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Abstract

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

The associations between diabetes, smoking, obesity, and intrahepatic cholangiocarcinoma (ICC) risk remain inconclusive. Metformin is purportedly associated with a reduced risk for various cancers. This case-control study evaluated risk factors for ICC and explored the effects of metformin on ICC risk in a clinic/hospital-based cohort. ICC patients observed at the Mayo Clinic (Rochester, MN) between January 2000 and May 2010 were identified. Age, sex, ethnicity, and residential area-matched controls were selected from among Mayo Clinic Biobank participants. The associations between potential factors and ICC risk were determined. Six hundred and twelve cases and 594 controls were identified. Factors associated with increased ICC risk included biliary tract diseases (adjusted odds ratio [AOR]: 81.8; 95% confidence interval [CI]: 11.2-598.8; P < 0.001), cirrhosis (AOR, 8.0; 95% CI: 1.8-36.5; P = 0.007), diabetes (AOR, 3.6; 95% CI: 2.3-5.5; P < 0.001), and smoking (AOR, 1.6; 95% CI: 1.3-2.1; P < 0.001). Compared to diabetic patients not treated with metformin, the odds ratio (OR) for ICC for diabetic patients treated with metformin was significantly decreased (OR, 0.4; 95% CI: 0.2-0.9; P = 0.04). Obesity and metabolic syndrome were not associated with ICC. Conclusion: This study confirmed diabetes and smoking as independent risk factors for ICC. A novel finding was that treatment with metformin was significantly associated with a 60% reduction in ICC risk in diabetic patients. (HEPATOLOGY 2013)

Cholangiocarcinoma (CC) is categorized based on anatomic location as intra- or extrahepatic CC, which are considered as separate diseases with different genetic alterations and clinical characteristics. Intrahepatic CC (ICC) is increasing in importance because its incidence has been rising around the world, including in the United States.1-3 We recently showed that the incidence of ICC in Olmsted County, Minnesota, increased 7-fold between the 1976-1990 and 2000-2008 time periods.3 The cause of this increasing trend in ICC incidence is unknown.

A number of case-control studies have consistently identified several risk factors for ICC.4-12 These include biliary tract diseases (i.e., primary sclerosing cholangitis [PSC], choledochal cyst, or hepatolithiasis), parasitic infestation of the biliary tract by Clonorchis sinensis or Opisthorchis viverrini, and chronic liver diseases (CLDs), such as chronic hepatitis B virus (HBV) or hepatitis C virus (HCV) infection or cirrhosis from other causes.4-7, 9-12 Although diabetes mellitus (DM), smoking, and obesity have been shown to be risk factors for many cancers, the associations remain inconclusive for ICC.4-10

Metabolic syndrome (MetS) is an increasingly important health problem in the United States, with a prevalence as high as 25%.13 A recent report, using combined Surveillance, Epidemiology, and End Results and Medicare data, suggests that MetS is associated with an increased risk of ICC in the population over 65 years of age.14 Because the rising incidence of MetS is a possible cause of the rising incidence of ICC, validation of this result in other age groups, particularly in ICC patients under 65, is important.

Recent epidemiologic studies have shown that metformin use by patients with type 2 DM, but not use of other glucose-lowering agents, is associated with a decreased risk for a number of cancers, including hepatocellular carcinoma (HCC).15-20 Statin use has also been shown to decrease the risk for HCC in two large case-control studies in the United States and Taiwan.21, 22 However, it is unknown whether metformin or statin use are associated with a decreased risk for ICC.

The aims of our study were to (1) investigate the associations of controversial risk factors, including DM, smoking, and obesity, with risk of ICC, (2) validate the association between MetS and ICC risk, and (3) explore the effects of metformin or statin use on ICC risk.

Patients and Methods

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Study Population.

All patients with ICC observed at the Mayo Clinic (Rochester, MN) between January 2000 and May 2010 were included in the study. We searched for ICC cases in the Mayo Clinic Life Sciences System using the International Classification of Diseases, Ninth Revision, Clinical Modification, code of “155.1” and/or the keywords “cholangiocarcinoma” and “bile duct cancer” to identify all potential ICC patients (n = 1,828).

