Background:

Leukocyte telomere length has been associated with risk of subsequent pancreatic cancer. Few prospective studies have evaluated the association of prediagnostic leukocyte telomere length with pancreatic cancer survival.

Methods:

We prospectively examined the association of prediagnostic leukocyte telomere length with overall survival (OS) time among 423 participants diagnosed with pancreatic adenocarcinoma between 1984 and 2008 within the Health Professionals Follow-up Study, Nurses' Health Study, Physicians' Health Study, and Women's Health Initiative. We measured prediagnostic leukocyte telomere length in banked blood samples using quantitative PCR. Cox proportional hazards models were used to estimate HRs for OS with adjustment for potential confounders. We also evaluated 10 SNPs at the telomerase reverse transcriptase locus.

Results:

Shorter prediagnostic leukocyte telomere length was associated with reduced OS among patients with pancreatic cancer (Ptrend = 0.04). The multivariable-adjusted HR for OS comparing the lowest with highest quintiles of leukocyte telomere length was 1.39 (95% confidence interval, 1.01–1.93), corresponding to a 3-month difference in median OS time. In an analysis excluding cases with blood collected within 2 years of cancer diagnosis, the association was moderately stronger (HR, 1.55; 95% confidence interval, 1.09–2.21; comparing the lowest with highest quintiles; Ptrend = 0.01). No prognostic association or effect modification for the prognostic association of prediagnostic leukocyte telomere length was noted in relation to the studied SNPs.

Conclusions:

Prediagnostic leukocyte telomere length was associated with pancreatic cancer survival.

Impact:

Prediagnostic leukocyte telomere length can be a prognostic biomarker in pancreatic cancer.

This article is featured in Highlights of This Issue, p. 1769

Pancreatic cancer currently represents the third leading cause of cancer-related death in the United States (1). Despite increased efficacy of newer chemotherapy programs (2–4), patient prognosis remains poor with short survival times and an overall 5-year survival rate of <10% (1). A better understanding of prognostic factors may help develop novel therapeutic approaches to improve survival of patients with pancreatic cancer.

Telomeres are tandem repeats of TTAGGG nucleotides located at the ends of linear chromosomes, which are essential to maintain genome stability during cell division (5). Highly shortened telomeres can cause chromosomal instability and lead to cell immortalization and accumulation of genetic aberrations potentially contributing to carcinogenesis (5–7). Telomere shortening occurs early in pancreatic carcinogenesis (8–10). Telomerase reverse transcriptase is the catalytic subunit of telomerase, which plays a key role in maintaining telomere length, and genetic variants at the telomerase reverse transcriptase (TERT) locus are associated with pancreatic cancer risk (11–14).

Leukocyte telomere shortening may not only represent shortening of telomeres in the entire body, but also serve as a surrogate for long-term exposure to cancer risk factors including smoking, diabetes mellitus, and adiposity (15, 16). Epidemiologic studies suggest that prediagnostic leukocyte telomere length is associated with risk of various cancer types including pancreatic ductal adenocarcinoma (11, 16, 17). Further evidence points to impaired maintenance of leukocyte telomeres as a prognostic factor for cancer progression after diagnosis (18–21). Although recent studies support an association between shorter leukocyte telomere length and poorer survival among cancer patients overall (22, 23), the prognostic associations observed were inconsistent across studies, and only a small number of patients with pancreatic cancer have been evaluated.

To test the hypothesis that prediagnostic leukocyte telomere length might be associated with survival among patients with pancreatic ductal adenocarcinoma, we conducted a large prospective study using four U.S. cohorts that included banked blood samples and detailed information on lifestyle and clinical factors. We further examined SNPs at the TERT locus that have been associated with risk of multiple cancers (24) and their interactions with prediagnostic leukocyte telomere length, in relation to survival among patients with pancreatic cancer.

Study population

We evaluated pancreatic cancer cases from four U.S. prospective cohort studies: Health Professionals Follow-up Study (HPFS), Nurses' Health Study (NHS), Physicians' Health Study (PHS), and Women's Health Initiative (WHI; refs. 25, 26). The HPFS enrolled 51,529 male health professionals ages 40 to 75 years in 1986 (27–29). The NHS enrolled 121,700 female nurses ages 30 to 55 years in 1976 (28–30). The PHS is a randomized clinical trial of aspirin and β-carotene that enrolled 22,071 male physicians ages 40 to 84 years in 1982 (31). After completion of the randomized components in 1995, study participants have been followed as an observational cohort. The WHI Observational Study enrolled 93,676 postmenopausal women ages 50 to 79 years between 1994 and 1998 (32). In all studies, participants have completed regular mailed questionnaires (25, 26). Written-informed consent was obtained from all participants in each cohort. This study was conducted in accordance with the Declaration of Helsinki, and after approval by the Human Research Committee at Brigham and Women's Hospital (Boston, MA).

We included 423 patients diagnosed with pancreatic cancer between 1984 and 2008 with available prediagnostic blood samples (Table 1). As previously described (25, 26), incident pancreatic cancer cases were identified by self-report or during follow-up of participants' deaths. Physicians blinded to exposure status confirmed the diagnosis of pancreatic cancer by review of medical records, death certificates, or cancer registry data. Deaths were ascertained from next of kin, the U.S. postal service, or the National Death Index; this method has been shown to capture >98% of deaths (33). Exclusion criteria included patients with nonadenocarcinoma histology or lack of available survival data.

Table 1.

