Abstract
Objective:
To evaluate the association between statin use and risk of biliary tract cancers (BTCs).
Design:
This is a nested case-control study conducted in the United Kingdom Clinical Practice Research Datalink (CPRD). We included cases diagnosed with incident primary BTCs, including cancers of the gallbladder, bile duct (i.e., both intrahepatic and extrahepatic cholangiocarcinoma), ampulla of Vater, and mixed type, between 1990 and 2017. For each case, we selected five controls who did not develop BTCs at the time of case diagnosis, matched by sex, year of birth, calendar time, and years of enrollment in the general practice using incidence density sampling. Exposures were defined as two or more prescription records of statins 1 year prior to BTC diagnosis or control selection. Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between statins and BTC overall and by subtypes were estimated using conditional logistic regression, adjusted for relevant confounders.
Results:
We included 3,118 BTC cases and 15,519 cancer-free controls. Current statin use versus non-use was associated with a reduced risk of all BTCs combined (adjusted OR=0.88, 95%CI: 0.79–0.98). The reduced risks were most pronounced among long-term users, as indicated by increasing number of prescriptions (Ptrend = 0.016) and cumulative dose of statins (Ptrend = 0.008). The magnitude of association was similar for statin use and risk of individual types of BTCs. The reduced risk of BTCs associated with a record of current statin use versus non-use was more pronounced among persons with diabetes (adjusted OR=0.72, 95%CI: 0.57– 0.91). Among non-diabetics, the adjusted OR for current statin use versus non-use was 0.91 (95%CI: 0.81–1.03, Pheterogeneity=0.007).
Conclusion:
Compared with nonuse of statins, current statin use is associated with 12% lower risk of BTCs; no association found with former statin use. If replicated, particularly in countries with a high incidence of BTCs, our findings could pave the way for evaluating the value of statins for BTC chemoprevention.
Keywords: ampulla of Vater cancer, biliary tract cancer, cholangiocarcinoma, CPRD, gallbladder cancer, statin
Short summary
- What is already known about this subject?
- Statins are commonly used cholesterol-lowering medications that have demonstrated effectiveness in the primary and secondary prevention of cardiovascular disease.
- Several epidemiological studies have shown that statins are associated with a lower risk of gallstone disease (gallstones or a history of cholecystectomy), but associations with biliary tract cancers (BTCs) have not been well studied.
- What are the new findings?
- There was significantly reduced risk of biliary tract cancers among current users of statins, as compared with non-users (odds ratio, 0.88).
- The reduced risks were most pronounced among long-term users, as indicated by increasing number of prescriptions (P for trend = 0.016) and cumulative dose of statins (P for trend = 0.008).
- How might it impact on clinical practice in the foreseeable future?
- Current or long-term statin use may reduce risk of biliary tract cancers.
- If replicated in other settings, the value of statins for BTC chemoprevention should be evaluated.
Introduction
Biliary tract cancers (BTCs) are comprised of cancers of the gallbladder, bile duct (i.e., both intrahepatic and extrahepatic cholangiocarcinoma), and ampulla of Vater. BTCs are rare but highly fatal diseases, with a median overall survival of ~12 months.[1] Although the etiology of BTCs is largely unknown, the epidemiologic and molecular characteristics suggest that they are distinct disease entities.[1, 2] For example, gallbladder cancer (GBC) is more common in women than men, while other BTCs are more common in men.[3] Similarly, cirrhosis and infection with hepatitis B and C viruses are associated with intrahepatic cholangiocarcinoma, while their associations with GBC and ampulla of Vater cancer (AVC) are less clear.[1, 4]
Despite these differences, BTCs share common risk factors. For example, disorder of lipid regulation (i.e., hyperlipidemia) has been associated with an increased risk of cancer at all sites in the biliary tract.[5] Hyperlipidemia is thought to interact with inflammation and pro-inflammatory immune response to influence the risk of BTCs.[6, 7] For GBC, local inflammation due to gallstones plays a central role,[8] while for cholangiocarcinoma, both intrahepatic and extrahepatic sclerosing cholangitis play a major role.[1] Inflammation from biliary adenomas, which are seen in patients with familial adenomatous polyposis,[9] is thought to contribute to the 100-fold higher risk of AVC in that population.[10] Finally, other causes of inflammation, such as bacterial infection and obesity/metabolic syndrome, may play a role in the etiology of BTC.[1]
Given these strong ties with dyslipidemia and inflammation, statins (3-hydroxy-3-methylglutaryl coenzyme A [HMG-CoA] reductase inhibitors) could potentially reduce the risk of BTCs. Statins are commonly used cholesterol-lowering medications that have demonstrated effectiveness in the primary and secondary prevention of cardiovascular disease.[11] Several studies have shown that statins are associated with a lower risk of gallstone disease (gallstones or a history of cholecystectomy) [12, 13, 14, 15], but associations with BTCs have not been well studied. To further our understanding of the associations between statins and BTCs, we thus conducted a nested case-control study within a large database of primary care electronic medical records – the United Kingdom (UK) Clinical Practice Research Datalink (CPRD).[16]
Methods
This study is based on data from the CPRD GOLD database November, 2017 release, obtained from the UK Medicines and Healthcare Products Regulatory Agency database, reused with the permission of The Health & Social Care Information Centre. All rights reserved. The interpretation and conclusions contained in this study are those of the authors alone. The study was approved by the Independent Scientific Advisory Committee of the CPRD (proposal#17_160.R).
