切换至 "中华医学电子期刊资源库"

中华结直肠疾病电子杂志 ›› 2026, Vol. 15 ›› Issue (02) : 133 -145. doi: 10.3877/cma.j.issn.2095-3224.2026.02.005

论著

基于淋巴结转移的结直肠癌新分期与预后关系
温钰1,2, 张尊庶1,2, 丁泽浩1,2, 郑仁杰1,2, 武宾1,2, 孙海翔1,2, 韩超3, 黄陈1,2,3,()   
  1. 1 239001,安徽医科大学附属滁州医院胃肠外科
    2 239001,安徽省滁州市公济胃肠肿瘤研究所
    3 200080,上海交通大学医学院附属第一人民医院胃肠外科
  • 收稿日期:2025-12-01 出版日期:2026-04-25
  • 通信作者: 黄陈
  • 基金资助:
    国家自然科学基金青年科学基金项目(82072662)

A novel staging scheme based on positive lymph nodes and its relationship with prognosis in colorectal cancer

Yu Wen1,2, Zunshu Zhang1,2, Zehao Ding1,2, Renjie Zheng1,2, Bing Wu1,2, Haixiang Sun1,2, Chao Han3, Chen Huang1,2,3,()   

  1. 1 Department of Gastrointestinal Surgery, the Affiliated Chuzhou Hospital of Anhui Medical University, Chuzhou 239001, China
    2 Chuzhou Gongji Gastrointestinal Cancer Institute, Chuzhou 239001, China
    3 Department of Gastrointestinal Surgery, Shanghai General Hospital, Shanghai Jiao Tong University of Medicine, Shanghai 200080, China
  • Received:2025-12-01 Published:2026-04-25
  • Corresponding author: Chen Huang
引用本文:

温钰, 张尊庶, 丁泽浩, 郑仁杰, 武宾, 孙海翔, 韩超, 黄陈. 基于淋巴结转移的结直肠癌新分期与预后关系[J/OL]. 中华结直肠疾病电子杂志, 2026, 15(02): 133-145.

Yu Wen, Zunshu Zhang, Zehao Ding, Renjie Zheng, Bing Wu, Haixiang Sun, Chao Han, Chen Huang. A novel staging scheme based on positive lymph nodes and its relationship with prognosis in colorectal cancer[J/OL]. Chinese Journal of Colorectal Diseases(Electronic Edition), 2026, 15(02): 133-145.

目的

探讨在结直肠癌中,以转移淋巴结比例(LNR)和阳性淋巴结对数比(LODDS)为核心重构的新型分期肿瘤-淋巴结比率-转移(TRM)分期和肿瘤-淋巴结对数比-转移(TSM)分期的预后表现与AJCC制定的TNM分期的差异。

方法

训练集为SEER登记的术后且存在淋巴结转移的结直肠癌患者(2010年—2015年,n=13 469);外部验证集来自滁州市第一人民医院和上海市第一人民医院两中心(n=402)。采用X-tile确定LNR与LODDS截点(0.20/0.57;−0.58/0.17),据此构建TRM和TSM分期。采用多因素Cox回归分析筛选独立预后因素,并通过Harrell C指数、时间依赖受试者工作特征曲线(time-dependent ROC)、曲线下面积(AUC)、校准曲线及决策曲线分析(DCA)评价各模型的区分度、校准度及净临床获益,同时结合Akaike信息准则(AIC)、Bayesian信息准则(BIC)及似然比检验(LRT)比较模型性能。

结果

训练集中TRM和TSM为独立预后因子(均P<0.05),3年/5年AUC(TRM 0.829/0.828 vs. TSM 0.827/0.823 vs. TNM 0.823/0.822)及C指数(TRM 0.757 vs. TSM 0.755 vs. TNM 0.751)均略高于TNM;AIC/BIC与似然比检验均支持TRM。外部验证中,3年总体生存的AUC分别为TNM 0.757、TRM 0.827、TSM 0.829,5年总体生存的AUC分别为TNM 0.650、TRM 0.710、TSM 0.709;TRM的C指数最高,整体表现优于TNM和TSM。校准曲线显示3种模型总体拟合良好,DCA显示TRM和TSM在大多数阈值概率范围内较TNM具有更高净获益,其中TRM优势更为稳定。

