Abstract
Background
Obesity has been consistently associated with increased risk of pancreatic cancer incidence and mortality. However, studies of obesity and overall survival in patients with pancreatic cancer are notably lacking, especially in population-based studies.
Methods
Active and passive follow-up were used to determine vital status and survival for 510 pancreatic cancer patients diagnosed from 1995–1999 in a large population-based case-control study in the San Francisco Bay Area. Survival rates were computed using Kaplan-Meier methods. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated in multivariable Cox proportional hazards models as measures of the association between pre-diagnostic obesity and pancreatic cancer survival.
Results
An elevated hazard ratio of 1.3 (95% CI, 0.91–1.81) was observed for obese (body mass index [BMI] ≥30) compared with normal range BMI (<25) patients. Associations between overall survival and known pancreatic cancer prognostic and risk factors did not significantly vary by BMI (all P-interaction ≥0.18), yet elevated HRs consistently were observed for obese compared with normal BMI patients [localized disease at diagnosis (HR, 3.1), surgical resection (HR, 1.6), ever smokers (HR, 1.6), diabetics (HR, 3.3)]. Poor survival was observed among men, older patients, more recent and current smokers, whereas improved survival was observed for Asian/Pacific Islanders.
Conclusions
Our results in general provide limited support for an association between prediagnostic obesity and decreased survival in patients with pancreatic cancer. Patterns of reduced survival associated with obesity in some patient subgroups could be due to chance and require assessment in larger pooled studies.
Keywords: Pancreatic cancer, obesity, survival, population-based cohort
Introduction
Pancreatic cancer is the fourth leading cause of cancer death in U.S. men and women with a similar number of deaths and new cases diagnosed each year [1]. The prognosis of pancreatic cancer remains extremely poor, with an overall 5-year relative survival rate of 6% [2]. Although the etiology of this deadly disease remains largely unknown, epidemiologic data consistently have indicated that obesity is associated with increased risk of pancreatic cancer [3–6] and pancreatic cancer mortality [7–9]. Few recent observational studies, including two-hospital based studies and one multi-site clinic-based study, reported poorer survival among obese patients, and also found additional effects of smoking, diabetes and age at obesity in their effort to clarify the role of obesity and related biological mechanisms in pancreatic cancer survival [10–12]. In contrast, results have been mixed from clinical studies that evaluated the effect of obesity at time of pancreatic resection on patient outcomes, including survival [13–20]. As current results have largely been limited to clinic- and hospital-based studies or small clinical studies, confirmation and further investigation in population-based studies is needed to clarify the role of obesity in pancreatic cancer survival.
Here we address whether obesity before diagnosis is related to survival in pancreatic cancer patients who participated in our large San Francisco Bay Area population-based pancreatic cancer study that has more than 10 years of patient follow-up with <1% lost to follow-up [21]. Detailed collection of epidemiologic risk factor and clinical data also allowed us to further examine potential confounding or modification of the obesity-survival association by the known clinical prognostic factors (i.e. stage) and other risk factors (i.e. smoking, and diabetes) that have been reported in previous publications.
Materials and Methods
Study population
Study cases were patients newly diagnosed with adenocarcinoma of the exocrine pancreas identified by the Greater Bay Area Cancer Registry rapid case ascertainment and by Surveillance, Epidemiology and End Results (SEER) registry abstracts, met study eligibility criteria and participated in our population-based, case-control study. Study details have been described previously [22]. Briefly, eligible cases were 21–85 years old at diagnosis, residents of one of six San Francisco Bay Area counties, diagnosed with pancreatic adenocarcinoma from January 1, 1995 to December 31, 1999, alive at first contact, had no physician indicated contraindications to contact and were able to complete an interview in English. Pancreatic cancer diagnoses were confirmed by participants’ physicians and by SEER abstracts. Among the 798 eligible cases contacted, 532 completed the interview for a participation rate of 67%. There were 8 patients excluded after additional vital status update due to unconfirmed cancer diagnosis or diagnosis of cancer “in situ”. Fourteen out-of-area study patients were not included in the vital status update, leaving 510 patients for these survival analyses. The study was reviewed and approved by the University of California San Francisco Committee on Human Research.
Data collection
Detailed data including age, race, education, medical history, history of smoking, physical activity, and anthropometric measures were collected during in-person interviews by trained interviewers. No proxy interviews were conducted. Patient prognostic clinical information was obtained from SEER abstracts/registry data and from in-person interviews. For these analyses, age at diagnosis was grouped as <50, 50–59, 60–69, 70–79, 80+ years and race/ethnicity as non-Hispanic white, Hispanic white, black/African American, Asian/Pacific Islander/other. Usual adult body mass index (BMI: kg/m2) was classified into normal weight (BMI <25 kg/m2), overweight (BMI 25-<30 kg/m2), and obese (BMI ≥30 kg/m2) categories. Stage at diagnosis was determined by SEER registry abstractors using pathological and clinical data, and was classified as localized (confined to the pancreas), regional (extension to surrounding organs/or regional lymph nodes), or distant disease (metastases). Initial treatment data were obtained from SEER abstracts and in-person interviews and were coded as surgical resection (Whipple or local resection), chemotherapy/radiation therapy, bypass/stent, other treatment and therapy unknown.
Vital status
Patient vital status was determined using multiple passive and active methods as previously described [21]. In brief, date of death was actively ascertained as part of the patient recruitment process. In the years after the parent case-control study had ended, vital status and date of death were updated using SEER abstract and registry data, the Social Security Death Index and the California Death Records databases. When patient vital status was not available from the aforementioned sources, patients, their relatives, their treating physicians and/or the treating hospitals were contacted to determine patient vital status. Using these methods, vital status and survival-related data were completed for all patients through December 31, 2008. Survival time was defined as the time from diagnosis to death or to date of last contact for patients who remained alive or who were lost to follow-up.
Statistical analysis
We examined means and frequency distributions of demographic and clinical characteristics across BMI categories and tested for statistically significant associations using one-way ANOVA and chi-square tests. Kaplan-Meier methods and log-rank tests were used to estimate the mortality-free survival by categorical variables of interest. Multivariable Cox proportional hazards models were used to estimate the hazard ratios (HR) and 95% confidence intervals (CI) for associations among BMI, demographic, tumor and treatment factors and overall survival from pancreatic cancer [23]. An unknown category was created for variables of stage at diagnosis, tumor grade, site of tumor, and initial treatment when they were included in the model.
Statistical tests were two-sided and considered statistically significant for p <0.05. Statistical analyses were conducted using SAS software v9.2 (SAS Institute, Inc., Cary, NC).
Results
Study patients’ demographic and clinical characteristics by BMI categories are provided in Table 1. BMI was not associated with clinical prognostic factors, including cancer stage (P=0.92) and tumor grade (P=0.23). BMI also was not related to the tumor location (P=0.11) or to the initial treatment modalities (P=0.35). However, compared with patients whose BMI was in the normal range, obese patients were more likely to be younger, men, African American, never smokers, and diabetic (all P≤0.02).
Table 1.
Demographic and clinical characteristics of 510 pancreatic cancer patients by body mass index (BMI) from a population-based case-control study in the San Francisco Bay Area, 1995–1999
| Characteristics | Body Mass Index (kg/m2) | P-valuea | ||
|---|---|---|---|---|
| <25 (n=269) | 25-<30 (n=190) | ≥30 (n=51) | ||
| Age at diagnosis (yrs), mean (SD) | 66.1 (10.2) | 63.2 (10.6) | 62.0 (11.2) | 0.002 |
| n (%) | n (%) | n (%) | ||
| Age | 0.01 | |||
| <50 | 21 (7.8) | 15 (7.9) | 7 (13.7) | |
| 50–59 | 45 (16.7) | 55 (28.9) | 14 (27.5) | |
| 60–69 | 84 (31.2) | 64 (33.7) | 15 (29.4) | |
| 70–79 | 100 ( 37.2) | 42 (22.1) | 12 (23.5) | |
| ≥80 | 19 (7.1) | 14 (7.4) | 3 (5.9) | |
| Sex | <0.0001 | |||
| Men | 110 (40.9) | 136 (71.6) | 32 (62.8) | |
| Women | 159 (59.1) | 54 (28.4) | 19 (37.2) | |
| Race/Ethnicity | 0.01 | |||
| Non-Hispanic white | 224 (83.2) | 148 (77.9) | 36 (70.6) | |
| Hispanic white | 5 (1.9) | 7 (3.7) | 3 (5.9) | |
| African-American/Black | 14 (5.2) | 21 (11.0) | 10 (18.9) | |
| Asian/Other | 26 (9.7) | 14 (7.4) | 2 (3.8) | |
| Education | 0.61 | |||
| Less than high school | 28 (10.4) | 29 (15.3) | 8 (15.7) | |
| High school graduate | 86 (32.0) | 56 (29.5) | 19 (37.2) | |
| 1–4 years college | 106 (39.4) | 68 (35.8) | 16 (31.4) | |
| Graduate school | 49 (18.2) | 37 (19.5) | 8 (15.7) | |
| Smoking status | 0.02 | |||
| Never smokers | 83 (30.9) | 53 (27.9) | 22 (43.1) | |
| Former smokers, quit>15yrs | 58 (21.6) | 61 (32.1) | 8 (15.7) | |
| Former smokers, quit 1–15yrs | 54 (20.1) | 26 (13.7) | 5 (9.8) | |
| Current smokers +quit<1yr | 68 (25.2) | 44 (23.2) | 12 (23.5) | |
| Cigar smokers | 6 (2.2) | 6 (3.2) | 4 (7.8) | |
| Diabetes | <0.0001 | |||
| No | 243 (90.7) | 163 (85.8) | 31 (60.8) | |
| Yes | 25 (9.3) | 27 (14.2) | 20 (39.2) | |
| Stage at diagnosis | 0.92 | |||
| Local | 31 (11.5) | 26 (13.7) | 6 (11.8) | |
| Regional | 113 (42.0) | 83 (43.7) | 25 (49.0) | |
| Distant | 86 (32.0) | 53 (27.9) | 14 (27.4) | |
| Unstaged/unknown | 39 (14.5) | 28 (14.7) | 6 (11.8) | |
| Tumor grade | 0.23 | |||
| Well differentiated | 33 (12.3) | 22 (11.6) | 2 (3.9) | |
| Mod-Well differentiated | 10 (3.7) | 10 (5.2) | 4 (7.8) | |
| Moderate differentiated | 61 (22.7) | 28 (14.7) | 9 (17.6) | |
| Mod-Poor differentiated | 19 (7.1) | 15 (7.9) | 4 (7.8) | |
| Poorly differentiated | 38 (14.1) | 25 (13.2) | 12 (23.5) | |
| Not graded/unknown | 108 (40.1) | 92 (47.4) | 20 (39.2) | |
| Tumor site | 0.11 | |||
| Head | 164 (61.0) | 132 (69.5) | 35 (68.6) | |
| body | 30 (11.1) | 8 (4.2) | 3 (5.9) | |
| Tail | 14 (5.2) | 15 (7.9) | 4 (7.8) | |
| Head/body/tail | 22 (8.2) | 8 (4.2) | 2 (3.9) | |
| NOS/Unknown | 39 (14.5) | 27 (14.2) | 7 (13.7) | |
| Initial treatment | 0.35 | |||
| Whipple or local resection | 85 (31.6) | 58 (30.5) | 15 (29.4) | |
| Chemo/radiation | 71 (26.4) | 56 (29.5) | 20 (39.2) | |
| Other treatment | 27 (10.0) | 15 (7.9) | 3 (5.9) | |
| Bypass/stent | 18 (6.7) | 20 (10.5) | 6 (11.8) | |
| Treatment unknown | 68 (25.3) | 41 (21.6) | 7 (13.7) | |
NOS: not otherwise specified
P-value of chi-square test or Fisher’s exact test (if more than 25% of cells with an expected value less than 5) for categorical variables or of one-way ANOVA for continuous variables
Median survival duration and overall patient survival associated with demographic characteristics, clinical factors and other covariates assessed using Cox proportional hazards regression are presented in Table 2. With a median follow-up of 10.1 years, 495 (97.0%) patients were confirmed dead, 11(2.2%) were alive at last contact, and vital status was unknown for 4 (0.8%) patients. The median overall survival was 10.1 months. The association of BMI with overall survival in pancreatic cancer patients was estimated in a model adjusted for age, sex, race/ethnicity, education level, and for smoking status, diabetes and clinical prognostic factors. An elevated hazard ratio of 1.28 (95% CI, 0.91–1.81, P=0.16) was observed for obese compared with normal BMI patients. Risk of dying was highest, as expected, among older patients (80+ years old, HR=2.65) and among patients who were diagnosed with distant disease (HR= 1.93) or poorly differentiated tumor (HR= 1.73). In contrast, the lowest HRs were observed among patients whose initial treatment was surgical resection and other active treatment modalities (HRs from 0.40 to 0.74) relative to those with unknown initial treatment. Better overall survival also was observed among Asians or Pacific Islanders when compared with non-Hispanic whites, and among women when compared with men.
Table 2.
Hazard ratios (HR) and 95% confidence intervals (CI) as estimates of risk of dying associated with body mass index (BMI), demographic, clinical and other lifestyle factors in 510 pancreatic cancer patients from a population-based case-control study, San Francisco Bay Area, 1995–1999
| Characteristics | Patients N (%) |
Deaths (N) | Survival in mos. Med. (IQR) |
HR (95% CI)a | HR (95% CI)b | P-valuec |
|---|---|---|---|---|---|---|
| Total patient cohort | 510 | 495 | 10.1 (6.4–17.9) | |||
| Body mass index (BMI) | 0.32 | |||||
| <25 | 269 (52.8) | 261 | 9.9 (6.3–18.5) | 1.00 | 1.00 | |
| 25-<30 | 190 (37.2) | 184 | 10.7 (6.4–17.2) | 1.01 (0.83–1.22) | 1.04 (0.83–1.28) | |
| ≥30 | 51 (10.0) | 50 | 9.1 (6.4–15.7) | 1.27 (0.93–1.72) | 1.28 (0.91–1.81) | |
| Age at diagnosis | <0.0001 | |||||
| <50 | 43 (8.4) | 37 | 9.8 (5.1–26.6) | 1.00 | 1.00 | |
| 50–59 | 114 (22.4) | 110 | 11.5 (7.0–17.2) | 1.25 (0.86–1.82) | 1.21 (0.80–1.83) | |
| 60–69 | 163 (32.0) | 161 | 11.0 (6.8–19.3) | 1.25 (0.87–1.79) | 1.05 (0.70–1.57) | |
| 70–79 | 154 (30.2) | 151 | 9.2 (6.0–17.0) | 1.46 (1.01–2.09) | 1.62 (1.07–2.45) | |
| 80+ | 36 (7.0) | 36 | 7.8 (4.7–9.8) | 2.46 (1.54–3.91) | 2.65 (1.57–4.49) | |
| Sex | 0.01 | |||||
| Men | 278 (54.5) | 273 | 10.0 (6.2–16.2) | 1.00 | 1.00 | |
| Women | 232 (45.5) | 222 | 11.0 (6.6–21.0) | 0.78 (0.65–0.94) | 0.77 (0.62–0.95) | |
| Race | 0.02 | |||||
| Non-Hispanic white | 408 (80.0) | 399 | 9.9 (6.2–17.0) | 1.00 | 1.00 | |
| Hispanic white | 15 (2.9) | 15 | 19.3 (9.4–26.6) | 0.72 (0.42–1.25) | 0.80 (0.45–1.42) | |
| African American/Black | 45 (8.8) | 44 | 9.6 (6.8–15.8) | 1.07 (0.78–1.46) | 0.85 (0.59–1.23) | |
| Asian/other | 42 (8.2) | 37 | 14.9 (7.1–23.5) | 0.78 (0.55–1.09) | 0.58 (0.40–0.83) | |
| Education | 0.93 | |||||
| Less than high school | 65 (12.8) | 65 | 9.2 (6.4–13.2) | 1.00 | 1.00 | |
| High school graduate | 161 (31.6) | 158 | 10.2 (6.6–17.8) | 0.77 (0.57–1.03) | 0.91 (0.66–1.26) | |
| 1–4 years college | 190 (37.2) | 185 | 11.3 (6.4–18.8) | 0.74 (0.55–0.99) | 0.89 (0.65–1.23) | |
| Graduate school | 94 (18.4) | 87 | 9.8 (6.0–23.1) | 0.66 (0.47–0.92) | 0.91 (0.63–1.32) | |
| Diabetes status | 0.26 | |||||
| No | 437 (85.8) | 422 | 10.2 (6.4–18.1) | 1.00 | 1.00 | |
| Yes | 72 (14.2) | 72 | 9.9 (6.2–16.1) | 1.16 (0.90–1.50) | 0.85 (0.64–1.13) | |
| Smoking | 0.03 | |||||
| Never smokers | 158 (31.0) | 150 | 11.3 (6.7–21.8) | 1.00 | 1.00 | |
| Former smokers, quit>15yrs | 127 (24.9) | 123 | 10.4 (6.4–20.3) | 1.01 (0.79–1.29) | 0.98 (0.74–1.28) | |
| Former smokers, quit 1–15yrs | 85 (16.7) | 85 | 9.4 (6.2–14.6) | 1.60 (1.22–2.10) | 1.46 (1.09–1.96) | |
| Current smokers +quit<1yr | 124 (24.3) | 121 | 9.7 (6.0–17.8) | 1.24 (0.97–1.58) | 1.22 (0.94–1.58) | |
| Cigar/pipe smokers | 16 (3.1) | 16 | 9.8 (7.2–17.3) | 1.14 (0.68–1.92) | 0.81 (0.47–1.42) | |
| Stage at diagnosis | <0.0001 | |||||
| Local | 63 (12.4) | 56 | 14.6 (7.3–32.9) | 1.00 | 1.00 | |
| Regional | 221 (43.3) | 215 | 12.8 (7.7–21.5) | 1.44 (1.06–1.94) | 1.21 (0.88–1.66) | |
| Distant | 153 (30.0) | 152 | 7.0 (4.8–11.2) | 3.02 (2.20–4.14) | 1.93 (1.35–2.77) | |
| Unstaged/Unknown | 72 (14.3) | 72 | 9.7 (7.3–18.9) | 1.72 (1.20–2.46) | 0.99 (0.65–1.51) | |
| Tumor grade | 0.09 | |||||
| Well differentiated | 57 (11.2) | 54 | 13.4 (9.0–32.9) | 1.00 | 1.00 | |
| Moderately-well differentiated | 24 (4.7) | 21 | 12.0 (7.9–21.0) | 1.17 (0.70–1.95) | 1.32 (0.78–2.23) | |
| Moderately differentiated | 98 (19.2) | 92 | 13.6 (7.0–21.9) | 1.32 (0.94–1.86) | 1.36 (0.95–1.93) | |
| Moderately-poor differentiated | 38 (7.4) | 36 | 10.6 (4.6–23.4) | 1.25 (0.82–1.92) | 1.32 (0.85–2.05) | |
| Poor differentiated | 75 (14.7) | 75 | 8.6 (5.4–14.9) | 2.23 (1.56–3.19) | 1.73 (1.16–2.58) | |
| Not graded/unknown | 218 (42.8) | 217 | 9.1 (6.1–14.3) | 2.02 (1.49–2.74) | 1.42 (1.02–1.99) | |
| Tumor site | ||||||
| Head | 331 (64.9) | 317 | 10.5 (6.6–19.1) | 1.00 | 1.00 | 0.30 |
| Body | 41 (8.0) | 41 | 8.9 (6.1–11.2) | 1.95 (1.40–2.72) | 1.49 (1.04–2.14) | |
| Tail | 33 (6.5) | 33 | 11.5 (9.1–17.9) | 1.05 (0.73–1.50) | 1.01 (0.69–1.47) | |
| Head/body/tail | 32 (6.3) | 32 | 7.5 (5.8–11.3) | 1.46 (1.01–2.11) | 1.15 (0.77–1.73) | |
| NOS/unknown | 73 (14.3) | 72 | 11.1 (5.2–18.9) | 1.11 (0.86–1.44) | 1.05 (0.79–1.38) | |
| Initial treatment | ||||||
| Treatment unknown | 158 (31.0) | 144 | 8.5 (5.5–12.9) | 1.00 | 1.00 | <0.0001 |
| Whipple or local resection | 147 (28.8) | 147 | 17.9 (9.9–34.4) | 0.37 (0.29–0.48) | 0.40 (0.29–0.56) | |
| Chemo/radiation therapy | 45 (8.8) | 45 | 10.1 (6.3–14.6) | 0.87 (0.69–1.11) | 0.74 (0.56–0.98) | |
| Other treatment | 44 (8.6) | 44 | 8.5 (5.1–13.2) | 0.98 (0.70–1.39) | 0.70 (0.48–1.02) | |
| Bypass/stent | 116 (22.8) | 115 | 8.0 (6.1–11.8) | 1.10 (0.78–1.56) | 1.02 (0.69–1.51) |
Med.: Median; IQR: interquartile range; HR: hazard ratio; 95% CI: 95% confidence interval, NOS: not otherwise specified
Results were from age-adjusted analysis
Results were from multivariable-adjusted model including age, sex, race, education, body mass index, smoking status, diabetes, stage, tumor grade, tumor site, and primary treatment
P-value is from Wald Chi-Square test in multivariable-adjusted models
The association of BMI with overall survival in pancreatic cancer patients stratified by stage, by smoking status and by diabetes was determined using multivariable Cox proportional hazards models adjusted for age, sex, race/ethnicity, education level, and for smoking status, diabetes and clinical prognostic factors as appropriate (Table 3). Obesity was associated with reduced overall survival among patients with localized stage at diagnosis (HR= 3.08) or who had received surgical resection (HR= 1.58), although confidence intervals were wide and included unity. Results also suggested that association between obesity and overall survival differed by smoking status (non-smokers vs. smokers) and by history of diabetes. In stratified analyses, risk of dying was greater for smokers (HR= 1.58; 95% CI, 0.86–2.90) and for diabetics (HR= 3.31; 95% CI, 1.16–9.44), although formal tests of statistical interaction were not statistically significant (all P ≥0.18).
Table 3.
Hazard rations (HR) and 95% confidence intervals (CI) for body mass index (BMI) associated with overall survival in stratified analyses among 510 pancreatic cancer patients from a population-based case-control study, San Francisco Bay Area, 1995–1999
| Characteristics | BMI (kg/m2) | Cases N (%) | HR (95% CI)a | HR (95% CI)b | |
|---|---|---|---|---|---|
| Stage | |||||
| Local | |||||
| <25 | 31 (49.2) | 1.00 | 1.00 | ||
| 25-<30 | 26 (41.3) | 1.09 (0.62–1.93) | 0.53 (0.19–1.46) | ||
| ≥30 | 6 (9.5) | 2.37 (0.92– 6.11) | 3.08 (0.46–20.73) | ||
| Regional | |||||
| <25 | 113 (51.1) | 1.00 | 1.00 | ||
| 25-<30 | 83 (37.6) | 1.04 (0.77–1.40) | 0.96 (0.67–1.38) | ||
| ≥30 | 25 (11.3) | 1.28 (0.83–1.99) | 1.03 (0.56–1.88) | ||
| Distant | |||||
| <25 | 86 (56.2) | 1.00 | 1.00 | ||
| 25-<30 | 53 (34.6) | 1.01 (0.71–1.44) | 0.87 (0.55–1.38) | ||
| ≥30 | 14 (9.2) | 1.28 (0.71–2.31) | 1.06 (0.53–2.11) | ||
| Unstaged/Unknown | |||||
| <25 | 39 (53.4) | 1.00 | 1.00 | ||
| 25-<30 | 28 (37.5) | 1.02 (0.60–1.75) | 0.84 (0.41–1.70) | ||
| ≥30 | 6 (8.2) | 1.67 (0.50–5.58) | 0.91 (0.21–3.91) | ||
| PBMI×Stage | 0.89 | ||||
| Surgery (initial treatment) | |||||
| No | |||||
| <25 | 184 (52.3) | 1.00 | 1.00 | ||
| 25-<30 | 132 (37.5) | 0.98 (0.78–1.23) | 1.04 (0.80–1.35) | ||
| ≥30 | 36 (10.2) | 1.05 (0.73–1.52) | 1.22 (0.82–1.83) | ||
| Yes | |||||
| <25 | 85 (53.8) | 1.00 | 1.00 | ||
| 25-<30 | 58 (36.7) | 0.92 (0.64–1.34) | 0.64 (0.42–0.99) | ||
| ≥30 | 15 (9.5) | 1.75 (1.00–3.06) | 1.58 (0.76–3.32) | ||
| PBMI×Surgery | 0.54 | ||||
| Smoking statusc | |||||
| Non-smoker | |||||
| <25 | 147 (48.8) | 1.00 | 1.00 | ||
| 25-<30 | 120 (39.9) | 1.08 (0.85–1.39) | 0.90 (0.67–1.20) | ||
| ≥30 | 34 (11.3) | 1.37 (0.93–2.01) | 1.05 (0.67–1.65) | ||
| Ever smoker | |||||
| <25 | 122 (58.4) | 1.00 | 1.00 | ||
| 25-<30 | 70 (33.5) | 0.92 (0.66–1.27) | 1.14 (0.79–1.66) | ||
| ≥30 | 17 (8.1) | 1.25 (0.74–2.11) | 1.58 (0.86–2.90) | ||
| PBMI×Smoking | 0.26 | ||||
| Diabetes | |||||
| No | |||||
| <25 | 243 (55.6) | 1.00 | 1.00 | ||
| 25-<30 | 163 (37.3) | 1.00 (0.81–1.22) | 0.94 (0.74–1.19) | ||
| ≥30 | 31 (7.1) | 1.32 (0.90–1.94) | 1.21 (0.80–1.82) | ||
| Yes | |||||
| <25 | 25 (34.7) | 1.00 | 1.00 | ||
| 25-<30 | 27 (37.5) | 1.08 (0.62–1.88) | 1.20 (0.50–2.88) | ||
| ≥30 | 20 (27.8) | 1.08 (0.59–1.97) | 3.31 (1.16–9.44) | ||
| PBMI×Diabetes | 0.18 | ||||
HR: hazard ratio; 95% CI: 95% confidence interval
Results were from age-adjusted analysis
Estimates were from multivariable Cox proportional hazards models that included adjustment for age, sex, race, education, smoking status, diabetes, stage, tumor grade, tumor site, and primary treatment, but excluded the specific stratified variable from the model (i.e., stage, surgical status, smoking status, and diabetes status)
Non-smokers: never smokers and former smokers who had quit >15 years ago; Smokers: current smokers and former smokers who had quit <1 to 15 years ago
Discussion
Pre-diagnostic obesity (BMI ≥30) based on usual adult weight was not statistically significantly associated with overall survival for pancreatic cancer in our study population. The association between known pancreatic cancer prognostic and risk factors did not significantly vary by BMI. Relatively few obese patients may have constrained our analyses. Chance could not be eliminated as the reason for the observed pattern of elevated HRs between obesity and overall survival by cancer stage at diagnosis, initial therapy, smoking status and diabetes.
Most published studies of obesity and pancreatic cancer survival are small clinical studies that investigated the relationship between BMI and various patient outcomes, including survival, after pancreatic resection. The association between obesity and survival from these studies has been mixed [13, 17, 19, 20] and may be explained by a variety of factors including small study size, assessment of outcomes unrelated to obesity, and heterogeneity in criteria for study enrollment and in BMI measures [24]. Additionally, many of these studies were designed to determine how obesity at time of surgery affected patient surgical outcome(s), rather than to assess the relationship between usual adult obesity (or obesity at a specific age) and survival duration in pancreatic cancer patients. Further, results from these studies are generalizable only to the approximate 20% of patients who received surgical resections (most of whom have localized disease), thus preventing an overall conclusion about the association between obesity and survival in pancreatic cancer patients.
Few epidemiological studies have evaluated the effect of obesity on pancreatic cancer survival after accounting for known risk factors, grade, stage and treatment. Our results are consistent in magnitude and direction of obesity-related effects reported in these few studies [10–12]. Our observation that obesity was associated with poorer survival in certain subgroups of patients, including those diagnosed with localized disease or who had received surgical resection, was similar to results from recent studies conducted at MD Anderson Cancer Center (MDACC) [10] and at Memorial Sloan Kettering Cancer Center (MSKCC) [11]. Both the MDACC and MSKCC studies reported that obesity was associated with decreased overall survival, particularly in the resected group (MDACC HR=3.4; MSKCC: HR=1.6), although results from MSKCC, 9 similar to our study, were not statistically significant. Results from a large clinic-based study at the Mayo Clinic also showed decreased survival with increased BMI in the total cohort of patients (BMI ≥30: HR=1.3; BMI ≥40: HR=1.6, p for trend <0.001) but found no differences by cancer stage [12]. Data from clinical studies suggest that obese patients may have had higher complication rates following their surgery, thus leading to shorter survival and a greater likelihood of dying [13, 15, 16]. However, it should be noted that a relatively small proportion of patients in our study population were obese (10%) compared with these other studies (23% to 36%), thus limiting the power of our study to detect a statistically significant effect. It also is possible that underlying differences in patients recruited from clinic- and hospital-based studies that tend to be conducted in single tertiary care institutions such as MSKCC, MDACC and the Mayo Clinic, and from population-based studies such as ours, may further explain some of the variation in results across observational studies. Additional large population-based studies are needed to examine this association further, particularly given the growing prevalence of obesity among U.S. adults over the past decade.
Smoking and diabetes have been consistently associated with increased risk of pancreatic cancer [25–31], and although each has been associated with obesity, little is known about whether they modify the association between obesity and survival from pancreatic cancer. In our analyses by smoking and by diabetes, we found that obese current smokers and obese diabetics had poorer survival than obese patients without these exposures/conditions. These suggestive joint effects require further study but may be partly explained by obesity-related mechanisms that are tumor enhancing. Obesity and diabetes are both associated with insulin resistance and insulin resistance results in higher circulating levels of insulin and insulin-like growth-factor 1 (IGF-1). Higher circulating insulin and IGF-1 have been shown to promote tumor progression 10 and metastasis [32–35] and thus may impact overall survival. Obesity also results in increased levels of leptin and other adipokines that can promote angiogenesis, an important factor in the growth and spread of many cancers [36–39]. Finally, obesity induces a pro-inflammatory environment including increased circulating tumor necrosis factor α and interleukins that also may contribute to tumor progression and metastasis [40–42].
Study patients were identified from a population-based cancer registry and we had extensive epidemiologic data available that allowed us to conduct detailed analyses of obesity and survival including assessment of multiple potential covariates, such as smoking and diabetes. We also had long-term follow-up for a median duration of 10 years for a total of 510 pancreatic cancer patients. Our use of active follow-up methods that included contact of physicians’ offices, hospitals, patients’ relatives and patients in addition to multiple passive follow-up approaches that included use of SEER data and various vital statistics databases, allowed us to obtain nearly complete vital status and survival assessment (<1% loss to follow-up). Our findings are consistent with published data but several factors should be considered when interpreting our results. Clinical data were obtained mainly from the SEER abstracts and thus tumor-related data were unknown for some patients. However, to diminish the effect of unknown data on our estimates, unknown data were grouped and included in our analyses. Given the high fatality rate of pancreatic cancer, cases who were interviewed and included in our study were healthier and more likely to have had better survival. Our study patients had longer median survival duration (10 months) than pancreatic cancer patients in the California SEER registry (3.5 months) diagnosed during the same time period. If obese patients were more likely to die before contact and thus are under-represented in our study, our results may underestimate the effect of obesity on overall survival. Further, the small number of obese patients limited our ability to adequately test some hypotheses in the stratified analyses, and these results require confirmation and further investigation.
In conclusion, our results in general are consistent with those from previously published studies and provide support for an association between pre-diagnostic obesity and decreased survival in patients with pancreatic cancer. Results that show the risk of dying associated with obesity was greater in some patient subgroups, such as among diabetics, should be interpreted conservatively and require confirmation. Because obesity is a risk factor for multiple diseases including pancreatic cancer, and is both preventable and amenable to intervention, it is important to continue to stress this message in public health presentations. Given the accumulating but limited research to suggest that obesity may be associated with survival in pancreatic cancer patients, larger pooled studies, especially from population-based projects, are warranted to further address this association.
Acknowledgments
This work was supported in part by National Cancer Institute grants (CA59706, CA108370, CA109767, CA89726, and CA121846 to E.A. Holly) and by the Rombauer Pancreatic Cancer Research Fund. The collection of cancer incidence data for the UCSF study was supported by the California Department of Public Health as part of the statewide cancer reporting program; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under contract N01-PC-35136 awarded to the Northern California Cancer Center; and the Centers for Disease Control and Prevention’s National Program of Cancer Registries, under agreement #U55/CCR921930-02 awarded to the Public Health Institute.
Footnotes
Conflict of interest
The authors declare that they have no conflict of interest.
References
- 1.American Cancer Society. Cancer Facts & Figures 2011. Atlanta: American Cancer Society; [Google Scholar]
- 2.Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. 2010;60:277–300. doi: 10.3322/caac.20073. [DOI] [PubMed] [Google Scholar]
- 3.Reeves GK, Pirie K, Beral V, Green J, Spencer E, Bull D. Cancer incidence and mortality in relation to body mass index in the Million Women Study: cohort study. BMJ. 2007;335:1134. doi: 10.1136/bmj.39367.495995.AE. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Genkinger JM, Spiegelman D, Anderson KE, Bernstein L, van den Brandt PA, Calle EE, et al. A pooled analysis of 14 cohort studies of anthropometric factors and pancreatic cancer risk. Int J Cancer. 2011;129:1708–1717. doi: 10.1002/ijc.25794. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Jiao L, Berrington de Gonzalez A, Hartge P, Pfeiffer RM, Park Y, Freedman DM, et al. Body mass index, effect modifiers, and risk of pancreatic cancer: a pooled study of seven prospective cohorts. Cancer Causes Control. 2010;21:1305–1314. doi: 10.1007/s10552-010-9558-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Arslan AA, Helzlsouer KJ, Kooperberg C, Shu XO, Steplowski E, Bueno-de-Mesquita HB, et al. Anthropometric measures, body mass index, and pancreatic cancer: a pooled analysis from the Pancreatic Cancer Cohort Consortium (PanScan) Arch Intern Med. 2010;170:791–802. doi: 10.1001/archinternmed.2010.63. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Stevens RJ, Roddam AW, Spencer EA, Pirie KL, Reeves GK, Green J, et al. Factors associated with incident and fatal pancreatic cancer in a cohort of middle-aged women. Int J Cancer. 2009;124:2400–2405. doi: 10.1002/ijc.24196. [DOI] [PubMed] [Google Scholar]
- 8.Coughlin SS, Calle EE, Patel AV, Thun MJ. Predictors of pancreatic cancer mortality among a large cohort of United States adults. Cancer Causes Control. 2000;11:915–923. doi: 10.1023/a:1026580131793. [DOI] [PubMed] [Google Scholar]
- 9.Calle EE, Rodriguez C, Walker-Thurmond K, Thun MJ. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N Engl J Med. 2003;348:1625–1638. doi: 10.1056/NEJMoa021423. [DOI] [PubMed] [Google Scholar]
- 10.Li D, Morris JS, Liu J, Hassan MM, Day RS, Bondy ML, et al. Body mass index and risk, age of onset, and survival in patients with pancreatic cancer. Jama. 2009;301:2553–2562. doi: 10.1001/jama.2009.886. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Olson SH, Chou JF, Ludwig E, O'Reilly E, Allen PJ, Jarnagin WR, et al. Allergies, obesity, other risk factors and survival from pancreatic cancer. Int J Cancer. 2010;127:2412–2419. doi: 10.1002/ijc.25240. [DOI] [PubMed] [Google Scholar]
- 12.McWilliams RR, Matsumoto ME, Burch PA, Kim GP, Halfdanarson TR, de Andrade M, et al. Obesity adversely affects survival in pancreatic cancer patients. Cancer. 2010;116:5054–5062. doi: 10.1002/cncr.25465. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Benns M, Woodall C, Scoggins C, McMasters K, Martin R. The impact of obesity on outcomes following pancreatectomy for malignancy. Ann Surg Oncol. 2009;16:2565–2569. doi: 10.1245/s10434-009-0573-7. [DOI] [PubMed] [Google Scholar]
- 14.Williams TK, Rosato EL, Kennedy EP, Chojnacki KA, Andrel J, Hyslop T, et al. Impact of obesity on perioperative morbidity and mortality after pancreaticoduodenectomy. J Am Coll Surg. 2009;208:210–217. doi: 10.1016/j.jamcollsurg.2008.10.019. [DOI] [PubMed] [Google Scholar]
- 15.Noun R, Riachy E, Ghorra C, Yazbeck T, Tohme C, Abboud B, et al. The impact of obesity on surgical outcome after pancreaticoduodenectomy. Jop. 2008;9:468–476. [PubMed] [Google Scholar]
- 16.House MG, Fong Y, Arnaoutakis DJ, Sharma R, Winston CB, Protic M, et al. Preoperative predictors for complications after pancreaticoduodenectomy: impact of BMI and body fat distribution. J Gastrointest Surg. 2008;12:270–278. doi: 10.1007/s11605-007-0421-7. [DOI] [PubMed] [Google Scholar]
- 17.Fleming JB, Gonzalez RJ, Petzel MQ, Lin E, Morris JS, Gomez H, et al. Influence of obesity on cancer-related outcomes after pancreatectomy to treat pancreatic adenocarcinoma. Arch Surg. 2009;144:216–221. doi: 10.1001/archsurg.2008.580. [DOI] [PubMed] [Google Scholar]
- 18.Balentine CJ, Enriquez J, Fisher W, Hodges S, Bansal V, Sansgiry S, et al. Intra-abdominal fat predicts survival in pancreatic cancer. J Gastrointest Surg. 2010;14:1832–1837. doi: 10.1007/s11605-010-1297-5. [DOI] [PubMed] [Google Scholar]
- 19.Khan S, Sclabas G, Reid-Lombardo K, Sarr MG, Nagorney D, Kendrick ML, et al. Does body mass index/morbid obesity influence outcome in patients who undergo pancreatoduodenectomy for pancreatic adenocarcinoma? J Gastrointest Surg. 2010;14:1820–1825. doi: 10.1007/s11605-010-1285-9. [DOI] [PubMed] [Google Scholar]
- 20.Tsai S, Choti MA, Assumpcao L, Cameron JL, Gleisner AL, Herman JM, et al. Impact of obesity on perioperative outcomes and survival following pancreaticoduodenectomy for pancreatic cancer: a large single-institution study. J Gastrointest Surg. 2010;14:1143–1150. doi: 10.1007/s11605-010-1201-3. [DOI] [PubMed] [Google Scholar]