Study Population and Design
The UK CPRD was established in 1987 and contains information on ~8.5% (13.3 million) of the UK population. All data are provided by general practitioners; the CPRD population is representative of the general UK population.[17] Detailed information includes demographic data, physician contacts, tests conducted, and medications prescribed. Diagnoses, physical findings, symptoms, and administrative events, such as referrals to specialists, are recorded using Read codes, the standard clinical terminology system used in general practice in the UK.[18]
In this nested case-control study, we included all persons whose most recent active registration at a CPRD practice overlapped with the study period from 1990 (three years after the establishment of the database) through 2017. Exit date was defined as the date of cancer diagnosis/selection, death, leaving the practice, or last collection of data from the practice, whichever occurred first. Eligible cases included persons aged 21–100 years with a first cancer diagnosis (except non-melanoma skin cancer) of BTC (Read codes provided in Supplementary Table 1) identified in CPRD during 1990–2017. To ascertain statin use, we excluded the 1-year period prior to cancer diagnosis to minimize the possibility of reverse causation (i.e., incipient cancer leading to statin use). All cases were required to have at least two years of recorded activity in the CPRD prior to the date of cancer diagnosis.
Five controls per case were randomly selected using incidence density sampling. Controls were individually matched on sex, year of birth (±3 years), diagnosis year (±3 years), and number of years in the general practice and in the CPRD prior to diagnosis/selection date. All controls were required to be alive, cancer-free (except for non-melanoma skin cancer) and had at least two years of recorded activity in the CPRD prior to the diagnosis date of their matched case. Selected controls with exit date before entry were excluded (N=55).
Ascertainment of Statins and Covariates
Records of prescribed medications with more than 1 year prior to diagnosis/selection were obtained from the electronic patient prescription records. Drugs of interest included statins, other lipid-lowering agents (i.e., bile acid sequestrant, cholesterol absorption inhibitor, fibrate, nicotinic acid derivative, Omega-3 fatty acid, and Bis-phenol antioxidant), treatment for type 2 diabetes (i.e., metformin, insulin, Acetohexamide, Tolbutamide, Chlorpropamide, Glibenclamide, Glibornuride, Gliclazide, Rosiglitazone, Tolazamide, and Tolbutamide), aspirin, and cortisone, which were included because of their potential effect on metabolism. Statin use was defined as having two or more records of statin prescriptions, and nonuse of statins was defined as having 0 or 1 prescription record.[19] Former statin use was defined as use ending more than two years prior to the diagnosis/selection date. Use ending within two years prior to the diagnosis/selection date was considered as current use. Based on the distribution among controls, statin use was classified by time since first recorded statin use to one year prior to the diagnosis/selection (0–2, 3–5, 6–8, and 9+ years), number of prescriptions (2–15, 16–35, 36–65, and 66+, representing approximate duration of use) and cumulative dose (quartiles), which was defined as number of pills multiplied by the dose per pill. This grouping strategy permitted examination of the trend for the association of increasing statin use with risk for BTCs. Finally, specific commonly used statins (atorvastatin, simvastatin, pravastatin, and rosuvastatin) were examined individually.
Because body mass index (BMI), smoking, alcohol drinking, diabetes mellitus, gallstones, cirrhosis, hepatitis virus infection, chronic heart disease, and dyslipidemia may be associated with both statin use and BTCs or BTCs at specific subsites, we identified persons who had these conditions more than one year prior to the diagnosis/selection. We also assessed healthy user effect, healthy adherer effect, and functional status more than one year prior to the diagnosis/selection, because these factors have been suggested as important confounders in observational studies (Supplementary Materials).[20]
Statistical analyses
We used conditional logistic regression to estimate odds ratios (ORs) for the association of statins with BTCs overall and with individual types (i.e., GBC, cholangiocarcinoma, and AVC). The regression model included adjustment for known BTC risk factors: BMI, smoking status, alcohol drinking status, and a history of diabetes.[21] GBC-specific analyses excluded 177 controls with a history of cholecystectomy because those controls were not at risk for developing GBC, and history of gallstones was additionally included in the model. Cholangiocarcinoma-specific analyses additionally included history of cirrhosis in the model.
Other potential confounders were selected if they changed the adjusted OR for BTC and statin use status by more than 10%. We first considered a fully adjusted model that included all potential confounders: a history of hepatitis virus infection, chronic heart disease, dyslipidemia, high exercise, healthy diet, cancer screening, influenza vaccination, pneumonia, dementia, comorbidity, and use of treatment for type 2 diabetes, aspirin, cortisone, or other lipid-lowering agents. However, additional adjustment for those variables resulted in only marginal changes (<10%) in the ORs (Supplementary Table 2); such adjustments were therefore not included in the final model. We also selected covariates by mutually entering all potential confounders into a stepwise logistic regression model, with P<0.15 as the model entry criterion and P<0.05 for a variable to remain in the model. Likewise, adjustment for variables selected resulted in OR changes of less than 10% (Supplementary Table 2). We thus only present results from the minimally adjusted model. We tested for linear trends across statin use categories with the Wald test using categorical values of the number of prescriptions and cumulative dose with 1 degree of freedom.
We evaluated potential effect modification by matching variables (i.e., sex, age at one year prior to the diagnosis/selection [≤70 versus >70 years; the age cutoff was chosen to create two equally large age groups among the control subjects, among whom the median age was 72 years], and calendar year at diagnosis/selection [≤2005 versus >2005 because 10 mg of simvastatin became available over the counter in August 2004] [22]). Likelihood ratio tests were used to compare models with and without an interaction term between statin use and each potential modifier. Because statin use has been associated with increased risk of diabetes,[23, 24, 25] we conducted a joint analysis of diabetes and statin use initiated before or after diabetes diagnosis. We used patients with diabetes who did not use statins as the reference group for a model focused on the potential protective effect of statins on BTCs among patients with diabetes; this model was additionally adjusted for treatment for type 2 diabetes. We then reran the model using non-diabetic patients who did not use statins as the reference group to focus on the effect of former or current statin use among non-diabetics.
In sensitivity analyses, we studied only incident statin users, defined as people who had their first recorded use of statins 5 years or longer after entering CPRD. Studying a cohort of incident users allows us to obtain results more robust to bias from treatment assignment, a common limitation to study medication use in an observational setting, as opposed to in a randomized controlled trial.[26] We also conducted analyses excluding 145 cases with carcinoma in situ of the biliary system and their matched controls, excluding subjects with non-biliary cancer in situ (i.e., all carcinoma in situ except that of the biliary system) since diagnosis of in situ cancer may have led to lifestyle changes, or excluding subjects with missing/unknown information on smoking, alcohol drinking, and BMI.
