Please wait a minute...
Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

Postal Subscription Code 80-967

2018 Impact Factor: 1.847

Front. Med.    2015, Vol. 9 Issue (3) : 350-355     DOI: 10.1007/s11684-015-0402-2
RESEARCH ARTICLE |
Exploring the diagnosis markers for gallbladder cancer based on clinical data
Lingqiang Zhang1,Runchen Miao1,Xiude Zhang2,Wei Chen1,Yanyan Zhou1,Ruitao Wang1,Ruiyao Zhang1,Qing Pang1,Xinsen Xu1,Chang Liu1,*()
1. Department of Hepatobiliary Surgery, the First Affiliated Hospital, School of Medicine, Xi’an Jiaotong University, Xi’an 710061, China
2. Department of Endocrinology, Xian Yang Center Hospital, Xianyang 712000, China
Download: PDF(202 KB)   HTML
Export: BibTeX | EndNote | Reference Manager | ProCite | RefWorks
Abstract  

Presently, no effective markers are available to facilitate gallbladder cancer (GBC) diagnosis. This study aims to explore available markers for GBC diagnosis. Clinical data of 144 GBC and 116 cholelithiasis patients were retrospectively reviewed. Logistic regression analysis was performed to evaluate GBC risk factors. A receiver operating characteristic (ROC) curve was used to assess the diagnosis value of the risk factors. By comparing the characteristic of GBC and cholelithiasis patients, the following factors exhibited statistical difference: age, gender, gallstones, total bilirubin (TB), alkaline phosphatase (ALP), aspartate aminotransferase (AST), alanine aminotransferase (ALT), platelet count (PLT), CA125 (carcinoembryonic antigen 125), and CA199 (carbohydrate antigen 199). Logistic regression analysis indicated that age [odds ratio (OR), 1.032; 95% confidence interval (95% CI), 1.004 to 1.061; P = 0.024], gender (OR, 0.346; 95% CI, 0.167 to 0.716; P = 0.004), gallstones (OR, 0.027; 95% CI, 0.007 to 0.095; P<0.001), ALP (OR, 1.003; 95% CI, 1.000 to 1.006; P = 0.032), TB (OR, 1.004; 95% CI, 1.000 to 1.009; P = 0.042), and CA125 (OR, 1.007; 95% CI, 1.002 to 1.013; P = 0.011) were independent risk factors for GBC. According to the ROC curve, CA125 [area under curve (AUC), 0.720], ALP (AUC, 0.713), TB (AUC, 0.636), and age (AUC, 0.573) were valuable diagnosis markers. Additionally, based on the independent risk factors, the GBC diagnosis model was established. Age, TB, ALP, and CA125 can be used as auxiliary diagnosis factors of GBC. The diagnosis model provides a quantitative tool for GBC diagnosis when comprehensively considering various risk factors.

Keywords marker      gallbladder cancer      diagnosis     
Corresponding Authors: Chang Liu   
Just Accepted Date: 15 June 2015   Online First Date: 17 July 2015    Issue Date: 26 August 2015
URL:  
http://academic.hep.com.cn/fmd/EN/10.1007/s11684-015-0402-2     OR     http://academic.hep.com.cn/fmd/EN/Y2015/V9/I3/350
Parameter Cholelithiasis patients (n = 116) (mean±SD) GBC patients (n = 144) (mean±SD) P value
Male, n (%) 58 (50) 46 (31.94) 0.003
Age (year) 58.91±14.87 63.26±11.15 0.008
Gallstones, n (%) 116 (100) 78 (68.42) 0.001
AST (U/L) 75.98±156.01 123.27±152.95 0.015
ALT (U/L) 73.98±137.36 111.16±139.15 0.032
ALP (U/L) 139.27±124.68 328.92±321.36 <0.0001
TB (μmol/L) 38.97±66.50 119.99±140.22 <0.0001
ALB (g/L) 37.04±5.56 37.03±6.29 0.995
RBC (×1012/L) 4.02±0.72 4.22±3.72 0.512
HGB (g/L) 123.19±23.93 119.26±16.56 0.120
PLT (×109/L) 180.77±94.11 216.86±90.85 0.002
WBC (×109/L) 7.32±5.47 7.08±3.53 0.659
LYM (×109/L) 1.33±0.81 1.53±2.31 0.324
NEU (×109/L) 5.41±4.78 4.97±3.36 0.388
CEA (ng/ml) 7.68±42.37 20.91±129.55 0.251
AFP (ng/ml) 215.08±2049.57 8.08±51.35 0.227
CA125 (U/ml) 27.49±38.9 91.18±328.31 0.039
CA199 (U/ml) 245.47±1136.57 935.21±2040.61 0.001
