021, 18: 1-24. doi: 10.1007/s10388-020-00785-y [9] 毛友生, 高树庚, 王群, 等. 中国食管癌临床流行特征及外科治疗概况大数据分析[J]. 中华肿瘤杂志, 2020, 42: 228-233. Mao YS, Gao SG, Wang Q, et al. Epidemiological characteristic and current status of surgical treatment for esophageal cancer by analysis of national registry database[J]. Zhonghua Zhongliu Zazhi, 2020, 42: 228-233. doi: 10.3760/cma.j.cn112152-20191112-00729 Mao YS, Gao SG, Wang Q, et al. Epidemiological characteristic and current status of surgical treatment for esophageal cancer by analysis of national registry database[J]. Zhonghua Zhongliu Zazhi, 2020, 42: 228-233. doi: 10.3760/cma.j.cn112152-20191112-00729 [10] Yang HX, Ling L, Zhang X, et al. Outcome of elderly patients with oesophageal squamous cell carcinoma after surgery[J]. Br J Surg, 2010, 97: 862-867. doi: 10.1002/bjs.7005 [11] Bohanes P, Yang D, Chhibar RS, et al. Influence of sex on the survival of patients with esophageal cancer[J]. J Clin Oncol, 2012, 30: 2265-2272. doi: 10.1200/JCO.2011.38.8751 [12] He Y, Liang D, Du L, et al. Clinical characteristics and survival of 5283 esophageal cancer patients: A multicenter study from eighteen hospitals across six regions in China[J]. Cancer Commun (Lond), 2020, 40: 531-544. doi: 10.1002/cac2.12087 [13] Wang BY, Goan YG, Hsu PK, et al. Tumor length as a prognostic factor in esophageal squamous cell carcinoma[J]. Ann Thorac Surg, 2011, 91: 887-893. doi: 10.1016/j.athoracsur.2010.11.011 [14] Smyth EC, Lagergren J, Fitzgerald RC, et al. Oesophageal cancer[J]. Nat Rev Dis Primers, 2017, 3: 17048. doi: 10.1038/nrdp.2017.48 [15] Miyata H, Yamasaki M, Kurokawa Y, et al. Prognostic value of an inflammation-based score in patients undergoing pre-operative chemotherapy followed by surgery for esophageal cancer[J]. Exp Ther Med, 2011, 2: 879-885. doi: 10.3892/etm.2011.308 [16] Su D, Zhou X, Chen Q, et al. Prognostic Nomogram for Thoracic Esophageal Squamous Cell Carcinoma after Radical Esophagectomy[J]. PLoS One, 2015, 10: e0124437. doi: 10.1371/journal.pone.0124437 [17] Shao Y, Ning Z, Chen J, et al. Prognostic nomogram integrated systemic inflammation score for patients with esophageal squamous cell carcinoma undergoing radical esophagectomy[J]. Sci Rep, 2015, 5: 18811. doi: 10.1038/srep18811 [18] Chen GP, Huang Y, Yang X, et al. A Nomogram to Predict Prognostic Value of Red Cell Distribution Width in Patients with Esophageal Cancer[J]. Mediators Inflamm, 2015, 2015: 854670. [19] Liu JS, Huang Y, Yang X, et al. A nomogram to predict prognostic values of various inflammatory biomarkers in patients with esophageal squamous cell carcinoma[J]. Am J Cancer Res, 2015, 5: 2180-2189. [20] Yu S, Zhang W, Ni W, et al. Nomogram and recursive partitioning analysis to predict overall survival in patients with stage ⅡB-Ⅲ thoracic esophageal squamous cell carcinoma after esophagectomy[J]. Oncotarget, 2016, 7: 55211-55221. doi: 10.18632/oncotarget.10904 [21] Duan J, Deng T, Ying G, et al. Prognostic nomogram for previously untreated patients with esophageal squamous