Baseline characteristics of patients with pancreatic cancer

CharacteristicaPancreatic cancer cases (n = 423)
Age at blood collection, years 64.7 ± 8.8 
Age at cancer diagnosis, years 71.9 ± 7.8 
Female sex 283 (66.9) 
Race/ethnicity 
 White 369 (87.2) 
 Black 16 (3.8) 
 Other 10 (2.4) 
 Unknown 28 (6.6) 
Year of diagnosis 
 1984–2000 219 (51.8) 
 2001–2008 204 (48.2) 
Median time from blood collection to cancer diagnosis, years 6.1 
Smoking status 
 Never 183 (43.2) 
 Past 179 (42.3) 
 Current 57 (13.5) 
 Unknown 4 (1.0) 
BMI, kg/m2 26.5 ± 5.1 
Physical activity, MET-hours/week 17.9 ± 22.9 
History of diabetes 28 (6.6) 
Cancer stage at diagnosis 
 Localized 53 (12.5) 
 Locally advanced 103 (24.4) 
 Metastatic 194 (45.8) 
 Unknown 73 (17.3) 
Median survival time by stage, months 
 Localized 16 
 Locally advanced 10 
 Metastatic 
CharacteristicaPancreatic cancer cases (n = 423)
Age at blood collection, years 64.7 ± 8.8 
Age at cancer diagnosis, years 71.9 ± 7.8 
Female sex 283 (66.9) 
Race/ethnicity 
 White 369 (87.2) 
 Black 16 (3.8) 
 Other 10 (2.4) 
 Unknown 28 (6.6) 
Year of diagnosis 
 1984–2000 219 (51.8) 
 2001–2008 204 (48.2) 
Median time from blood collection to cancer diagnosis, years 6.1 
Smoking status 
 Never 183 (43.2) 
 Past 179 (42.3) 
 Current 57 (13.5) 
 Unknown 4 (1.0) 
BMI, kg/m2 26.5 ± 5.1 
Physical activity, MET-hours/week 17.9 ± 22.9 
History of diabetes 28 (6.6) 
Cancer stage at diagnosis 
 Localized 53 (12.5) 
 Locally advanced 103 (24.4) 
 Metastatic 194 (45.8) 
 Unknown 73 (17.3) 
Median survival time by stage, months 
 Localized 16 
 Locally advanced 10 
 Metastatic 

Abbreviation: MET, metabolic equivalent of task.

aData are presented as mean ± SD or number of patients (%), unless otherwise noted.

Data collection

As previously described (25, 26), clinical data were collected from the prospective cohort studies. Information on demographics, lifestyle habits, and medical history was obtained from questionnaires preceding blood collection in HPFS and NHS, and from baseline questionnaires at enrollment (coinciding with blood collection) in PHS and WHI. In all cohorts, data were available for age at blood collection, sex, race/ethnicity, smoking status, body mass index (BMI), physical activity, and history of diabetes mellitus. Date of pancreatic cancer diagnosis and stage at diagnosis were determined through physician review of medical records. Cancer stage was classified as localized (amenable to surgical resection); locally advanced (unresectable due to extrapancreatic extension but no distant metastases); or metastatic.

Measurement of leukocyte telomere length

As previously described (25, 26), blood samples were collected from 18,225 men in HPFS from 1993 to 1995, 32,826 women in NHS from 1989 to 1990, 14,916 men in PHS from 1982 to 1984, and 93,676 women in WHI from 1994 to 1998. All blood samples have been stored in well-monitored freezers. Procedures for collection, transportation, and storage of blood samples in these cohorts have been detailed elsewhere (34).

As previously described (11, 35), relative leukocyte telomere length was measured by a quantitative real-time PCR-based assay. Genomic DNA was extracted from peripheral leukocytes using QIAamp 96 DNA Blood Kit (Qiagen), and was quantified using the PicoGreen reagent and 96-well spectrophotometer (Molecular Devices). The ratio of telomere repeat copy number to a single-gene copy number (T/S ratio) was assayed in triplicate using a modified high-throughput quantitative PCR assay (7900HT Sequence Detection System; Applied Biosystems; refs. 35, 36). Relative telomere length was calculated as exponentiated T/S ratio corrected for a reference sample. Coefficients of variation (CV) within triplicates of telomere and single-gene assays were 0.6% and 0.5%, respectively, and CVs for the exponentiated T/S ratio were 12.9% (11).

Selection and genotyping of SNPs at the TERT locus

As previously described (11), we genotyped four SNPs at the TERT gene locus which were associated with cancer risk: rs401681 (pancreatic cancer; ref. 14), rs402710 (lung cancer; ref. 37), rs2736100 (lung cancer and glioma; refs. 37, 38), and rs2853676 (glioma; ref. 38). DNA was extracted from pooled blood samples as described above, and whole-genome amplification was carried out using the Genomiphi Kit (GE Healthcare). All genotyping was performed using a custom-designed Illumina Golden Gate genotyping assay at Partners HealthCare Center for Personalized Genetic Medicine. Replicate samples included for quality control (n = 44) had mean genotype concordance of 97.2% across the four SNPs (11). No SNP deviated from the Hardy–Weinberg equilibrium at P < 0.01. As previously described (11), we additionally obtained data on six independent risk loci at the TERT locus (rs451360, rs2736098, rs2853677, rs7726159, rs10069690, and rs13172201; ref. 24) for 320 pancreatic cancer cases which were included in recent genome-wide association studies of pancreatic cancer (PanScan studies; refs. 13, 14). Genotyping and imputation methods in the PanScan studies were described previously (13).

Statistical analysis

We examined the association between prediagnostic leukocyte telomere length and overall survival among patients with pancreatic cancer. Telomeres shorten biologically with increasing age, and thus, age-adjusted leukocyte telomere length was computed by subtracting the predicted telomere length from the observed telomere length for each patient with pancreatic cancer (39–41). Considering potential alterations in leukocyte telomere length preceding pancreatic cancer diagnosis (11, 16, 17), we computed age-adjusted leukocyte telomere length for pancreatic cancer cases based on leukocyte telomere length among cancer-free individuals. In our previous nested case–control study (11), we randomly selected up to three controls for each pancreatic cancer case, matching on year of birth, prospective cohort (also matched on sex), smoking status, fasting status at blood collection, and month/year of blood collection. Using 936 controls matched to the current study population of 423 cases, we conducted a linear regression on leukocyte telomere length according to age at blood collection, and used the coefficients to calculate predicted leukocyte telomere length for patients with pancreatic cancer. We defined quintiles of age-adjusted prediagnostic leukocyte telomere length among all patients with pancreatic cancer. Overall survival time was calculated as time from pancreatic cancer diagnosis to death or last follow-up, whichever came first.