Statistical analyses were performed using R Statistical Software (Foundation for Statistical Computing, Vienna, Austria). All statistical tests were 2-sided, and P<0.05 was considered statistically significant.
Results
Table 1 shows the distribution of demographic characteristics and other potential risk factors. A total of 3,118 BTC cases (708 GBC, 1678 cholangiocarcinoma, 228 AVC, 500 mixed, 4 unknown) and 15,519 cancer-free controls were included (Table 1). By design, cases and controls were individually-matched on sex, age, calendar year, and years in the CPRD participating practice. Cases were more likely to be obese; be current smokers; drink alcohol; have a history of chronic diseases, including diabetes, gallstones, and cirrhosis; be infected with hepatitis viruses; have treatment for type 2 diabetes; and use aspirin or cortisone. Controls were more likely to be diagnosed with dementia.
Table 1.
Characteristics of cases with biliary tract cancer and controls, CPRD
| Characteristic | Case (n=3,118) | Control (n=15,519) | P value |
|---|---|---|---|
| Cancer site (n, %) | -- | ||
| Gallbladder | 708 (22.7) | -- | |
| Bile duct | 1678 (53.8) | -- | |
| Ampulla of Vater | 228 (7.3) | -- | |
| Mixed | 500 (16.0) | -- | |
| Missing | 4 (0.1) | -- | |
| Diagnosis/selection year (n, %) | |||
| 1990–1999 | 297 (9.5) | 1479 (9.5) | -- |
| 2000–2004 | 562 (18.0) | 2797 (18.0) | |
| 2005–2009 | 846 (27.1) | 4234 (27.3) | |
| 2010–2017 | 1413 (45.3) | 7009 (45.2) | |
| Years in CPRD prior to diagnosis/selection date | |||
| Mean ± SD | 23.4 ± 17.0 | 23.6 ± 17.0 | -- |
| Age at diagnosis/selection date, years (n, %) | |||
| 21–49 | 477 (15.3) | 2378 (15.3) | -- |
| 50–69 | 698 (22.4) | 3508 (22.6) | |
| 70–79 | 1012 (32.5) | 5073 (32.7) | |
| 80–100 | 931 (29.9) | 4560 (29.4) | |
| Mean ± SD | 72.0 (11.9) | 72.0 (11.8) | |
| Sex (n, %) | -- | ||
| Male | 1439 (46.2) | 7156 (46.1) | -- |
| Female | 1679 (53.8) | 8363 (53.9) | |
| Body mass index, kg/m2 (n, %) | <0.001 | ||
| <18.5 (low) | 28 (0.9) | 168 (1.1) | |
| 18.5–24.9 (normal) | 853 (27.4) | 4788 (30.9) | |
| 25.0–29.9 (overweight) | 1102 (35.3) | 5120 (33.0) | |
| 30.0+ (obese) | 650 (20.8) | 2577 (16.6) | |
| Missing/Unknown | 485 (15.6) | 2866 (18.5) | |
| Smoking status (n, %) | <0.001 | ||
| Never | 618 (19.8) | 3472 (22.4) | |
| Former | 1484 (47.6) | 7340 (47.3) | |
| Current | 764 (24.5) | 2964 (19.1) | |
| Missing/Unknown | 252 (8.1) | 1743 (11.2) | |
| Alcohol drinking status (n, %) | 0.002 | ||
| Never | 458 (14.7) | 2339 (15.1) | |
| Former | 131 (4.2) | 548 (3.5) | |
| Current | 2022 (64.8) | 9709 (62.6) | |
| Missing/Unknown | 507 (16.3) | 2923 (18.8) | |
| Chronic disease history (n, %) | |||
| Diabetes | 458 (14.7) | 1648 (10.6) | <0.001 |
| Gallstone | 234 (7.5) | 480 (3.1) | <0.001 |
| Cirrhosis | 29 (0.9) | 34 (0.2) | <0.001 |
| Hepatitis virus infection | 15 (0.5) | 11 (0.1) | <0.001 |
| Cholecystectomy a | 127 (5.3) | 546 (4.5) | 0.138 |
| Chronic heart disease | 677 (21.7) | 3171 (20.4) | 0.113 |
| Dyslipidemia | 481 (15.4) | 2540 (16.4) | 0.203 |
| Prescription drug use history (n, %) | |||
| Treatment for Type 2 diabetes | 330 (10.6) | 1234 (8.0) | <0.001 |
| Aspirin | 1070 (34.3) | 4927 (31.7) | 0.002 |
| Cortisone | 925 (29.7) | 4032 (26.0) | <0.001 |
| Other lipid-lowering agents | 134 (4.3) | 594 (3.8) | 0.236 |
| Healthy user effect (n, %) | |||
| High exercise | 26 (0.8) | 186 (1.2) | 0.097 |
| Healthy diet | 633 (20.3) | 2989 (19.3) | 0.188 |
| Healthy adherer effect (n, %) | |||
| Cancer screening | 672 (21.6) | 3152 (20.3) | 0.123 |
| Influenza vaccination | 398 (12.8) | 1916 (12.3) | 0.537 |
| Functional status or cognitive impairment (n, %) | |||
| Pneumonia | 101 (3.2) | 500 (3.2) | 1.000 |
| Dementia | 33 (1.1) | 336 (2.2) | <0.001 |
| Comorbidity | 155 (5.0) | 673 (4.3) | 0.128 |
Abbreviation: CPRD, Clinical Practice Research Datalink
Excludes 708 cases with gallbladder cancer and their 3,508 matched controls.