结论

基于LNR与LODDS的TRM/TSM分期较传统TNM具有更好的判别能力与潜在临床价值,外部验证结果予以支持。未来需开展多中心前瞻性验证并进行再校准以促进临床推广。

Objective

To evaluate the prognostic performance of two lymph node-based staging systems, tumor-ratio-metastasis (TRM) and tumor-log odds-metastasis (TSM), developed from the lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS), and to compare them with the American Joint Committee on Cancer (AJCC) TNM staging system in colorectal cancer.

Methods

The training cohort consisted of postoperative colorectal cancer patients with pathologically confirmed lymph node metastasis registered in the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015 (n=13 469). The external validation cohort was a two-center cohort composed of patients treated at Chuzhou First People's Hospital and Shanghai General Hospital between 2018 and 2022 (n=402). X-tile software was used to determine the optimal cut-off values for LNR and LODDS (0.20/0.57 and −0.58/0.17, respectively), on the basis of which the TRM and TSM staging systems were constructed. Prognostic performance was assessed using multivariable Cox regression, Harrell's concordance index, time-dependent receiver operating characteristic curves and the corresponding area under the receiver operating characteristic curve at 36 and 60 months, calibration plots, and decision curve analysis. Model fit and comparative performance were further evaluated using the Akaike information criterion, Bayesian information criterion, and likelihood ratio test.

Results

In the training cohort, both TRM and TSM were independent prognostic factors for overall survival (both P<0.05). The 3-and 5-year area under the receiver operating characteristic curve values were 0.829 and 0.828 for TRM, 0.827 and 0.823 for TSM, and 0.823 and 0.822 for TNM, respectively. Harrell's C-index was also slightly higher for TRM (0.757) and TSM (0.755) than for TNM (0.751). The Akaike information criterion, Bayesian information criterion, and likelihood ratio test consistently favored TRM. In the external validation cohort, the 3-year area under the receiver operating characteristic curve values were 0.757 for TNM, 0.827 for TRM, and 0.829 for TSM, while the corresponding 5-year values were 0.650, 0.710, and 0.709. TRM showed the highest C-index overall and outperformed TNM and TSM in overall predictive performance. Calibration plots showed acceptable agreement between predicted and observed survival. Decision curve analysis indicated greater net clinical benefit for TRM and TSM than for TNM across most clinically relevant threshold probabilities, with TRM showing the most consistent overall performance.

Conclusion

The TRM and TSM systems, derived from LNR and LODDS, provided better prognostic discrimination and potential clinical utility than the conventional AJCC TNM staging system in colorectal cancer. External validation in a two-center cohort further supported their robustness, and TRM showed the most favorable overall performance. Further large-scale prospective multicenter studies are needed to confirm their generalizability and support clinical implementation.