In our primary analyses, we pooled data from the four cohort studies and used Cox proportional hazards regression models to calculate HR and 95% confidence intervals (CI) for overall mortality by quintiles of age-adjusted leukocyte telomere length before pancreatic cancer diagnosis. Tests for trend were conducted by entering quintile-specific median values as a continuous variable in Cox regression models and evaluating the Wald test. The multivariable Cox regression models were adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown; ref. 42), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2; ref. 43), diabetes status (yes or no; ref. 44), and cancer stage (localized, locally advanced, metastatic, or unknown). Subsequently, we further adjusted for time from blood collection to cancer diagnosis (<5, 5–10, or ≥10 years). We examined a possible nonlinear association between prediagnostic leukocyte telomere length and pancreatic cancer survival using restricted cubic splines (45). The assumption of proportionality of hazards was satisfied by evaluating a time-dependent covariate, which was the cross-product of quintile-specific median values of prediagnostic leukocyte telomere length (continuous) and survival time (P = 0.69). We estimated median overall survival time and survival curves adjusted for covariates by using direct adjusted survival estimation (46, 47). This method uses the Cox regression model to estimate survival probabilities at each time-point for each individual and then averages them to obtain an overall survival estimate. We examined the heterogeneity in the association of prediagnostic leukocyte telomere length with pancreatic cancer survival between the cohorts using Cochran's Q statistic (48). We computed a pooled HR for overall mortality by a standard deviation decrease in prediagnostic leukocyte telomere length using the DerSimonian and Laird random-effects model (49). As exploratory analyses, we assessed whether the association of prediagnostic leukocyte telomere length with pancreatic cancer survival differed by time between measurements of leukocyte telomere length and cancer diagnosis. We also performed analyses stratified by sex, smoking status, BMI, cancer stage at diagnosis, and SNPs at the TERT locus associated with leukocyte telomere length (11, 50, 51). We assessed statistical interaction by entering main effect terms and the cross-product of leukocyte telomere length quartiles and a stratification variable into the model and evaluating likelihood ratio test. Given limited numbers of patients in strata of covariates of interest, we used quartiles of prediagnostic leukocyte telomere length in stratified analyses. As exploratory analyses, we examined the association of SNPs at the TERT locus with patient survival by entering each 3-level genotype as a continuous variable into multivariable-adjusted Cox regression model (additive model).

Two-sided P values < 0.05 were considered statistically significant in all analyses. All statistical analyses were performed using SAS statistical software (version 9.4, SAS Institute).

Characteristics of 423 patients diagnosed with incident pancreatic ductal adenocarcinoma overall and by cohort are summarized in Table 1 and Supplementary Table S1, respectively. The median time from blood collection to pancreatic cancer diagnosis was 6.1 years. Prediagnostic leukocyte telomere length was inversely associated with age at blood collection (Spearman r = -0.14, P = 0.004). Among patients with available data on cancer stage (n = 350), 15.1%, 29.4%, and 55.5% of patients had localized, locally advanced, and metastatic disease, respectively. Prediagnostic leukocyte telomere length was not associated with cancer stage at diagnosis (Supplementary Table S2). In the combined cohort, median adjusted survival time was 16, 10, and 4 months for localized, locally advanced, and metastatic disease, respectively. At the end of follow-up, 401 pancreatic cancer cases (94.8% of combined cohort) were deceased.

Shorter prediagnostic leukocyte telomere length was associated with reduced survival time of pancreatic cancer patients (Ptrend = 0.04, Table 2 and Fig. 1). The patients in the lowest versus highest quintiles had an HR for overall mortality of 1.39 (95% CI, 1.01–1.93), corresponding to a 3-month shorter median survival. In the multivariable model further adjusted for time from blood collection to cancer diagnosis, our findings remained largely unchanged (Table 2). We fitted a restricted cubic spline curve for prediagnostic leukocyte telomere length in relation to pancreatic cancer survival, which did not suggest a nonlinear association (Pnonlinearity = 0.59). Taking into account the possible influence of subclinical malignancy on leukocyte telomere length, we conducted a sensitivity analysis excluding patients who were diagnosed with pancreatic cancer within 2 years of blood collection, which yielded a modestly stronger association between prediagnostic leukocyte telomere length and patient survival (Ptrend = 0.01; Supplementary Table S3). We did not observe significant heterogeneity in the prognostic association of prediagnostic leukocyte telomere length between patients in the four cohorts (Pheterogeneity = 0.95, Fig. 2).

Table 2.

