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. Author manuscript; available in PMC: 2024 Jul 20.
Published in final edited form as: Int J Cancer. 2022 Sep 5;152(2):172–182. doi: 10.1002/ijc.34235

Autoimmune conditions and pancreatic cancer risk in older American adults

Fangcheng Yuan 1, Ruth M Pfeiffer 1, Sachelly Julián-Serrano 1, Simran Arjani 1, Michael J Barrett 2, Jill Koshiol 1, Rachael Z Stolzenberg-Solomon 1
PMCID: PMC11260175  NIHMSID: NIHMS1997814  PMID: 36059225

Abstract

Pancreatic cancer (PC) is highly fatal, and its incidence is increasing in the United States. Population-based registry studies suggest associations between a few autoimmune conditions and PC risk, albeit based on a relatively small number of cases. We conducted a population-based, nested case-control study to examine the association between autoimmune conditions and PC risk within the Surveillance, Epidemiology, and End Results Program (SEER)-Medicare population. Incident primary malignant PC cases (n=80,074) were adults ≥ 66 years and diagnosed between 1992 and 2015. Controls (n=320,296) were alive at the time cases were diagnosed and frequency-matched to cases (4:1 ratio) by age, sex, and year of diagnosis. We used multivariable-adjusted, unconditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for 45 autoimmune conditions identified from Medicare claims. Eight autoimmune conditions including ankylosing spondylitis (OR = 1.45; 95% CI: 1.14–1.84), Graves’ disease (OR = 1.18; 95% CI: 1.03–1.34), localized scleroderma (OR = 1.27; 95% CI: 1.06–1.52), pernicious anemia (OR = 1.08; 95% CI: 1.02–1.14), primary sclerosing cholangitis (OR = 1.37; 95% CI: 1.18–1.59), pure red cell aplasia (OR = 1.31; 95% CI: 1.16–1.47), type 1 diabetes (OR = 1.11; 95% CI: 1.07–1.15), and ulcerative colitis (OR = 1.18; 95% CI: 1.07–1.31) were associated with increased PC risk (false discovery rate-adjusted P values < 0.10). In subtype analyses, these conditions were associated with pancreatic ductal adenocarcinoma, whereas only ulcerative colitis was associated with pancreatic neuroendocrine tumors. Our results support the hypothesis that autoimmune conditions may play a role in PC development.

Keywords: pancreatic cancer, autoimmune conditions, SEER-Medicare data, epidemiology

Introduction

The incidence of pancreatic cancer (PC) has been increasing in the US and worldwide.1, 2 Pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine tumors (PNETs) are the two most common PC subtypes. Cigarette smoking, diabetes mellitus, chronic pancreatitis and excess weight are known risk factors for PDAC.3 Risk factors for PNETs are largely unknown beyond rare inherited genetic syndromes.4

Autoimmune conditions are characterized by immune dysregulation and have been associated with increased risks of gastrointestinal tract cancers in registry-based studies.5–18 However, current evidence on the associations of autoimmune conditions, particularly Crohn’s disease,6, 7, 10, 16, 17 ulcerative colitis,7, 8, 10, 16, 17, 19 and systemic lupus erythematosus,10, 15 and celiac disease10–12, 16 have been inconsistent. Many of these studies have insufficient power to detect associations due to the relatively low prevalence of autoimmune conditions and PC in the general population. Previously, we showed that joint effects of common variants in genomic regions containing susceptibility loci for Crohn’s disease and ulcerative colitis were associated with PDAC, suggesting a shared genetic architecture between the diseases.20

In this study, we examined associations between autoimmune conditions and PC risk in a large population-based, nested case-control study of older adults within the US Surveillance, Epidemiology, and End Results Program (SEER)-Medicare linked data. We hypothesize that autoimmune conditions are associated with the risk of PC.

Methods

Data sources

We conducted a population-based, nested case-control study within the SEER-18 Medicare database.21 Briefly, the National Cancer Institute’s SEER Program collects information on cancer incidence, mortality, and survival from population-based cancer registries which currently cover approximately 35% of the US population.22 Medicare is a federally funded health insurance program that provides coverage for 97% of the US population aged 65 years or older and younger people with end-stage renal disease and disabilities. All Medicare beneficiaries are enrolled in Part A benefits which includes inpatient hospital, skilled-nursing facility, hospice and some home health care. Ninety-six percent of those enrolled in Part A also subscribe to Part B which covers physician and outpatient services.

The SEER-Medicare is an electronic linkage database in which SEER cancer registries data are matched to Medicare beneficiaries and claims.23 Approximately 95% of individuals aged 65 or older in the SEER database are linked to the Medicare enrollment file. Research using the SEER-Medicare data is deemed exempt by the National Institutes of Health Office of Human Subjects Research Protection.

Case ascertainment and selection of controls

PC cases were defined as participants with primary malignant disease [first and later (i.e., PC diagnosed after diagnosis of a primary malignant neoplasm at sites other than the pancreas) primary; International Classification of Disease for Oncology, ICD-O codes C25.0-C25.9 with malignant code 3], identified in the SEER-Medicare Patient Entitlement Diagnosis Summary File (PEDSF) between January 1, 1992 and December 31, 2015. PC diagnosed at autopsy or by death certificates only were excluded because they differed from cancers diagnosed clinically.24 Cases were required to have at least 13 months of Medicare Part A and B, non-health maintenance organization (HMO) coverage, making the minimum age at PC diagnosis 66 years. Cases were also required to have at least one Medicare claim [Medicare Provider Analysis and Review (MedPAR), National Claims History (NCH), or Outpatient] more than 12 months prior to PC diagnosis to ensure that they utilized Medicare benefits. Cases over the age of 99 were excluded (online supplementary figure 1). We used the ICD-O morphological classification to create mutually exclusive PC subgroups for PDAC (8000, 8010, 8140, 8144, 8145, 8255, 8440, 8450, 8453, 8460, 8470, 8471, 8480, 8481, 8490, 8500, 8503, 8504, 8507, 8510, 8514, 8521, 8523, 8560, 8570) and PNETs (8240, 8243–8245,8150, 8246,8151–8153, 8155).

Controls were randomly selected in a 4:1 ratio for each first primary case from a 5% representative random sample of Medicare-enrolled beneficiaries without cancer residing in the geographic region covered by SEER, or from a 5% random sample of participants from the SEER-Medicare PEDSF. Controls were alive and either free of cancer or PC (for first primary or later primary, respectively) as of July 1 of the calendar year that the case was diagnosed, and frequency-matched to the cases by age (66–69, 70–74, 75–79, 80–84, 85–89, 90–94, and 95–99), sex, and calendar year of diagnosis (±1 year). Controls were subject to the same exclusion criteria as the cases.

Ascertainment of autoimmune conditions and other exposures

Forty-five autoimmune conditions identified by International Classification of Diseases 9th edition (ICD-9) codes from Medicare claims were included in this study (online supplementary table 1). A diagnosis of autoimmune condition was defined as having a minimum of one inpatient claim (MeDPAR) or two physician/outpatient (NCH or Outpatient) claims at least 30 days apart. We required autoimmune conditions be diagnosed at least 12 months before cancer diagnosis/control selection to minimize surveillance bias and reverse causation.

We used ICD-9 codes from Medicare claims for certain medical conditions as surrogate measures for smoking and heavy alcohol use. Subjects with chronic obstructive pulmonary disorder (COPD; except asthma, 490, 491, 492, 494, 495, or 496), personal history of tobacco use (V15.82) or non-dependent tobacco use disorder (305.1) were considered smokers and those with any alcohol-induced liver disorders (571.0, 571.1, 571.2, 571.3), alcohol-induced psychiatric or neurologic disorders (291), alcohol intoxication (303), non-dependent alcohol abuse (305), or a personal history of alcoholism (V11.3) were classified as heavy alcohol users. Type 2 diabetes (250.00, 250.02, 250.10, 250.12, 250.20, 250.22, 250.30, 250.32, 250.40, 250.42, 250.50, 250.52, 250.60, 250.62, 250.70, 250.72, 250.80, 250.82, 250.90, 250.92, 790.2), overweight/obesity (278.0, 278.01, 278.02, 278.1, V77.8, 783.1, 278.00, 278.01), and chronic/acute pancreatitis (577.0, 577.1) diagnoses were also determined with ICD-9 codes.