Tab.1  Comparison of clinical and biochemical characteristics between GBC patients and cholelithiasis patients
Variable Univariate analysis Multivariate analysis
OR (95%CI) P value OR (95%CI) P value
Gender 0.469 (0.283?0.778) 0.003 0.346 (0.167?0.716) 0.004
Age (year) 1.026 (1.007?1.046) 0.009 1.032 (1.004?1.061) 0.024
Gallstones 0.031 (0.010?0.103) <0.001 0.027 (0.007?0.095) <0.001
AST 1.002 (1.000?1.004) 0.020 1.002 (0.997?1.006) 0.450
ALT 1.002 (1.000?1.004) 0.040 0.997 (0.992?1.002) 0.300
ALP 1.005 (1.003?1.007) <0.001 1.003 (1.000?1.006) 0.032
TB 1.008 (1.005?1.011) <0.001 1.004 (1.000?1.009) 0.042
PLT 1.005 (1.002?1.008) 0.003 1.003 (0.999?1.007) 0.109
CA125 1.013 (1.005?1.021) 0.001 1.007 (1.002?1.013) 0.011
CA199 1.000 (1.000?1.001) 0.010 1.000 (1.000?1.000) 0.552
Tab.2  Evaluation of risk factors for GBC by univariate and multivariate analysis
Fig.1  Comparison of diagnosis value of the risk factors for GBC. The area under curves of CA125, ALP, TB, and age were 0.72, 0.71, 0.64, and 0.57, respectively. CA125: carcinoembryonic antigen 125; CA199: carbohydrate antigen 199; TB: total bilirubin; ALP: alkaline phosphatase.
Variable Cut-off value AUC SN (%) SP (%) PPV (%) NPV (%) Accuracy (%) P value
Age (year) 57 0.573 0.729 0.422 0.389 0.443 0.408 0.043
ALP (U/L) 113.885 0.713 0.688 0.647 0.293 0.375 0.331 <0.0001
TB (μmol/L) 147.615 0.636 0.375 0.948 0.100 0.450 0.369 <0.0001
CA125 (U/ml) 13.665 0.720 0.882 0.466 0.344 0.246 0.319 <0.0001
Model 2.5 0.791 0.764 0.664 0.262 0.306 0.281 <0.0001
Tab.3  Comparison of diagnosis value of the risk factors for GBC
Fig.2  Association between ALP and T category. There was no statistical difference among the different groups. ALP: alkaline phosphatase. T category: T1, tumor invades lamina propria or muscular layer; T2: tumor invades perimuscular connective tissue; no extension beyond serosa or into liver; T3: tumor perforates the serosa (visceral peritoneum) or directly invades the liver or another adjacent organ or structure, such as the stomach, duodenum, colon, pancreas, omentum, or extrahepatic bile ducts; T4: tumor invades main portal vein or hepatic artery or invades two or more extrahepatic organs or structures. We defined T1 and T2 as early stage, and T3 and T4 as advanced stage.
Variable Category OR (95% CI) P value
Gender Male vs. female 2.338 (1.290?4.239) 0.005
Age (year) >57 vs.≤57 2.141 (1.147?3.999) 0.017
ALP level (U/L) >113.885 vs.≤113.885 2.491 (1.321?4.697) 0.005
TB level (μmol/L) >147.615 vs.≤147.615 4.822 (1.811?12.839) 0.002
CA125 level (U/ml) >13.665 vs.≤13.665 3.145 (1.582?6.250) 0.001
Tab.4  Multivariate analysis of potential risk factors based on binary data
1 Bizama C, García P, Espinoza JA, Weber H, Leal P, Nervi B, Roa JC. Targeting specific molecular pathways holds promise for advanced gallbladder cancer therapy. Cancer Treat Rev 2015; 41(3): 222–234
doi: 10.1016/j.ctrv.2015.01.003 pmid: 25639632
2 Maurya SK, Tewari M, Mishra RR, Shukla HS. Genetic aberrations in gallbladder cancer. Surg Oncol 2012; 21(1): 37–43
doi: 10.1016/j.suronc.2010.09.003 pmid: 20880699
3 Alvi AR, Siddiqui NA, Zafar H. Risk factors of gallbladder cancer in Karachi—a case-control study. World J Surg Oncol 2011; 9(1): 164
doi: 10.1186/1477-7819-9-164 pmid: 22151791
4 Srivastava K, Srivastava A, Mittal B. Potential biomarkers in gallbladder cancer: present status and future directions. Biomarkers 2013; 18(1): 1–9
doi: 10.3109/1354750X.2012.717105 pmid: 22931385
5 Jiao X, Ren J, Chen H, Ma J, Rao S, Huang K, Wu S, Fu J, Su X, Luo C, Shi J, Broelsch CE. Ala499Val (C>T) and Lys939Gln (A>C) polymorphisms of the XPC gene: their correlation with the risk of primary gallbladder adenocarcinoma—a case-control study in China. Carcinogenesis 2011; 32(4): 496–501