图1 X-tile确定LNR与LODDS的最佳截点。1A:LNR的直方图分布显示最佳截点为0.20和0.57;1B:LODDS的直方图分布显示最佳截点为−0.58和0.17
图2 基于LNR与LODDS分组的Kaplan-Meier生存曲线。2A:LNR分组患者的总生存曲线,Log-rank检验差异具有统计学意义(P<0.001);2B:LODDS分组患者的总生存曲线,Log-rank检验差异具有统计学意义(P<0.001)
表1 TRM及TSM分期中位时间表
表2 训练集及验证集单因素Cox分析[例(%)]
临床特征 例数 单因素Cox(训练集)
训练(n=13 469) 验证(n=402) HR(95%CI P
年龄(岁)
≥65 6 753(50.14) 224(55.72) 1.00(参考)
<65 6 716(49.86) 178(44.28) 0.53(0.51~0.56) <0.001
性别
男性 6 761(50.20) 246(61.19) 1.00(参考)
女性 6 708(49.80) 156(38.81) 0.99(0.95~1.04) 0.672
种族
白种人 10 610(78.77) 1.00(参考)
黑种人 1 516(11.26) 1.07(1.01~1.15) 0.049
其他 1 161(8.62) 0.85(0.78~0.92) <0.001
亚洲 1 82(1.35) 402(100.00) 0.65(0.52~0.81) <0.001
肿瘤位置
左半 4 859(36.08) 111(27.61) 1.00(参考)
右半 6 355(47.18) 116(28.86) 1.37(1.31~1.44) <0.001
直肠 977(7.25) 173(43.03) 1.01(0.92~1.10) 0.904
直乙交界 1 278(9.49) 2(0.50) 0.93(0.85~1.01) 0.074
肿瘤直径(cm)
≥5 6 479(48.10) 156(38.81)
<5 6 990(51.90) 246(61.19)
T分期
T1 381(2.83) 7(1.74) 1.00(参考)
T2 966(7.17) 24(5.97) 1.61(1.26~2.04) <0.001
T3 8 351(62.00) 104(25.87) 3.36(2.71~4.18) <0.001
T4a 2 573(19.10) 252(62.69) 5.89(4.73~7.33) <0.001
T4b 1 198(8.89) 15(3.73) 7.19(5.75~8.99) <0.001
N分期
N1a 3 668(27.23) 137(34.08) 1.00(参考)
N1b 3 950(29.33) 121(30.10) 1.30(1.22~1.39) <0.001
N2a 2 757(20.47) 74(18.41) 1.67(1.56~1.78) <0.001
N2b 3 094(22.97) 70(17.41) 2.63(2.47~2.80) <0.001
M分期
M0 10 035(74.50) 389(96.77) 1.00(参考)
M1a 2 006(14.89) 9(2.24) 3.17(3.00~3.35) <0.001
M1b 1 428(10.60) 2(0.50) 4.62(4.34~4.91) <0.001
M1c 2(0.50)
放疗
801(5.95) 1.00(参考)
12 668(94.05) 1.49(1.34~1.65) <0.001
化疗
8 673(64.39) 342(85.07) 1.00(参考)
4 796(35.61) 60(14.93) 2.23(2.14~2.33) <0.001
CEA(ng/mL)
≤5 4 127(30.64) 138(34.33) 1.00(参考)
>5 4 456(33.08) 123(30.60)
2.13(2.01~2.25) <0.001
未知 4 886(36.28) 141(35.07) 1.60(1.51~1.70) <0.001
神经浸润
9 498(70.52) 231(57.46) 1.00(参考)
2 873(21.33) 171(42.54) 1.61(1.53~1.70) <0.001
未知 1 098(8.15) 1.24(1.15~1.34) <0.001
脉管侵犯
211(52.49)
191(47.51)
病理类型
黏液腺癌 1 158(8.60) 45(11.19) 1.00(参考)
印戒细胞癌 231(1.72) 25(6.22) 1.50(1.27~1.77) <0.001
腺癌 10 822(80.35) 299(74.38) 0.86(0.79~0.93) <0.001
其他 1 258(9.34) 33(8.21) 0.59(0.53~0.65) <0.001
TNM分期
ⅢA 1 113(8.26) 30(7.46) 1.00(参考)
ⅢB 6 374(47.32) 244(60.70) 2.04(1.81~2.31) <0.001
ⅢC 2 548(18.92) 115(28.61) 3.74(3.30~4.24) <0.001
ⅣA 2 006(14.89) 9(2.24) 7.18(6.34~8.13) <0.001
ⅣB 1 428(10.60) 2(0.50) 10.52(9.26~11.95) <0.001
ⅣC 2(0.50)
TRM分期
rⅢA 5 293(39.30) 52(12.94) 1.00(参考)
rⅢB 2 819(20.93) 218(54.23) 1.58(1.48~1.69) <0.001