The diagnosis of CC was confirmed by histopathology, and the anatomic location of the tumor was determined by review of histopathology and radiology (computerized tomography, magnetic resonance imaging, or endoscopic retrograde cholangiopancreatography). CCs were categorized as “intrahepatic” if the lesion arose within the hepatic parenchyma and did not extend beyond the secondary hilar branches of the biliary tree. After review, 1,216 of the 1,828 potential ICC patients were excluded (965 had extrahepatic CC, 60 had HCC, 92 had other malignancy or liver metastasis, 23 had benign liver lesions, and 76 had no pathological or radiologic information). The remaining 612 patients with confirmed ICC were included in the analysis.

Control subjects were selected from the Mayo Clinic Biobank, which comprises patients receiving care at the Mayo Clinic who have agreed to participate in this clinic-based database. This database includes a large group of patients observed at the Mayo Clinic and is designed to provide control groups for studies performed at the Mayo Clinic, allowing selection of controls that are matched to cases by age, gender, ethnicity, and residence. Mayo Clinic Biobank participants include local patients seeking their routine medical care in the Department of Family Medicine or the Division of Community Internal Medicine and nonlocal referral patients seeking care for both routine and serious medical conditions in the Division of General Internal Medicine. Biobank participants provide a blood sample, complete a health questionnaire, and give authorization for use of their medical records in research. Recruitment of Biobank participants began in April 2009.

Cases were matched by age (±5 years), sex, ethnicity, and residence (Olmsted County Minnesota, Southeast Minnesota, Other Minnesota, Iowa, Wisconsin, North and South Dakota, and other regions of the United States [Northeast, Southeast, Southwest, Northwest and Midwest]) to subjects who enrolled in the Mayo Clinic Biobank between April 2009 and May 2010. Controls did not have a history of any cancers.

Clinical Information.

Demographic data, clinical information, medications, and laboratory results were abstracted from the electronic medical record. Data on risk factors were abstracted from a general health and family information form. This self-administered questionnaire is routinely completed by patients and included in the medical record.

Risk factors abstracted included body mass index (BMI), history of liver disease (i.e., HBV or HCV infection, cirrhosis, nonalcoholic steatohepatitis [NASH], PSC, choledochal cyst, or hepatolithiasis), DM, hyperlipidemia, family history of liver cancer, and smoking status. We excluded alcohol from the analysis because data on the amount and duration of alcohol use were missing in over 10% of both the case and control groups.

We abstracted the results of tests for HBV and HCV infection for all cases and controls. HBV infection was defined as a positive hepatitis B surface antigen, and HCV infection was defined as a positive HCV RNA. A diagnosis of HBV or HCV in the physician's note was accepted as proof of viral infection.

Obesity was defined by a BMI ≥30 kg/m2. MetS was defined according to the American Heart Association/National Cholesterol Education Program Adult Treatment Panel III criteria (at least three of the following five criteria: triglyceride level ≥150 mg/dL, high-density lipoprotein cholesterol <40 mg/dL in men or <50 mg/dL in women, systolic blood pressure ≥130 mmHg or diastolic blood pressure ≥85 mmHg, fasting plasma glucose ≥110 mg/dL, and waist circumference >102 cm in men or >88 cm in women).23 Because data on waist circumference were not available, we used obesity as a proxy variable for elevated waist circumference. NASH was diagnosed by histopathology or evidence of fatty infiltration on radiologic imaging with elevation of serum aminotransferase enzymes and exclusion of other CLDs and excessive alcohol drinking (>140 and >70 g/week in men and women, respectively). Cirrhosis was diagnosed by radiologic evidence of a nodular liver, caudate lobe hypertrophy, or portal hypertension (collateral vessels, varices, and splenomegaly).