doi: 10.1093/carcin/bgq250 pmid: 21113018
6 Gabbi C, Kim HJ, Barros R, Korach-Andrè M, Warner M, Gustafsson J?. Estrogen-dependent gallbladder carcinogenesis in LXRβ-/- female mice. Proc Natl Acad Sci USA 2010; 107(33): 14763–14768
doi: 10.1073/pnas.1009483107 pmid: 20679224
7 Srivastava K, Srivastava A, Mittal B. Caspase-8 polymorphisms and risk of gallbladder cancer in a northern Indian population. Mol Carcinog 2010; 49(7): 684–692
pmid: 20564345
8 Xu HL, Cheng JR, Andreotti G, Gao YT, Rashid A, Wang BS, Shen MC, Chu LW, Yu K, Hsing AW. Cholesterol metabolism gene polymorphisms and the risk of biliary tract cancers and stones: a population-based case-control study in Shanghai, China. Carcinogenesis 2011; 32(1): 58–62
doi: 10.1093/carcin/bgq194 pmid: 21062971
9 Sharma KL, Yadav A, Gupta A, Tulsayan S, Kumar V, Misra S, Kumar A, Mittal B. Association of genetic variants of cancer stem cell gene CD44 haplotypes with gallbladder cancer susceptibility in North Indian population. Tumour Biol 2014; 35(3): 2583–2589
doi: 10.1007/s13277-013-1340-8 pmid: 24186075
10 Rai R, Sharma KL, Sharma S, Misra S, Kumar A, Mittal B. Death receptor (DR4) haplotypes are associated with increased susceptibility of gallbladder carcinoma in north Indian population. PLoS ONE 2014; 9(2): e90264
doi: 10.1371/journal.pone.0090264 pmid: 24587306
11 Rai R, Sharma KL, Misra S, Kumar A, Mittal B. PSCA gene variants (rs2294008 and rs2978974) confer increased susceptibility of gallbladder carcinoma in females. Gene 2013; 530(2): 172–177
doi: 10.1016/j.gene.2013.08.058 pmid: 23988503
12 Srivastava A, Sharma KL, Srivastava N, Misra S, Mittal B. Significant role of estrogen and progesterone receptor sequence variants in gallbladder cancer predisposition: a multi-analytical strategy. PLoS ONE 2012; 7(7): e40162
doi: 10.1371/journal.pone.0040162 pmid: 22808109
13 Isambert M, Leux C, Métairie S, Paineau J. Incidentally-discovered gallbladder cancer: when, why and which reoperation? J Visc Surg 2011; 148(2): e77–e84
doi: 10.1016/j.jviscsurg.2011.02.005 pmid: 21478068
14 Hundal R, Shaffer EA. Gallbladder cancer: epidemiology and outcome. Clin Epidemiol 2014; 6: 99–109
pmid: 24634588
15 Park SK, Andreotti G, Rashid A, Chen J, Rosenberg PS, Yu K, Olsen J, Gao YT, Deng J, Sakoda LC, Zhang M, Shen MC, Wang BS, Han TQ, Zhang BH, Yeager M, Chanock SJ, Hsing AW. Polymorphisms of estrogen receptors and risk of biliary tract cancers and gallstones: a population-based study in Shanghai, China. Carcinogenesis 2010; 31(5): 842–846
doi: 10.1093/carcin/bgq038 pmid: 20172949
16 Wang YF, Feng FL, Zhao XH, Ye ZX, Zeng HP, Li Z, Jiang XQ, Peng ZH. Combined detection tumor markers for diagnosis and prognosis of gallbladder cancer. World J Gastroenterol 2014; 20(14): 4085–4092
doi: 10.3748/wjg.v20.i14.4085 pmid: 24744600
17 Kim JM, Kwon CH, Joh JW, Park JB, Ko JS, Lee JH, Kim SJ, Park CK. The effect of alkaline phosphatase and intrahepatic metastases in large hepatocellular carcinoma. World J Surg Oncol 2013; 11(1): 40
doi: 10.1186/1477-7819-11-40 pmid: 23432910
18 Sharma U, Pal D, Singh SK, Kakkar N, Prasad R. Reduced L/B/K alkaline phosphatase gene expression in renal cell carcinoma: plausible role in tumorigenesis. Biochimie 2014; 104: 27–35
doi: 10.1016/j.biochi.2014.05.011 pmid: 24909115
19 Xie Y, Wei ZB, Duan XW. Prognostic value of pretreatment serum alkaline phosphatase in nasopharyngeal carcinoma. Asian Pac J Cancer Prev 2014; 15(8): 3547–3553
doi: 10.7314/APJCP.2014.15.8.3547 pmid: 24870755
