中文English
ISSN 1001-5256 (Print)
ISSN 2097-3497 (Online)
CN 22-1108/R

Risk factors for concurrent hepatic hydrothorax before intervention in primary liver cancer and construction of a nomogram prediction model

DOI: 10.12449/JCH250112
Research funding:

Kunming Municipal Health Commission Fund Project (2022-03-08-008)

More Information
  • Corresponding author: LIU Chunyun, 751440760@qq.com (ORCID: 0000-0001-5343-5305); LIU Li, liuli197210@163.com (ORCID: 0000-0001-7712-4931)
  • Received Date: 2024-06-20
  • Accepted Date: 2024-08-20
  • Published Date: 2025-01-25
  •   Objective  To investigate the influencing factors for hepatic hydrothorax (HH) before intervention for primary hepatic carcinoma (PHC), and to construct and assess the nomogram risk prediction model.  Methods  A retrospective analysis was performed for the clinical data of 353 hospitalized patients who attended the Third People’s Hospital of Kunming for the first time from October 2012 to October 2021 and there diagnosed with PHC, and according to the presence or absence of HH, they were divided into HH group with 153 patients and non-HH group with 200 patients. General data and the data of initial clinical testing after admission were collected from all PHC patients. The independent-samples t test was used for comparison of normally distributed continuous data between two groups, and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups; the chi-square test or the Fisher’s exact test was used for comparison of categorical data between groups. After the multicollinearity test was performed for the variables with statistical significance determined by the univariate analysis, the multivariate Logistic regression analysis was used to identify independent influencing factors. The “rms” software package was used to construct a nomogram risk prediction model, and the Hosmer-Lemeshow test and the receiver operating characteristic (ROC) curve were used to assess the risk prediction model; the “Calibration Curves” software package was used to plot the calibration curve, and the “rmda” software package was used to plot the clinical decision curve and the clinical impact curve.  Results  Among the 353 patients with PHC, there were 153 patients with HH, with a prevalence rate of 43.34%. Child-Pugh class B (odds ratio [OR]=2.652, 95% confidence interval [CI]: 1.050 — 6.698, P=0.039), Child-Pugh class C (OR=7.963, 95%CI: 1.046‍ ‍—‍ ‍60.632, P=0.045), total protein (OR=0.947, 95%CI: 0.914‍ ‍—‍ ‍0.981, P=0.003), high-sensitivity C-reactive protein (OR=1.007, 95%CI: 1.001‍ ‍—‍ ‍1.014, P=0.025), and interleukin-2 (OR=0.801, 95%CI: 0.653‍ ‍—‍ ‍0.981, P=0.032) were independent influencing factors for HH before PHC intervention, and a nomogram risk prediction model was established based on these factors. The Hosmer-Lemeshow test showed that the model had a good degree of fitting (χ2=5.006, P=0.757), with an area under the ROC curve of 0.752 (95%CI: 0.701‍ ‍—‍ ‍0.803), a sensitivity of 78.40%, and a specificity of 63.50%. The calibration curve showed that the model had good consistency in predicting HH before PHC intervention, and the clinical decision curve and the clinical impact curve showed that the model had good clinical practicability within a certain threshold range.  Conclusion  Child-Pugh class, total protein, interleukin-2, and high-sensitivity C-reactive protein are independent influencing factors for developing HH before PHC intervention, and the nomogram model established based on these factors can effectively predict the risk of developing HH.

     

  • [1]
    RUMGAY H, ARNOLD M, FERLAY J, et al. Global burden of primary liver cancer in 2020 and predictions to 2040[J]. J Hepatol, 2022, 77( 6): 1598- 1606. DOI: 10.1016/j.jhep.2022.08.021.
    [2]
    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( 3): 209- 249. DOI: 10.3322/caac.21660.
    [3]
    ZHOU MG, WANG HD, ZENG XY, et al. Mortality, morbidity, and risk factors in China and its provinces, 1990-2017: A systematic analysis for the global burden of disease study 2017[J]. Lancet, 2019, 394( 10204): 1145- 1158. DOI: 10.1016/S0140-6736(19)30427-1.
    [4]
    LI JJ, YANG HH, HUO G. Analysis of clinical features,cell morphology and prognostic factors in patients with primary liver cancer[J]. J Clin Exp Med, 2024, 23( 6): 566- 570. DOI: 10.3969/j.issn.1671-4695.2024.06.002.