Statistical analysis

We used unconditional logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between autoimmune conditions and PC. Models were adjusted for age category (66–69, 70–74, 75–79, 80–84, 85–89, 90–99 years), sex, calendar year category of PC diagnosis/selection (1992–2000, 2001–2005, 2006–2009, 2010–2015), race/ethnicity (non-Hispanic White, non-Hispanic Black, Asian/Pacific Islander, Hispanic, other/unknown), geographic region (SEER registry), Medicaid eligibility (ever, never), average number of physician visits per 6 months in the 5 years before diagnosis/selection (quintiles in controls), average duration of Medicare part A, B, non-HMO coverage (quintiles in controls), Medicare low-income subsidy (ever, never, unknown), overweight/obesity (ever, never diagnosed), smoking behavior-related diagnoses (ever, never diagnosed), COPD (ever, never diagnosed), alcohol-related diagnoses (ever, never diagnosed), type 2 diabetes mellitus (ever, never diagnosed), chronic or acute pancreatitis (ever, never diagnosed).

We conducted exploratory stratified analyses by PC subtypes (PDAC, PNETs for the most significant autoimmune conditions), sex, age (< 75 years, ≥ 75 years), and race (non-Hispanic White, non-Hispanic Black). Race of other categories were not included in the analysis due to limited sample size. We fitted a two-stage hierarchical logistic regression model (online supplementary methods) separately to three groups (“primary gastrointestinal”, “secondary gastrointestinal-associated”, and “not gastrointestinal-associated”) to assess the combined effects of conditions within the same group.25 The hierarchical models also account for correlations due to multiple autoimmune conditions occurring in the same individual and thus improve the accuracy of risk estimates. To account for the long duration of pancreatic cancer development and surveillance bias due to autoimmune disease diagnosis, we also conducted a sensitivity analysis to examine the associations of autoimmune conditions with all primary PC among participants whose cancer diagnosis/control selection was at least five years after autoimmune condition diagnosis. All statistical tests were two-sided. We considered a false discovery rate (FDR)-adjusted P (PFDR) value < 0.10 statistically significant.26 Analyses were conducted using SAS version 9.4 (SAS Institute, Inc., Cary, North Carolina).

Results

Our study included 80,074 incident PC cases and 320,296 population-based controls (Table 1). Among the PC cases, 61,081 (76.3%) were first primary and 18,993 (23.7%) were later primary. Compared with controls, PC cases were more likely to be non-Hispanic Black, have longer Medicare Part A, B, non-HMO coverage, visit physicians more frequently six months prior to diagnosis/selection, and have diagnoses of overweight/obesity, COPD, acute/chronic pancreatitis, type 2 diabetes, and smoking behavior- and alcohol-related comorbidities. Compared with first primary cases, later primary cases were more likely to be older, male, non-Hispanic White, have longer Medicare Part A, B, non-HMO coverage and more physician visits six months prior to diagnosis, and have diagnoses of overweight/obesity, COPD, acute/chronic pancreatitis, type 2 diabetes, and smoking behavior- or alcohol-related comorbidities.

Table 1.

Characteristics of SEER-Medicare pancreatic cancer cases and frequency-matched controlsa, 1992–2015.

Characteristics Pancreatic cancer cases
Control
N = 320,296		 First primary
N = 61,081 (76.3%)		 Later primary
N = 18,993 (23.7%)		 All primary
N = 80,074
Age (years), n (%)
66–69 42,388 (13.2) 8,590 (14.1) 2,007 (10.6) 10,597 (13.2)
70–74 71,148 (22.2) 13,979 (22.9) 3,808 (20.0) 17,787 (22.2)
75–79 75,692 (23.6) 14,253 (23.3) 4,670 (24.6) 18,923 (23.6)
80–84 66,048 (20.6) 12,140 (19.9) 4,372 (23.0) 16,512 (20.6)
85–89 43,496 (13.6) 7,991 (13.1) 2,883 (15.2) 10,874 (13.6)
90–94 17,524 (5.5) 3,357 (5.5) 1,024 (5.4) 4,381 (5.5)
95–99 4000 (1.2) 771 (1.3) 229 (1.2) 1,000 (1.2)
Median (IQR) 77 (72–83) 77 (72–83) 78 (73–84) 78 (72–83)
Sex, n (%)
Male 144,484 (45.1) 26,277 (43.0) 9,844 (51.8) 36,121 (45.1)
Female 175,812 (54.9) 34,804 (57.0) 9,149 (48.2) 43,953 (54.9)
Race, n (%)
White (non-Hispanic) 264,161 (82.5) 49,619 (81.2) 16,171 (85.1) 65,790 (82.2)
Black (non-Hispanic) 23,841 (7.4) 6,179 (10.1) 1,705 (9.0) 7,884 (9.8)
Asian/Pacific Islander 14,483 (4.5) 2,176 (3.6) 442 (2.3) 2,618 (3.3)
Hispanic 7,893 (2.5) 1,227 (2.0) 237 (1.2) 1,464 (1.8)
Other/Unknown 9,918 (3.1) 1,880 (3.1) 438 (2.3) 2,318 (2.9)
Year of diagnosis/selectionb, n (%)
1992–2000 61,352 (19.2) 12,382 (20.3) 2,956 (15.6) 15,338 (19.2)
2001–2005 73,460 (22.9) 14,279 (23.4) 4,086 (21.5) 18,365 (22.9)
2006–2009 71,592 (22.4) 13,537 (22.2) 4,361 (23.0) 17,898 (22.4)
2010–2015 113,892 (35.6) 20,883 (34.2) 7,590 (40.0) 28,473 (35.6)
SEER registry, n (%)
San Francisco 15,050 (4.7) 2,867 (4.7) 943 (5.0) 3,810 (4.8)
Connecticut 23,327 (7.3) 5,009 (8.2) 1,402 (7.4) 6,411 (8.0)
Detroit 24,417 (7.6) 5,494 (9.0) 1,852 (9.8) 7,346 (9.2)
Hawaii 5,776 (1.8) 1,123 (1.8) 340 (1.8) 1,463 (1.8)
Iowa 22,532 (7.0) 4,313 (7.1) 1,355 (7.1) 5,668 (7.1)
New Mexico 9,546 (3.0) 1,591 (2.6) 376 (2.0) 1,967 (2.5)
Seattle 19,413 (6.1) 3,936 (6.4) 1,368 (7.2) 5,304 (6.6)
Utah 9,949 (3.1) 1,653 (2.7) 443 (2.3) 2,096 (2.6)
Atlanta 10,493 (3.3) 2,000 (3.3) 598 (3.1) 2,598 (3.2)
San Jose 9,260 (2.9) 1,721 (2.8) 469 (2.5) 2,190 (2.7)
Los Angeles 30,262 (9.4) 5,611 (9.2) 1,628 (8.6) 7,239 (9.0)
Rural Georgia 935 (0.3) 157 (0.3) 35 (0.2) 192 (0.2)
Greater California 48,584 (15.2) 8,490 (13.9) 2,744 (14.4) 11,234 (14.0)
Kentucky 18,661 (5.8) 3,256 (5.3) 992 (5.2) 4,248 (5.3)
Louisiana 15,862 (5.0) 3,200 (5.2) 993 (5.3) 4,193 (5.2)
New Jersey 36,189 (11.3) 7,140 (11.7) 2,440 (12.8) 9,580 (12.0)
Greater Georgia 20,040 (6.3) 3,520 (5.8) 1,015 (5.3) 4,535 (5.7)
Medicare coverage (months)c, median (IQR)
Part A, B, non-HMO 67 (42–82) 71 (42–84) 74 (48–85) 72 (43–84)
Part D 18 (0–52) 17 (0–48) 15 (0–49) 16 (0–49)
Number of physician visits per 6 monthsd, median (IQR) 3.0 (1.3–5.5) 3.1 (1.4–5.8) 4.3 (2.3–7.1) 3.4 (1.5–6.1)
Any low-income subsidy/Medicaid eligibilitye, n (%)
Ever 37,034 (11.6) 6695 (11.0) 1,720 (9.1) 8,415 (10.5)
Never 130,922 (40.9) 24,398 (39.9) 9,176 (48.3) 33,574 (41.9)
Unknown 152,340 (47.6) 29,988 (49.1) 8,097 (42.6) 38,085 (47.6)
Comorbidityf, n (%)
Overweight/Obesity diagnoses 17,980 (5.6) 4,113 (6.7) 1,398 (7.4) 5,511 (6.9)
Smoking behavior-related diagnosesg 23,803 (7.4) 5,787 (9.5) 2,472 (13.0) 8,259 (10.3)
COPD 59,294 (18.5) 12,734 (20.8) 4,705 (24.8) 17,439 (21.8)
Alcohol-related diagnosesh 14,294 (4.5) 4,102 (6.7) 1,475 (7.8) 5,577 (7.0)
Acute/Chronic pancreatitis 3,609 (1.1) 1,685 (2.8) 591 (3.1) 2,276 (2.8)
Type 2 diabetes 90,232 (28.2) 21,993 (36.0) 7,149 (37.6) 29,142 (36.4)
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Abbreviations: COPD, chronic obstructive pulmonary disease; HMO, health maintenance organization; IQR, interquartile range; SEER, Surveillance, Epidemiology, and End Results.

a

Controls were frequency-matched to cases by age (66–69, 70–74, 75–79, 80–84, 85–89, 90–94, and 95–99), sex, and calendar year of diagnosis (±1 year).

b

Calendar year of cancer diagnosis or control selection.

c

Months of Medicare coverage from entry to 12 months immediately before cancer diagnosis or control selection.

d

Physician visit claims in the 12-month period immediately before cancer diagnosis or control selection were excluded. We also excluded claims from specialists with limited direct patient care responsibilities (i.e., radiologists, anesthesiologists and pathologists) to account for surveillance bias.

e

Any low-income subsidy or Medicaid coverage before cancer diagnosis or control selection.

f

Defined as one inpatient claim or two physician/outpatient claims 30 days apart, excluding the 12-month period prior to cancer diagnosis or control selection.

g

Defined as any diagnosis of personal history of tobacco use or non-dependent tobacco use disorder.

h

Defined as any diagnosis of alcohol-induced liver disorders, alcohol-induced psych/neurologic disorders, alcohol intoxication, non-dependent alcohol abuse, or personal history of alcoholism.

Eight autoimmune conditions were significantly associated with an elevated risk of all PC at PFDR value < 0.10 (Table 2): ankylosing spondylitis (OR = 1.45; 95% CI: 1.14–1.84), Graves’ disease (OR = 1.18; 95% CI: 1.03–1.34), localized scleroderma (OR = 1.27; 95% CI: 1.06–1.52), pernicious anemia (OR = 1.08; 95% CI: 1.02–1.14), primary sclerosing cholangitis (OR = 1.37; 95% CI: 1.18–1.59), pure red cell aplasia (OR = 1.31; 95% CI: 1.16–1.47), type 1 diabetes (OR = 1.11; 95% CI: 1.07–1.15), and ulcerative colitis (OR = 1.18; 95% CI: 1.07–1.31). We also observed a suggestive positive association for discoid lupus erythematosus (OR = 1.30; 95% CI: 1.03–1.64; PFDR value = 0.12). These associations were similar in magnitude or in the same direction for first and later primary PC except for pure red cell aplasia which was only associated with later primary PC (OR = 2.00; 95% CI: 1.68–2.37). In addition, aplastic anemia (OR = 2.09; 95% CI: 1.21–3.61) was positively associated with later primary PC, whereas rheumatoid arthritis (OR = 0.89; 95% CI: 0.81–0.97) was inversely associated. Associations with PC were generally similar in stratified analyses, although stronger associations were present in women compared with men for Graves’ disease; in participants ≥ 75 years old compared with < 75 years old for localized scleroderma, primary sclerosing cholangitis, and pure red cell aplasia; and in non-Hispanic White compared with non-Hispanic Black for pernicious anemia and pure red cell aplasia (online supplementary tables 2–4). In hierarchical models that mutually adjusted for conditions in the same group, the eight top autoimmune conditions remained significantly associated with PC (online supplementary table 5). Among participants diagnosed with autoimmune conditions five years or more before PC diagnosis (online supplementary table 6, n=56,624 cases and 220,531 controls), Graves’ disease (OR =1.33; 95% CI: 1.10–1.62), pure red cell aplasia (OR = 1.45; 95% CI: 1.19–1.77), type 1 diabetes (OR = 1.15; 95% CI: 1.10–1.21), and ulcerative colitis (OR = 1.22; 95% CI: 1.05–1.43) remained significant after adjusting for multiple comparison, whereas the associations for ankylosing spondylitis (OR = 1.61; 95% CI: 1.11–2.35) and localized scleroderma (OR = 1.40; 95% CI: 1.07–1.83) were positive however not at PFDR value < 0.10. The associations for pernicious anemia (OR = 1.06; 95% CI: 0.97–1.15) and primary sclerosing cholangitis (OR = 0.96; 95% CI: 0.69–1.34) became non-significant.

Table 2.

Associations between autoimmune conditions and pancreatic cancers in the SEER-Medicare database, 1992–2015a