20 Aminian A, Karimian F, Mirsharifi R, Alibakhshi A, Hasani SM, Dashti H, Jahangiri Y, Ghaderi H, Meysamie A. Correlation of serum alkaline phosphatase with clinicopathological characteristics of patients with oesophageal cancer. East Mediterr Health J 2011; 17(11): 862–866
pmid: 22276495
21 Yamamoto K, Awogi T, Okuyama K, Takahashi N. Nuclear localization of alkaline phosphatase in cultured human cancer cells. Med Electron Microsc 2003; 36(1): 47–51
doi: 10.1007/s007950300006 pmid: 12658351
22 Wang GY, Yang Y, Li H, Zhang J, Jiang N, Li MR, Zhu HB, Zhang Q, Chen GH. A scoring model based on neutrophil to lymphocyte ratio predicts recurrence of HBV-associated hepatocellular carcinoma after liver transplantation. PLoS ONE 2011; 6(9): e25295
doi: 10.1371/journal.pone.0025295 pmid: 21966488
23 Gondo T, Nakashima J, Ohno Y, Choichiro O, Horiguchi Y, Namiki K, Yoshioka K, Ohori M, Hatano T, Tachibana M. Prognostic value of neutrophil-to-lymphocyte ratio and establishment of novel preoperative risk stratification model in bladder cancer patients treated with radical cystectomy. Urology 2012; 79(5): 1085–1091
doi: 10.1016/j.urology.2011.11.070 pmid: 22446338
[1] Jing Zhang,Shan Gao,Zhongping Duan,Ke-Qin Hu. Overview on acute-on-chronic liver failure[J]. Front. Med., 2016, 10(1): 1-17.
[2] Wanqiu Huang,Yang Luan,Lu Jin,Tao Wang,Ruibao Chen,Zheng Liu,Zhiqiang Chen,Ruzhu Lan. Small cell carcinoma of the urinary bladder without gross hematuria: a case report[J]. Front. Med., 2015, 9(3): 384-387.
[3] Yi Cao. Environmental pollution and DNA methylation: carcinogenesis, clinical significance, and practical applications[J]. Front. Med., 2015, 9(3): 261-274.
[4] Farhad Sahebjam,John M. Vierling. Autoimmune hepatitis[J]. Front. Med., 2015, 9(2): 187-219.
[5] Feng Wang,Chen Chen,Daowen Wang. Circulating microRNAs in cardiovascular diseases: from biomarkers to therapeutic targets[J]. Front. Med., 2014, 8(4): 404-418.
[6] Xiao Liu, Hui Ren, Daizhi Peng. Sepsis biomarkers: an omics perspective[J]. Front Med, 2014, 8(1): 58-67.
[7] Lunxiu Qin. Osteopontin is a promoter for hepatocellular carcinoma metastasis: a summary of 10 years of studies[J]. Front Med, 2014, 8(1): 24-32.
[8] Somanath Padhi, Renu G’ Boy Varghese, Anita Ramdas, Manjiri Dilip Phansalkar, RajLaxmi Sarangi. Hemophagocytic lymphohistiocytosis: critical reappraisal of a potentially under-recognized condition[J]. Front Med, 2013, 7(4): 492-498.
[9] Li Shang, Mingrong Wang. Molecular alterations and clinical relevance in esophageal squamous cell carcinoma[J]. Front Med, 2013, 7(4): 401-410.
[10] Salomone Di Saverio, Kenji Kawamukai, Andrea Biscardi, Silvia Villani, Luca Zucchini, Gregorio Tugnoli. Trauma-induced “Macklin effect” with pneumothorax and large pneumomediastinum, disguised by allergy[J]. Front Med, 2013, 7(3): 386-388.
[11] Chuanbao Zhang, Zhaoshi Bao, Wei Zhang, Tao Jiang. Progress on molecular biomarkers and classification of malignant gliomas[J]. Front Med, 2013, 7(2): 150-156.
[12] Xianghu Meng, Jihong Liu, Xiao Yu, Shaogang Wang, Cong Liu, Zhangqun Ye. A giant Müllerian duct cyst in the perineum: a case report[J]. Front Med, 2012, 6(4): 440-443.
[13] Yu Liao, Yufei Xiang, Zhiguang Zhou. Diagnostic criteria of latent autoimmune diabetes in adults (LADA): a review and reflection[J]. Front Med, 2012, 6(3): 243-247.
[14] Zhonghua Sun. Multislice computed tomography angiography in the diagnosis of cardiovascular disease: 3D visualizations[J]. Front Med, 2011, 5(3): 254-270.
[15] Huimin Gao, Zhimin Wang, Yujuan Li, Zhongzhi Qian. Overview of the quality standard research of traditional Chinese medicine[J]. Front Med, 2011, 5(2): 195-202.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed