Abstract
Background: Persons with Barrett's esophagus experience increased risk of esophageal adenocarcinoma. Prediagnostic inflammation markers predict several cancers, but their role in predicting esophageal adenocarcinoma is unknown.
Methods: We investigated whether biomarkers of inflammation [C-reactive protein (CRP), interleukin-6 (IL6), soluble tumor necrosis factor (sTNF) receptors I and II], and of oxidative stress (F2-isoprostanes) predicted progression to esophageal adenocarcinoma in a prospective cohort of 397 patients with Barrett's esophagus, 45 of whom developed esophageal adenocarcinoma. Biomarkers were measured in stored plasma samples from two time points during follow-up, the mean of which served as the primary predictor. Adjusted hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression.
Results: CRP level above the median was associated with an 80% increased risk of esophageal adenocarcinoma. The HR and 95% CI adjusted for age, gender, and further adjusted for waist–hip ratio and smoking were 1.98 (1.05–3.73) and 1.77 (0.93–3.37), respectively, with Ptrend for continuous CRP = 0.04. Persons with IL6 levels above the median also had almost 2-fold increased risk [HR and 95% CI adjusted for age and gender, and further adjusted for waist–hip ratio and smoking were 1.95 (1.03–3.72) and 1.79 (0.93–3.43), respectively, but no evidence of a trend was observed]. Concentrations of TNF receptors and F2-isoprostanes were not associated with esophageal adenocarcinoma risk.
Conclusions: Further research is needed to evaluate the role of inflammation and associated markers in esophageal adenocarcinoma development in persons with Barrett's esophagus.
Impact: This prospective study suggests that inflammation markers, particularly CRP and IL6, may help identify persons at higher risk of progression to esophageal adenocarcinoma. Cancer Epidemiol Biomarkers Prev; 23(11); 2393–403. ©2014 AACR.
Introduction
Chronic inflammation has been hypothesized to play an important role in the pathogenesis of cancers of the lung, colon, and other organs (1–5). Similarly, oxidative stress has been implicated in cancers of the lung (6), breast (7), and prostate (8). Inflammation may contribute to cancer development through multiple mechanisms, including DNA damage, angiogenesis, promotion of cellular proliferation, and inhibition of apoptosis (1). Inflammatory processes also lead to generation of reactive oxygen species (ROS), which may cause inactivating mutations in tumor-suppressor genes or posttranslational modifications in DNA repair proteins, thus promoting carcinogenesis (1, 5).
In the gastrointestinal tract, several chronic inflammatory conditions have been associated with cancer: inflammatory bowel disease with colorectal cancer (9), hepatitis B and C with liver cancer (10), and chronic Helicobacter pylori gastritis with gastric cancer (11). Similarly, inflammatory conditions of the esophagus, namely reflux esophagitis and Barrett's esophagus, are implicated in the development of esophageal adenocarcinoma, with Barrett's esophagus widely considered to be a premalignant lesion for esophageal adenocarcinoma (12–14). The inflammatory link with esophageal adenocarcinoma is further strengthened by the observation that regular use of nonsteroidal anti-inflammatory drugs (NSAID) and aspirin is associated with decreased risk (15–17).
The incidence of esophageal adenocarcinoma has increased dramatically over the past four decades (18). Although the relative risk of esophageal adenocarcinoma is at least 30-times higher in individuals with Barrett's esophagus compared with those without (19), absolute risk of progression is relatively low (0.12%–0.6% per year; refs. 20–22), and it is not yet clear which persons with Barrett's esophagus are most likely to develop esophageal adenocarcinoma, or whether lifestyle modifications might help prevent esophageal adenocarcinoma within this higher-risk population. Previous studies identified obesity, cigarette smoking, gastroesophageal reflux, and diet as potential modifiable risk factors for esophageal adenocarcinoma (14, 23). However, the roles of inflammation and oxidative stress as potentially modifiable risk factors or predictors for esophageal adenocarcinoma have not been studied directly. In this report, we assess the association between markers of systemic inflammation and oxidative stress and the subsequent risk of esophageal adenocarcinoma in a well-characterized Barrett's esophagus cohort followed for up to 14.5 years.
Materials and Methods
Study population, follow-up, and cancer ascertainment
The Seattle Barrett's Esophagus Study (SBES), is a prospective cohort study aimed at understanding the risk factors and mechanisms underlying neoplastic progression to esophageal adenocarcinoma among persons with Barrett's esophagus. The SBES cohort is one of the largest and longest-running well-characterized cohorts of persons with Barrett's esophagus in the world. Details of the cohort have been described previously (23, 24). The study involves periodic endoscopic surveillance for all participants, with multiple biopsies of the Barrett's segment. The current report includes the 427 SBES participants with Barrett's esophagus and no history of esophageal cancer enrolled between February 1995 and September 2009, of whom 411 (96.3%) had at least one follow-up visit. At their baseline visit, participants underwent an extensive personal interview, anthropometric assessment, endoscopy with biopsy, and blood draw. At subsequent follow-up visits, baseline information was updated, additional blood was collected, and a repeat endoscopy with biopsies was performed (12, 13, 25). Specimens were fixed, processed, and interpreted by a single pathologist blinded to the participants' exposure status (12). Individuals were classified as having Barrett's esophagus, low-grade dysplasia, high-grade dysplasia, or esophageal adenocarcinoma based on their most severe histologic diagnosis. Participants with high-grade dysplasia at their initial endoscopy (80 of 411 participants; 19.46%) were endoscoped twice more within 5 months to detect any occult cancers missed at baseline. Of the 411 SBES participants eligible for analyses, 14 individuals had less than 5 months of follow-up and 11 of these developed cancer. Because of an a priori concern that cancers diagnosed during this early period of intensive search for occult malignancies may have been present at baseline, these 14 individuals were excluded from the primary statistical analyses. Esophageal adenocarcinoma was defined as invasion of neoplastic epithelium beyond the basement membrane of the esophageal mucosa into the surrounding lamina propria, muscularis mucosa, or submucosa (12). This study was approved by the Institutional Review Boards at the University of Washington and Fred Hutchinson Cancer Research Center.
Inflammation marker measurements
Fasting blood samples were collected, processed (most within 2 hours after collection), and stored at −80°C until analysis. Potential inflammation markers were identified from the literature, and selected for use in this study based on the sensitivity and accuracy of available assays, giving consideration to their cost. Plasma levels of C-reactive protein (CRP), IL6, and soluble tumor necrosis factor (sTNF) receptors were measured using samples from the first two available time points (baseline and first follow-up for most participants, mean duration between two samples, 1.8 years). F2-isoprostanes were measured at a single time point (earliest available, baseline for most). Intra- and interbatch coefficients of variation (CV) were calculated using blinded pooled plasma samples included as quality controls within each batch. Intraclass correlation coefficients (ICC) and 95% confidence intervals (CI) were calculated using the two cytokine measurements per participant, as described previously (26).
Briefly, CRP concentrations were measured in never-thawed plasma samples with a high-sensitivity assay using immunonephelometry [Dade Behring Inc; Interbatch CV; 2.9%; ICC (95% CI), 54.9% (47.4–62.5)]. The assay detectable limit was 0.2 mg/L; a value of 0.1 mg/L was assigned to all participants with CRP concentrations below the detection limit (<1% samples). IL6 was assayed in never-thawed plasma samples using the Quantikine HS human IL6 Elisa kit [R&D Systems Inc; HS600B; interbatch CV, 4.4%; intrabatch CV, 4.1%; ICC (95% CI), 56.4% (49.4–63.4)]. Samples were run in duplicate with a median duplicate CV of 2.7%; samples with CVs greater than 12% were rerun and the repeat measurements were used for analysis. sTNFR-I and sTNFR-II were measured on previously thawed and refrozen plasma samples using the MILLIPLEX MAP Human Soluble Cytokine Receptor Panel [Millipore; HSCR-32K; sTNFR-I: interbatch CV, 8.9%; intrabatch CV, 5.9%; ICC (95% CI), 89.2% (87.2–91.3); sTNFR-II: interbatch CV, 6.1%; intrabatch CV, 2.4%, ICC (95% CI), 84.9% (82.1–87.8)]. Samples were run in duplicate with a median duplicate CV of 4.1% and 3.4% for sTNFRI and sTNFRII, respectively. F2-isoprostanes were estimated in never-thawed plasma samples using gas chromatography/negative ion chemical ionization mass spectrometry (GC/NICI-MS) as described previously (6890N Agilent gas chromatograph, 5973 quadruple mass spectrometer; refs. 27, 28). This assay had a precision of ±3%, accuracy of 97%, and a detection limit of 20 pg/mL.
Other covariates
Detailed information on medical, family, and medication histories, as well as on lifestyle exposures such as tobacco use, were collected in a personal interview conducted by trained staff. Anthropometric measurements, including height, weight, and waist, hip, thigh, and abdominal circumferences, were determined using an established protocol (23) and were used to calculate waist–hip ratio (WHR) and body mass index [BMI; weight (kg)/height (m)2], which was categorized as normal (<25 kg/m2), overweight (≥25 and <30 kg/m2), and obese (≥30 kg/m2). Cumulative pack-years of smoking were computed using the number of packs smoked per day and the number of years smoked.
Statistical analysis
We estimated the associations between markers of inflammation and oxidative stress and the risk of esophageal adenocarcinoma by calculating hazard ratios (HR) and 95% CIs using separate Cox models for each biomarker. As we dropped individuals with less than 5 months of follow-up from our primary statistical analyses, time at risk to development of esophageal adenocarcinoma began 5 months postbaseline for all participants. For participants with inflammation marker measurements available at two time points during the follow-up, the mean of the two measures was used as the primary predictor; otherwise, the lone measure was used. If the outcome occurred during the same visit as a biomarker measurement, only the first measurement was used for risk prediction. A priori, we decided to exclude CRP values more than 10 mg/L from analyses due to the possibility that such elevated concentrations may be the result of acute rather than chronic inflammation (29, 30). Eight participants had both their CRP measures more than 10 mg/L and, hence, were dropped from all CRP-related analyses. Biomarker concentrations were tested for associations with esophageal adenocarcinoma risk using three models: unadjusted; age- and gender-adjusted; and adjusted for obesity, smoking, and NSAID use in addition to age and gender. These specific confounders were selected on the basis of the previously established risk factors of esophageal adenocarcinoma (increasing age, male gender, smoking, higher WHR, and use of NSAIDs; refs. 14, 23) determined a priori, and their correlations with the biomarkers, based on Pearson correlation coefficients. Although it is more conventional to adjust for the effects of obesity by adjusting for BMI, we chose to adjust for WHR (a measure of central adiposity) in the current analyses as there is good evidence that WHR is more strongly associated with Barrett's esophagus as compared with BMI (31). Analyses were conducted on quartiles of the various biomarkers, as well as by median level. Analyses were repeated restricted to males (number of females was too small for meaningful results). Tests for trend were based on the likelihood-ratio test associated with addition of the biomarker being evaluated in its continuous form. A two-sided P value less than 0.05 was considered statistically significant. The assumption of proportional hazards over time was tested. All analyses were performed using STATA statistical package, release 12 (StataCorp).
Results
Participant characteristics for the 411 individuals eligible for current analyses are presented in Table 1. The majority of the cohort was Caucasian (96.6%) and male (81.3%), with a mean age of 61.2 years. More than 39% of the participants were obese, 64% were current or former smokers, 81.5% reported regular alcohol use in their lifetime, and 60.6% had regularly taken NSAIDs at some point in their life. The mean WHR for the entire cohort was 0.95 (males, 0.96; females, 0.87).
Variable . | All participants (n = 411) . | Males (n = 334) . | Females (n = 77) . |
---|---|---|---|
. | N [% or median (IQR)] . | N [% or median (IQR)] . | N [% or median (IQR)] . |
Agea, y | |||
30–44.9 | 30 (7.3) | 25 (7.5) | 5 (6.5) |
45–54.9 | 97 (23.6) | 83 (24.9) | 14 (18.2) |
55–64.9 | 110 (26.8) | 84 (25.2) | 26 (33.8) |
65–74.9 | 114 (27.7) | 93 (27.8) | 21 (27.3) |
≥75 | 60 (14.6) | 49 (14.7) | 11 (14.3) |
Racea | |||
White | 397 (96.6) | 324 (97.0) | 73 (94.8) |
Non-White | 14 (3.4) | 10 (3.0) | 4 (5.2) |
BMIa (kg/m2) | |||
≤25 | 56 (13.6) | 41 (12.3) | 15 (19.5) |
25.1–≤30 | 194 (47.2) | 167 (50.0) | 27 (35.1) |
30.1–≤35 | 125 (30.4) | 102 (30.5) | 23 (29.9) |
>35 | 36 (8.8) | 24 (7.2) | 12 (15.6) |
Cigarette smokinga,c | |||
Current | 40 (9.7) | 28 (8.4) | 12 (15.6) |
Former | 223 (54.3) | 192 (57.5) | 31 (40.3) |
Never | 148 (36.0) | 114 (34.1) | 34 (44.1) |
NSAID usea,d | |||
Current | 169 (41.1) | 145 (43.4) | 24 (31.2) |
Former | 79 (19.2) | 58 (17.4) | 21 (27.3) |
Never | 162 (39.4) | 130 (38.9) | 32 (41.6) |
WHRb,e | 409 [0.95 (0.91–0.99)] | 332 [0.96 (0.93–1.00)] | 77 [0.87 (0.81–0.91)] |
Variable . | All participants (n = 411) . | Males (n = 334) . | Females (n = 77) . |
---|---|---|---|
. | N [% or median (IQR)] . | N [% or median (IQR)] . | N [% or median (IQR)] . |
Agea, y | |||
30–44.9 | 30 (7.3) | 25 (7.5) | 5 (6.5) |
45–54.9 | 97 (23.6) | 83 (24.9) | 14 (18.2) |
55–64.9 | 110 (26.8) | 84 (25.2) | 26 (33.8) |
65–74.9 | 114 (27.7) | 93 (27.8) | 21 (27.3) |
≥75 | 60 (14.6) | 49 (14.7) | 11 (14.3) |
Racea | |||
White | 397 (96.6) | 324 (97.0) | 73 (94.8) |
Non-White | 14 (3.4) | 10 (3.0) | 4 (5.2) |
BMIa (kg/m2) | |||
≤25 | 56 (13.6) | 41 (12.3) | 15 (19.5) |
25.1–≤30 | 194 (47.2) | 167 (50.0) | 27 (35.1) |
30.1–≤35 | 125 (30.4) | 102 (30.5) | 23 (29.9) |
>35 | 36 (8.8) | 24 (7.2) | 12 (15.6) |
Cigarette smokinga,c | |||
Current | 40 (9.7) | 28 (8.4) | 12 (15.6) |
Former | 223 (54.3) | 192 (57.5) | 31 (40.3) |
Never | 148 (36.0) | 114 (34.1) | 34 (44.1) |
NSAID usea,d | |||
Current | 169 (41.1) | 145 (43.4) | 24 (31.2) |
Former | 79 (19.2) | 58 (17.4) | 21 (27.3) |
Never | 162 (39.4) | 130 (38.9) | 32 (41.6) |
WHRb,e | 409 [0.95 (0.91–0.99)] | 332 [0.96 (0.93–1.00)] | 77 [0.87 (0.81–0.91)] |
aFrequency (%) of categorical variables.
bMedian (interquartile range) for continuous variables.
cCigarette smoking was based on whether participants smoked one cigarette/day for 6 months or longer, currently, in the past, or never.
dNSAID use was defined as having taken NSAID at least once a week for 6 months or longer; NSAID use history for 1 male participant was missing.
eTwo male participants had missing information on WHR.
The medians and interquartile ranges for the various biomarkers overall and by gender are presented in Table 2 (distributions by gender were based on sex-specific quartiles). Overall, the distributions of the various biomarkers evaluated in this study are comparable with other studies of older populations and obese individuals (32–34).
. | All participants (n = 411) . | Males (n = 334) . | Females (n = 77) . | ||||||
---|---|---|---|---|---|---|---|---|---|
. | N . | Median . | IQR . | N . | Median . | IQR . | N . | Median . | IQR . |
CRPa (mg/L) | 398 | 1.90 | 0.95–3.60 | 329 | 1.80 | 0.90–3.35 | 69 | 2.95 | 1.7–4.35 |
IL6b (pg/mL) | 407 | 1.88 | 1.34–3.06 | 332 | 1.77 | 1.31–2.87 | 75 | 2.62 | 1.48–3.79 |
sTNF-receptor Ib (ng/mL) | 407 | 1.39 | 1.14–1.65 | 332 | 1.42 | 1.15–1.66 | 75 | 1.31 | 1.08–1.61 |
sTNF-receptor IIb (ng/mL) | 407 | 5.35 | 4.71–6.44 | 332 | 5.34 | 4.68–6.40 | 75 | 5.49 | 4.74–6.62 |
Isoprostanesc (pg/mL) | 390 | 53 | 41–74 | 320 | 51 | 40–66 | 70 | 74 | 47–107 |
. | All participants (n = 411) . | Males (n = 334) . | Females (n = 77) . | ||||||
---|---|---|---|---|---|---|---|---|---|
. | N . | Median . | IQR . | N . | Median . | IQR . | N . | Median . | IQR . |
CRPa (mg/L) | 398 | 1.90 | 0.95–3.60 | 329 | 1.80 | 0.90–3.35 | 69 | 2.95 | 1.7–4.35 |
IL6b (pg/mL) | 407 | 1.88 | 1.34–3.06 | 332 | 1.77 | 1.31–2.87 | 75 | 2.62 | 1.48–3.79 |
sTNF-receptor Ib (ng/mL) | 407 | 1.39 | 1.14–1.65 | 332 | 1.42 | 1.15–1.66 | 75 | 1.31 | 1.08–1.61 |
sTNF-receptor IIb (ng/mL) | 407 | 5.35 | 4.71–6.44 | 332 | 5.34 | 4.68–6.40 | 75 | 5.49 | 4.74–6.62 |
Isoprostanesc (pg/mL) | 390 | 53 | 41–74 | 320 | 51 | 40–66 | 70 | 74 | 47–107 |
Abbreviation: N, number/frequency.
aCRP was not measured in 4 people due to exhausted baseline plasma. CRP levels more than 10 mg/L were excluded as per an a priori hypothesis. Four people had plasma measured only at one time point and it was greater than 10 mg/L; 5 people had both CRP measurements greater than 10 mg/L.
bIL6 and TNF receptors were not measured in 4 people due to exhausted baseline plasma samples.
cIsoprostanes were not measured in 16 people due to exhausted baseline plasma samples; 5 samples were not successfully measured by the laboratory.
The Pearson correlation coefficients between the biomarkers and risk factors for esophageal adenocarcinoma are shown in Table 3. The correlations between the biomarkers themselves were small to moderate (0.12–0.63), and were statistically significant (except IL6 and F2-isoprostanes). Therefore, these biomarkers were evaluated in separate models with respect to their esophageal adenocarcinoma risk. Most of the biomarkers were significantly correlated with age, WHR, and cigarette pack-years, suggesting that these factors might confound the biomarker–esophageal adenocarcinoma associations.
. | CRP . | IL6 . | sTNF-RI . | sTNF-RII . | Isoprostanes . |
---|---|---|---|---|---|
Agea | 0.08 | 0.18d | 0.37d | 0.43d | −0.03 |
WHRa | 0.10d | 0.08 | 0.13d | 0.08 | −0.12d |
Cigarette pack-yearsb | 0.24d | 0.22d | 0.22d | 0.12d | 0.07 |
NSAID usec | −0.15 | 0.21 | 0.01 | 0.04 | −0.06 |
CRPa | — | 0.44d | 0.18d | 0.20d | 0.22d |
IL6a | — | — | 0.21d | 0.26d | 0.08 |
sTNF-RIa | — | — | — | 0.63d | 0.12d |
sTNF-RIIa | — | — | — | — | 0.14d |
Isoprostanesa | — | — | — | — | — |
. | CRP . | IL6 . | sTNF-RI . | sTNF-RII . | Isoprostanes . |
---|---|---|---|---|---|
Agea | 0.08 | 0.18d | 0.37d | 0.43d | −0.03 |
WHRa | 0.10d | 0.08 | 0.13d | 0.08 | −0.12d |
Cigarette pack-yearsb | 0.24d | 0.22d | 0.22d | 0.12d | 0.07 |
NSAID usec | −0.15 | 0.21 | 0.01 | 0.04 | −0.06 |
CRPa | — | 0.44d | 0.18d | 0.20d | 0.22d |
IL6a | — | — | 0.21d | 0.26d | 0.08 |
sTNF-RIa | — | — | — | 0.63d | 0.12d |
sTNF-RIIa | — | — | — | — | 0.14d |
Isoprostanesa | — | — | — | — | — |
NOTE: NSAIDs are coded as noncurrent vs. current. Non-smokers are coded as have smoked zero pack-years.
aPearson correlation coefficient.
bSpearman correlation coefficient.
cDifference in biomarker (β coefficient) between current users and noncurrent users of NSAIDs.
dP < 0.05.
Table 4 presents the HRs and 95% CIs for developing esophageal adenocarcinoma according to biomarker levels among the 397 participants in the primary analysis. They were followed for a median of 6.14 years (31,677 person-months), and 45 developed cancer. Plasma samples were not available for 3 individuals. For analyses involving CRP, we omitted 8 participants for whom all available CRP values were more than 10 mg/L (2 out of these 8 developed esophageal adenocarcinoma; total 43 cancers in analyses based on CRP). Ultimately, analyses were conducted on 394 participants for IL6 and sTNF receptors, 386 participants for CRP, and 377 participants for F2-isoprostanes.
Biomarker . | EA cases/total . | Unadjusted HR (95% CI) . | Adjusted for agea and gender HR (95% CI) . | Adjusted for agea, gender, WHRb, smokingc, and NSAID used HR (95% CI) . |
---|---|---|---|---|
CRP (mg/L)e | ||||
All participants | ||||
Median | ||||
Below | 15/192 | REF | REF | REF |
Above | 28/194 | 1.83 (0.98–3.43) | 1.98 (1.05–3.73) | 1.77 (0.93–3.37) |
Quartiles | ||||
Q1 (0.1–) | 6/95 | REF | REF | REF |
Q2 (0.9–) | 9/97 | 1.29 (0.46–3.63) | 1.18 (0.42–3.32) | 1.05 (0.37–2.99) |
Q3 (1.9–) | 15/95 | 2.35 (0.91–6.06) | 2.29 (0.89–5.92) | 2.12 (0.81–5.56) |
Q4 (3.6–) | 13/99 | 1.90 (0.72–5.01) | 2.06 (0.78–5.44) | 1.55 (0.56–4.24) |
Continuous Ptrendf | 0.03 | 0.01 | 0.04 | |
Males | ||||
Median | ||||
Below | 12/155 | REF | REF | REF |
Above | 28/165 | 2.31 (1.18–4.55) | 2.21 (1.12–4.36) | 1.93 (0.96–3.89) |
Quartiles | ||||
Q1 (0.1–) | 5/79 | REF | REF | REF |
Q2 (0.9–) | 7/76 | 1.20 (0.38–3.77) | 1.20 (0.38–3.79) | 1.09 (0.34–3.49) |
Q3 (1.8–) | 15/84 | 2.74 (0.99–7.55) | 2.55 (0.92–7.02) | 2.33 (0.83–6.51) |
Q4 (3.4–) | 13/81 | 2.37 (0.85–6.66) | 2.36 (0.84–6.62) | 1.76 (0.60–5.15) |
Continuous Ptrendf | 0.01 | 0.01 | 0.05 | |
IL6 (pg/mL) | ||||
All participants | ||||
Median | ||||
Below | 15/197 | REF | REF | REF |
Above | 30/197 | 2.06 (1.11–3.82) | 1.95 (1.03–3.72) | 1.79 (0.93–3.43) |
Quartiles | ||||
Q1 (0.4–) | 7/98 | REF | REF | REF |
Q2 (1.3–) | 8/99 | 1.14 (0.41–3.15) | 0.95 (0.34–2.66) | 0.82 (0.29–2.34) |
Q3 (1.9–) | 19/99 | 2.74 (1.15–6.52) | 2.35 (0.96–5.77) | 1.93 (0.78–4.79) |
Q4 (3.1–) | 11/98 | 1.65 (0.64–4.24) | 1.40 (0.52–3.78) | 1.17 (0.42–3.26) |
Continuous Ptrendf | 0.64 | 0.94 | 0.87 | |
Males | ||||
Median | ||||
Below | 10/161 | REF | REF | REF |
Above | 31/161 | 3.19 (1.57–6.52) | 2.85 (1.38–5.92) | 2.52 (1.19–5.33) |
Quartiles | ||||
Q1 (0.4–) | 6/81 | REF | REF | REF |
Q2 (1.3–) | 4/80 | 0.67 (0.19–2.36) | 0.56 (0.16–2.01) | 0.53 (0.15–1.89) |
Q3 (1.8–) | 18/80 | 3.06 (1.21–7.71) | 2.51 (0.96–6.51) | 2.04 (0.77–5.41) |
Q4 (2.9–) | 13/81 | 2.25 (0.86–5.93) | 1.77 (0.64–4.86) | 1.56 (0.55–4.43) |
Continuous Ptrendf | 0.66 | 0.99 | 0.81 | |
sTNF-I (ng/mL) | ||||
All participants | ||||
Median | ||||
Below | 18/197 | REF | REF | REF |
Above | 27/197 | 1.62 (0.89–2.93) | 1.29 (0.69–2.42) | 0.99 (0.51–1.92) |
Quartiles | ||||
Q1 (0.3–) | 11/98 | REF | REF | REF |
Q2 (1.1–) | 7/99 | 0.64 (0.25–1.64) | 0.56 (0.22–1.45) | 0.60 (0.23–1.56) |
Q3 (1.4–) | 13/98 | 1.24 (0.55–2.76) | 0.94 (0.41–2.15) | 0.87 (0.38–1.98) |
Q4 (1.7–) | 14/99 | 1.41 (0.64–3.10) | 1.02 (0.44–2.37) | 0.68 (0.27–1.68) |
Continuous Ptrendf | 0.18 | 0.68 | 0.69 | |
Males | ||||
Median | ||||
Below | 17/161 | REF | REF | REF |
Above | 24/161 | 1.56 (0.84–2.90) | 1.23 (0.63–2.41) | 0.95 (0.47–1.94) |
Quartiles | ||||
Q1 (0.3–) | 11/80 | REF | REF | REF |
Q2 (1.1–) | 6/81 | 0.51 (0.19–1.37) | 0.47 (0.17–1.26) | 0.51 (0.19–1.38) |
Q3 (1.4–) | 12/80 | 1.10 (0.48–2.49) | 0.85 (0.36–2.00) | 0.73 (0.31–1.74) |
Q4 (1.7–) | 12/81 | 1.23 (0.54–2.80) | 0.88 (0.36–2.14) | 0.66 (0.26–1.71) |
Continuous Ptrendf | 0.30 | 0.83 | 0.57 | |
sTNF-II (ng/mL) | ||||
All participants | ||||
Median | ||||
Below | 15/197 | REF | REF | REF |
Above | 30/197 | 2.23 (1.20–4.15) | 1.90 (0.98–3.67) | 1.78 (0.90–3.52) |
Quartiles | ||||
Q1 (1.6–) | 8/98 | REF | REF | REF |
Q2 (4.7–) | 7/99 | 0.83 (0.30–2.29) | 0.78 (0.28–2.17) | 0.81 (0.29–2.25) |
Q3 (5.4–) | 13/98 | 1.68 (0.70–4.05) | 1.46 (0.59–3.61) | 1.47 (0.59–3.70) |
Q4 (6.4–) | 17/99 | 2.44 (1.05–5.66) | 1.95 (0.76–4.95) | 1.75 (0.68–4.49) |
Continuous Ptrendf | 0.22 | 0.75 | 0.86 | |
Males | ||||
Median | ||||
Below | 14/161 | REF | REF | REF |
Above | 27/161 | 2.18 (1.14–4.16) | 1.81 (0.91–3.62) | 1.63 (0.80–3.34) |
Quartiles | ||||
Q1 (1.6–) | 8/80 | REF | REF | REF |
Q2 (4.7–) | 6/81 | 0.69 (0.24–1.98) | 0.62 (0.21–1.80) | 0.69 (0.24–2.00) |
Q3 (5.3–) | 12/80 | 1.52 (0.62–3.72) | 1.27 (0.50–3.23) | 1.28 (0.50–3.30) |
Q4 (6.4–) | 15/81 | 2.17 (0.92–5.14) | 1.59 (0.60–4.19) | 1.44 (0.54–3.83) |
Continuous Ptrendf | 0.20 | 0.78 | 0.78 | |
Isoprostanes (pg/mL) | ||||
All participants | ||||
Median | ||||
Below | 27/186 | REF | REF | REF |
Above | 18/191 | 0.60 (0.33–1.09) | 0.69 (0.38–1.26) | 0.56 (0.30–1.03) |
Quartiles | ||||
Q1 (14–) | 13/90 | REF | REF | REF |
Q2 (41–) | 14/96 | 0.98 (0.46–2.09) | 1.18 (0.55–2.53) | 0.93 (0.43–2.02) |
Q3 (53–) | 10/98 | 0.68 (0.30–1.54) | 0.76 (0.33–1.74) | 0.61 (0.26–1.41) |
Q4 (74–) | 8/93 | 0.52 (0.22–1.26) | 0.74 (0.30–1.85) | 0.46 (0.18–1.20) |
Continuous Ptrendf | 0.34 | 0.92 | 0.41 | |
Males | ||||
Median | ||||
Below | 23/143 | REF | REF | REF |
Above | 18/157 | 0.74 (0.40–1.36) | 0.79 (0.42–1.46) | 0.64 (0.34–1.20) |
Quartiles | ||||
Q1 (14–) | 11/74 | REF | REF | REF |
Q2 (40–) | 12/79 | 1.03 (0.45–2.33) | 1.18 (0.52–2.69) | 0.98 (0.43–2.27) |
Q3 (51–) | 11/80 | 0.96 (0.42–2.21) | 1.04 (0.45–2.41) | 0.80 (0.34–1.88) |
Q4 (66–) | 7/77 | 0.55 (0.21–1.43) | 0.66 (0.25–1.72) | 0.47 (0.18–1.25) |
Continuous Ptrendf | 0.88 | 0.79 | 0.54 |
Biomarker . | EA cases/total . | Unadjusted HR (95% CI) . | Adjusted for agea and gender HR (95% CI) . | Adjusted for agea, gender, WHRb, smokingc, and NSAID used HR (95% CI) . |
---|---|---|---|---|
CRP (mg/L)e | ||||
All participants | ||||
Median | ||||
Below | 15/192 | REF | REF | REF |
Above | 28/194 | 1.83 (0.98–3.43) | 1.98 (1.05–3.73) | 1.77 (0.93–3.37) |
Quartiles | ||||
Q1 (0.1–) | 6/95 | REF | REF | REF |
Q2 (0.9–) | 9/97 | 1.29 (0.46–3.63) | 1.18 (0.42–3.32) | 1.05 (0.37–2.99) |
Q3 (1.9–) | 15/95 | 2.35 (0.91–6.06) | 2.29 (0.89–5.92) | 2.12 (0.81–5.56) |
Q4 (3.6–) | 13/99 | 1.90 (0.72–5.01) | 2.06 (0.78–5.44) | 1.55 (0.56–4.24) |
Continuous Ptrendf | 0.03 | 0.01 | 0.04 | |
Males | ||||
Median | ||||
Below | 12/155 | REF | REF | REF |
Above | 28/165 | 2.31 (1.18–4.55) | 2.21 (1.12–4.36) | 1.93 (0.96–3.89) |
Quartiles | ||||
Q1 (0.1–) | 5/79 | REF | REF | REF |
Q2 (0.9–) | 7/76 | 1.20 (0.38–3.77) | 1.20 (0.38–3.79) | 1.09 (0.34–3.49) |
Q3 (1.8–) | 15/84 | 2.74 (0.99–7.55) | 2.55 (0.92–7.02) | 2.33 (0.83–6.51) |
Q4 (3.4–) | 13/81 | 2.37 (0.85–6.66) | 2.36 (0.84–6.62) | 1.76 (0.60–5.15) |
Continuous Ptrendf | 0.01 | 0.01 | 0.05 | |
IL6 (pg/mL) | ||||
All participants | ||||
Median | ||||
Below | 15/197 | REF | REF | REF |
Above | 30/197 | 2.06 (1.11–3.82) | 1.95 (1.03–3.72) | 1.79 (0.93–3.43) |
Quartiles | ||||
Q1 (0.4–) | 7/98 | REF | REF | REF |
Q2 (1.3–) | 8/99 | 1.14 (0.41–3.15) | 0.95 (0.34–2.66) | 0.82 (0.29–2.34) |
Q3 (1.9–) | 19/99 | 2.74 (1.15–6.52) | 2.35 (0.96–5.77) | 1.93 (0.78–4.79) |
Q4 (3.1–) | 11/98 | 1.65 (0.64–4.24) | 1.40 (0.52–3.78) | 1.17 (0.42–3.26) |
Continuous Ptrendf | 0.64 | 0.94 | 0.87 | |
Males | ||||
Median | ||||
Below | 10/161 | REF | REF | REF |
Above | 31/161 | 3.19 (1.57–6.52) | 2.85 (1.38–5.92) | 2.52 (1.19–5.33) |
Quartiles | ||||
Q1 (0.4–) | 6/81 | REF | REF | REF |
Q2 (1.3–) | 4/80 | 0.67 (0.19–2.36) | 0.56 (0.16–2.01) | 0.53 (0.15–1.89) |
Q3 (1.8–) | 18/80 | 3.06 (1.21–7.71) | 2.51 (0.96–6.51) | 2.04 (0.77–5.41) |
Q4 (2.9–) | 13/81 | 2.25 (0.86–5.93) | 1.77 (0.64–4.86) | 1.56 (0.55–4.43) |
Continuous Ptrendf | 0.66 | 0.99 | 0.81 | |
sTNF-I (ng/mL) | ||||
All participants | ||||
Median | ||||
Below | 18/197 | REF | REF | REF |
Above | 27/197 | 1.62 (0.89–2.93) | 1.29 (0.69–2.42) | 0.99 (0.51–1.92) |
Quartiles | ||||
Q1 (0.3–) | 11/98 | REF | REF | REF |
Q2 (1.1–) | 7/99 | 0.64 (0.25–1.64) | 0.56 (0.22–1.45) | 0.60 (0.23–1.56) |
Q3 (1.4–) | 13/98 | 1.24 (0.55–2.76) | 0.94 (0.41–2.15) | 0.87 (0.38–1.98) |
Q4 (1.7–) | 14/99 | 1.41 (0.64–3.10) | 1.02 (0.44–2.37) | 0.68 (0.27–1.68) |
Continuous Ptrendf | 0.18 | 0.68 | 0.69 | |
Males | ||||
Median | ||||
Below | 17/161 | REF | REF | REF |
Above | 24/161 | 1.56 (0.84–2.90) | 1.23 (0.63–2.41) | 0.95 (0.47–1.94) |
Quartiles | ||||
Q1 (0.3–) | 11/80 | REF | REF | REF |
Q2 (1.1–) | 6/81 | 0.51 (0.19–1.37) | 0.47 (0.17–1.26) | 0.51 (0.19–1.38) |
Q3 (1.4–) | 12/80 | 1.10 (0.48–2.49) | 0.85 (0.36–2.00) | 0.73 (0.31–1.74) |
Q4 (1.7–) | 12/81 | 1.23 (0.54–2.80) | 0.88 (0.36–2.14) | 0.66 (0.26–1.71) |
Continuous Ptrendf | 0.30 | 0.83 | 0.57 | |
sTNF-II (ng/mL) | ||||
All participants | ||||
Median | ||||
Below | 15/197 | REF | REF | REF |
Above | 30/197 | 2.23 (1.20–4.15) | 1.90 (0.98–3.67) | 1.78 (0.90–3.52) |
Quartiles | ||||
Q1 (1.6–) | 8/98 | REF | REF | REF |
Q2 (4.7–) | 7/99 | 0.83 (0.30–2.29) | 0.78 (0.28–2.17) | 0.81 (0.29–2.25) |
Q3 (5.4–) | 13/98 | 1.68 (0.70–4.05) | 1.46 (0.59–3.61) | 1.47 (0.59–3.70) |
Q4 (6.4–) | 17/99 | 2.44 (1.05–5.66) | 1.95 (0.76–4.95) | 1.75 (0.68–4.49) |
Continuous Ptrendf | 0.22 | 0.75 | 0.86 | |
Males | ||||
Median | ||||
Below | 14/161 | REF | REF | REF |
Above | 27/161 | 2.18 (1.14–4.16) | 1.81 (0.91–3.62) | 1.63 (0.80–3.34) |
Quartiles | ||||
Q1 (1.6–) | 8/80 | REF | REF | REF |
Q2 (4.7–) | 6/81 | 0.69 (0.24–1.98) | 0.62 (0.21–1.80) | 0.69 (0.24–2.00) |
Q3 (5.3–) | 12/80 | 1.52 (0.62–3.72) | 1.27 (0.50–3.23) | 1.28 (0.50–3.30) |
Q4 (6.4–) | 15/81 | 2.17 (0.92–5.14) | 1.59 (0.60–4.19) | 1.44 (0.54–3.83) |
Continuous Ptrendf | 0.20 | 0.78 | 0.78 | |
Isoprostanes (pg/mL) | ||||
All participants | ||||
Median | ||||
Below | 27/186 | REF | REF | REF |
Above | 18/191 | 0.60 (0.33–1.09) | 0.69 (0.38–1.26) | 0.56 (0.30–1.03) |
Quartiles | ||||
Q1 (14–) | 13/90 | REF | REF | REF |
Q2 (41–) | 14/96 | 0.98 (0.46–2.09) | 1.18 (0.55–2.53) | 0.93 (0.43–2.02) |
Q3 (53–) | 10/98 | 0.68 (0.30–1.54) | 0.76 (0.33–1.74) | 0.61 (0.26–1.41) |
Q4 (74–) | 8/93 | 0.52 (0.22–1.26) | 0.74 (0.30–1.85) | 0.46 (0.18–1.20) |
Continuous Ptrendf | 0.34 | 0.92 | 0.41 | |
Males | ||||
Median | ||||
Below | 23/143 | REF | REF | REF |
Above | 18/157 | 0.74 (0.40–1.36) | 0.79 (0.42–1.46) | 0.64 (0.34–1.20) |
Quartiles | ||||
Q1 (14–) | 11/74 | REF | REF | REF |
Q2 (40–) | 12/79 | 1.03 (0.45–2.33) | 1.18 (0.52–2.69) | 0.98 (0.43–2.27) |
Q3 (51–) | 11/80 | 0.96 (0.42–2.21) | 1.04 (0.45–2.41) | 0.80 (0.34–1.88) |
Q4 (66–) | 7/77 | 0.55 (0.21–1.43) | 0.66 (0.25–1.72) | 0.47 (0.18–1.25) |
Continuous Ptrendf | 0.88 | 0.79 | 0.54 |
Abbreviation: EA, esophageal adenocarcinoma.
aAge was modeled as a continuous variable.
bWHR was modeled as a continuous variable.
cCigarette smoking was modeled as pack-years smoked, never smokers were assigned a pack-year value of 0.
dNSAID use was modeled as current vs. noncurrent users of NSAIDs at the baseline visit.
eCRP measurements more than 10 mg/L were excluded from the analysis.
fTest for trend was based on the likelihood-ratio test associated with addition of the variable under consideration in its continuous form.
Mean CRP levels above the median of 1.9 mg/L were associated with a 2-fold increased esophageal adenocarcinoma risk compared with those with values below the median, after adjustment for age and gender (HR, 1.98; 95% CI, 1.05–3.73, Ptrend for continuous CRP = 0.01). Further adjustment for WHR, smoking, and NSAIDs attenuated the association somewhat (HR, 1.77; 95% CI, 0.93–3.37; Ptrend for continuous CRP = 0.04). Analyses limited to men revealed slightly stronger associations with CRP.
Participants with average IL6 levels above the median had a 2-fold increased risk for esophageal adenocarcinoma (HR, 1.95; 95% CI, 1.03–3.72) but no evidence of a trend was observed (Ptrend = 0.94). The increase in risk was more pronounced among males, with an almost 3-fold increased risk (HR, 2.85; 95% CI, 1.38–5.92) after adjustment for age and gender. Overall as well as in the subgroup analysis for males, additional adjustment for obesity, smoking, and NSAIDs had little effect. No evidence of an association between sTNF-RI and esophageal adenocarcinoma risk was observed. For sTNF-RII, although univariate analyses overall and among males revealed statistically significant associations, adjustment for confounders attenuated the association substantially such that it was no longer statistically significant. Circulating levels of F2-isoprostanes were not associated with increased risk of esophageal adenocarcinoma in this cohort.
To evaluate if the significant associations observed with CRP and IL6 were more pronounced within the first few years of follow-up, we conducted subanalyses restricting the follow-up time to 3 and 5 years from baseline (Fig. 1). The associations with CRP were stronger and the statistical trends more pronounced (Ptrend for continuous CRP = 0.02 in a fully adjusted model) with the restricted 5-year follow-up. The associations with IL6 did not alter much after restricting the follow-up to 3 or 5 years. We repeated our main analyses after adding the 14 individuals with less than 5 months of follow-up that we had initially excluded, with no important differences found (data not shown). To examine whether prolonged storage of biologic samples affected our results, we also conducted a sensitivity analysis restricted to only those individuals whose biologic samples had been stored for 10 years or less (mean storage time for the earlier of the two samples from an individual was 12 years). We found that although the results for CRP were slightly stronger and those for IL6 were weaker as compared with the main statistical analysis, the overall conclusions remained the same (data not shown). As IL6 may be produced by the metaplastic epithelium (35), we also investigated the effect of adjustment for Barrett's esophagus segment length in models involving IL6 and found that the point estimate was reduced by a small amount—from 1.79 to 1.60.
We also computed an “inflammation score” based on the quartile categories for various biomarkers such that individuals in the lowest quartile for a biomarker received a score of 0 and those in the highest quartile received a score of 3. Using the summed combined score as the primary predictor, we found that esophageal adenocarcinoma risk nonsignificantly increased by 2% per unit increase in the score in adjusted models (data not shown).
Discussion
In this prospective study, we observed that elevated prediagnostic blood concentrations of CRP and possibly IL6 are associated with subsequent increased incidence of esophageal adenocarcinoma among persons with Barrett's esophagus. Plasma levels of sTNF receptors or isoprostanes were not statistically significantly associated with esophageal adenocarcinoma risk.
The role of inflammation and resulting oxidative stress in the development of cancer has been the focus of extensive research (3, 36, 37). More recently, inflammation markers, particularly CRP and IL6, have been reported to be associated with all cancers in prospective and nested case–control studies. In a prospective Danish cohort of 10,000 individuals, the risk for any cancer associated with CRP levels more than 3 mg/L was 1.3 (95% CI, 1.0–1.6; ref. 38); a similar 1.2-fold (95% CI, 1.10–1.32) increased risk for any cancer with increasing CRP was observed in a Greek cohort (39). In another prospective study involving the Health Aging and Body Composition cohort, risk for all cancers increased with higher levels of CRP, IL6, and TNFα (40). In studies looking at individual cancer sites, the evidence for a possible role of chronic inflammation is the strongest for colon cancer (38, 40–43). Elevated levels of inflammatory markers have also been shown to be associated with cancers of the lung (38–40, 44, 45), breast (39, 40, 45) and ovary (46). Oxidative stress markers such as F2-isoprostanes and oxodeoxyguanosine have been shown to be associated with cancers of colon, lung, prostate, and breast (6–8, 47, 48).
Our study adds to the accumulating evidence for a key role of inflammation in esophageal adenocarcinoma development, even among persons already diagnosed with Barrett's esophagus. Exposure of the esophageal epithelium to bile salts and acid resulting from gastroesophageal reflux can cause chronic inflammation of the lower esophagus and result in increased release of proinflammatory mediators (49–51), which may, in turn, cause DNA damage and promote progression (1, 49). In support of this hypothesis, an experimental study showed that Barrett's esophagus tissue secretes significant amounts of IL6 resulting in an increased expression of STAT3 transcription factor that may lead to neoplastic conversion (35). In another study, the levels of ROS were higher in biopsy specimens from patients with Barrett's esophagus than those from controls, suggesting that they play a role in the tissue injury associated with Barrett's esophagus (52). In our own cohort, we have previously shown that leukocyte telomere length, a measure of person's long-term inflammation level and oxidative damage (53), was associated with more than a 3-fold increased risk of esophageal adenocarcinoma (Ptrend = 0.009; ref. 54), and that anti-inflammatory drugs such as NSAIDs reduce the risk of esophageal adenocarcinoma even among those with dysplastic changes in their Barrett's segment (15). Here, we show a link between prediagnostic concentrations of inflammation markers and esophageal adenocarcinoma among patients with Barrett's esophagus, suggesting that pathways involving inflammatory biomarkers present prevention targets.
Blood-based markers of chronic systemic inflammation may also reflect systemic response to other exposures that predispose to esophageal cancer, such as obesity. Inflammatory cytokines, including IL6 and TNF-α, have been observed to be systematically elevated in obesity (55, 56), and dietary intervention studies have shown that weight loss reduces CRP levels among obese individuals (57). We have previously reported a modest increase in esophageal adenocarcinoma risk associated with measures of central adiposity (23). Results from the present study indicate that CRP and IL6 may be predictive in esophageal adenocarcinoma development even after adjustment for confounding effects of obesity in patients with Barrett's esophagus. Taken together, these results suggest that inflammation markers may mediate the association of obesity with esophageal adenocarcinoma, but they also have some independent effect on esophageal adenocarcinoma development beyond their effect through obesity.
This study has several strengths. Its prospective design allowed for measurement of multiple markers of inflammation and oxidative stress before the development of cancer, minimizing the possibility of reverse causality. For the majority of the biomarkers, we also were able to assess plasma levels at two time points during follow-up, thus reducing random measurement error and the potential for regression dilution bias (58, 59). In addition, measuring the biomarkers at two time points enabled us to improve on the ICCs reported earlier (Materials and Methods) by capturing some of the intraperson variation. For example, the ICC of 0.55 for CRP that we reported earlier is actually improved to 0.71 just by averaging over two CRP measurements (60). We also blinded the laboratory personnel to participants' disease status. Comprehensive measurement of covariates such as WHR and pack-years of smoking enabled us to limit confounding. We also carried out analyses restricting to the first 3 and 5 years of follow-up, so as to minimize the misclassification of inflammation marker status due to prolonged duration between measurement of inflammation markers and occurrence of esophageal adenocarcinoma events, and observed stronger associations and more pronounced trends.
Our study is limited by the relatively small number of incident esophageal adenocarcinoma cases, despite being one of the largest, well-characterized cohorts of patients with Barrett's esophagus reported in the literature. Although we controlled for potential confounding effects of smoking, obesity, and NSAID use in multivariable analyses, we cannot exclude the possibility of residual confounding by measured and unmeasured risk factors. In particular, we did not collect data on Helicobacter pylori status, which has been shown to be inversely related to esophageal adenocarcinoma risk (61, 62), while at the same time being associated with systemic inflammation (63) such that H. pylori eradication therapies reduce the blood levels of proinflammatory cytokines, including CRP (64). We did not adjust for confounding by the length of Barrett's segment in our analysis. Although a recent study showed that presence of long-segment Barrett's esophagus carried a 7-fold increased risk of progression to esophageal adenocarcinoma (65), Barrett's esophagus segment length is only modestly associated with the risk of esophageal adenocarcinoma in our cohort (66). We attempted to limit measurement error by using high sensitivity and reliable assays for biomarker measurement. However, we cannot exclude the possibility of errors in biomarker measurement resulting from degradation of biologic samples during storage. Finally, as the study cohort represents a specialty clinic, results presented in the current report should be cautiously interpreted in terms of their generalizability to the general population.
In conclusion, our results indicate that systemic levels of CRP and, to some extent, IL6 are associated with progression to esophageal adenocarcinoma in persons with Barrett's esophagus. Soluble TNF receptors and F2-isoprostanes were not found to be associated with increased esophageal adenocarcinoma risk. Our findings with CRP and IL6 are consistent with the literature that supports the role of chronic inflammation in the development of cancer, and esophageal adenocarcinoma in particular. Additional analyses involving further follow-up of this and other cohorts are needed to confirm these findings, as well as to evaluate the utility of biomarker assessment in clinical prediction and risk stratification of esophageal adenocarcinoma.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Disclaimer
The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the article.
Authors' Contributions
Conception and design: S. Hardikar, M. Kratz, B.J. Reid, T.L. Vaughan
Development of methodology: S. Hardikar, T.J. Montine, T.L. Vaughan
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): S. Hardikar, X. Song, A.M. Wilson, T.J. Montine, P.L. Blount, B.J. Reid, T.L. Vaughan
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): S. Hardikar, M. Kratz, G.L. Anderson, B.J. Reid, E. White, T.L. Vaughan
Writing, review, and/or revision of the manuscript: S. Hardikar, L. Onstad, X. Song, T.J. Montine, M. Kratz, G.L. Anderson, P.L. Blount, B.J. Reid, E. White, T.L. Vaughan
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): S. Hardikar, L. Onstad, X. Song
Study supervision: X. Song, T.L. Vaughan
Acknowledgments
The authors thank Tricia Christopherson for project management; Terri Watson for database management; and Christine Karlsen for coordination of patient care.
Grant Support
This work was supported by NIH grants P01CA091955 (to B.J. Reid), K05CA124911 (to T.L. Vaughan), and R25CA094880 (to E. White).
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