    李姣姣, 杨会会, 霍刚. 原发性肝癌患者临床特征、细胞形态学分析及其预后的影响因素分析[J]. 临床和实验医学杂志, 2024, 23( 6): 566- 570. DOI: 10.3969/j.issn.1671-4695.2024.06.002.
    [5]
    BØDTGER U, HALLIFAX R. Epidemiology: why is pleural disease becoming more common?[M]// Pleural Disease. European Respiratory Society, 2020: 1- 12.
    [6]
    WILKINS H, BRITT E, BHATNAGAR M, et al. Hepatic hydrothorax[J]. J Thorac Dis, 2024, 16( 2): 1662- 1673. DOI: 10.21037/jtd-23-1649.
    [7]
    BANINI BA, ALWATARI Y, STOVALL M, et al. Multidisciplinary management of hepatic hydrothorax in 2020: An evidence-based review and guidance[J]. Hepatology, 2020, 72( 5): 1851- 1863. DOI: 10.1002/hep.31434.
    [8]
    CHAABAN T, KANJ N, AKL I BOU. Hepatic hydrothorax: An updated review on a challenging disease[J]. Lung, 2019, 197( 4): 399- 405. DOI: 10.1007/s00408-019-00231-6.
    [9]
    WILKINS H, BRITT E, BHATNAGAR M, et al. Hepatic hydrothorax[J]. J Thorac Dis, 2024, 16( 2): 1662- 1673. DOI: 10.21037/jtd-23-1649.
    [10]
    VIDYANI A, SIBARANI CI, WIDODO B, et al. Diagnosis and management of hepatic hydrothorax[J]. Korean J Gastroenterol, 2024, 83( 2): 45- 53. DOI: 10.4166/kjg.2023.107.
    [11]
    CADRANEL JF D, OLLIVIER-HOURMAND I, CADRANEL J, et al. International survey among hepatologists and pulmonologists on the hepatic hydrothorax: Plea for recommendations[J]. BMC Gastroenterol, 2023, 23( 1): 305. DOI: 10.1186/s12876-023-02931-z.
    [12]
    GILBERT CR, SHOJAEE S, MALDONADO F, et al. Pleural interventions in the management of hepatic hydrothorax[J]. Chest, 2022, 161( 1): 276- 283. DOI: 10.1016/j.chest.2021.08.043.
    [13]
    PIPPARD B, BHATNAGAR M, MCNEILL L, et al. Hepatic hydrothorax: A narrative review[J]. Pulm Ther, 2022, 8( 3): 241- 254. DOI: 10.1007/s41030-022-00195-8.
    [14]
    XIE YX, QIU JJ, TANG WZ, et al. Establishment of risk prediction model for intractable pleural effusion in patients with hepatocellular carcinoma after hepatectomy[J]. Chin Nurs Res, 2024, 38( 1): 130- 134. DOI: 10.12102/j.issn.1009-6493.2024.01.021.

    谢远喜, 邱洁净, 唐雯桢, 等. 肝癌病人肝切除术后难治性胸腔积液风险预测模型的构建[J]. 护理研究, 2024, 38( 1): 130- 134. DOI: 10.12102/j.issn.1009-6493.2024.01.021.
    [15]
    ZHAO JY, LIN HY, GONG CF, et al. Establishment and validation of a predictive nomogram for severe pleural effusion in liver cancer patients after hepatectomy[J]. Medicine(Baltimore), 2024, 103( 10): e36556. DOI: 10.1097/MD.0000000000036556.
    [16]
    ZHU LM, HUANG JX, JIN CH, et al. Retrospective cohort study on the correlation analysis among peri-procedural factors, complications, and local tumor progression of lung tumors treated with CT-guided microwave ablation[J]. J Thorac Dis, 2023, 15( 12): 6915- 6927. DOI: 10.21037/jtd-23-1799.
    [17]
    PATEL BH, MELAMED KH, WILHALME H, et al. Implications of pleural fluid composition in persistent pleural effusion following orthotopic liver transplant[J]. Med Sci(Basel), 2023, 11( 1): 24. DOI: 10.3390/medsci11010024.
    [18]
    General Office of National Health Commission. Standard for diagnosis and treatment of primary liver cancer(2022 edition)[J]. J Clin Hepatol, 2022, 38( 2): 288- 303. DOI: 10.3969/j.issn.1001-5256.2022.02.009.