Overall survival among patients with pancreatic cancer by quintiles of prediagnostic leukocyte telomere length

Leukocyte telomere length
Q5 (longest)Q4Q3Q2Q1 (shortest)Ptrendc
Person-months 1,266 777 886 721 858  
Number of cases/deaths 84/79 85/78 85/80 85/82 84/82  
Median survival, months  
Age-adjusted HR (95% CI) 1 (referent) 1.27 (0.93–1.74) 1.29 (0.94–1.76) 1.42 (1.04–1.94) 1.29 (0.94–1.76) 0.06 
Multivariable HRa (95% CI) 1 (referent) 1.20 (0.87–1.66) 1.08 (0.79–1.49) 1.36 (0.98–1.88) 1.39 (1.01–1.93) 0.04 
Multivariable HRb (95% CI) 1 (referent) 1.18 (0.85–1.63) 1.07 (0.78–1.48) 1.37 (0.99–1.91) 1.38 (0.99–1.91) 0.04 
Leukocyte telomere length
Q5 (longest)Q4Q3Q2Q1 (shortest)Ptrendc
Person-months 1,266 777 886 721 858  
Number of cases/deaths 84/79 85/78 85/80 85/82 84/82  
Median survival, months  
Age-adjusted HR (95% CI) 1 (referent) 1.27 (0.93–1.74) 1.29 (0.94–1.76) 1.42 (1.04–1.94) 1.29 (0.94–1.76) 0.06 
Multivariable HRa (95% CI) 1 (referent) 1.20 (0.87–1.66) 1.08 (0.79–1.49) 1.36 (0.98–1.88) 1.39 (1.01–1.93) 0.04 
Multivariable HRb (95% CI) 1 (referent) 1.18 (0.85–1.63) 1.07 (0.78–1.48) 1.37 (0.99–1.91) 1.38 (0.99–1.91) 0.04 

Abbreviation: Q1–5, quintiles 1–5.

aThe Cox proportional hazards regression model was adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown).

bFurther adjusted for time from blood collection to cancer diagnosis (<5, 5–10, or ≥10 years).

cPtrend was calculated by entering quintile-specific median values of leukocyte telomere length (continuous) in the Cox regression model.

Figure 1.

Overall survival curves of patients with pancreatic cancer by prediagnostic leukocyte telomere length [quintile 1 (shortest) vs. quintile 5 (longest)]. Survival probabilities were adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown). Q1, quintile 1; Q5, quintile 5.

Figure 1.

Overall survival curves of patients with pancreatic cancer by prediagnostic leukocyte telomere length [quintile 1 (shortest) vs. quintile 5 (longest)]. Survival probabilities were adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown). Q1, quintile 1; Q5, quintile 5.

Close modal
Figure 2.

Forest plot and meta-analysis of HRs for overall mortality per SD decrease in prediagnostic leukocyte telomere length among patients with pancreatic cancer in the HPFS, NHS, PHS, and WHI. Squares and horizontal lines indicate cohort-specific multivariable-adjusted HRs and 95% CIs, respectively. Area of the square reflects cohort-specific weight (inverse of the variance). Diamond indicates pooled multivariable-adjusted HR (center) and 95% CI (width). HRs were adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown).

Figure 2.

Forest plot and meta-analysis of HRs for overall mortality per SD decrease in prediagnostic leukocyte telomere length among patients with pancreatic cancer in the HPFS, NHS, PHS, and WHI. Squares and horizontal lines indicate cohort-specific multivariable-adjusted HRs and 95% CIs, respectively. Area of the square reflects cohort-specific weight (inverse of the variance). Diamond indicates pooled multivariable-adjusted HR (center) and 95% CI (width). HRs were adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown).

Close modal

In exploratory analyses, we examined the temporal association of prediagnostic leukocyte telomere length with pancreatic cancer survival (Table 3). The association was stronger in patients whose blood samples were collected ≥6.1 years (median) before cancer diagnosis (Ptrend = 0.03); in these patients, the HR for overall mortality comparing extreme quartiles of leukocyte telomere length was 1.60 (95% CI, 1.02–2.50).

Table 3.

Overall survival among patients with pancreatic cancer by quartiles of prediagnostic leukocyte telomere length, stratified by time from blood collection to cancer diagnosis

Multivariable HR (95% CI) for quartiles of leukocyte telomere lengthb
Time from blood collection to cancer diagnosisaNumber of casesQ4 (longest)Q3Q2Q1 (shortest)Ptrendc
0 to <6.1 years 212 1 (referent) 1.05 (0.69–1.59) 0.79 (0.52–1.21) 1.10 (0.71–1.69) 0.96 
≥6.1 years 211 1 (referent) 1.11 (0.74–1.68) 1.42 (0.93–2.17) 1.60 (1.02–2.50) 0.03 
Multivariable HR (95% CI) for quartiles of leukocyte telomere lengthb
Time from blood collection to cancer diagnosisaNumber of casesQ4 (longest)Q3Q2Q1 (shortest)Ptrendc
0 to <6.1 years 212 1 (referent) 1.05 (0.69–1.59) 0.79 (0.52–1.21) 1.10 (0.71–1.69) 0.96 
≥6.1 years 211 1 (referent) 1.11 (0.74–1.68) 1.42 (0.93–2.17) 1.60 (1.02–2.50) 0.03 

Abbreviation: Q1–4, quartiles 1–4.

aDichotomized by the median value.

bThe Cox proportional hazards regression model was adjusted for age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown).

cPtrend was calculated by entering quartile-specific median values of leukocyte telomere length (continuous) in the Cox regression model.

In stratified analyses, we observed no statistically significant effect modification for the prognostic association of prediagnostic leukocyte telomere length by sex, smoking status, BMI, or cancer stage (all Pinteraction > 0.25, Table 4).

Table 4.

Overall survival among patients with pancreatic cancer by quartiles of prediagnostic leukocyte telomere length, stratified by covariates

Multivariable HR (95% CI) for quartiles of leukocyte telomere lengtha
Stratification variableNumber of casesQ4 (longest)Q3Q2Q1 (shortest)Pinteractionb
Sex      0.87 
 Female 283 1 (referent) 1.15 (0.81–1.63) 1.29 (0.92–1.82) 1.30 (0.88–1.92)  
 Male 140 1 (referent) 1.00 (0.56–1.77) 1.07 (0.59–1.94) 1.23 (0.73–2.06)  
Smoking status      0.64 
 Never 183 1 (referent) 1.00 (0.62–1.63) 0.93 (0.60–1.45) 0.98 (0.61–1.60)  
 Past 179 1 (referent) 0.87 (0.56–1.36) 1.73 (1.09–2.77) 1.46 (0.92–2.31)  
 Current 57 1 (referent) 3.07 (0.98–9.62) 0.81 (0.27–2.45) 1.01 (0.32–3.16)  
BMI      0.99 
 <30 kg/m2 341 1 (referent) 1.04 (0.75–1.43) 1.20 (0.86–1.67) 1.23 (0.89–1.71)  
 ≥30 kg/m2 82 1 (referent) 0.90 (0.41–1.99) 1.16 (0.55–2.43) 1.32 (0.58–3.01)  
Cancer stage      0.26 
 Localized 53 1 (referent) 1.48 (0.43–5.14) 1.44 (0.55–3.74) 1.67 (0.67–4.14)  
 Locally advanced 103 1 (referent) 0.88 (0.49–1.60) 1.04 (0.54–2.03) 1.41 (0.70–2.81)  
 Metastatic 194 1 (referent) 0.99 (0.65–1.52) 0.94 (0.61–1.47) 1.07 (0.67–1.71)  
Multivariable HR (95% CI) for quartiles of leukocyte telomere lengtha
Stratification variableNumber of casesQ4 (longest)Q3Q2Q1 (shortest)Pinteractionb
Sex      0.87 
 Female 283 1 (referent) 1.15 (0.81–1.63) 1.29 (0.92–1.82) 1.30 (0.88–1.92)  
 Male 140 1 (referent) 1.00 (0.56–1.77) 1.07 (0.59–1.94) 1.23 (0.73–2.06)  
Smoking status      0.64 
 Never 183 1 (referent) 1.00 (0.62–1.63) 0.93 (0.60–1.45) 0.98 (0.61–1.60)  
 Past 179 1 (referent) 0.87 (0.56–1.36) 1.73 (1.09–2.77) 1.46 (0.92–2.31)  
 Current 57 1 (referent) 3.07 (0.98–9.62) 0.81 (0.27–2.45) 1.01 (0.32–3.16)  
BMI      0.99 
 <30 kg/m2 341 1 (referent) 1.04 (0.75–1.43) 1.20 (0.86–1.67) 1.23 (0.89–1.71)  
 ≥30 kg/m2 82 1 (referent) 0.90 (0.41–1.99) 1.16 (0.55–2.43) 1.32 (0.58–3.01)  
Cancer stage      0.26 
 Localized 53 1 (referent) 1.48 (0.43–5.14) 1.44 (0.55–3.74) 1.67 (0.67–4.14)  
 Locally advanced 103 1 (referent) 0.88 (0.49–1.60) 1.04 (0.54–2.03) 1.41 (0.70–2.81)  
 Metastatic 194 1 (referent) 0.99 (0.65–1.52) 0.94 (0.61–1.47) 1.07 (0.67–1.71)  

Abbreviation: Q1–4, quartiles 1–4.

aThe Cox proportional hazards regression model was adjusted for the following covariates except for the stratification variable: age at diagnosis (continuous), cohort (HPFS, NHS, PHS, or WHI; also adjusted for sex), race/ethnicity (white, black, other, or unknown), year of diagnosis (continuous), smoking status (never, past, current, or unknown), BMI (<25, 25–29.9, 30–34.9, or ≥35 kg/m2), diabetes status (yes or no), and cancer stage (localized, locally advanced, metastatic, or unknown).

bPinteraction was calculated by entering a cross-product term of quartile-specific median values of leukocyte telomere length (continuous) and stratification variable in the Cox regression model and evaluating likelihood ratio tests.

In additional exploratory analyses, we examined patient survival in relation to 10 SNPs at the TERT gene locus. We observed no association of those SNPs with patient survival (all P > 0.15, Supplementary Table S4). We observed no statistically significant effect modification for the prognostic association of prediagnostic leukocyte telomere length by three SNPs at the TERT locus associated with leukocyte telomere length (Pinteraction > 0.36, Supplementary Table S5).

In the current pooled study conducted within four U.S. prospective cohorts, we found that shorter leukocyte telomere length before diagnosis of pancreatic cancer was associated with reduced patient survival. Specifically, patients with the shortest prediagnostic leukocyte telomere length had a 3-month reduction in median survival. Interestingly, leukocyte telomere length appeared to be more strongly associated with survival among patients with pancreatic cancer when measured more than 6 years before cancer diagnosis. Our findings raise the possibility that long-term impaired telomere maintenance preceding pancreatic cancer diagnosis may affect patient overall survival.

Evidence suggests that leukocyte telomere length may be associated with survival among cancer patients (22, 23), but data on pancreatic cancer are limited. In a Danish prospective cohort study involving 47,102 participants, prediagnostic leukocyte telomere length was not associated with survival among 124 patients with pancreatic cancer (HR for a 1-kilobase decrease in telomere length, 1.02; 95% CI, 0.83–1.26; ref. 18). However, this study was limited by a small sample size of pancreatic cancer cases and lack of adjustment for potential confounding factors including smoking status (11, 15, 16). Given that the association of prediagnostic leukocyte telomere length and patient survival has not been universally observed across cancer types (18–23, 52–54), comprehensive analyses focusing on specific cancer types are warranted. The current study is the first prospective cohort study to provide evidence for an association between prediagnostic leukocyte telomere shortening and pancreatic cancer patient survival. Our results implicate telomere maintenance in the clinical course of pancreatic cancer after diagnosis, with potential therapeutic implications for this highly aggressive malignancy (55).

Telomere shortening and resultant chromosomal instability can occur in precursor lesions of pancreatic cancer, including pancreatic intraepithelial neoplasia and intraductal papillary mucinous neoplasm, and develop at increasing rates during progression from precursor lesions to invasive ductal carcinoma (8–10). The surrogacy of leukocyte telomere length for cellular aging, telomere length in pancreatic tissue, and exposure to cancer risk factors may underline the association of shorter prediagnostic leukocyte telomere length and reduced survival among patients with pancreatic cancer (15, 16). The dynamics of leukocyte telomere attrition may vary during the process of carcinogenesis (56), and notably, we found a stronger prognostic association of prediagnostic leukocyte telomere length measured at earlier time-points before pancreatic cancer diagnosis. These findings also implicate a potential latency period from initiation of impaired telomere maintenance to clinically significant alterations of pancreatic cancer characteristics. Further studies are needed to understand how leukocyte telomere shortening might modify the biology and thus clinical behavior of pancreatic cancer in human populations.

Our study has notable strengths, including a prospective study design and nearly complete follow-up (25, 26). The banked blood samples and extended follow-up time allowed for examination of prediagnostic leukocyte telomere shortening and pancreatic cancer survival while minimizing bias due to reverse causation. Importantly, our study population consisted of patients with all stages of pancreatic cancer who were diagnosed at hospitals throughout the United States, which increases the generalizability of our findings and minimizes selection bias. Within our cohorts, the median survival times for patients with pancreatic cancer were similar to those in the National Cancer Database (57), supporting the validity of our cohorts as a representative sample of pancreatic cancer patients in the United States. Prospectively collected data allowed us to rigorously adjust for potential confounders and to evaluate effect modification by other prognostic factors.

Our study has several limitations. We analyzed the length of leukocyte telomeres rather than that of telomeres in pancreatic tissue; nonetheless, telomere length in leukocytes is reasonably correlated with that in cells from different tissues (58–60) and is a readily available biomarker that can be measured from peripheral blood. Our cohort studies collected limited data on cancer treatments, and chemotherapy regimens for our patients were not known (25, 26). Nonetheless, prediagnostic leukocyte telomere length is unlikely to be associated with choice of treatment regimen, and chemotherapy options available during the study period were primarily limited to 5-fluorouracil/folinic acid or gemcitabine. In addition, our results remained largely unchanged after adjusting for year of cancer diagnosis and cancer stage, which are major determinants of treatment strategies. Similarly, though we cannot rule out the possibility of unmeasured confounding, our multivariable models included a variety of known and potential variables associated with pancreatic cancer survival, and this adjustment did not significantly alter our results. The sample size of the current study limits statistical power in subgroup analyses, including for stratified analyses by individual cohort studies and patient characteristics. Overall mortality was used as the primary study endpoint rather than pancreatic cancer–specific mortality, and leukocyte telomere length may be associated with overall mortality in the general population (61, 62). However, pancreatic cancer is a highly lethal malignancy, and the majority of patients die from this disease, such that overall mortality is considered a reasonable surrogate for clinical outcomes of pancreatic cancer. Finally, our study population predominantly consisted of white participants. Given evidence on a differential association of leukocyte telomere length with mortality outcomes by ethnicity (61, 62), our findings should be validated in a more racially diverse population.

In conclusion, shorter prediagnostic leukocyte telomere length was associated with worse clinical outcome in patients with pancreatic cancer from four large U.S. cohort studies. Although our findings require validation, this study suggests an important role of telomere shortening in patient survival after clinical diagnosis of pancreatic cancer.

K. Ng reports receiving commercial research grants from Celgene and Gilead. C.S. Fuchs is Director at CytomX Therapeutics; has ownership interest (including patents) in CytomX Therapeutics and Entrinsic Health; and is a consultant/advisory board member for Agios, Bain Capital, KEW, Merck, Merrimack Therapeutics, Pfizer, Sanofi, Taiho, Unum Therapeutics, Bayer, Celgene, Dicerna, Five Prime Therapeutics, Gilead Sciences, Eli Lilly, Entrinsic Health, and Genentech. No potential conflicts of interest were disclosed by the other authors.

The content is solely the responsibility of the authors and does not necessarily represent the official views of NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the article.

Conception and design: T. Hamada, C. Yuan, I. De Vivo, B.M. Wolpin

Development of methodology: T. Hamada, C. Yuan, Y. Bao, I. De Vivo

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): T. Hamada, C. Yuan, N. Khalaf, B.B. Cochrane, J.M. Gaziano, E.L. Giovannucci, J.E. Manson, H.D. Sesso, C.S. Fuchs, I. De Vivo

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): T. Hamada, C. Yuan, Y. Bao, M. Zhang, A. Babic, V. Morales-Oyarvide, E.L. Giovannucci, P. Kraft, K. Ng, H.D. Sesso, L.T. Amundadottir, I. De Vivo, S. Ogino, B.M. Wolpin

Writing, review, and/or revision of the manuscript: T. Hamada, C. Yuan, Y. Bao, N. Khalaf, A. Babic, V. Morales-Oyarvide, B.B. Cochrane, J.M. Gaziano, E.L. Giovannucci, P. Kraft, J.E. Manson, K. Ng, J.A. Nowak, T.E. Rohan, H.D. Sesso, M.J. Stampfer, L.T. Amundadottir, I. De Vivo, S. Ogino, B.M. Wolpin

Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): M. Zhang, B.B. Cochrane, P. Kraft, J.E. Manson, M.J. Stampfer

Study supervision: K. Ng, C.S. Fuchs, I. De Vivo, S. Ogino, B.M. Wolpin

The HPFS is supported by U.S. NIH grants UM1 CA167552 and U01 CA167552. The NHS is supported by NIH grants UM1 CA186107, P01 CA87969, and R01 CA49449. The PHS is supported by NIH grants R01 CA097193, R01 CA034944-03, R01 CA040360, R01 HL026490-03, and R01 HL034595-07. The WHI program is supported by the National Heart, Lung, and Blood Institute, NIH, and U.S. Department of Health and Human Services through contracts HHSN268201600018C, HHSN268201600001C, HHSN268201600002C, HHSN268201600003C, and HHSN268201600004C. This work was additionally supported by NIH R01 CA205406 and the Broman Fund for Pancreatic Cancer Research to K. Ng; by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), NIH, to L.T. Amundadottir; by NIH R35 CA197735 to S. Ogino; and by Hale Center for Pancreatic Cancer Research, NIH/NCI U01 CA210171, NIH/NCI P50 CA127003, Department of Defense CA130288, Lustgarten Foundation, Pancreatic Cancer Action Network, Stand Up To Cancer, Noble Effort Fund, Peter R. Leavitt Family Fund, Wexler Family Fund, and Promises for Purple to B.M. Wolpin.