Table 2 shows adjusted ORs for statin use and risk of all BTCs combined. Although former statin use was not associated with BTC risk, current use versus non-use was associated with a reduced risk of BTCs (adjusted OR=0.88, 95%CI: 0.79–0.98, Table 2). Individuals who started using statins nine or more years before one year prior to the diagnosis/selection had reduced risk of BTCs (OR=0.85, 95%CI: 0.72–1.01), but the trend was not consistent across increasing categories of time since first statin use (Ptrend=0.128). Although there was some evidence of a dose-response trend with increasing number of prescriptions (Ptrend=0.016) and cumulative dose of statins (Ptrend=0.008), the trend was not consistent across all categories, but only the comparison between highest quartile (Q4) and nonuse of statins was statistically significant. For example, compared with nonuse of statins, the adjusted OR of the highest quartile (Q4) for cumulative dose was 0.81 (95%CI: 0.68–0.96). We did not observe heterogeneity by type of statin but had limited statistical power for individual types of statins (Supplementary Table 3).
Table 2.
Association between statin use and biliary tract cancers, CPRD
| Characteristic | Case (n=3,118) |
Control (n=15,519) |
Adjusted OR (95% CI) a |
|---|---|---|---|
| Any statin use | |||
| Nonusers | 2159 (69.2) | 10934 (70.5) | ref. |
| Ever | 959 (30.8) | 4585 (29.5) | 0.92 (0.83, 1.02) |
| Former b | 199 (6.4) | 831 (5.4) | 1.10 (0.92, 1.31) |
| Current | 760 (24.4) | 3754 (24.2) | 0.88 (0.79, 0.98) |
|
Time since first statin use recorded (years) |
|||
| Nonusers | 2159 (69.2) | 10934 (70.5) | ref. |
| 0–2 | 206 (6.6) | 1064 (6.9) | 0.87 (0.74, 1.02) |
| 3–5 | 292 (9.4) | 1316 (8.5) | 0.98 (0.84, 1.13) |
| 6–8 | 233 (7.5) | 1060 (6.8) | 0.97 (0.82, 1.14) |
| 9+ | 228 (7.3) | 1145 (7.4) | 0.85 (0.72, 1.01) |
| P trend | 0.128 | ||
| No. of prescriptions | |||
| Nonusers | 2159 (69.2) | 10934 (70.5) | ref. |
| 2–15 | 254 (8.1) | 1169 (7.5) | 0.98 (0.84, 1.14) |
| 16–35 | 236 (7.6) | 1144 (7.4) | 0.92 (0.79, 1.08) |
| 36–65 | 252 (8.1) | 1089 (7.0) | 1.00 (0.85, 1.17) |
| 66+ | 217 (7.0) | 1183 (7.6) | 0.76 (0.64, 0.91) |
| P trend | 0.016 | ||
| Cumulative dose c | |||
| Nonusers | 2159 (69.2) | 10934 (70.5) | ref. |
| Q1 | 269 (8.6) | 1146 (7.4) | 1.07 (0.93, 1.24) |
| Q2 | 225 (7.2) | 1147 (7.4) | 0.85 (0.73, 1.00) |
| Q3 | 242 (7.8) | 1147 (7.4) | 0.90 (0.77, 1.06) |
| Q4 | 223 (7.2) | 1144 (7.4) | 0.81 (0.68, 0.96) |
| Missing | 0 | 1 | |
| P trend | 0.008 | ||
Abbreviation: CI, confidence interval; CPRD, Clinical Practice Research Datalink; Q, quartile; OR, odds ratio
Adjusted for body mass index, smoking, alcohol drinking, and diabetes
Former: Stopped using statins 2+ years before diagnosis/selection date
Q1=13175, Q2=32480, Q3=65520
The reduced risk associated with statin use was similar for individual types of BTCs (Table 3). For example, the adjusted ORs for current statin use versus nonuse and risk of GBC, cholangiocarcinoma, and AVC were 0.86 (95%CI: 0.67–1.09), 0.87 (0.75–1.01), and 0.89 (0.59– 1.34), respectively. There were no clear dose-response relationships between risk of individual types of BTCs and number of prescriptions and cumulative dose, but the ORs were of similar magnitude to those for BTCs overall.
Table 3.
Association between statin use and subsites of biliary tract cancer, CPRD a
| Characteristic | Gallbladder b | Bile duct c | Ampulla of Vater | ||||||
|---|---|---|---|---|---|---|---|---|---|
| Case (n=708) |
Control (n=3331) |
Adjusted OR (95% CI) |
Case (n=1678) |
Control (n=8322) |
Adjusted OR (95% CI) |
Case (n=228) |
Control (n=1125) |
Adjusted OR (95% CI) a |
|
| Any statin use | |||||||||
| Nonusers | 495 (69.9) | 2374 (71.3) | ref. | 1167 (69.5) | 5880 (70.7) | ref. | 162 (71.1) | 802 (71.3) | ref. |
| Ever | 213 (30.1) | 957 (28.7) | 0.89 (0.71, 1.11) | 511 (30.5) | 2442 (29.3) | 0.92 (0.80, 1.05) | 66 (28.9) | 323 (28.7) | 0.96 (0.66, 1.41) |
| Former | 49 (6.9) | 198 (5.9) | 1.01 (0.69, 1.48) | 106 (6.3) | 426 (5.1) | 1.14 (0.89, 1.45) | 17 (7.5) | 65 (5.8) | 1.30 (0.68, 2.46) |
| Current | 164 (23.2) | 759 (22.8) | 0.86 (0.67, 1.09) | 405 (24.1) | 2016 (24.2) | 0.87 (0.75, 1.01) | 49 (21.5) | 258 (22.9) | 0.89 (0.59, 1.34) |