    国家卫生健康委办公厅. 原发性肝癌诊疗指南(2022年版)[J]. 临床肝胆病杂志, 2022, 38( 2): 288- 303. DOI: 10.3969/j.issn.1001-5256.2022.02.009.
    [19]
    Pleural and Mediastinal Diseases Working Group of Chinese Thoracic Society. Chinese expert consensus on diagnosis of pleural effusion[J]. Chin J Tuberc Respir Dis, 2022, 45( 11): 1080- 1096. DOI: 10.3760/cma.j.cn112147-20220511-00403.

    中华医学会呼吸病学分会胸膜与纵隔疾病学组. 胸腔积液诊断的中国专家共识[J]. 中华结核和呼吸杂志, 2022, 45( 11): 1080- 1096. DOI: 10.3760/cma.j.cn112147-20220511-00403.
    [20]
    MA B, SHANG TL, HUANG JJ, et al. Advances and challenges in clinical research on hepatic hydrothorax[J]. J Clin Hepatol, 2022, 38( 2): 452- 456. DOI: 10.3969/j.issn.1001-5256.2022.02.040.

    马博, 尚天玲, 黄剑洁, 等. 肝性胸水临床研究进展与挑战[J]. 临床肝胆病杂志, 2022, 38( 2): 452- 456. DOI: 10.3969/j.issn.1001-5256.2022.02.040.
    [21]
    AITHAL GP, PALANIYAPPAN N, CHINA L, et al. Guidelines on the management of ascites in cirrhosis[J]. Gut, 2021, 70( 1): 9- 29. DOI: 10.1136/gutjnl-2020-321790.
    [22]
    SOBOTKA LA, SPITZER C, HINTON A, et al. Management of hepatic hydrothorax and effect on length of stay, mortality, cost, and 30-day hospital readmission[J]. J Gastroenterol Hepatol, 2020, 35( 4): 641- 647. DOI: 10.1111/jgh.14842.
    [23]
    European Association for the Study of the Liver. EASL clinical practice guidelines for the management of patients with decompensated cirrhosis[J]. J Hepatol, 2018, 69( 2): 406- 460. DOI: 10.1016/j.jhep.2018.03.024.
    [24]
    CARTIN-CEBA R, KROWKA MJ. Pulmonary complications of portal hypertension[J]. Clin Liver Dis, 2019, 23( 4): 683- 711. DOI: 10.1016/j.cld.2019.06.003.
    [25]
    LV Y, HAN GH, FAN DM. Hepatic hydrothorax[J]. Ann Hepatol, 2018, 17( 1): 33- 46. DOI: 10.5604/01.3001.0010.7533.
    [26]
    ZHANG LN, MA ZG, MA WF, et al. Clinical features and risk factors of decompensated liver cirrhosis with hepatic hydrothorax[J]. Chin J Pract Intern Med, 2023, 43( 7): 578- 582. DOI: 10.19538/j.nk2023070110.

    张丽娜, 马治国, 马伟芳, 等. 失代偿期肝硬化合并肝性胸水临床特点及危险因素分析[J]. 中国实用内科杂志, 2023, 43( 7): 578- 582. DOI: 10.19538/j.nk2023070110.
    [27]
    LIU Y. Analysis of related factors of pleural effusion after microwave ablation of primary liver cancer[D]. Changchun: Jilin University, 2023.

    刘洋. 原发性肝癌微波消融术后胸腔积液相关因素分析[D]. 长春: 吉林大学, 2023.
    [28]
    BADILLO R, ROCKEY DC. Hepatic hydrothorax: Clinical features, management, and outcomes in 77 patients and review of the literature[J]. Medicine(Baltimore), 2014, 93( 3): 135- 142. DOI: 10.1097/MD.0000000000000025.
    [29]
    BAI X, LIU XY, SHI YH, et al. Risk factors for hepatic hydrothorax in patients with cirrhosis: A clinical retrospective study[J]. Front Med(Lausanne), 2023, 10: 1165604. DOI: 10.3389/fmed.2023.1165604.
    [30]
    GE HL, YANG Y, YU WX, et al. Risk factors of pleural effusion after radical resection of intrahepatic cholangiocarcinoma[J]. J Clin Exp Med, 2023, 22( 9): 945- 948. DOI: 10.3969/j.issn.1671-4695.2023.09.013.