Current or previous use of metformin or a statin was ascertained from the medication list and physician's notes. For cases, we reviewed the medication list from 1 year before ICC diagnosis until the date of ICC diagnosis to ensure that metformin or the statin was not withdrawn because of the diagnosis of malignancy. Similarly, for controls, we reviewed the medication list from 1 year before until study enrollment. Smoking status was classified as never-smoker or ever-smoker. The amount and duration of cigarette smoking were abstracted for subjects who ever smoked.

The durations of risk factors preceding diagnosis of ICC in cases or before study enrollment in controls were abstracted. Fifteen percent of cases and controls were randomly selected to assess the agreement of self-reported patient questionnaire data with physicians' notes, laboratory results, and/or radiologic imaging (as the gold standard).

Statistical Analysis.

Kappa statistics were calculated for the agreement of self-reported data from the patient questionnaire with data directly abstracted from physicians' notes in the medical record, with a mean kappa value of 0.91 (substantial to almost perfect observer agreement).24 Because cases and controls were not enrolled within the same period of time (cases were from January 2000 to May 2010; controls were from April 2009 to May 2010), changes in frequencies of variables over time might have influenced the results. To account for this, ICC cases were categorized into four groups based on year of diagnosis (group 1: 2000-2002; group 2: 2003-2005; group 3: 2006-2008; and group 4: 2009-2010). Change in frequency of each risk-factor variable in ICC patients by year group was assessed by trend analysis.

Logistic regression was used to estimate the univariate association of each variable with ICC. Because the frequency of statin use increased over time during the study period, propensity scores for statin-use variable were calculated and included in the analysis model. Similarly, to correct for possible imbalances in frequency of metformin use, we balanced the data using sampling weights. This method of adjusting for imbalance is a standard approach in survey sampling, particularly complex surveys.25 Variables with P < 0.05 in the univariate models were included in the multivariate model. Age, gender, and ethnicity, which were considered to be potential confounders, were also included in the multivariate model. The duration of existing conditions significantly associated with ICC was compared using the Wilcoxon rank-sum test. Data analysis was performed using SAS 9.1 (SAS Institute Inc., Gary, NC).

Sensitivity analysis

Given the disparity between date of diagnosis of cases and date of enrollment of controls into the Mayo Biobank database, we repeated the analyses restricted to cases who were enrolled from 2006 to 2010 (groups 3 and 4; n = 279 cases) and controls enrolled from 2009 to 2010, thus limiting the cases to those diagnosed within 3 years of enrollment of controls.

Results

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Patient Characteristics.

Six hundred and twelve ICC cases and 594 controls were included in the analysis. Table 1 summarizes the baseline characteristics and frequency of risk factors for the case and control groups. Demographics were comparable between groups. There were 149 cases observed from 2000 to 2002 (group 1), 184 from 2003 to 2005 (group 2), 186 from 2006 to 2008 (group 3), and 93 from 2009 to May 2010 (group 4). Trend analysis showed that frequencies of risk-factor variables did not change significantly over time, except for frequencies of metformin use among diabetic patients and of statin use among hyperlipidemic patients (Supporting Table 1). Frequency of metformin use among diabetic patients showed a significantly increasing trend during the time period over which cases were observed (i.e., 7.7%, 27.3%, 34.6%, and 30.0% in groups 1, 2, 3, and 4, respectively; Pfor trend = 0.04), particularly increasing between the first and second time periods. Between the second and fourth time periods (groups 2, 3, and 4), there was no statistically significant difference in frequency of metformin use (Pfor trend = 0.77). Unlike the early rise in use of metformin, frequency of statin use increased continuously over the time of the study, from 23.8% in group 1 to 43.5%, 46.9%, and 67.9% in groups 2, 3, and 4, respectively (Pfor trend < 0.01).

Table 1. Baseline Characteristics of ICC Cases and Controls*
CharacteristicsICC Cases (n = 612)Controls (n = 594)P Value
  • Abbreviation: SD, standard deviation.

  • *

    All data except for age are shown in number (%).

  • One ICC case had both choledochal cyst and hepatolithiasis.