|
Time since first statin use recorded (years) |
|||||||||
| Nonusers | 495 (69.9) | 2374 (71.3) | ref. | 1167 (69.5) | 5880 (70.7) | ref. | 162 (71.1) | 802 (71.3) | ref. |
| 0–2 | 41 (5.8) | 195 (5.9) | 0.84 (0.57, 1.24) | 110 (6.6) | 572 (6.9) | 0.82 (0.66, 1.04) | 14 (6.1) | 82 (7.3) | 0.74 (0.39, 1.41) |
| 3–5 | 63 (8.9) | 297 (8.9) | 0.85 (0.61, 1.19) | 160 (9.5) | 691 (8.3) | 1.02 (0.84, 1.25) | 15 (6.6) | 81 (7.2) | 0.88 (0.47, 1.63) |
| 6–8 | 60 (8.5) | 228 (6.8) | 1.08 (0.76, 1.54) | 125 (7.4) | 569 (6.8) | 0.97 (0.78, 1.22) | 14 (6.1) | 82 (7.3) | 0.86 (0.45, 1.65) |
| 9+ | 49 (6.9) | 237 (7.1) | 0.79 (0.54, 1.17) | 116 (6.9) | 610 (7.3) | 0.82 (0.65, 1.05) | 23 (10.1) | 78 (6.9) | 1.68 (0.89, 3.15) |
| P trend | 0.391 | 0.246 | 0.433 | ||||||
| No. of prescriptions | |||||||||
| Nonusers | 495 (69.9) | 2374 (71.3) | ref. | 1167 (69.5) | 5880 (70.7) | ref. | 162 (71.1) | 802 (71.3) | ref. |
| 2–15 | 54 (7.6) | 227 (6.8) | 0.98 (0.69, 1.39) | 136 (8.1) | 642 (7.7) | 0.93 (0.76, 1.15) | 19 (8.3) | 83 (7.4) | 1.02 (0.58, 1.81) |
| 16–35 | 47 (6.6) | 248 (7.4) | 0.76 (0.53, 1.09) | 133 (7.9) | 608 (7.3) | 0.97 (0.79, 1.20) | 18 (7.9) | 71 (6.3) | 1.20 (0.66, 2.15) |
| 36–65 | 60 (8.5) | 242 (7.3) | 0.97 (0.69, 1.36) | 136 (8.1) | 568 (6.8) | 1.04 (0.83, 1.29) | 14 (6.1) | 81 (7.2) | 0.80 (0.42, 1.54) |
| 66+ | 52 (7.3) | 240 (7.2) | 0.84 (0.58, 1.24) | 106 (6.3) | 624 (7.5) | 0.71 (0.55, 0.90) | 15 (6.6) | 88 (7.8) | 0.77 (0.39, 1.50) |
| P trend | 0.306 | 0.063 | 0.498 | ||||||
| Cumulative dose d | |||||||||
| Nonusers | 495 (69.9) | 2374 (71.3) | ref. | 1167 (69.5) | 5880 (70.7) | ref. | 162 (71.1) | 802 (71.3) | ref. |
| Q1 | 62 (8.8) | 240 (7.2) | 1.08 (0.78, 1.49) | 145 (8.6) | 635 (7.6) | 1.02 (0.83, 1.25) | 15 (6.6) | 77 (6.8) | 0.92 (0.51, 1.65) |
| Q2 | 52 (7.3) | 239 (7.2) | 0.88 (0.62, 1.25) | 114 (6.8) | 598 (7.2) | 0.83 (0.66, 1.04) | 22 (9.6) | 81 (7.2) | 1.30 (0.74, 2.31) |
| Q3 | 44 (6.2) | 239 (7.2) | 0.66 (0.45, 0.97) | 139 (8.3) | 601 (7.2) | 1.00 (0.81, 1.24) | 10 (4.4) | 82 (7.3) | 0.67 (0.33, 1.36) |
| Q4 | 55 (7.8) | 238 (7.1) | 0.91 (0.62, 1.32) | 113 (6.7) | 608 (7.3) | 0.79 (0.62, 1.00) | 19 (8.3) | 83 (7.4) | 0.97 (0.51, 1.85) |
| P trend | 0.141 | 0.081 | 0.739 | ||||||
Abbreviation: CI, confidence interval; CPRD, Clinical Practice Research Datalink; Q, quartile; OR, odds ratio
ORs are adjusted for body mass index, smoking, alcohol drinking, and diabetes.
ORs are additionally adjusted for gallstones. Excludes 177 controls with a history of cholecystectomy.
ORs are additionally adjusted for cirrhosis.
For gallbladder cancer, Q1=14560, Q2= 34720, Q3= 66080; for cancer in Bile duct, Q1= 13440, Q2= 32480, Q3= 66080; for cancer of Ampulla of Vater, Q1= 12320, Q2=33600, Q3=63840.
The observed associations were similar for men and women, for individuals ≤70 and >70 years of age at one year prior to the diagnosis/selection, and for those with a diagnosis/selection year of ≤2005 and >2005 (all Pheterogeneity>0.05, Supplementary Table 4). In the joint analysis by history of diabetes, we found that statin use was associated with a lower risk of BTCs among patients with diabetes, with an adjusted OR for current statin use versus non-use of 0.72 (95%CI: 0.57–0.91). Among non-diabetics, the adjusted OR for current statin use versus non-use was 0.91 (95%CI: 0.81–1.03. Pheterogeneity=0.007). The reduced risk of BTCs was more pronounced among participants with statins prescribed before diabetes was diagnosed (adjusted OR=0.59, 95%CI: 0.44–0.81) than among those with statins prescribed after diabetes was diagnosed (0.84 [0.66–1.08], Pheterogeneity=0.03).
The sensitivity analyses remained agreed that current statin use is associated with reduced BTCs among incident statin users (OR=0.81, 95%CI: 0.70–0.94), excluding persons with biliary carcinoma in situ and their controls (0.88, 95%CI: 0.79–0.98), and among cases and controls without a history of cancer in situ except carcinoma in situ of biliary system (0.89, 95%CI: 0.79– 0.99) or without missing/unknown status for smoking, alcohol drinking, and BMI (0.90, 95%CI: 0.80–1.02).
Discussion
In this large study, we observed a reduced risk of BTCs among current statin users compared to nonusers. Reduced risk of BTCs was also more pronounced among subjects with the highest number of prescriptions and cumulative dose of statins, suggesting that long-term statin users may have a lower risk of developing BTCs. The risk estimate was consistent across individual types of BTCs, age groups, sex, and calendar time. Adjustment for various risk factors did not substantively alter the results. Finally, we also observed a risk reduction among persons with diabetes. If replicated in other studies, these findings suggest that statins may have a role as chemopreventive agents.
Comparison to other studies
To our knowledge, this study is the first to address the association between statin use and risk of cancer across the biliary tract. Our findings are in line with the one previous study focusing on cholangiocarcinoma in Taiwan, which reported that the adjusted OR for statin use versus nonuse for cholangiocarcinoma was 0.80 (95%CI: 0.71–0.90).[27] The results are also consistent with studies that have demonstrated a decreased risk of gallstone disease,[12, 13, 14, 15] a risk factor for BTCs,[28] especially GBC.[1, 2] Statins could potentially reduce risk of BTCs through suppression of biliary cholesterol secretion and saturation and anti-inflammatory and endothelial effects.[29, 30] The reduction in hepatic and gallbladder bile cholesterol concentrations could alter bile acid composition and interfere with gallstone production or even promote gallstone dissolution.[31] In addition, both experimental and clinical studies provide evidence that statins have anti-inflammatory effects.[29, 30] Statins reduce circulating C-reactive protein and pro-inflammatory cytokines and chemokines.[32, 33] Statins also favorably affect important pathways regulating nitric oxide bioavailability, which is critical for maintaining endothelium homeostasis via statins’ vasodilatory, anti-inflammatory, and overall anti-atherogenic effects. In addition, statins have been shown to regulate expression of many inflammatory genes.[30] Associations between statin use and lower risk of cancers in the digestive system related to inflammation, including cancers of the colorectum [34, 35], liver [19, 36, 37], and esophagus [38, 39, 40], have been reported in epidemiological studies. However, we did not observe a joint effect of use of both statins and aspirin (data not shown), as has been reported for esophageal cancer [39, 40].
Our findings of reduced BTC risk among persons with diabetes using statins should be interpreted with caution. Some studies suggest that statins may increase the risk of diabetes, although results are inconsistent.[23, 24] Experimental data support the hypothesis that statins may cause diabetes by altering glucose homeostasis through both impaired insulin secretion and diminished insulin sensitivity.[41] Following this hypothesis, statins could increase the risk of BTCs by increasing risk of diabetes. However, in the present study, we observed a reduced risk of BTCs among persons with diabetes who used statins before their diabetes was diagnosed, as compared with those with diabetes who did not use statins. Lipophilic (simvastatin and atorvastatin) and hydrophilic (pravastatin and rosuvastatin) statins have been observed to have different diabetogenic effects,[42] but we lacked the power to investigate whether the observed reduced risk of BTCs was driven by specific types of statins. Additional studies are needed to clarify the associations between statins, diabetes, and BTCs, but overall our results suggest that statins reduce the risk of BTCs both in patients with diabetes and those without.
Our study has several strengths. First, it was conducted using a large, well-established, validated, longitudinal primary-care database with long-term follow-up. This database is known for accuracy of diagnoses, including cancer, and completeness of pharmacy data.[43, 44, 45, 46] Second, all information on diseases and drug exposures in the CPRD is recorded prior to BTC diagnosis and in the absence of a study hypothesis, reducing the risk of recall bias. Third, we could evaluate the impact of various important confounders (BMI, smoking, alcohol drinking, a history of diabetes, hepatitis virus infection, chronic heart disease, dyslipidemia, and use of treatment for type 2 diabetes, aspirin, cortisone, or other lipid-lowering agents); such information is usually not accessible in registry-based studies. Although we did not adjust for socioeconomic status (SES), SES has been not associated with statin prescribing in England.[47] In addition, cases and controls were matched on general practice, and the universal health care coverage in the UK may, to some degree, control for SES. Finally, we conducted a large number of sensitivity analyses that further support the robustness of our findings.
Our study has a few limitations. First, although our sample size was sufficient for all BTCs combined, power was limited for individual types of BTCs and individual statins. Second, compliance rates among persons taking statins could not be evaluated, leading to potential exposure misclassification. Third, although we adjusted for several factors, these conditions could be inconsistently and incompletely recorded by general practitioners. For example, our adjustment for confounding by healthy user effect, healthy adherer effect, and functional status or cognitive impairment, which are not usually considered in observational studies [20], did not change the magnitude of the association between statin use and risk of BTCs. This result could be explained by the fact that residual confounding is possible even after our adjustment. Fourth, previous validation studies have reported that cancer diagnoses recorded by general practitioners in CPRD are accurate and complete.[43, 45, 46] However, the diagnosis of BTCs in the present study was not verified against pathology records, and some misclassification cannot be ruled out. We therefore believe that further studies conducted in databases with validated cancer diagnosis are warranted. Fifth, use of statins may not be accurately ascertained in CPRD due to introduction of over-the-counter 10-mg simvastatin in 2004.[22] We do not have evidence to support that the misclassification occurred differentially based on cases and controls status. In a case that the mis-classification of statin use is nondifferential by case-control status, statin may actually have an even more significant risk reduction on BTCs than currently observed in this study. Finally, we cannot rule out a potential role of chance for false positives findings, given the number of tests evaluated in this study.
In conclusion, this large observational study provides evidence that current or long-term statin use is associated with decreased risk of BTCs. Our findings should be replicated in other populations, particularly in high-risk areas, such as Chile, to confirm our observations and further establish the potential value of statins for BTC chemoprevention.
Supplementary Material
Acknowledgments
Funding: Intramural Research Program of the National Institutes of Health, National Cancer Institute, Division of Cancer Epidemiology and Genetics. The funders had no role in the conduct of this research.
Abbreviations:
- AVC
ampulla of Vater cancer
- BMI
body mass index
- BTC
Biliary tract cancer
- CI
confidence interval
- CPRD
Clinical Practice Research Datalink
- GBC
gallbladder cancer
- Q
quartile
- OR
odds ratios
Footnotes
Conflicts of Interest: The fifth author, Dr. Tsai, is currently an employee of the US Food and Drug Administration. The views expressed in this article are those of the authors and not necessarily those of the Food and Drug Administration. Other authors have none to declare.
Reference
- 1.Valle JW, Lamarca A, Goyal L, Barriuso J, Zhu AX. New Horizons for Precision Medicine in Biliary Tract Cancers. Cancer Discov 2017;7:943–62. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.de Groen PC, Gores GJ, LaRusso NF, Gunderson LL, Nagorney DM. Biliary tract cancers. N Engl J Med 1999;341:1368–78. [DOI] [PubMed] [Google Scholar]
- 3.Randi G, Malvezzi M, Levi F, Ferlay J, Negri E, Franceschi S, et al. Epidemiology of biliary tract cancers: an update. Ann Oncol 2009;20:146–59. [DOI] [PubMed] [Google Scholar]
- 4.Parag M, Engels EA, Koshiol J. Hepatitis B virus infection and the risk of cancer in the elderly US population. Int J Cancer 2018. [DOI] [PMC free article] [PubMed]
- 5.Andreotti G, Chen J, Gao YT, Rashid A, Chang SC, Shen MC, et al. Serum lipid levels and the risk of biliary tract cancers and biliary stones: A population-based study in China. Int J Cancer 2008;122:2322–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Espinoza JA, Bizama C, Garcia P, Ferreccio C, Javle M, Miquel JF, et al. The inflammatory inception of gallbladder cancer. Biochim Biophys Acta 2016;1865:245–54. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Koshiol J, Ferreccio C, Devesa SS, Roa JC, Fraumeni JFJ. Biliary Tract Cancer. Cancer Epidemiology and Prevention 2017.
- 8.Nogueira L, Freedman ND, Engels EA, Warren JL, Castro F, Koshiol J. Gallstones, cholecystectomy, and risk of digestive system cancers. Am J Epidemiol 2014;179:731–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Sanabria JR, Croxford R, Berk TC, Cohen Z, Bapat BV, Gallinger S. Familial segregation in the occurrence and severity of periampullary neoplasms in familial adenomatous polyposis. Am J Surg 1996;171:136–40; discussion 40–1. [DOI] [PubMed] [Google Scholar]
- 10.Offerhaus GJ, Giardiello FM, Krush AJ, Booker SV, Tersmette AC, Kelley NC, et al. The risk of upper gastrointestinal cancer in familial adenomatous polyposis. Gastroenterology 1992;102:1980–2. [DOI] [PubMed] [Google Scholar]
- 11.Cholesterol Treatment Trialists C, Baigent C, Blackwell L, Emberson J, Holland LE, Reith C, et al. Efficacy and safety of more intensive lowering of LDL cholesterol: a meta-analysis of data from 170,000 participants in 26 randomised trials. Lancet 2010;376:1670–81. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Suuronen S, Niskanen L, Paajanen P, Paajanen H. Declining cholecystectomy rate during the era of statin use in Finland: a population-based cohort study between 1995 and 2009. Scand J Surg 2013;102:158–63. [DOI] [PubMed] [Google Scholar]
- 13.Erichsen R, Froslev T, Lash TL, Pedersen L, Sorensen HT. Long-term statin use and the risk of gallstone disease: A population-based case-control study. Am J Epidemiol 2011;173:162–70. [DOI] [PubMed] [Google Scholar]
- 14.Tsai CJ, Leitzmann MF, Willett WC, Giovannucci EL. Statin use and the risk of cholecystectomy in women. Gastroenterology 2009;136:1593–600. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Bodmer M, Brauchli YB, Krahenbuhl S, Jick SS, Meier CR. Statin use and risk of gallstone disease followed by cholecystectomy. JAMA 2009;302:2001–7. [DOI] [PubMed] [Google Scholar]
- 16.Herrett E, Gallagher AM, Bhaskaran K, Forbes H, Mathur R, van Staa T, et al. Data Resource Profile: Clinical Practice Research Datalink (CPRD). Int J Epidemiol 2015;44:827–36. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Lawson DH, Sherman V, Hollowell J. The General Practice Research Database. Scientific and Ethical Advisory Group. QJM 1998;91:445–52. [DOI] [PubMed] [Google Scholar]
- 18.O’Neil M, Payne C, Read J. Read Codes Version 3: a user led terminology. Methods Inf Med 1995;34:187–92. [PubMed] [Google Scholar]
- 19.McGlynn KA, Hagberg K, Chen J, Graubard BI, London WT, Jick S, et al. Statin use and risk of primary liver cancer in the Clinical Practice Research Datalink. J Natl Cancer Inst 2015;107. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Shrank WH, Patrick AR, Brookhart MA. Healthy user and related biases in observational studies of preventive interventions: a primer for physicians. J Gen Intern Med 2011;26:546–50. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Ren HB, Yu T, Liu C, Li YQ. Diabetes mellitus and increased risk of biliary tract cancer: systematic review and meta-analysis. Cancer Causes Control 2011;22:837–47. [DOI] [PubMed] [Google Scholar]
- 22.Filion KB, Delaney JA, Brophy JM, Ernst P, Suissa S. The impact of over-the-counter simvastatin on the number of statin prescriptions in the United Kingdom: a view from the General Practice Research Database. Pharmacoepidemiol Drug Saf 2007;16:1–4. [DOI] [PubMed] [Google Scholar]
- 23.Preiss D, Seshasai SR, Welsh P, Murphy SA, Ho JE, Waters DD, et al. Risk of incident diabetes with intensive-dose compared with moderate-dose statin therapy: a meta-analysis. JAMA 2011;305:2556–64. [DOI] [PubMed] [Google Scholar]
- 24.Sattar N, Preiss D, Murray HM, Welsh P, Buckley BM, de Craen AJ, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet 2010;375:735–42. [DOI] [PubMed] [Google Scholar]