rⅢC 1 923(14.28) 117(29.10) 2.87(2.68~3.08) <0.001
rⅣA 1 740(12.92) 8(1.99) 4.19(3.91~4.48) <0.001
rⅣB 1 694(12.58) 7(1.74) 7.04(6.58~7.53) <0.001
TSM分期
sⅢA 5 045(37.46) 63(15.67) 1.00(参考)
sⅢB 2 920(21.68) 207(51.49) 1.63(1.52~1.74) <0.001
sⅢC 1 786(13.26) 118(29.35) 2.53(2.35~2.72) <0.001
sⅣA 2 679(19.89) 9(2.24) 4.59(4.31~4.88) <0.001
sⅣB 1 039(7.71) 5(1.24) 7.94(7.34~8.59) <0.001
表3 训练集中TNM、TRM、TSM分期多因素Cox分析
临床特征 TNM(训练集) TRM(训练集) TSM(训练集)
P HR(95%CI P HR(95%CI P HR(95%CI
年龄(岁)
≥65 1.00(参考) 1.00(参考) 1.00(参考)
<65 <0.001 0.59(0.56~0.62) <0.001 0.59(0.56~0.62) <0.001 0.60(0.57~0.63)
种族
白种人 1.00(参考) 1.00(参考) 1.00(参考)
黑种人 0.002 1.11(1.04~1.19) <0.001 1.13(1.06~1.21) <0.001 1.14(1.07~1.22)
其他 <0.001 0.82(0.76~0.90) <0.001 0.81(0.75~0.88) <0.001 0.83(0.76~0.90)
亚洲 0.019 0.77(0.61~0.96) 0.034 0.79(0.63~0.98) 0.010 0.75(0.60~0.93)
肿瘤位置
左半 1.00(参考) 1.00(参考) 1.00(参考)
右半 <0.001 1.16(1.10~1.22) <0.001 1.17(1.11~1.23) <0.001 1.14(1.08~1.20)
直肠 0.002 1.16(1.06~1.28) 0.002 1.16(1.06~1.28) 0.023 1.12(1.02~1.23)
直乙交界 0.326 0.96(0.88~1.04) 0.553 0.97(0.89~1.06) 0.385 0.96(0.88~1.05)
肿瘤直径(cm)
≥5 1.00(参考) 1.00(参考) 1.00(参考)
<5 0.004 0.94(0.89~0.98) <0.001 0.92(0.88~0.97) <0.001 0.92(0.88~0.96)
术后放疗
1.00(参考) 1.00(参考) 1.00(参考)
0.931 1.00(0.89~1.11) 0.928 1.01(0.90~1.12) 0.246 1.07(0.96~1.19)
术后化疗
1.00(参考) 1.00(参考) 1.00(参考)
<0.001 2.40(2.28~2.51) <0.001 2.40(2.29~2.52) <0.001 2.35(2.24~2.46)
CEA(ng/mL)
≤5 1.00(参考) 1.00(参考) 1.00(参考)
>5 <0.001 1.44(1.36~1.53) <0.001 1.44(1.35~1.53) <0.001 1.52(1.43~1.61)
未知 <0.001 1.32(1.25~1.40) <0.001 1.32(1.24~1.40) <0.001 1.33(1.25~1.41)
神经浸润
1.00(参考) 1.00(参考) 1.00(参考)
<0.001 1.33(1.26~1.40) <0.001 1.29(1.22~1.36) <0.001 1.26(1.20~1.33)
未知 0.011 1.10(1.02~1.19) 0.032 1.09(1.01~1.17) 0.805 0.99(0.92~1.07)
病理类型
黏液腺癌 1.00(参考) 1.00(参考) 1.00(参考)
印戒细胞癌 0.003 1.29(1.09~1.52) 0.054 1.18(1.00~1.39) 0.535 1.05(0.89~1.24)
腺癌 0.277 0.96(0.89~1.03) 0.231 0.95(0.88~1.03) 0.777 0.99(0.92~1.07)
其他 0.448 0.96(0.86~1.07) 0.138 0.92(0.82~1.03) 0.572 0.97(0.87~1.08)
临床分期
ⅢA 1.00(参考) 1.00(参考) 1.00(参考)
ⅢB <0.001 1.75(1.55~1.98) <0.001 1.57(1.46~1.68) <0.001 1.65(1.54~1.77)
ⅢC <0.001 3.28(2.89~3.74) <0.001 2.76(2.57~2.96) <0.001 2.83(2.63~3.05)
ⅣA <0.001 7.03(6.17~8.00) <0.001 4.63(4.31~4.97) <0.001 5.01(4.69~5.35)
ⅣB <0.001 10.08(8.81~11.53) <0.001 7.71(7.17~8.30) <0.001 8.45(7.77~9.18)
图3 预测结直肠癌3年及5年总生存率的列线图。3A:TNM分期模型;3B:TRM分期模型;3C:TSM分期模型
表4 三种分期模型的信息准则与LRT比较
图4 训练集中TNM、TRM、TSM分期模型对比。4A:3年生存ROC曲线对比;4B:5年生存ROC曲线对比;4C:3年总生存的校准曲线;4D:5年总生存的校准曲线;4E:3年总生存决策曲线;4F:5年总生存决策曲线
表5 验证集中不同模型综合性能比较
图5 验证集中三种模型对比。5A:3年生存ROC曲线对比;5B:5年生存ROC曲线对比;5C:3年总生存校准曲线;5D:5年总生存校准曲线;5E:3年总生存决策曲线;5F:5年总生存决策曲线5G:误差曲线图
[1]
Bray F, Laversanne M, Sung H, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries[J]. CA Cancer J Clin, 2024, 74(3): 229-263.
[2]
Weiser MR. AJCC 8th edition: Colorectal cancer[J]. Ann Surg Oncol, 2018, 25(6): 1454-1455.
[3]
Pan SW, wang PL, xing YN, et al. Lymph node dissection in different anatomical sites of gastric cancer: suggested optimal number, comparison with other lymph node staging and its impact on prognosis[J]. Chinese Journal of Cancer, 2020, 39(1): 32-44.
[4]
Wu W, Zhang RX, Weng JY, et al. Exploring the prognostic value of positive lymph node ratio in stage Ⅲ colorectal cancer patients and establishing a predictive model[J]. China Oncology, 2024, 34(9): 873-880.
[5]
Li Y, Wu G, Zhang Y, et al. Log odds of positive lymph nodes as a novel prognostic predictor for colorectal cancer: a systematic review and meta-analysis[J]. BMC Cancer, 2022, 22(1): 290.
[6]
Wu JH, Han FH, Chen JZ. Retrospective analysis of the relationship between metastatic lymph node ratio and survival in stage I~Ⅲ colorectal cancer[J/CD]. Chin J Colorec Dis ( Electronic Edition), 2016, 5(2): 138.
[7]
Zhang Y, Cao Y, Zhang J, et al. Lymph node ratio improves prediction of overall survival in esophageal cancer patients receiving neoadjuvant chemoradiotherapy: a national cancer database analysis[J]. Ann Surg, 2022, 277(6): e1239-e1246.
[8]
Huang QM, Weng X, Hu YL, et al. Recommended optimal range for the count of examined lymph nodes and lymph node ratio for postoperative adjuvant radiotherapy in patients with pN2 non-small cell lung cancer: a multicenter retrospective cohort investigation[J]. J Thorac Dis, 2025, 17(2): 784-795.
[9]
Occhionorelli S, Andreotti D, Vallese P, et al. Evaluation on prognostic efficacy of lymph nodes ratio (LNR) and log odds of positive lymph nodes (LODDS) in the assessment of complicated colon cancer[J]. World J Surg Oncol, 2018, 16(1): 186.
[10]
Zhang HY, Liu GH, Ye YW, et al. Construction of a new staging system for stage N3 gastric cancer based on the metastatic lymph node ratio[J]. Chinese Journal of General Surgery, 2025, 40(2): 123-130.
[11]
Yang XY, Meng QK, Ma B, et al. Prognostic prediction for stage Ⅱ~Ⅲ colorectal cancer patients using a nomogram model based on the logarithmic odds of positive lymph nodes[J]. Chinese Clinical Oncology, 2025, 30(4): 394-400.