Age, years, mean ± SD (range)61.2 ± 13.1 (20-92)61.6 ± 12.9 (21-92)0.600
Male (%)308 (50.3)291 (49.0)0.640
White (%)448 (94.3)565 (96.4)0.100
Biliary tract diseases (%)74 (12.1)1 (0.2)<0.001
 PSC60 (9.8)1 (0.2)<0.001
 Choledochal cyst11 (1.8)0 (0.0)<0.001
 Hepatolithiasis4 (0.7)0 (0.0)0.020
Cirrhosis (%)42 (6.9)2 (0.3)< 0.001
HCV infection (%)13 (2.1)2 (0.3)0.020
HBV infection (%)3 (0.5)3 (0.5)0.970
Other comorbidities (%)   
 Obesity191 (31.2)205 (34.6)0.210
 Hyperlipidemia165 (27.0)256 (43.1)<0.001
 MetS140 (22.9)142 (23.9)0.670
 DM105 (17.2)34(5.7)<0.001
 NASH7 (1.1)12 (2.0)0.220
Smoking status (%)  0.001
 Ever-smoker308 (53.0)255 (43.7) 
 Never-smoker273 (47.0)329 (56.3) 
Family history of liver cancer (%)4 (0.7)3 (0.5)0.730
Statin use among hyperlipidemic patients (%)72 of 165 (43.6)165 of 256 (64.5)<0.001
Metformin use among diabetic patients (%)26 of 105 (24.8)22 of 34 (64.7)<0.001

Diabetes and Smoking Are Associated With an Increased Risk for ICC.

As expected, the relative odds of ICC were markedly increased in patients with a history of biliary tract diseases (PSC, choledochal cysts, or hepatolithiasis) (OR, 81.6; 95% CI: 11.3-589.0; P < 0.001). Univariate analysis of other risk-factor variables with ICC showed that cirrhosis (OR, 21.8; 95% CI: 5.3-90.5; P < 0.001), HCV infection (OR, 6.4; 95% CI: 1.4-28.5; P = 0.001), DM (OR, 3.3; 95% CI: 2.2-4.9; P < 0.001), and smoking (OR, 1.5; 95% CI: 1.2-1.8; P = 0.02) were significantly associated with an increased OR of ICC. In contrast, the OR for ICC was significantly reduced (OR, 0.5; 95% CI: 0.4-0.6; P < 0.001) in patients with hyperlipidemia, compared to individuals without hyperlipidemia. HBV infection (OR, 1.0; 95% CI: 0.2-4.8), obesity (OR, 0.9; 95% CI: 0.7-1.1), MetS (OR, 0.9; 95% CI: 0.7-1.2), NASH (OR, 0.6; 95% CI: 0.2-1.4), and family history of liver cancer (OR, 1.3; 95% CI: 0.3-5.8) were not associated with ICC (P > 0.05 for all five variables). Univariate analyses results remained unchanged in the sensitivity analyses restricting to group 3 and 4 ICC cases (data not shown).

Table 2 shows the multivariate adjusted OR (AOR) for biliary tract diseases, cirrhosis, HCV infection, DM, smoking, and hyperlipidemia of all ICC cases and of case groups 3 and 4. Biliary tract diseases (AOR, 81.8; 95% CI: 11.2-598.8; P < 0.001) and cirrhosis (AOR, 8.0; 95% CI: 1.8-36.5; P = 0.007) were associated with ICC. HCV infection was not associated with ICC in the multivariate model (AOR, 2.6; 95% CI: 0.5-13.5; P = 0.25). Because the very high OR for biliary tract diseases could potentially conceal the effect of other risk variables, we performed a sensitivity analysis by excluding the biliary tract diseases variable in the univariate and multivariate model. The overall results did not change (Supporting Table 2).

Table 2. Multivariate Logistic Regression Analysis of Potential Risk Factors for ICC*
 (A) All ICC Cases (n = 612)(B) Case Groups 3 and 4 (n = 279)
Risk FactorAOR95% CIP ValueAOR95% CIP Value
  • *

    Sensitivity analysis of all ICC cases (n = 612) versus controls (n = 594) (A) and case groups 3 and 4 ICC (n = 279) versus controls (n = 594) (B).