- 25.Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM Jr., Kastelein JJ, et al. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008;359:2195–207. [DOI] [PubMed] [Google Scholar]
- 26.Schneeweiss S, Patrick AR, Sturmer T, Brookhart MA, Avorn J, Maclure M, et al. Increasing levels of restriction in pharmacoepidemiologic database studies of elderly and comparison with randomized trial results. Med Care 2007;45:S131–42. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Peng YC, Lin CL, Hsu WY, Chang CS, Yeh HZ, Tung CF, et al. Statins are associated with a reduced risk of cholangiocarcinoma: a population-based case-control study. Br J Clin Pharmacol 2015;80:755–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Hsing AW, Gao YT, Han TQ, Rashid A, Sakoda LC, Wang BS, et al. Gallstones and the risk of biliary tract cancer: a population-based study in China. Br J Cancer 2007;97:1577–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Antonopoulos AS, Margaritis M, Lee R, Channon K, Antoniades C. Statins as anti-inflammatory agents in atherogenesis: molecular mechanisms and lessons from the recent clinical trials. Curr Pharm Des 2012;18:1519–30. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Jain MK, Ridker PM. Anti-inflammatory effects of statins: clinical evidence and basic mechanisms. Nat Rev Drug Discov 2005;4:977–87. [DOI] [PubMed] [Google Scholar]
- 31.Tazuma S, Kajiyama G, Mizuno T, Yamashita G, Miura H, Kajihara T, et al. A combination therapy with simvastatin and ursodeoxycholic acid is more effective for cholesterol gallstone dissolution than is ursodeoxycholic acid monotherapy. J Clin Gastroenterol 1998;26:287–91. [DOI] [PubMed] [Google Scholar]
- 32.Albert MA, Danielson E, Rifai N, Ridker PM, Investigators P. Effect of statin therapy on C-reactive protein levels: the pravastatin inflammation/CRP evaluation (PRINCE): a randomized trial and cohort study. JAMA 2001;286:64–70. [DOI] [PubMed] [Google Scholar]
- 33.Rezaie-Majd A, Maca T, Bucek RA, Valent P, Muller MR, Husslein P, et al. Simvastatin reduces expression of cytokines interleukin-6, interleukin-8, and monocyte chemoattractant protein-1 in circulating monocytes from hypercholesterolemic patients. Arterioscler Thromb Vasc Biol 2002;22:1194–9. [DOI] [PubMed] [Google Scholar]
- 34.Poynter JN, Gruber SB, Higgins PD, Almog R, Bonner JD, Rennert HS, et al. Statins and the risk of colorectal cancer. N Engl J Med 2005;352:2184–92. [DOI] [PubMed] [Google Scholar]
- 35.Nguyen DM, Richardson P, El-Serag HB. Medications (NSAIDs, statins, proton pump inhibitors) and the risk of esophageal adenocarcinoma in patients with Barrett’s esophagus. Gastroenterology 2010;138:2260–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Singh S, Singh PP, Singh AG, Murad MH, Sanchez W. Statins are associated with a reduced risk of hepatocellular cancer: a systematic review and meta-analysis. Gastroenterology 2013;144:323–32. [DOI] [PubMed] [Google Scholar]
- 37.McGlynn KA, Divine GW, Sahasrabuddhe VV, Engel LS, VanSlooten A, Wells K, et al. Statin use and risk of hepatocellular carcinoma in a U.S. population. Cancer Epidemiol 2014;38:523–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Singh S, Singh AG, Singh PP, Murad MH, Iyer PG. Statins are associated with reduced risk of esophageal cancer, particularly in patients with Barrett’s esophagus: a systematic review and meta-analysis. Clin Gastroenterol Hepatol 2013;11:620–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Kastelein F, Spaander MC, Biermann K, Steyerberg EW, Kuipers EJ, Bruno MJ, et al. Nonsteroidal anti-inflammatory drugs and statins have chemopreventative effects in patients with Barrett’s esophagus. Gastroenterology 2011;141:2000–8; quiz e13-4. [DOI] [PubMed] [Google Scholar]
- 40.Beales IL, Vardi I, Dearman L. Regular statin and aspirin use in patients with Barrett’s oesophagus is associated with a reduced incidence of oesophageal adenocarcinoma. Eur J Gastroenterol Hepatol 2012;24:917–23. [DOI] [PubMed] [Google Scholar]
- 41.Aiman U, Najmi A, Khan RA. Statin induced diabetes and its clinical implications. J Pharmacol Pharmacother 2014;5:181–5. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Baker WL, Talati R, White CM, Coleman CI. Differing effect of statins on insulin sensitivity in non-diabetics: a systematic review and meta-analysis. Diabetes Res Clin Pract 2010;87:98–107. [DOI] [PubMed] [Google Scholar]
- 43.Jick H, Jick SS, Derby LE. Validation of information recorded on general practitioner based computerised data resource in the United Kingdom. BMJ 1991;302:766–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Jick SS, Kaye JA, Vasilakis-Scaramozza C, Garcia Rodriguez LA, Ruigomez A, Meier CR, et al. Validity of the general practice research database. Pharmacotherapy 2003;23:686–9. [DOI] [PubMed] [Google Scholar]
- 45.Dregan A, Moller H, Murray-Thomas T, Gulliford MC. Validity of cancer diagnosis in a primary care database compared with linked cancer registrations in England. Population-based cohort study. Cancer Epidemiol 2012;36:425–9. [DOI] [PubMed] [Google Scholar]
- 46.Boggon R, van Staa TP, Chapman M, Gallagher AM, Hammad TA, Richards MA. Cancer recording and mortality in the General Practice Research Database and linked cancer registries. Pharmacoepidemiol Drug Saf 2013;22:168–75. [DOI] [PubMed] [Google Scholar]
- 47.Reid FD, Cook DG, Whincup PH. Use of statins in the secondary prevention of coronary heart disease: is treatment equitable? Heart 2002;88:15–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
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