[12]
Bhutiani N, Peacock O, Uppal A, et al. The prognostic impact of tumor deposits in colorectal cancer: more than just N1c[J]. Cancer, 2024, 130(23): 4052-4060.
[13]
Sun ZG, Chen SX, Sun BL, et al. Important role of tumor deposits and negative lymph nodes in prognosis of N1c colorectal cancer patients[J]. World J Gastroenterol, 2025, 31(31): 109857.
[14]
Pyo DH, Kim SH, Ha SY, et al. Revised nodal staging integrating tumor deposit counts with positive lymph nodes in patients with stage Ⅲ colon cancer[J]. Ann Surg, 2021, 277(4): e825-e831.
[15]
Kim J, Lee DW, Park JW, et al. Tumor deposits as an adverse prognostic indicator in stage Ⅲ colon cancer: a multicenter database study[J]. Ann Surg Open, 2024, 5(3): e456.
[16]
Pantoja-Galicia N, Xiong C, Pepe MS, et al. Concordance measures and time-dependent ROC methods[J]. Biostatistics and Epidemiology, 2021, 5(1): 27-54.
[17]
Harrell FE. Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis[M]. New York: Springer, 2015.
[18]
Blanche P, Dartigues JF, Jacqmin~Gadda H. Estimating and comparing time-dependent areas under receiver operating characteristic curves for censored event times with competing risks[J]. Stat Med, 2013, 32(30): 5381-5397.
[19]
Vickers AJ, Elkin EB. Decision curve analysis: a novel method for evaluating prediction models, diagnostic tests, and molecular markers[J]. Med Decis Making, 2006, 26(6): 565-574.
[20]
Vickers AJ, Van Calster B, Steyerberg EW. A simple, step-by-step guide to interpreting decision curve analysis[J]. Diagn Progn Res, 2019, 3(1): 18.
[21]
Budczies J, Klauschen F, Sinn BV, et al. Cutoff finder: a comprehensive and straightforward web application enabling rapid biomarker cutoff optimization[J]. Plos One, 2012, 7(12): e51862.
[22]
Yu JZ, Fei ZL, Zhou B. Postoperative staging and diagnostic value of tumor deposits in colorectal cancer patients: a systematic review[J/OL]. Chin J Colorec Dis (Electronic Edition), 2022, 11(4): 288-296.
[23]
Lin YH, Chen QX, Lu LB, et al. Readjustment of nodal staging by integrating tumor deposits and positive lymph nodes in patients with stage Ⅲ colon cancer: a population-based analysis[J]. Am J Cancer Res, 2023, 13(10): 4976-4988.
[24]
Lundström S, Agger E, Lydrup ML, et al. Tumour deposit count is an independent prognostic factor in colorectal cancer-a population-based cohort study[J]. Br J Surg, 2024, 112(1): znae309.