  • Model included age, gender, and ethnicity.

Biliary tract diseases81.811.2-598.8<0.00196.012.7-724.4<0.001
Cirrhosis8.01.8-36.50.00711.32.4-53.40.002
DM3.62.3-5.5<0.0013.11.8-5.3<0.001
HCV infection2.60.5-13.50.2504.60.8-16.40.080
Ever-smoker1.61.3-2.1<0.0011.51.1-2.10.010
Hyperlipidemia0.40.3-0.6<0.0010.40.3-0.6<0.001

Diabetes was associated with ICC (AOR, 3.6; 95% CI: 2.3-5.5; P < 0.001). Median (interquartile range; IQR) duration of DM was 10.1 years (IQR, 4.2-16.5) before ICC diagnosis in the 60 ICC cases with DM for whom data were available (of a total of 105 ICC cases with DM). Duration of DM was 8.4 years (IQR, 5.1-12.0) before the date of Biobank enrollment in the 31 controls with DM for whom data were available (of a total of 35 controls with DM). There was no significant difference in duration of DM before ICC diagnosis or Biobank enrollment (P = 0.44).

Smoking conferred a significantly increased risk for ICC (AOR, 1.6; 95% CI: 1.3-2.1; P < 0.001); however, no dose-response relationship between smoking and ICC was demonstrated (data not shown).

Hyperlipidemia was associated with a decreased risk for ICC (AOR, 0.4; 95% CI: 0.3-0.6; P < 0.001). This association might be the result of a protective effect of treatment with statins. Compared to hyperlipidemic patients who were not treated with statins, the OR for ICC for hyperlipidemic patients treated with statins was significantly decreased to 0.6 (95% CI: 0.4-0.9; P = 0.03). However, the rate of statin use increased significantly over the course of the study. To test for spurious associations, we performed sensitivity analyses restricting the comparison to ICC cases with hyperlipidemia in year groups 3 and 4 versus controls with hyperlipidemia and to ICC cases with hyperlipidemia in group 4 who were diagnosed within the same time period of controls versus controls with hyperlipidemia. For these comparisons, the OR (95% CI) for ICC was 0.9 (0.5-1.6; P = 0.81) and 1.2 (0.5-2.7; P = 0.73), respectively (Table 3A), suggesting that the purported association between statin use and ICC risk among hyperlipidemic patients was the result of changes in statin use over time.

Table 3. Univariate Analyses of the Association Between Statin Use and ICC Risk Among Hyperlipidemic ICC Cases (Number Indicated in Table) Versus Hyperlipidemic Controls (n = 256) (A)* and Between Metformin Use and ICC Risk Among Diabetic ICC Cases (Number Indicated in Table) Versus Diabetic Controls (n = 34) (B)
(A)
HyperlipidemiaAll ICC Cases (n = 165)Groups 3 and 4 ICC Cases (n = 77)Group 4 ICC Cases (n = 28)
Statin UseOR95% CIP ValueOR95% CIP ValueOR95% CIP Value
Yes0.60.4-0.90.030.90.5-1.60.811.20.5-2.70.73
No1.0Reference1.0Reference1.0Reference
(B)
DMAll ICC Cases (n = 105)Groups 2, 3, and 4 ICC Cases (n = 79)Groups 3 and 4 ICC Cases (n = 46)Group 4 ICC Cases (n = 20)
Metformin UseOR95% CIP ValueOR95% CIP ValueOR95% CIP ValueOR95% CIP Value
  • *

    Model included propensity scores for statin use to account for change in frequency of use of statins over the study period.

  • Frequency of metformin use was balanced using the sampling-weights method. The weights assigned to each patient are specific to metformin and are not appropriate for the other variables in the multivariate analyses.

Yes0.20.1-0.4<0.0010.40.2-0.90.040.40.1-0.90.040.30.1-0.960.047
No1.0Reference1.0Reference1.0Reference1.0Reference

There Is a Strong Inverse Relationship Between Metformin Use and ICC Risk.