- 21.Gong Z, Holly EA, Bracci PM. Survival in Population-based Pancreatic Cancer Patients: San Francisco Bay Area: 1995–1999. Am J Epidemiol. 2011;174:1373–1381. doi: 10.1093/aje/kwr267. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Holly EA, Eberle CA, Bracci PM. Prior history of allergies and pancreatic cancer in the San Francisco Bay area. Am J Epidemiol. 2003;158:432–441. doi: 10.1093/aje/kwg174. [DOI] [PubMed] [Google Scholar]
- 23.Cox DR. Regression models with life-tables (with discussion) J Roy. Statistic Soc: Series B. 1972;34:187–220. [Google Scholar]
- 24.Ramsey AM, Martin RC. Body Mass Index and Outcomes from Pancreatic Resection: a Review and Meta-analysis. J Gastrointest Surg. 2011;15:1633–1642. doi: 10.1007/s11605-011-1502-1. [DOI] [PubMed] [Google Scholar]
- 25.Ben Q, Xu M, Ning X, Liu J, Hong S, Huang W, et al. Diabetes mellitus and risk of pancreatic cancer: A meta-analysis of cohort studies. Eur J Cancer. 2011;47:1928–1937. doi: 10.1016/j.ejca.2011.03.003. [DOI] [PubMed] [Google Scholar]
- 26.Li D, Tang H, Hassan MM, Holly EA, Bracci PM, Silverman DT. Diabetes and risk of pancreatic cancer: a pooled analysis of three large case-control studies. Cancer Causes Control. 2011;22:189–197. doi: 10.1007/s10552-010-9686-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Lynch SM, Vrieling A, Lubin JH, Kraft P, Mendelsohn JB, Hartge P, et al. Cigarette smoking and pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium. Am J Epidemiol. 2009;170:403–413. doi: 10.1093/aje/kwp134. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Ansary-Moghaddam A, Huxley R, Barzi F, Lawes C, Ohkubo T, Fang X, et al. The effect of modifiable risk factors on pancreatic cancer mortality in populations of the Asia-Pacific region. Cancer Epidemiol Biomarkers Prev. 2006;15:2435–2440. doi: 10.1158/1055-9965.EPI-06-0368. [DOI] [PubMed] [Google Scholar]
- 29.Wang F, Gupta S, Holly EA. Diabetes mellitus and pancreatic cancer in a population-based case-control study in the San Francisco Bay Area, California. Cancer Epidemiol Biomarkers Prev. 2006;15:1458–1463. doi: 10.1158/1055-9965.EPI-06-0188. [DOI] [PubMed] [Google Scholar]
- 30.Bosetti C, Lucenteforte E, Silverman DT, et al. Cigarette smoking and pancreatic cancer: an analysis from the International Pancreatic Cancer Case-Control Consortium (Panc4) Ann Oncol. 2011;22:1420–1426. doi: 10.1093/annonc/mdq613. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Tranah GJ, Holly EA, Wang F, Bracci PM. Cigarette, cigar and pipe smoking, passive smoke exposure, and risk of pancreatic cancer: a population-based study in the San Francisco Bay Area. BMC cancer. 2011;11:138. doi: 10.1186/1471-2407-11-138. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Godsland IF. Insulin resistance and hyperinsulinaemia in the development and progression of cancer. Clin Sci (Lond) 2010;118:315–332. doi: 10.1042/CS20090399. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Kahn BB, Flier JS. Obesity and insulin resistance. J Clin Invest. 2000;106:473–481. doi: 10.1172/JCI10842. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Kahn SE, Hull RL, Utzschneider KM. Mechanisms linking obesity to insulin resistance and type 2 diabetes. Nature. 2006;444:840–846. doi: 10.1038/nature05482. [DOI] [PubMed] [Google Scholar]
- 35.Mossner J, Logsdon CD, Goldfine ID, Williams JA. Do insulin and the insulin like growth factors (IGFs) stimulate growth of the exocrine pancreas? Gut. 1987;28(Suppl):51–55. doi: 10.1136/gut.28.suppl.51. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Margetic S, Gazzola C, Pegg GG, Hill RA. Leptin: a review of its peripheral actions and interactions. Int J Obes Relat Metab Disord. 2002;26:1407–1433. doi: 10.1038/sj.ijo.0802142. [DOI] [PubMed] [Google Scholar]
- 37.White PB, True EM, Ziegler KM, Wang SS, Swartz-Basile DA, Pitt HA, et al. Insulin, leptin, and tumoral adipocytes promote murine pancreatic cancer growth. J Gastrointest Surg. 2010;14:1888–1893. doi: 10.1007/s11605-010-1349-x. discussion 1893–1894. [DOI] [PubMed] [Google Scholar]
- 38.Becker S, Dossus L, Kaaks R. Obesity related hyperinsulinaemia and hyperglycaemia and cancer development. Arch Physiol Biochem. 2009;115:86–96. doi: 10.1080/13813450902878054. [DOI] [PubMed] [Google Scholar]
- 39.Skibola CF, Holly EA, Forrest MS, Hubbard A, Bracci PM, Skibola DR, et al. Body mass index, leptin and leptin receptor polymorphisms, and non-hodgkin lymphoma. Cancer Epidemiol Biomarkers Prev. 2004;13:779–786. [PubMed] [Google Scholar]
- 40.Ramos EJ, Xu Y, Romanova I, et al. Is obesity an inflammatory disease? Surgery. 2003;134:329–335. doi: 10.1067/msy.2003.267. [DOI] [PubMed] [Google Scholar]
- 41.Aggarwal BB, Shishodia S, Sandur SK, Pandey MK, Sethi G. Inflammation and cancer: how hot is the link? Biochem Pharmacol. 2006;72:1605–1621. doi: 10.1016/j.bcp.2006.06.029. [DOI] [PubMed] [Google Scholar]
- 42.Kulbe H, Thompson R, Wilson JL, Robinson S, Hagemann T, Fatah R, et al. The inflammatory cytokine tumor necrosis factor-alpha generates an autocrine tumor-promoting network in epithelial ovarian cancer cells. Cancer Res. 2007;67:585–592. doi: 10.1158/0008-5472.CAN-06-2941. [DOI] [PMC free article] [PubMed] [Google Scholar]