cell carcinoma after esophagectomy followed by adjuvant chemotherapy[J]. Jpn J Clin Oncol, 2016, 46: 336-343. doi: 10.1093/jjco/hyv206 [22] Chen S, Yang X, Feng JF. A novel inflammation-based prognostic score for patients with esophageal squamous cell carcinoma: the c-reactive protein/prognostic nutritional index ratio[J]. Oncotarget, 2016, 7: 62123-62132. doi: 10.18632/oncotarget.11389 [23] Deng W, Wang Q, Xiao Z, et al. A prognostic nomogram for overall survival after neoadjuvant radiotherapy or chemoradiotherapy in thoracic esophageal squamous cell carcino-ma: a retrospective analysis[J]. Oncotarget, 2017, 8: 41102-41112. doi: 10.18632/oncotarget.17062 [24] Deng W, Zhang W, Yang J, et al. Nomogram to Predict Overall Survival for Thoracic Esophageal Squamous Cell Carcinoma Patients After Radical Esophagectomy[J]. Ann Surg Oncol, 2019, 26: 2890-2898. doi: 10.1245/s10434-019-07393-w [25] Li X, Xu J, Zhu L, et al. A novel nomogram with preferable capability in predicting the overall survival of patients after radical esophageal cancer resection based on accessible clinical indicators: A comparison with AJCC staging[J]. Cancer Med, 2021, 10: 4228-4239. doi: 10.1002/cam4.3878 [26] Shao CY, Liu XL, Yao S, et al. Development and validation of a new clinical staging system to predict survival for esophageal squamous cell carcinoma patients: Application of the nomogram[J]. Eur J Surg Oncol, 2021, 47: 1473-1480. doi: 10.1016/j.ejso.2020.12.004 [27] Jung HA, Adenis A, Lee J, et al. Nomogram to predict treatment outcome of fluoropyrimidine/platinum-based chemotherapy in metastatic esophageal squamous cell carcinoma[J]. Cancer Res Treat, 2013, 45: 285-294. doi: 10.4143/crt.2013.45.4.285 [28] Wang J, Wu LL, Zhang Y, et al. Establishing a survival prediction model for esophageal squamous cell carcinoma based on CT and histopathological images[J]. Phys Med Biol, 2021, 66. doi: 10.1088/1361-6560/ac1020. [29] Zhao P, Yan W, Fu H, et al. Efficacy of postoperative adjuvant chemotherapy for esophageal squamous cell carcinoma: A meta-analysis[J]. Thorac Cancer, 2018, 9: 1048-1055. doi: 10.1111/1759-7714.12787 [30] Lin HN, Chen LQ, Shang QX, et al. A meta-analysis on surgery with or without postoperative radiotherapy to treat squamous cell esophageal carcinoma[J]. Int J Surg, 2020, 80: 184-191. doi: 10.1016/j.ijsu.2020.06.046 [31] Kang J, Chang JY, Sun X, et al. Role of Postoperative Concurrent Chemoradiotherapy for Esophageal Carcinoma: A meta-analysis of 2165 Patients[J]. J Cancer, 2018, 9: 584-593. doi: 10.7150/jca.20940 [32] National Comprehensive Cancer Network. Esophageal and Esophagogastric Junction Cancers[EB/OL]. (2021-08-03)[2022-01-14]. https://www.nccn.org/professionals/physician_gls/pdf/esophageal.pdf. [33] Noh SH, Park SR, Yang HK, et al. Adjuvant capecitab-ine plus oxaliplatin for gastric cancer after D2 gastrectomy (CLASSIC): 5-year follow-up of an open-label, randomised phase 3 trial[J]. Lancet Oncol, 2014, 15: 1389-1396. doi: 10.1016/S1470-2045(14)70473-5 [34] Smalley