This research was also supported by a Stand Up To Cancer-Lustgarten Foundation Pancreatic Cancer Interception Translational Cancer Research Grant (grant number: SU2C-AACR-DT25-17). Stand Up To Cancer is a division of the Entertainment Industry Foundation. Research grants are administered by the American Association for Cancer Research, the scientific partner of SU2C.

The authors would like to thank the participants and staff of the HPFS, NHS, PHS, and WHI for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, and WY. The authors assume full responsibility for analyses and interpretation of the data.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Siegel
RL
,
Miller
KD
,
Jemal
A
. 
Cancer statistics, 2019
.
CA Cancer J Clin
2019
;
69
:
7
34
.
2.
Conroy
T
,
Desseigne
F
,
Ychou
M
,
Bouche
O
,
Guimbaud
R
,
Becouarn
Y
, et al
FOLFIRINOX versus gemcitabine for metastatic pancreatic cancer
.
N Engl J Med
2011
;
364
:
1817
25
.
3.
Von Hoff
DD
,
Ervin
T
,
Arena
FP
,
Chiorean
EG
,
Infante
J
,
Moore
M
, et al
Increased survival in pancreatic cancer with nab-paclitaxel plus gemcitabine
.
N Engl J Med
2013
;
369
:
1691
703
.
4.
Rubinson
DA
,
Wolpin
BM
. 
Therapeutic approaches for metastatic pancreatic adenocarcinoma
.
Hematol Oncol Clin North Am
2015
;
29
:
761
76
.
5.
Shay
JW
. 
Role of telomeres and telomerase in aging and cancer
.
Cancer Discov
2016
;
6
:
584
93
.
6.
Maciejowski
J
,
de Lange
T
. 
Telomeres in cancer: tumour suppression and genome instability
.
Nat Rev Mol Cell Biol
2017
;
18
:
175
86
.
7.
Campbell
PJ
,
Yachida
S
,
Mudie
LJ
,
Stephens
PJ
,
Pleasance
ED
,
Stebbings
LA
, et al
The patterns and dynamics of genomic instability in metastatic pancreatic cancer
.
Nature
2010
;
467
:
1109
13
.
8.
Matsuda
Y
,
Ishiwata
T
,
Izumiyama-Shimomura
N
,
Hamayasu
H
,
Fujiwara
M
,
Tomita
K
, et al
Gradual telomere shortening and increasing chromosomal instability among PanIN grades and normal ductal epithelia with and without cancer in the pancreas
.
PLoS One
2015
;
10
:
e0117575
.
9.
van Heek
NT
,
Meeker
AK
,
Kern
SE
,
Yeo
CJ
,
Lillemoe
KD
,
Cameron
JL
, et al
Telomere shortening is nearly universal in pancreatic intraepithelial neoplasia
.
Am J Pathol
2002
;
161
:
1541
7
.
10.
Hashimoto
Y
,
Murakami
Y
,
Uemura
K
,
Hayashidani
Y
,
Sudo
T
,
Ohge
H
, et al
Telomere shortening and telomerase expression during multistage carcinogenesis of intraductal papillary mucinous neoplasms of the pancreas
.
J Gastrointest Surg
2008
;
12
:
17
28
;
discussion 28–9
.
11.
Bao
Y
,
Prescott
J
,
Yuan
C
,
Zhang
M
,
Kraft
P
,
Babic
A
, et al
Leucocyte telomere length, genetic variants at the TERT gene region and risk of pancreatic cancer
.
Gut
2017
;
66
:
1116
22
.
12.
Liu
CL
,
Zang
XX
,
Wang
C
,
Kong
YL
,
Zhang
H
,
Zhang
HY
. 
Association between CLPTM1L-TERT rs401681 polymorphism and risk of pancreatic cancer: a meta-analysis
.
Clin Exp Med
2015
;
15
:
477
82
.
13.
Wolpin
BM
,
Rizzato
C
,
Kraft
P
,
Kooperberg
C
,
Petersen
GM
,
Wang
Z
, et al
Genome-wide association study identifies multiple susceptibility loci for pancreatic cancer
.
Nat Genet
2014
;
46
:
994
1000
.
14.
Petersen
GM
,
Amundadottir
L
,
Fuchs
CS
,
Kraft
P
,
Stolzenberg-Solomon
RZ
,
Jacobs
KB
, et al
A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33
.
Nat Genet
2010
;
42
:
224
8
.
15.
Herrmann
M
,
Pusceddu
I
,
Marz
W
,
Herrmann
W
. 
Telomere biology and age-related diseases
.
Clin Chem Lab Med
2018
;
56
:
1210
22
.
16.
Antwi
SO
,
Petersen
GM
. 
Leukocyte telomere length and pancreatic cancer risk: updated epidemiologic review
.
Pancreas
2018
;
47
:
265
71
.
17.
Campa
D
,
Mergarten
B
,
De Vivo
I
,
Boutron-Ruault
MC
,
Racine
A
,
Severi
G
, et al
Leukocyte telomere length in relation to pancreatic cancer risk: a prospective study
.
Cancer Epidemiol Biomarkers Prev
2014
;
23
:
2447
54
.
18.
Weischer
M
,
Nordestgaard
BG
,
Cawthon
RM
,
Freiberg
JJ
,
Tybjaerg-Hansen
A
,
Bojesen
SE
. 
Short telomere length, cancer survival, and cancer risk in 47,102 individuals