    葛海龙, 杨岳, 虞卫新, 等. 肝内胆管细胞癌根治术后胸腔积液的危险因素研究[J]. 临床和实验医学杂志, 2023, 22( 9): 945- 948. DOI: 10.3969/j.issn.1671-4695.2023.09.013.
    [31]
    LUO L, CHEN H, CHENG YL, et al. Meta-analysis of risk factors for pleural effusion after hepatectomy for liver cancer[J]. Chin J Gen Surg, 2021, 30( 7): 761- 771. DOI: 10.7659/j.issn.1005-6947.2021.07.002.

    罗林, 陈浩, 程永浪, 等. 肝癌切除术后胸腔积液危险因素的Meta分析[J]. 中国普通外科杂志, 2021, 30( 7): 761- 771. DOI: 10.7659/j.issn.1005-6947.2021.07.002.
    [32]
    JEONG HW, KIM JW, SHIN WJ, et al. Early postoperative hypoalbuminaemia is associated with pleural effusion after donor hepatectomy: A propensity score analysis of 2316 donors[J]. Sci Rep, 2019, 9( 1): 2790. DOI: 10.1038/s41598-019-39126-0.
    [33]
    NGUYEN MH, DAO QM, BUI TTH, et al. Diagnostic values of different cytokines in identifying tuberculous pleural effusion[J]. Trop Biomed, 2020, 37( 2): 372- 378.
    [34]
    WU JH, SHU JK, ZHANG JQ, et al. TNF-α, IFN-γ, IL-2 and IL-4 in tuberculous and malignant pleural effusion[J]. J Kunming Med Univ, 2019, 40( 12): 103- 107. DOI: 10.3969/j.issn.1003-4706.2019.12.021.

    武江海, 舒敬奎, 张剑青, 等. 结核与肿瘤患者胸腔积液中TNF-α, IFN-γ, IL-2, IL-4的水平及临床意义[J]. 昆明医科大学学报, 2019, 40( 12): 103- 107. DOI: 10.3969/j.issn.1003-4706.2019.12.021.
    [35]
    DU FJ, DU BP, JIA HY, et al. Study on the value of screening cytokines in pleural effusion by liquid array technology in the diagnosis of tuberculous pleurisy[J]. Tianjin Med J, 2024, 52( 3): 319- 323. DOI: 10.11958/20230793.

    杜凤娇, 杜博平, 贾红彦, 等. 液态芯片技术筛选胸腔积液细胞因子对结核性胸膜炎的诊断价值[J]. 天津医药, 2024, 52( 3): 319- 323. DOI: 10.11958/20230793.
    [36]
    CHEN XY, ZHU F, WANG B, et al. Clinical effect of iodine-125 seed implantation in patients with primary liver cancer and its effect on Th1/Th2 cells in peripheral blood[J]. J Oncol, 2021, 2021: 6199732. DOI: 10.1155/2021/6199732.
    [37]
    LIU L, SHU JK, WU JH, et al. Study on relationship between Th1/Th2 cells/cell cytokines and tuberculosis pleural effusion adhesion[J]. J Pract Med, 2018, 34( 2): 239- 242, 246. DOI: 10.3969/j.issn.1006-5725.2018.02.020.

    刘凌, 舒敬奎, 武江海, 等. Th1/Th2细胞及细胞因子和结核性胸膜炎粘连的相关性[J]. 实用医学杂志, 2018, 34( 2): 239- 242, 246. DOI: 10.3969/j.issn.1006-5725.2018.02.020.
    [38]
    WANG J, FENG ZX, REN T, et al. Novel clinical biomarkers in blood and pleural effusion for diagnosing patients with tuberculosis distinguishing from malignant tumor[J]. Medicine(Baltimore), 2022, 101( 41): e31027. DOI: 10.1097/MD.0000000000031027.
    [39]
    ZENG RH, WANG XL, ZENG Y, et al. Roles of CA125, NLR, PLR and hs-CRP combined determination for community-acquired pneumonia with pleural effusion based on datum mining model[J]. Lab Med, 2020, 35( 11): 1103- 1107. DOI: 10.3969/j.issn.1673-8640.2020.11.005.