SR, Benedetti JK, Haller DG, et al. Updated analysis of SWOG-directed intergroup study 0116: a phase Ⅲ trial of adjuvant radiochemotherapy versus observation after curative gastric cancer resection[J]. J Clin Oncol, 2012, 30: 2327-2333. doi: 10.1200/JCO.2011.36.7136 [35] Rice TW, Blackstone EH, Rusch VW. 7th edition of the AJCC Cancer Staging Manual: esophagus and esophagogastric junction[J]. Ann Surg Oncol, 2010, 17: 1721-1724. doi: 10.1245/s10434-010-1024-1 [36] Harrell Jr FE, Harrell Jr MFE. Package'hmisc '[J]. CRAN2018, 2019, 2019: 235-236. [37] Wang Y, Li J, Xia Y, et al. Prognostic nomogram for intrahepatic cholangiocarcinoma after partial hepatectomy[J]. J Clin Oncol, 2013, 31: 1188-1195. doi: 10.1200/JCO.2012.41.5984 [38] Tian H, Yang W, Hu Y, et al. Estimating cancer incidence based on claims data from medical insurance systems in two areas lacking cancer registries in China[J]. EClinicalMedicine, 2020, 20: 100312. doi: 10.1016/j.eclinm.2020.100312 [39] He Z, Ke Y. Precision screening for esophageal squamous cell carcinoma in China[J]. Chin J Cancer Res, 2020, 32: 673-682. doi: 10.21147/j.issn.1000-9604.2020.06.01 [40] Jiang YQ, Chen SF, Zhu B. Prognostic factors and family history for survival of esophageal squamous cell carcinoma patients after surgery[J]. Ann Thorac Surg, 2010, 90: 908-913. doi: 10.1016/j.athoracsur.2010.05.060 [41] Visser E, Markar SR, Ruurda JP, et al. Prognostic Value of Lymph Node Yield on Overall Survival in Esophageal Cancer Patients: A Systematic Review and Meta-analysis[J]. Ann Surg, 2019, 269: 261-268. doi: 10.1097/SLA.0000000000002824 [42] Anandavadivelan P, Lagergren P. Cachexia in patients with oesophageal cancer[J]. Nat Rev Clin Oncol, 2016, 13: 185-198. doi: 10.1038/nrclinonc.2015.200 [43] Huang XZ, Yang YC, Chen Y, et al. Preoperative Anemia or Low Hemoglobin Predicts Poor Prognosis in Gastric Cancer Patients: A Meta-Analysis[J]. Dis Markers, 2019, 2019: 7606128. [44] Lu Z, Fang Y, Liu C, et al. Early Interdisciplinary Supportive Care in Patients With Previously Untreated Metastatic Esophagogastric Cancer: A Phase Ⅲ Randomized Controlled Trial[J]. J Clin Oncol, 2021, 39: 748-756. doi: 10.1200/JCO.20.01254 [45] Zhang SS, Yang H, Xie X, et al. Adjuvant chemotherapy versus surgery alone for esophageal squamous cell carcinoma: a meta-analysis of randomized controlled trials and nonrandomized studies[J]. Dis Esophagus, 2014, 27: 574-584. doi: 10.1111/dote.12073 [46] Ni W, Yu S, Zhang W, et al. A phase-Ⅱ/Ⅲ randomized controlled trial of adjuvant radiotherapy or concurrent chemoradiotherapy after surgery versus surgery alone in patients with stage-ⅡB/Ⅲ esophageal squamous cell carcinoma[J]. BMC Cancer, 2020, 20: 130. doi: 10.1186/s12885-020-6592-2 [47] Rucker AJ, Raman V, Jawitz OK, et al. The Impact of Adjuvant Therapy on Survival After Esophagectomy for Node-negative Esophageal Adenocarcinoma[J]. Ann Surg, 2022, 275: 348-355. doi: 10.1097/SLA.0000000000003886 -
点击查看大图
图(4) / 表(3)
计量
- 文章访问数: 2126
- HTML全文浏览量: 519
- PDF下载量: 107
- 被引次数: 0