Autoimmune conditions Control First primary cases
 Later primary cases
 All primary cases
N = 320,296 N = 61,081 OR (95% CI)b N = 18,993 OR (95% CI)b N = 80,074 OR (95% CI)b P value PFDR value c
Addison’s disease 629 114 0.88 (0.71–1.08) 56 1.04 (0.76–1.43) 170 0.93 (0.78–1.11) 0.41 0.73
Alopecia areata 261 41 0.81 (0.57–1.14) 23 1.09 (0.67–1.78) 64 0.89 (0.68–1.18) 0.42 0.73
Amyotrophic lateral sclerosis 54 >11 1.12 (0.59–2.13) <11 0.97 (0.31–3.03) 17 1.09 (0.62–1.91) 0.76 0.91
Ankylosing spondylitis 260 71 1.51 (1.14–2.00) 28 1.26 (0.80–1.98) 99 1.45 (1.14–1.84) 0.002 0.019
Aplastic anemia 190 34 0.77 (0.53–1.12) 24 2.09 (1.21–3.61) 58 1.03 (0.76–1.39) 0.84 0.91
Autoimmune hemolytic anemia 136 23 0.87 (0.55–1.39) 13 1.11 (0.57–2.14) 36 0.96 (0.66–1.40) 0.82 0.91
Autoimmune hepatitis 34 <11 0.97 (0.42–2.27) <11 0.86 (0.15–4.97) <11 0.95 (0.44–2.04) 0.90 0.93
Celiac disease 341 66 0.95 (0.72–1.25) 24 1.05 (0.66–1.68) 90 0.97 (0.76–1.23) 0.79 0.91
Chronic rheumatic heart disease 6,073 1,328 1.03 (0.96–1.09) 483 0.93 (0.83–1.03) 1,811 1.00 (0.95–1.06) 0.96 0.96
Crohn’s disease 961 212 1.11 (0.95–1.30) 83 1.11 (0.86–1.44) 295 1.11 (0.97–1.27) 0.11 0.34
Dermatitis herpetiformis 81 <11 0.61 (0.31–1.20) <11 0.92 (0.38–2.20) 17 0.72 (0.42–1.23) 0.23 0.62
Discoid lupus erythematosus 298 80 1.33 (1.03–1.72) 23 1.19 (0.72–1.96) 103 1.30 (1.03–1.64) 0.02 0.12
Erythema nodosum 47 <11 0.79 (0.35–1.81) <11 0.76 (0.21–2.78) <11 0.79 (0.40–1.59) 0.52 0.83
Granulomatosis with polyangiitis 69 >11 1.28 (0.73–2.25) <11 1.30 (0.49–3.47) 22 1.28 (0.79–2.09) 0.32 0.70
Graves’ disease 1,010 235 1.16 (1.00–1.35) 85 1.23 (0.95–1.59) 320 1.18 (1.03–1.34) 0.01 0.074
Guillain-Barré syndrome 187 >40 1.25 (0.89–1.74) <11 0.58 (0.28–1.20) 57 1.06 (0.78–1.44) 0.69 0.89
Hashimoto’s thyroiditis 1,116 214 1.00 (0.86–1.17) 97 1.11 (0.88–1.41) 311 1.03 (0.91–1.18) 0.60 0.86
Hypersensitivity angiitis 92 >11 0.92 (0.53–1.58) <11 0.81 (0.32–2.06) 23 0.89 (0.55–1.42) 0.62 0.86
Immune thrombocytopenic purpura 223 44 1.01 (0.72–1.42) 27 1.45 (0.91–2.32) 71 1.15 (0.87–1.51) 0.33 0.70
Localized scleroderma 522 120 1.22 (0.99–1.50) 46 1.43 (1.00–2.04) 166 1.27 (1.06–1.52) 0.009 0.058
Membranous nephropathy 109 >20 0.93 (0.57–1.50) <11 0.95 (0.38–2.35) 28 0.92 (0.60–1.40) 0.68 0.89
Multiple sclerosis 502 83 0.80 (0.63–1.01) 31 0.91 (0.60–1.37) 114 0.83 (0.67–1.01) 0.07 0.26
Myasthenia gravis 370 58 0.79 (0.59–1.05) 25 0.92 (0.59–1.45) 83 0.82 (0.64–1.04) 0.10 0.34
Pernicious anemia 6,112 1,288 1.05 (0.99–1.12) 512 1.16 (1.04–1.29) 1,800 1.08 (1.02–1.14) 0.006 0.045
Polyarteritis nodosa 47 <11 0.99 (0.47–2.07) <11 1.18 (0.40–3.50) 14 1.06 (0.58–1.95) 0.85 0.89
Polymyalgia rheumatica 3,391 727 1.11 (1.02–1.21) 231 0.97 (0.83–1.13) 958 1.07 (1.00–1.16) 0.06 0.25
Polymyositis/dermatomyositis 248 47 0.97 (0.70–1.35) 16 0.85 (0.48–1.49) 63 0.94 (0.71–1.24) 0.66 0.91
Primary biliary cirrhosis 160 >20 0.89 (0.59–1.35) <11 0.64 (0.29–1.42) 37 0.82 (0.57–1.19) 0.30 0.70
Primary sclerosing cholangitis 602 206 1.42 (1.19–1.69) 76 1.28 (0.96–1.70) 282 1.37 (1.18–1.59) 3.7 × 10 −5 5.6×10 −4
Psoriasis 4,079 834 1.05 (0.97–1.14) 312 1.05 (0.92–1.19) 1,146 1.06 (0.99–1.13) 0.12 0.34
Pure red cell aplasia 1,074 172 0.85 (0.72–1.01) 235 2.00 (1.68–2.37) 407 1.31 (1.16–1.47) 8.4 × 10 −6 1.9×10 −4
Reactive arthritis 27 <11 0.89 (0.33–2.38) <11 0.43 (0.05–3.65) <11 0.76 (0.31–1.85) 0.54 0.84
Rheumatic fever 137 >30 1.31 (0.89–1.95) <11 0.78 (0.33–1.82) 41 1.16 (0.82–1.66) 0.40 0.73
Rheumatoid arthritis 11,182 2,318 1.02 (0.97–1.07) 716 0.89 (0.81–0.97) 3,034 0.98 (0.94–1.02) 0.39 0.73
Sarcoidosis 390 96 1.18 (0.93–1.50) 25 0.67 (0.43–1.05) 121 1.03 (0.84–1.27) 0.78 0.91
Scleritis 346 73 1.20 (0.92–1.57) 17 0.72 (0.42–1.22) 90 1.07 (0.84–1.36) 0.57 0.86
Sjögren’s syndrome 872 172 1.06 (0.89–1.26) 64 1.04 (0.78–1.39) 236 1.06 (0.91–1.22) 0.46 0.77
Systemic lupus erythematosus 963 214 1.13 (0.97–1.32) 71 0.95 (0.72–1.25) 285 1.08 (0.94–1.23) 0.28 0.69
Systemic sclerosis 285 43 0.76 (0.54–1.05) 17 0.97 (0.55–1.70) 60 0.80 (0.60–1.06) 0.12 0.34
Takayasu’s arteritis 17 <11 0.61 (0.13–2.79) <11 0.48 (0.05–4.84) <11 0.57 (0.16–2.01) 0.38 0.73
Temporal arteritis 912 205 1.15 (0.98–1.35) 68 1.11 (0.84–1.48) 273 1.14 (0.99–1.30) 0.07 0.26
Type 1 diabetes 15,932 4,378 1.13 (1.08–1.17) 1,402 1.06 (0.99–1.13) 5,780 1.11 (1.07–1.15) 5.1 × 10 −9 2.3×10 −7
Ulcerative colitis 1,585 347 1.14 (1.01–1.29) 164 1.25 (1.04–1.51) 511 1.18 (1.07–1.31) 0.001 0.016
Uveitis 558 105 0.94 (0.76–1.17) 47 1.27 (0.90–1.79) 152 1.02 (0.85–1.23) 0.81 0.91
Vitiligo 219 38 0.88 (0.62–1.26) 17 1.40 (0.78–2.50) 55 0.98 (0.73–1.33) 0.91 0.93
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Abbreviations: CI, confidence interval; FDR, false discovery rate; GI, gastrointestinal; HMO, health maintenance organization; OR, odds ratio; SEER, Surveillance, Epidemiology, and End Results.

a

Cells with < 11 observations and any cell that could be used to derive the value of a cell with < 11 observations were suppressed to comply with SEER-Medicare data use agreement.

b

Multivariable-adjusted unconditional logistic regression models were used to calculate OR and 95% CI, adjusting for age (grouped as 66–69, 70–74, 75–79, 80–84, 85–89, 90–99 years), sex, race/ethnicity (non-Hispanic White, non-Hispanic Black, Asian, Hispanic, other/unknown), calendar year of diagnosis/selection (1992–2000, 2001–2005, 2006–2009, 2010–2015), geographic region (SEER registry), Medicaid eligibility (ever, never), average number of physician visits per 6 months in the 5 years before diagnosis/selection (quintiles), average duration of Medicare part A, B, non-HMO coverage (quintiles), Medicare low-income subsidy (ever, never, unknown), overweight/obesity (ever, never diagnosed), smoking behavior-related diagnoses (ever, never diagnosed), chronic obstructive pulmonary disease (ever, never diagnosed), alcohol-related diagnoses (ever, never diagnosed), type 2 diabetes mellitus (ever, never diagnosed), acute/chronic pancreatitis (ever, never diagnosed).

c

PFDR value was calculated based on Benjamini-Hochberg procedure using an FDR threshold of 0.10. Associations that passed Benjamini-Hochberg correction (FDR = 0.10) were considered statistically significant and shown in bold.

Table 3 shows the results for the eight most significant, PC-associated autoimmune conditions (PFDR value < 0.10) stratified by the PDAC and PNET subtypes. Ankylosing spondylitis (OR = 1.42; 95% CI: 1.12–1.81), Graves’ disease (OR = 1.18; 95% CI: 1.04–1.35), localized scleroderma (OR = 1.24; 95% CI: 1.03–1.48), pernicious anemia (OR = 1.08; 95% CI: 1.02–1.14), primary sclerosing cholangitis (OR = 1.38; 95% CI: 1.19–1.60), pure red cell aplasia (OR = 1.33; 95% CI: 1.18–1.49), type 1 diabetes (OR = 1.11; 95% CI: 1.07–1.15), and ulcerative colitis (OR = 1.16; 95% CI: 1.05–1.29) were significantly associated with PDAC. Only ulcerative colitis was associated with PNETs (OR = 1.78; 95% CI: 1.17–2.70).

Table 3.

Associations between select autoimmune conditions and all primary pancreatic cancers by histological subtypes in the SEER-Medicare database, 1992–2015a

Autoimmune conditions Control Pancreatic ductal adenocarcinomab
 Pancreatic neuroendocrine tumorsc
N = 320,296 N = 76,321 ORd (95% CI) P value N = 2,102 OR (95% CI) P value
Ankylosing spondylitis 260 92 1.42 (1.12–1.81) 0.004 <11 1.88 (0.70–5.08) 0.21
Graves’ disease 1,010 307 1.18 (1.04–1.35) 0.01 <11 1.25 (0.65–2.43) 0.50
Localized scleroderma 522 155 1.24 (1.03–1.48) 0.02 <11 1.90 (0.85–4.28) 0.12
Pernicious anemia 6,112 1,724 1.08 (1.02–1.14) 0.008 45 1.19 (0.89–1.61) 0.25
Primary sclerosing cholangitis 602 271 1.38 (1.19–1.60) 2.8 × 10 −5 <11 0.87 (0.36–2.13) 0.77
Pure red cell aplasia 1,074 396 1.33 (1.18–1.49) 2.9 × 10 −6 <11 0.69 (0.29–1.67) 0.41
Type 1 diabetes 15,932 5,529 1.11 (1.07–1.15) 2.2 × 10 −9 146 1.02 (0.85–1.23) 0.79
Ulcerative colitis 1,585 477 1.16 (1.05–1.29) 0.005 23 1.78 (1.17–2.70) 0.007
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Abbreviation: CI, confidence interval; FDR, false discovery rate; HMO, health maintenance organization; ICD-O, International Classification of Diseases for Oncology; IPMN, intraductal papillary mucinous neoplasm; NOS, not otherwise specified; OR, odds ratio; PDAC, pancreatic ductal adenocarcinoma; PNETs, pancreatic neuroendocrine tumors; SEER, Surveillance, Epidemiology, and End Results.

a

Autoimmune conditions showing the strongest associations with all primary pancreatic cancer cases by the univariate model in Table 2 (PFDR value < 0.10) were presented in this table. Results for pancreatic cancer subtypes other than PDAC or PNETs were not shown due to very small sample size. Cells with < 11 observations and any cell that could be used to derive the value of a cell with < 11 observations were suppressed to comply with SEER-Medicare data use agreement.

b

PDAC group was comprised of the following histological subtypes (ICD-O morphology codes): ductal adenocarcinoma, NOS (8140); ductal adenocarcinoma, excluding cystic/mucinous (8255, 8490, 8500, 8507, 8510, 8514, 8521, 8523, 8560, 8570); ductal, poorly specified (8000, 8010); ductal, specified as arising from an IPMN (8144, 8450, 8453, 8471, 8503); ductal, specified as cystic adenocarcinoma (8440, 8470, 8504); ductal, specified as mucinous adenocarcinoma (8480, 8481); other specified adenocarcinoma (8145, 8460).

c

PNETs group consisted of the following histological subtypes (ICD-O morphology codes): endocrine, carcinoid (8240, 8243, 8244, 8245); endocrine, non-secretory (8150, 8246); endocrine, secretory (8151, 8152, 8153, 8155).

d

Multivariable-adjusted unconditional logistic regression models were used to calculate OR and 95% CI, adjusting for age (grouped as 66–69, 70–74, 75–79, 80–84, 85–89, 90–99 years), sex, race/ethnicity (non-Hispanic White, non-Hispanic Black, Asian, Hispanic, other/unknown), calendar year of diagnosis/selection (1992–2000, 2001–2005, 2006–2009, 2010–2015), geographic region (SEER registry), Medicaid eligibility (ever, never), average number of physician visits per 6 months in the 5 years before diagnosis/selection (quintiles), average duration of Medicare part A, B, non-HMO coverage (quintiles), Medicare low-income subsidy (ever, never, unknown), overweight/obesity (ever, never diagnosed), smoking behavior-related diagnoses (ever, never diagnosed), chronic obstructive pulmonary disease (ever, never diagnosed), alcohol-related diagnoses (ever, never diagnosed), type 2 diabetes mellitus (ever, never diagnosed), acute/chronic pancreatitis (ever, never diagnosed).

NOTE: Associations that passed Benjamini-Hochberg correction (FDR = 0.10) were considered statistically significant and shown in bold.

Discussion

In this largest, most comprehensive study to date, prior diagnoses of ankylosing spondylitis, Graves’ disease, localized scleroderma, pernicious anemia, primary sclerosing cholangitis, pure red cell aplasia, type 1 diabetes, and ulcerative colitis were significantly associated with 8–45% increased risk of primary PC. The associations were in the same direction for first and later primary PC except for pure red cell aplasia, where a positive association was only present with risk of later primary. In analyses stratified by PC histological subtypes, the eight autoimmune conditions were similarly associated with an elevated PDAC risk, whereas only ulcerative colitis was significantly associated with 78% increased PNETs risk.

The positive associations we observe for ankylosing spondylitis, Graves’ disease, and localized scleroderma with overall PC and PDAC, and for ulcerative colitis with PNETs are novel. Studies based on US Veterans Affairs hospital admissions or registry-based cohort studies in Sweden and Taiwan have not observed significant associations for ankylosing spondylitis, Graves’ disease, or localized scleroderma and PC, although these studies included small numbers of PC cases (N = 1–24).10, 27–29 Ankylosing spondylitis has been significantly associated with cancer risk of the ampulla of Vater,14 which connects pancreatic ducts to the small intestine. Methimazole, an antithyroid medication used to treat Graves’ disease, has been shown to increase the risk of acute pancreatitis and might contribute to the association we observe.30 To the best of our knowledge, no previous study has examined the association of ulcerative colitis with PNETs. One population-based study based on the Dutch Pathology Registry reported a higher prevalence of colonic neuroendocrine tumors among inflammatory bowel disease patients compared with the general population.31 Future observational and animal studies are needed to replicate our results and elucidate plausible disease mechanisms.

Previous studies on the association of primary sclerosing cholangitis with PC risk are limited. Two Swedish studies have reported 8 to 14-fold elevated risk for primary sclerosing cholangitis, albeit based on ≤ 20 PC cases.9, 18 The observed association may be partially explained by the misdiagnosis of PC with extrahepatic cholangiocarcinoma,32 a malignancy which is strongly associated with primary sclerosing cholangitis.14 However, this is unlikely a limitation of our study because cancer diagnoses from SEER registries are of the highest data quality33 and our study included a large number of PC cases. Current evidence on the association of ulcerative colitis with PC risk is inconsistent. Scandinavian registry-based studies have observed significant 35–45% elevated PC risk associated with ulcerative colitis diagnosis.7, 8 One case-control study among 1,705 PC cases and 1,084 controls from PanGenEU (European Study into Digestive Illnesses and Genetics) study reported a null association between ulcerative colitis and PC risk,19 however was based on 15 cases and 16 controls reporting ulcerative colitis. A more recent case-control study in the SEER-Medicare population reported a suggestive positive association between ulcerative colitis and first primary PC risk (OR = 1.12; 95% CI: 0.99–1.27).17 In contrast to our study, this earlier SEER-Medicare study did not include later primary PC and did not adjust for overweight/obesity, smoking behavior-related diagnoses, alcohol-related diagnoses, type 2 diabetes mellitus, and acute/chronic pancreatitis. Our findings are also consistent with our earlier investigation using genome-wide association study (GWAS) data which suggested that ulcerative colitis shared genetic architecture with PDAC.20 We did not observe a statistically significant association of genomic regions for primary sclerosing cholangitis (P value = 0.078) with PDAC in our earlier analysis, partly due to few established GWAS loci for primary sclerosing cholangitis.20 Patients with inflammatory bowel diseases, particularly ulcerative colitis, are known to have a higher prevalence of primary sclerosing cholangitis,34 and it is possible that the positive PC associations observed for both autoimmune conditions could be driven by the same underlying mechanism of carcinogenesis.

Diabetes is a known risk factor for PC, most notably type 2 diabetes related to excess adiposity.35, 36 Growing evidence suggests type 1 diabetes may be associated with PC.37, 38 In a meta-analysis based on three cohort and six case-control studies with a total of 39 PC cases, patients diagnosed with type 1 or young-onset diabetes before the age of 40 had a two-fold increased PC risk compared with non-diabetic subjects.37 A population-based registry study from five European countries including 387 PC cases found statistically significant 1.53- and 1.25-fold elevated PC risks among male and female patients with type 1 diabetes, respectively. The associations were attenuated 10 to 15 years after diabetes diagnosis possibly due to reverse causation.38 A limitation of these studies is the potential misclassification of diabetes type because type 1 diabetes was frequently defined as having diabetes at a young age without a specific diagnosis.37, 38 Although we used ICD-9 codes to ascertain type 1 diabetes, diabetes misclassification may still be present in our study.

Findings from previous studies on the association between pernicious anemia and PC are conflicting. Two population-based cohort studies and one case-control study reported null associations between pernicious anemia and PC among hospitalized male US veterans, patients in the Health Improvement Network database of the United Kingdom, and participants of the PanGenEU study.10, 19, 39 Possible explanations for discrepancies in the reported association between our study and these earlier studies include differences in study design and/or population, sample size, and adjusted covariates in regression models. A Swedish population-based hospital discharge cohort40 and an earlier population-based, case-control study in the SEER-Medicare population both found significant positive associations between pernicious anemia diagnosis and PC risk,41 which are consistent with our findings. Pernicious anemia is an autoimmune condition that results from autoantibody-mediated destruction of intrinsic factor-secreting parietal cells, and manifests primarily as vitamin B12 deficiency, achlorhydria and subsequent elevated serum gastrin concentration.42 In vitro studies have shown that gastrin stimulates the proliferation and metastasis of human PC cells.43, 44 Given that our association between pernicious anemia and PC became non-significant when we excluded cases with autoimmune conditions first reported less than five years prior to PC diagnosis, our results might also be explained by reverse causation.

The biological basis for our observed associations is speculative. Most of the autoimmune conditions that we observed significant associations with PC affect the gastrointestinal tract either directly or secondarily. Chronic inflammation and subsequent tissue damage caused by autoimmune conditions, or their therapies may promote tumorigenesis and progression through multiple mechanisms, including DNA damage and oncogenic mutations, angiogenesis, antagonizing anti-tumor immunity, cell growth and survival, and enhanced invasion and metastasis.45 Immunosuppressive treatments for ulcerative colitis and localized scleroderma,46, 47 hyperglycemia and exogenous insulin treatment related to type 1 diabetes,38 and tumor-promoting effect of thyroid hormones for Graves’ disease could also contribute.48 The associations of pure red cell aplasia and aplastic anemia with later primary PC risk might be sequelae of the earlier malignancies or cancer therapies, respectively.49, 50

Strengths of our study includes large numbers of PC cases which allowed for examination of rare autoimmune conditions and PC subtype analyses. SEER-Medicare is representative of the US population aged 65 years and older.21 The PC cases were identified through SEER registries, which employs rigorous standards to ensure accuracy of cancer case ascertainment.33 By using Medicare claims for autoimmune conditions identified more than one year prior to cancer diagnosis instead of self-report, we reduced the likelihood of reverse causation and recall bias.

Our study also has limitations. Since many autoimmune conditions causes symptoms that are associated with pancreatic cancer, surveillance bias could potentially affect the study findings (e.g., fatigue and weight loss caused by Graves’ disease and red cell dysplasia could make physicians monitor pancreatic disorders more closely). However, we attempted to minimize surveillance bias by adjusting for the average number of physician visits per 6 months in the 5 years before cancer diagnosis/control selection and excluding autoimmune conditions diagnosed within 12 months of pancreatic cancer diagnosis. Additionally, we conducted a sensitivity analysis in which only autoimmune conditions diagnosed at least 5 years before pancreatic cancer diagnosis were included. Our findings were robust and mostly remained in all these analyses. Given that our study examined the associations of 45 autoimmune conditions with pancreatic cancer risk, some of the significant findings may be due to chance; however, we controlled for multiple comparisons by employing a false discovery rate of < 0.10. Thus, among the 8 findings (or 4 after excluding cancer cases diagnosed within 5 years of autoimmune condition diagnosis), at most 10% could be false positives. Due to the nature of Medicare claims data, some autoimmune conditions (e.g., primary sclerosing cholangitis)51 and risk factors (e.g., overweight/obesity, smoking and alcohol use) may be under-ascertained, particularly if medical conditions were diagnosed prior to age 66. We applied strict definitions of disease diagnoses (i.e., ≥ one inpatient claim or two physician/outpatient claims) to reduce potential misclassification of autoimmune conditions and would expect under-ascertainment to attenuate associations. We used alcohol- and smoking behavior-related disorders and diseases as proxies for heavy drinker and smokers, and thus some residual confounding may be present. Our study lacks complete information on treatments for autoimmune conditions, which could influence cancer risk.46 Finally, our findings may not be generalizable to younger persons with autoimmune conditions.

In conclusion, results from our large, comprehensive analysis support autoimmune conditions, particularly those that affect gastrointestinal tract either directly or secondarily, are associated with increased PC risk in older US adults. The prevalence of autoimmune conditions is increasing in the US, particularly in older people,52 and could plausibly be contributing to the increasing incidence of PC in addition to other known PC risk factors. Further population and experimental investigations are warranted to confirm our findings and elucidate the mechanisms by which immune dysregulation contributes to pancreatic carcinogenesis.

Supplementary Material

supplementary material

Novelty and Impact.

This large population-based, nested case-control study found that eight autoimmune conditions, ankylosing spondylitis, Graves’ disease, localized scleroderma, pernicious anemia, primary sclerosing cholangitis, pure red cell aplasia, type 1 diabetes, and ulcerative colitis were significantly associated with elevated risks of pancreatic cancer overall and pancreatic ductal adenocarcinoma. Ulcerative colitis was significantly associated with pancreatic neuroendocrine tumors. Our results support the role for autoimmunity and immune dysregulation in the etiology of pancreatic cancer.

Acknowledgments

This study used the linked SEER-Medicare database. The interpretation and reporting of the SEER-Medicare linkage data are the sole responsibility of the authors. The collection of cancer incidence data used in this study was supported by the California Department of Public Health as part of the statewide cancer reporting program mandated by California Health and Safety Code Section 103885; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, contract HHSN261201000035C awarded to the University of Southern California, and contract HHSN261201000034C awarded to the Public Health Institute; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement # U58DP003862–01 awarded to the California Department of Public Health. The ideas and opinions expressed herein are those of the author(s) and endorsement by the State of California Department of Public Health, the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors is not intended nor should be inferred. The authors acknowledge the efforts of the National Cancer Institute; the Office of Research, Development and Information, CMS; Information Management Services (IMS), Inc.; and the Surveillance, Epidemiology, and End Results (SEER) Program tumor registries in the creation of the SEER-Medicare database.

Funding

This work was supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health, Department of Health and Human Services. The funders had no role in the design of the study; the collection, analysis, and interpretation of the data; the writing of the manuscript; and the decision to submit the manuscript for publication.

Abbreviations

CI

confidence interval

COPD

chronic obstructive pulmonary disease

FDR

false discovery rate

GWAS

genome wide association study

HMO

health maintenance organization

ICD

International Classification of Diseases

MedPAR

Medicare Provider Analysis and Review

NCH

National Claims History

OR

odds ratio

PC

pancreatic cancer

PDAC

pancreatic ductal adenocarcinoma

PEDSF

Patient Entitlement Diagnosis Summary File

PNET

pancreatic neuroendocrine tumor

SEER

Surveillance, Epidemiology, and End Results

US

United States

Footnotes

Conflict of Interest

The authors disclose no potential conflict of interest related to this study.

Disclaimer

The content of the article is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

Ethics Statement

Research using the SEER-Medicare data is deemed exempt by the National Institutes of Health Office of Human Subjects Research Protection.

Data Availability Statement

The SEER-Medicare data are available to investigators for research purposes. SEER-Medicare data are maintained by the Division of Cancer Control and Population Sciences at the National Cancer Institute, National Institutes of Health. Qualified researchers can apply to obtain SEER-Medicare data for specific research questions at: https://healthcaredelivery.cancer.gov/seermedicare/obtain/requests.html. Further information is available from the corresponding author upon request.

References

  • 1.Gaddam S, Abboud Y, Oh J, Samaan JS, Nissen NN, Lu SC, Lo SK. Incidence of Pancreatic Cancer by Age and Sex in the US, 2000–2018. JAMA 2021;326: 2075–7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Huang J, Lok V, Ngai CH, Zhang L, Yuan J, Lao XQ, Ng K, Chong C, Zheng ZJ, Wong MCS. Worldwide Burden of, Risk Factors for, and Trends in Pancreatic Cancer. Gastroenterology 2021;160: 744–54. [DOI] [PubMed] [Google Scholar]
  • 3.Ryan DP, Hong TS, Bardeesy N. Pancreatic adenocarcinoma. N Engl J Med 2014;371: 1039–49. [DOI] [PubMed] [Google Scholar]
  • 4.Geurts JL. Inherited syndromes involving pancreatic neuroendocrine tumors. J Gastrointest Oncol 2020;11: 559–66. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Hemminki K, Liu X, Ji J, Sundquist J, Sundquist K. Autoimmune disease and subsequent digestive tract cancer by histology. Ann Oncol 2012;23: 927–33. [DOI] [PubMed] [Google Scholar]
  • 6.Hemminki K, Li X, Sundquist J, Sundquist K. Cancer risks in Crohn disease patients. Ann Oncol 2009;20: 574–80. [DOI] [PubMed] [Google Scholar]
  • 7.Everhov AH, Erichsen R, Sachs MC, Pedersen L, Halfvarson J, Askling J, Ekbom A, Ludvigsson JF, Sorensen HT, Olen O. Inflammatory bowel disease and pancreatic cancer: a Scandinavian register-based cohort study 1969–2017. Aliment Pharmacol Ther 2020;52: 143–54. [DOI] [PubMed] [Google Scholar]
  • 8.Hemminki K, Li X, Sundquist J, Sundquist K. Cancer risks in ulcerative colitis patients. Int J Cancer 2008;123: 1417–21. [DOI] [PubMed] [Google Scholar]
  • 9.Bergquist A, Ekbom A, Olsson R, Kornfeldt D, Loof L, Danielsson A, Hultcrantz R, Lindgren S, Prytz H, Sandberg-Gertzen H, Almer S, Granath F, Broome U. Hepatic and extrahepatic malignancies in primary sclerosing cholangitis. J Hepatol 2002;36: 321–7. [DOI] [PubMed] [Google Scholar]
  • 10.Landgren AM, Landgren O, Gridley G, Dores GM, Linet MS, Morton LM. Autoimmune disease and subsequent risk of developing alimentary tract cancers among 4.5 million US male veterans. Cancer 2011;117: 1163–71. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Askling J, Linet M, Gridley G, Halstensen TS, Ekstrom K, Ekbom A. Cancer incidence in a population-based cohort of individuals hospitalized with celiac disease or dermatitis herpetiformis. Gastroenterology 2002;123: 1428–35. [DOI] [PubMed] [Google Scholar]
  • 12.Ilus T, Kaukinen K, Virta LJ, Pukkala E, Collin P. Incidence of malignancies in diagnosed celiac patients: a population-based estimate. Am J Gastroenterol 2014;109: 1471–7. [DOI] [PubMed] [Google Scholar]
  • 13.Castro FA, Liu X, Forsti A, Ji J, Sundquist J, Sundquist K, Koshiol J, Hemminki K. Increased risk of hepatobiliary cancers after hospitalization for autoimmune disease. Clin Gastroenterol Hepatol 2014;12: 1038–45 e7. [DOI] [PubMed] [Google Scholar]
  • 14.McGee EE, Castro FA, Engels EA, Freedman ND, Pfeiffer RM, Nogueira L, Stolzenberg-Solomon R, McGlynn KA, Hemminki K, Koshiol J. Associations between autoimmune conditions and hepatobiliary cancer risk among elderly US adults. Int J Cancer 2019;144: 707–17. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Westermann R, Zobbe K, Cordtz R, Haugaard JH, Dreyer L. Increased cancer risk in patients with cutaneous lupus erythematosus and systemic lupus erythematosus compared with the general population: A Danish nationwide cohort study. Lupus 2021;30: 752–61. [DOI] [PubMed] [Google Scholar]
  • 16.He MM, Lo CH, Wang K, Polychronidis G, Wang L, Zhong R, Knudsen MD, Fang Z, Song M. Immune-Mediated Diseases Associated With Cancer Risks. JAMA Oncol 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Wang JH, D’Arcy M, Barnes EL, Freedman ND, Engels EA, Song M. Associations of Inflammatory Bowel Disease and Subsequent Cancers in a Population-Based Study of Older Adults in the United States. JNCI Cancer Spectrum 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Lundberg Bave A, Bergquist A, Bottai M, Warnqvist A, von Seth E, Nordenvall C. Increased risk of cancer in patients with primary sclerosing cholangitis. Hepatol Int 2021;15: 1174–82. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Gomez-Rubio P, Pinero J, Molina-Montes E, Gutierrez-Sacristan A, Marquez M, Rava M, Michalski CW, Farre A, Molero X, Lohr M, Perea J, Greenhalf W, O’Rorke M, Tardon A, Gress T, Barbera VM, Crnogorac-Jurcevic T, Munoz-Bellvis L, Dominguez-Munoz E, Balsells J, Costello E, Yu J, Iglesias M, Ilzarbe L, Kleeff J, Kong B, Mora J, Murray L, O’Driscoll D, Poves I, Lawlor RT, Ye W, Hidalgo M, Scarpa A, Sharp L, Carrato A, Real FX, Furlong LI, Malats N, PanGen EUSI. Pancreatic cancer and autoimmune diseases: An association sustained by computational and epidemiological case-control approaches. Int J Cancer 2019;144: 1540–9. [DOI] [PubMed] [Google Scholar]
  • 20.Yuan F, Hung RJ, Walsh N, Zhang H, Platz EA, Wheeler W, Song L, Arslan AA, Beane Freeman LE, Bracci P, Canzian F, Du M, Gallinger S, Giles GG, Goodman PJ, Kooperberg C, Le Marchand L, Neale RE, Rosendahl J, Scelo G, Shu XO, Visvanathan K, White E, Zheng W, Albanes D, Amiano P, Andreotti G, Babic A, Bamlet WR, Berndt SI, Brennan P, Bueno-de-Mesquita B, Buring JE, Campbell PT, Chanock SJ, Fuchs CS, Gaziano JM, Goggins MG, Hackert T, Hartge P, Hassan MM, Holly EA, Hoover RN, Katzke V, Kirsten H, Kurtz RC, Lee IM, Malats N, Milne RL, Murphy N, Ng K, Oberg AL, Porta M, Rabe KG, Real FX, Rothman N, Sesso HD, Silverman DT, Thompson IM, Wactawski-Wende J, Wang X, Wentzensen N, Wilkens LR, Yu H, Zeleniuch-Jacquotte A, Shi J, Duell EJ, Amundadottir LT, Li D, Petersen GM, Wolpin BM, Risch HA, Yu K, Klein AP, Stolzenberg-Solomon R. Genome-Wide Association Study Data Reveal Genetic Susceptibility to Chronic Inflammatory Intestinal Diseases and Pancreatic Ductal Adenocarcinoma Risk. Cancer Res 2020;80: 4004–13. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21.Engels EA, Pfeiffer RM, Ricker W, Wheeler W, Parsons R, Warren JL. Use of surveillance, epidemiology, and end results-medicare data to conduct case-control studies of cancer among the US elderly. Am J Epidemiol 2011;174: 860–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.National Cancer Institute Surveillance Epidemiology and End Results Program. Overview of the SEER Program, vol. 2021. [Google Scholar]
  • 23.National Cancer Institute Division of Cancer Control and Population Sciences. SEER-Medicare: How the SEER & Medicare Data are Linked, vol. 2021. [Google Scholar]
  • 24.Johnson CJ, Hahn CG, Fink AK, German RR. Variability in cancer death certificate accuracy by characteristics of death certifiers. Am J Forensic Med Pathol 2012;33: 137–42. [DOI] [PubMed] [Google Scholar]
  • 25.De Roos AJ, Poole C, Teschke K, Olshan AF. An application of hierarchical regression in the investigation of multiple paternal occupational exposures and neuroblastoma in offspring. Am J Ind Med 2001;39: 477–86. [DOI] [PubMed] [Google Scholar]
  • 26.Benjamini Y, Hochberg Y. Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society Series B (Methodological) 1995;57: 289–300. [Google Scholar]
  • 27.Chan TM, Luo SF, Yu KH, See LC, Huang LH, Kuo CF. Risk of cancer in patients with ankylosing spondylitis: a nationwide cohort study in Taiwan. Scand J Rheumatol 2021;50: 132–8. [DOI] [PubMed] [Google Scholar]
  • 28.Shu X, Ji J, Li X, Sundquist J, Sundquist K, Hemminki K. Cancer risk in patients hospitalised for Graves’ disease: a population-based cohort study in Sweden. Br J Cancer 2010;102: 1397–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Rosenthal AK, McLaughlin JK, Gridley G, Nyren O. Incidence of cancer among patients with systemic sclerosis. Cancer 1995;76: 910–4. [DOI] [PubMed] [Google Scholar]
  • 30.Pecere A, Caputo M, Sarro A, Ucciero A, Zibetti A, Aimaretti G, Marzullo P, Barone-Adesi F. Methimazole Treatment and Risk of Acute Pancreatitis: A Population-based Cohort Study. J Clin Endocrinol Metab 2020;105. [DOI] [PubMed] [Google Scholar]
  • 31.Derikx LA, Vierdag WM, Kievit W, Bosch S, Hoentjen F, Nagtegaal ID. Is the prevalence of colonic neuroendocrine tumors increased in patients with inflammatory bowel disease? Int J Cancer 2016;139: 535–42. [DOI] [PubMed] [Google Scholar]
  • 32.Razumilava N, Gores GJ, Lindor KD. Cancer surveillance in patients with primary sclerosing cholangitis. Hepatology 2011;54: 1842–52. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Duggan MA, Anderson WF, Altekruse S, Penberthy L, Sherman ME. The Surveillance, Epidemiology, and End Results (SEER) Program and Pathology: Toward Strengthening the Critical Relationship. Am J Surg Pathol 2016;40: e94–e102. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Barberio B, Massimi D, Cazzagon N, Zingone F, Ford AC, Savarino EV. Prevalence of Primary Sclerosing Cholangitis in Patients With Inflammatory Bowel Disease: A Systematic Review and Meta-analysis. Gastroenterology 2021;161: 1865–77. [DOI] [PubMed] [Google Scholar]
  • 35.Stolzenberg-Solomon RZ, Graubard BI, Chari S, Limburg P, Taylor PR, Virtamo J, Albanes D. Insulin, glucose, insulin resistance, and pancreatic cancer in male smokers. JAMA 2005;294: 2872–8. [DOI] [PubMed] [Google Scholar]
  • 36.Bosetti C, Rosato V, Li D, Silverman D, Petersen GM, Bracci PM, Neale RE, Muscat J, Anderson K, Gallinger S, Olson SH, Miller AB, Bas Bueno-de-Mesquita H, Scelo G, Janout V, Holcatova I, Lagiou P, Serraino D, Lucenteforte E, Fabianova E, Baghurst PA, Zatonski W, Foretova L, Fontham E, Bamlet WR, Holly EA, Negri E, Hassan M, Prizment A, Cotterchio M, Cleary S, Kurtz RC, Maisonneuve P, Trichopoulos D, Polesel J, Duell EJ, Boffetta P, La Vecchia C, Ghadirian P. Diabetes, antidiabetic medications, and pancreatic cancer risk: an analysis from the International Pancreatic Cancer Case-Control Consortium. Ann Oncol 2014;25: 2065–72. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Stevens RJ, Roddam AW, Beral V. Pancreatic cancer in type 1 and young-onset diabetes: systematic review and meta-analysis. Br J Cancer 2007;96: 507–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Carstensen B, Read SH, Friis S, Sund R, Keskimaki I, Svensson AM, Ljung R, Wild SH, Kerssens JJ, Harding JL, Magliano DJ, Gudbjornsdottir S, Diabetes, Cancer Research C. Cancer incidence in persons with type 1 diabetes: a five-country study of 9,000 cancers in type 1 diabetic individuals. Diabetologia 2016;59: 980–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Shah P, Rhim AD, Haynes K, Hwang WT, Yang YX. Diagnosis of pernicious anemia and the risk of pancreatic cancer. Pancreas 2014;43: 422–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Hsing AW, Hansson LE, McLaughlin JK, Nyren O, Blot WJ, Ekbom A, Fraumeni JF, Jr. Pernicious anemia and subsequent cancer. A population-based cohort study. Cancer 1993;71: 745–50. [DOI] [PubMed] [Google Scholar]
  • 41.Murphy G, Dawsey SM, Engels EA, Ricker W, Parsons R, Etemadi A, Lin SW, Abnet CC, Freedman ND. Cancer Risk After Pernicious Anemia in the US Elderly Population. Clin Gastroenterol Hepatol 2015;13: 2282–9 e1–4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Toh BH, van Driel IR, Gleeson PA. Pernicious anemia. N Engl J Med 1997;337: 1441–8. [DOI] [PubMed] [Google Scholar]
  • 43.Smith JP, Fantaskey AP, Liu G, Zagon IS. Identification of gastrin as a growth peptide in human pancreatic cancer. Am J Physiol 1995;268: R135–41. [DOI] [PubMed] [Google Scholar]
  • 44.Mu G, Ding Q, Li H, Zhang L, Zhang L, He K, Wu L, Deng Y, Yang D, Wu L, Xu M, Zhou J, Yu H. Gastrin stimulates pancreatic cancer cell directional migration by activating the Galpha12/13-RhoA-ROCK signaling pathway. Exp Mol Med 2018;50: 1–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 45.Greten FR, Grivennikov SI. Inflammation and Cancer: Triggers, Mechanisms, and Consequences. Immunity 2019;51: 27–41. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Beyaert R, Beaugerie L, Van Assche G, Brochez L, Renauld JC, Viguier M, Cocquyt V, Jerusalem G, Machiels JP, Prenen H, Masson P, Louis E, De Keyser F. Cancer risk in immune-mediated inflammatory diseases (IMID). Mol Cancer 2013;12: 98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47.Shah AA, Casciola-Rosen L. Cancer and scleroderma: a paraneoplastic disease with implications for malignancy screening. Curr Opin Rheumatol 2015;27: 563–70. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Moeller LC, Fuhrer D. Thyroid hormone, thyroid hormone receptors, and cancer: a clinical perspective. Endocr Relat Cancer 2013;20: R19–29. [DOI] [PubMed] [Google Scholar]
  • 49.Sawada K, Fujishima N, Hirokawa M. Acquired pure red cell aplasia: updated review of treatment. Br J Haematol 2008;142: 505–14. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Young NS. Autoimmunity and its treatment in aplastic anemia. Ann Intern Med 1997;126: 166–8. [DOI] [PubMed] [Google Scholar]
  • 51.Molodecky NA, Myers RP, Barkema HW, Quan H, Kaplan GG. Validity of administrative data for the diagnosis of primary sclerosing cholangitis: a population-based study. Liver Int 2011;31: 712–20. [DOI] [PubMed] [Google Scholar]
  • 52.Dinse GE, Parks CG, Weinberg CR, Co CA, Wilkerson J, Zeldin DC, Chan EKL, Miller FW. Increasing Prevalence of Antinuclear Antibodies in the United States. Arthritis Rheumatol 2020;72: 1026–35. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

supplementary material
NIHMS1997814-supplement-supplementary_material.docx (129.7KB, docx)

Data Availability Statement

The SEER-Medicare data are available to investigators for research purposes. SEER-Medicare data are maintained by the Division of Cancer Control and Population Sciences at the National Cancer Institute, National Institutes of Health. Qualified researchers can apply to obtain SEER-Medicare data for specific research questions at: https://healthcaredelivery.cancer.gov/seermedicare/obtain/requests.html. Further information is available from the corresponding author upon request.

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