Twenty-six of one hundred and five (24.8%) ICC cases with DM and 22 of 34 (64.7%) controls with DM were treated with metformin (P < 0.001). Diabetic patients on metformin had a significantly smaller risk of ICC, as compared to those not on metformin (OR, 0.2; 95% CI: 0.1-0.4; P < 0.001). Because use of metformin increased during the study period, we repeated the analysis, excluding patients in group 1 and including patients in groups 2, 3, and 4, for whom frequency of metformin use was not statistically different (Pfor trend = 0.77). The repeat analysis showed that diabetic patients treated with metformin had an OR of 0.4 (95% CI: 0.2-0.9; P = 0.04) for developing ICC. This result also remained unchanged in the sensitivity analyses restricted to ICC cases with DM in groups 3 and 4 (OR, 0.4; 95% CI: 0.1-0.9; P = 0.04) and to ICC cases with DM in group 4 who were diagnosed within the same time period of controls (OR, 0.3; 95% CI: 0.1-0.96; P = 0.047) (Table 3B).

Discussion

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

We found significant associations of biliary tract diseases, cirrhosis, DM, smoking, and metformin use with ICC risk in this large hospital/clinic-based case-control study at a major referral center in the United States.

Our findings confirm that DM and smoking are independent risk factors for ICC. This is important because both DM and smoking are modifiable risk factors. Therefore, diabetes prevention and smoking cessation may reduce the risk of ICC, which is usually diagnosed at an advanced stage and has an extremely poor prognosis. Diabetes conferred a 3.6-fold increased risk for ICC in this study, a higher magnitude than was found in previous U.S. case-control studies (AOR, 1.8-2.0).5, 7 The carcinogenic effect of DM in humans is well established.26 An in vitro study has suggested that the insulin-like growth-factor–signaling pathway is involved in the pathogenesis of CC.27 Therefore, there is a biologically plausible hypothesis for our observation that DM increases the risk of ICC. This hypothesis is also supported by our finding of a long duration (10.1 years) of DM before ICC diagnosis.

The carcinogenic effect of smoking is also well established, including for HCC.28 Studies from Asia found no association between smoking and ICC, whereas most studies from Western countries show modest associations of smoking and ICC with ORs of 1.4-1.8.5-8 In the present study, smoking was associated with a 1.9-fold increased risk for ICC, a magnitude consistent with those of other Western studies.

In contrast to the results of the few case-control studies performed thus far in the United States, HCV was not found to be an independent risk factor for ICC.5-7 HCV was significantly associated with ICC risk in the univariate model and became a trend toward significance in the sensitivity analysis restricted to ICC case groups 3 and 4 (P = 0.08); thus, the lack of significance in the multivariate model may be the result of a lack of statistical power. Given the high AOR of 8.0 for cirrhosis, and the fact that HCV infection is a major risk factor for cirrhosis in the United States, it is possible that there is an interaction/confounding between these two variables in attribution of risk. Similar to previous U.S. case-control studies, frequency of HBV infection was very low and therefore there was no association of HBV with ICC in this population.5, 6

Our data showed that metformin use is associated with a 60% reduction in ICC risk in diabetic patients, a magnitude comparable to that shown in other cancers (50%-85% risk reduction), including HCC as well as pancreatic, colorectal, breast, and lung cancer.15-20 This is biologically plausible, as shown by in vivo and in vitro experiments demonstrating antitumor effects of metformin in breast and prostate cancer cells as a result of the activation of adenosine-monophosphate–activated protein kinase, which suppresses the activity of the mammalian target of rapamycin/ribosomal protein S6 kinase beta-1.29, 30 Whether metformin also has an effect on malignant cholangiocytes is currently unknown.