[25]
Heng Y, Huang M, Xu J, et al. Prognostic value of tumor deposits and positive lymph nodes in colorectal cancer surgery: improved staging for long-term prognosis[J]. BMC Gastroenterol, 2025, 25(1): 154.
[26]
Nagtegaal ID, Washington K, Brierley JD, et al. Tumor deposits in colorectal cancer: definitions for ninth edition of the tumor node metastasis staging system[J]. Mod Pathol, 2026, 39(1): 100924.
[27]
Baqar AR, Wilkins S, Wang W, et al. Log odds of positive lymph nodes is prognostically equivalent to lymph node ratio in non-metastatic colon cancer[J]. BMC Cancer, 2020, 20(1): 762.
[28]
Tao W, Cheng Y, Wang P, et al. Comparison of LNR- and LODDS-based predictive models for prognosis in non-elderly patients with locally advanced rectal cancer undergoing neoadjuvant therapy[J]. Int J Colorectal Dis, 2025, 40(1): 157.
[1] 冯学乾, 王千丹, 张旭. 乳腺叶状肿瘤的诊疗进展与全程管理策略[J/OL]. 中华乳腺病杂志(电子版), 2026, 20(02): 115-119.
[2] 曹喆, 翁桂湖, 刘涛, 张锰钢, 杨刚, 陈浩, 邱江东, 徐建威, 张太平. 新型预后营养炎症评分系统建立以有效预测胰腺癌根治术后患者的长期预后[J/OL]. 中华普通外科学文献(电子版), 2026, 20(02): 85-90.
[3] 邓励旺, 黄予希, 刘施沂, 李彬. 肝内胆管癌中三级淋巴结构及其他病理特征对预后的影响[J/OL]. 中华普通外科学文献(电子版), 2026, 20(02): 91-97.
[4] 樊伟伟, 许怀利, 杨喜佳. 中间入路与左侧前入路在中老年进展期胃癌腹腔镜根治术中的应用对比[J/OL]. 中华普外科手术学杂志(电子版), 2026, 20(02): 117-120.
[5] 邓玉飞, 王志鑫, 娄珂, 张林轩, 马桂春, 港措. 影像组学在肝癌精准诊断、疗效评估及治疗方案决策优化中应用[J/OL]. 中华肝脏外科手术学电子杂志, 2026, 15(02): 172-180.
[6] 吴杰嵘, 严庆, 胡健垣, 陈焕伟. 复发性肝细胞癌再次手术切除与射频消融临床疗效比较[J/OL]. 中华肝脏外科手术学电子杂志, 2026, 15(02): 211-218.
[7] 周嘉敏, 梁贇, 陈洁, 王鲁. 减瘤术在神经内分泌肿瘤肝转移应用中的安全性和疗效[J/OL]. 中华肝脏外科手术学电子杂志, 2026, 15(01): 89-94.
[8] 张雨霄, 潘怡, 邱田, 邹霜梅. 行二代测序结直肠癌患者cMET的表达水平与临床病理特征和分子特征的相关性及预后价值的研究[J/OL]. 中华结直肠疾病电子杂志, 2026, 15(02): 122-132.
[9] 王利明, 马浩越, 余永刚, 陈瑛罡. 结直肠癌手术切除范围的理论依据[J/OL]. 中华结直肠疾病电子杂志, 2026, 15(02): 115-121.
[10] 倪玮峰, 田文扬, 倪雨玲, 杨海宁, 施岳柱. 脂质代谢在七氟烷与丙泊酚麻醉对老年结直肠癌患者认知功能中的作用[J/OL]. 中华消化病与影像杂志(电子版), 2026, 16(02): 173-178.
[11] 董浩垚, 马东阳, 张华, 姚兰, 索利斌, 陈永杰, 王博, 李红培, 刘鲲鹏. 腹膜后肿瘤切除术中大量输血患者术后肺部并发症的危险因素分析[J/OL]. 中华临床医师杂志(电子版), 2026, 20(01): 6-12.
[12] 范辉健, 刘娟. 妊娠期子宫肌瘤肉瘤样变性的诊治[J/OL]. 中华产科急救电子杂志, 2026, 15(01): 21-27.
[13] 单子恒, 王帆, 马丽, 张涛, 邵丽. 头颈部CT血管成像联合头颅CT灌注成像评估急性缺血性脑卒中患者短期预后的效能[J/OL]. 中华脑血管病杂志(电子版), 2026, 20(02): 164-169.
[14] 李丽娜, 彭滢, 巩俪, 郑志东. 血清脂蛋白(a)、载脂蛋白B/载脂蛋白A1比值与急性脑梗死阿替普酶静脉溶栓治疗预后的关系[J/OL]. 中华脑血管病杂志(电子版), 2026, 20(02): 178-184.
[15] 卓玛, 陈玉秀, 连雨晴, 周立新, 郝渝, 季士勇, 胡亚雄, 丁志杰, 赵伟伟, 次旦卓嘎, 袁晶, 赵玉华. 久居高原地区高血压脑出血患者脑出血量与血清C反应蛋白水平的相关性[J/OL]. 中华脑血管病杂志(电子版), 2026, 20(01): 57-60.
阅读次数
全文


摘要


AI


AI小编
你好!我是《中华医学电子期刊资源库》AI小编,有什么可以帮您的吗?