    曾瑞璜, 王小林, 曾叶, 等. 基于数据挖掘模型分析CA125、NLR、PLR、hs-CRP联合检测对社区获得性肺炎伴胸腔积液的临床意义[J]. 检验医学, 2020, 35( 11): 1103- 1107. DOI: 10.3969/j.issn.1673-8640.2020.11.005.
    [40]
    LIU F, JI L, CHEN NN, et al. The value of AFP-L3, Hs-CRP and HBV-DNA in the diagnosis of hepatitis B cirrhosis and liver cancer[J]. Heilongjiang Med J, 2021, 45( 9): 984- 986. DOI: 10.3969/j.issn.1004-5775.2021.09.035.

    刘芳, 季良, 陈男男, 等. 血清甲胎蛋白异质体L3、超敏C反应蛋白及乙肝病毒载量在诊断乙肝肝硬化与肝癌中的价值[J]. 黑龙江医学, 2021, 45( 9): 984- 986. DOI: 10.3969/j.issn.1004-5775.2021.09.035.
    [41]
    GUO YY, PENG XL, ZHAN N, et al. Development and validation a simple model for identify malignant ascites[J]. Int J Med Sci, 2021, 18( 9): 1966- 1974. DOI: 10.7150/ijms.53743.
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    Created with Highcharts 5.0.7Chart context menuAccess Area Distribution其他: 5.1 %其他: 5.1 %Malvern: 0.3 %Malvern: 0.3 %Tiruchi: 0.3 %Tiruchi: 0.3 %上海: 2.4 %上海: 2.4 %中卫: 0.3 %中卫: 0.3 %六安: 0.3 %六安: 0.3 %包头: 0.6 %包头: 0.6 %北京: 7.8 %北京: 7.8 %南京: 0.9 %南京: 0.9 %南宁: 0.3 %南宁: 0.3 %南昌: 0.6 %南昌: 0.6 %厦门: 0.3 %厦门: 0.3 %呼和浩特: 0.3 %呼和浩特: 0.3 %哈尔滨: 0.3 %哈尔滨: 0.3 %哥伦布: 0.6 %哥伦布: 0.6 %嘉兴: 0.3 %嘉兴: 0.3 %天津: 1.2 %天津: 1.2 %山景城: 0.3 %山景城: 0.3 %常州: 0.3 %常州: 0.3 %常德: 0.6 %常德: 0.6 %平顶山: 0.3 %平顶山: 0.3 %广州: 0.3 %广州: 0.3 %张家口: 13.5 %张家口: 13.5 %成都: 1.2 %成都: 1.2 %扬州: 0.3 %扬州: 0.3 %昆明: 1.2 %昆明: 1.2 %杭州: 0.3 %杭州: 0.3 %柳州: 0.3 %柳州: 0.3 %汉中: 3.0 %汉中: 3.0 %海得拉巴: 0.9 %海得拉巴: 0.9 %淄博: 0.3 %淄博: 0.3 %湛江: 0.6 %湛江: 0.6 %烟台: 0.3 %烟台: 0.3 %石家庄: 2.1 %石家庄: 2.1 %科泽科德: 0.3 %科泽科德: 0.3 %秦皇岛: 0.3 %秦皇岛: 0.3 %芒廷维尤: 21.0 %芒廷维尤: 21.0 %芝加哥: 1.2 %芝加哥: 1.2 %苏州: 0.6 %苏州: 0.6 %莫斯科: 0.3 %莫斯科: 0.3 %襄阳: 0.3 %襄阳: 0.3 %西宁: 6.3 %西宁: 6.3 %西安: 0.9 %西安: 0.9 %诺沃克: 0.3 %诺沃克: 0.3 %贵阳: 0.9 %贵阳: 0.9 %赣州: 0.6 %赣州: 0.6 %运城: 0.6 %运城: 0.6 %连云港: 0.3 %连云港: 0.3 %邯郸: 0.6 %邯郸: 0.6 %郑州: 0.3 %郑州: 0.3 %长春: 16.8 %长春: 16.8 %长沙: 0.6 %长沙: 0.6 %青岛: 0.3 %青岛: 0.3 %其他MalvernTiruchi上海中卫六安包头北京南京南宁南昌厦门呼和浩特哈尔滨哥伦布嘉兴天津山景城常州常德平顶山广州张家口成都扬州昆明杭州柳州汉中海得拉巴淄博湛江烟台石家庄科泽科德秦皇岛芒廷维尤芝加哥苏州莫斯科襄阳西宁西安诺沃克贵阳赣州运城连云港邯郸郑州长春长沙青岛

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