It can be argued that the protective effects of metformin against ICC shown in this study may be the result of differences in the baseline characteristics of diabetic patients treated with metformin, compared to those not treated with metformin (i.e., metformin is a marker of lesser duration or less-severe stage of DM), leading to a lower prevalence of ICC among patients with shorter duration or less-severe DM. Because metformin is usually the initial therapy given when DM is diagnosed and is typically an effective treatment only for those who do not have very high serum-glucose levels, it is possible that patients treated with metformin in our cohort had less-severe DM than those not treated with metformin.31 Nevertheless, metformin can be used, regardless of the duration of DM, in combination with other oral hypoglycemic agents or insulin in severe diabetic patients or in those whose target serum-glucose level cannot be achieved with metformin treatment alone.31 In our ICC cohort patients with DM, median duration of DM was not different between those treated with metformin and not treated with metformin. We recognize that the duration of DM does not directly correlate with severity of disease, and that glycated hemoglobin or the presence of complications from DM (e.g., diabetic nephropathy or retinopathy) better reflect the severity of disease. These variables were not abstracted from the medical record because this was not in the scope of the present study. It will be interesting to explore the effect of severity of DM on ICC risk in future studies and to investigate whether patients with mild DM have a lower risk for ICC than those with more-severe DM.

Somewhat surprisingly, we found that hyperlipidemia was associated with a decreased risk for ICC. Because the association between hyperlipemia and ICC risk has never been reported on, additional validation studies are needed before we can conclude that this association is real. If this association is true, it may either be a causal relationship or simply reflect that the absence of hyperlipidemia is a marker of an occult cancer (i.e., the lower frequency of hyperlipidemia in ICC patients could possibly be the result of cancer-related fat malabsorption, a decrease in caloric intake and weight loss during cancer growth, or a decrease in lipid synthesis on account of impairment in liver function). To prove causality, further studies on the mechanistic effect of hyperlipidemia on ICC pathogenesis are also needed.

The mechanistic functions of statins on cancer have not been completely elucidated. Statins appear to have pleiotrophic effects that can either increase or decrease cancer risk.32 In this study, we did not find an association between statin use and ICC risk among patients with hyperlipidemia. Additional studies are warranted to validate this finding.

In contrast to recently published results, we did not find an association between MetS and ICC.14 This discrepancy may be related to the short duration of the diagnosis of MetS and the small numbers of subjects with NASH in our cohorts. The link between MetS and ICC risk may be related to the progression from steatohepatitis to fibrosis during the natural history of NASH. In our cohorts, the mean durations of MetS were only 6.5 and 8.3 years in the case and control groups, respectively. This duration may not have been long enough for the development of liver fibrosis.

The major strength of our study was that the diagnosis of ICC in all patients was confirmed by histological and radiological results. We used prospective collection of data from a patient questionnaire, and the method of data collection was comparable between the case and control groups. Our study had a large sample size and confirmed the associations between DM and smoking and ICC. Importantly, our study revealed the novel observation of inverse association between metformin use and risk of ICC. There were two main limitations of our study. First, the time periods during which cases and controls were assessed were not matched, so as to allow us to include the largest number of ICC cases as possible, because this is a relatively uncommon cancer. However, this limitation was mitigated by examining whether there were any changing trends in the prevalence of each variable over time and accounting for these trends in our analysis and by the sensitivity analyses. Second, because most patients in the case group were referred to our institution after the diagnosis of ICC, detailed information on baseline BMI before ICC diagnosis, the duration of underlying diseases, and medication use were not always available. Therefore, our findings should be further validated in independent cohorts. In particular, the protective effect of metformin should ideally be studied in patients known to be taking metformin in the period at least 2-5 years before the development of ICC. In addition, the prevalence of NASH in the case group might be underestimated, because we did not have data on serum transaminase enzyme levels before ICC diagnosis, in most cases. However, the prevalence of NASH in the control group (2.0%) was consistent with that in the general population (3%-5%).33

In conclusion, our findings are consistent with previous reports of associations between diabetes, smoking, and ICC. The novel observation of an inverse association between metformin use and ICC risk found in our study warrants further investigation.

References

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Patients and Methods
  4. Results
  5. Discussion
  6. References
  7. Supporting Information

Additional Supporting Information may be found in the online version of this article.

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HEP_26092_sm_SuppTable.doc77KSupporting Information Table

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