.
J Natl Cancer Inst
2013
;
105
:
459
68
.
19.
Chen
Y
,
Qu
F
,
He
X
,
Bao
G
,
Liu
X
,
Wan
S
, et al
Short leukocyte telomere length predicts poor prognosis and indicates altered immune functions in colorectal cancer patients
.
Ann Oncol
2014
;
25
:
869
76
.
20.
Callahan
CL
,
Schwartz
K
,
Ruterbusch
JJ
,
Shuch
B
,
Graubard
BI
,
Lan
Q
, et al
Leukocyte telomere length and renal cell carcinoma survival in two studies
.
Br J Cancer
2017
;
117
:
752
5
.
21.
Russo
A
,
Modica
F
,
Guarrera
S
,
Fiorito
G
,
Pardini
B
,
Viberti
C
, et al
Shorter leukocyte telomere length is independently associated with poor survival in patients with bladder cancer
.
Cancer Epidemiol Biomarkers Prev
2014
;
23
:
2439
46
.
22.
Zhang
C
,
Chen
X
,
Li
L
,
Zhou
Y
,
Wang
C
,
Hou
S
. 
The association between telomere length and cancer prognosis: evidence from a meta-analysis
.
PLoS One
2015
;
10
:
e0133174
.
23.
Xu
X
,
Qu
K
,
Pang
Q
,
Wang
Z
,
Zhou
Y
,
Liu
C
. 
Association between telomere length and survival in cancer patients: a meta-analysis and review of literature
.
Front Med
2016
;
10
:
191
203
.
24.
Wang
Z
,
Zhu
B
,
Zhang
M
,
Parikh
H
,
Jia
J
,
Chung
CC
, et al
Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
.
Hum Mol Genet
2014
;
23
:
6616
33
.
25.
Yuan
C
,
Qian
ZR
,
Babic
A
,
Morales-Oyarvide
V
,
Rubinson
DA
,
Kraft
P
, et al
Prediagnostic plasma 25-hydroxyvitamin D and pancreatic cancer survival
.
J Clin Oncol
2016
;
34
:
2899
905
.
26.
Yuan
C
,
Clish
CB
,
Wu
C
,
Mayers
JR
,
Kraft
P
,
Townsend
MK
, et al
Circulating metabolites and survival among patients with pancreatic cancer
.
J Natl Cancer Inst
2016
;
108
:
djv409
.
27.
Michaud
DS
,
Liu
Y
,
Meyer
M
,
Giovannucci
E
,
Joshipura
K
. 
Periodontal disease, tooth loss, and cancer risk in male health professionals: a prospective cohort study
.
Lancet Oncol
2008
;
9
:
550
8
.
28.
Hamada
T
,
Khalaf
N
,
Yuan
C
,
Babic
A
,
Morales-Oyarvide
V
,
Qian
ZR
, et al
Statin use and pancreatic cancer risk in two prospective cohort studies
.
J Gastroenterol
2018
;
53
:
959
66
.
29.
Hamada
T
,
Khalaf
N
,
Yuan
C
,
Morales-Oyarvide
V
,
Babic
A
,
Nowak
JA
, et al
Prediagnosis use of statins associates with increased survival times of patients with pancreatic cancer
.
Clin Gastroenterol Hepatol
2018
;
16
:
1300
6
e3
.
30.
Birmann
BM
,
Barnard
ME
,
Bertrand
KA
,
Bao
Y
,
Crous-Bou
M
,
Wolpin
BM
, et al
Nurses' Health Study contributions on the epidemiology of less common cancers: endometrial, ovarian, pancreatic, and hematologic
.
Am J Public Health
2016
;
106
:
1608
15
.
31.
Steering Committee of the Physicians' Health Study Research Group. Final report on the aspirin component of the ongoing Physician's Health Study
.
N Engl J Med
1989
;
321
:
129
35
.
32.
Langer
RD
,
White
E
,
Lewis
CE
,
Kotchen
JM
,
Hendrix
SL
,
Trevisan
M
. 
The Women's Health Initiative Observational Study: baseline characteristics of participants and reliability of baseline measures
.
Ann Epidemiol
2003
;
13
:
S107
21
.
33.
Rich-Edwards
JW
,
Corsano
KA
,
Stampfer
MJ
. 
Test of the national death index and equifax nationwide death search
.
Am J Epidemiol
1994
;
140
:
1016
9
.
34.
Mayers
JR
,
Wu
C
,
Clish
CB
,
Kraft
P
,
Torrence
ME
,
Fiske
BP
, et al
Elevation of circulating branched-chain amino acids is an early event in human pancreatic adenocarcinoma development
.
Nat Med
2014
;
20
:
1193
8
.
35.
Wang
H
,
Chen
H
,
Gao
X
,
McGrath
M
,
Deer
D
,
De Vivo
I
, et al
Telomere length and risk of Parkinson's disease
.
Mov Disord
2008
;
23
:
302
5
.
36.
Cawthon
RM
. 
Telomere measurement by quantitative PCR
.
Nucleic Acids Res
2002
;
30
:
e47
.
37.
McKay
JD
,
Hung
RJ
,
Gaborieau
V
,
Boffetta
P
,
Chabrier
A
,
Byrnes
G
, et al
Lung cancer susceptibility locus at 5p15.33
.
Nat Genet
2008
;
40
:
1404
6
.
38.
Shete
S
,
Hosking
FJ
,
Robertson
LB
,
Dobbins
SE
,
Sanson
M
,
Malmer
B
, et al
Genome-wide association study identifies five susceptibility loci for glioma
.
Nat Genet
2009
;
41
:
899
904
.
39.
Stuart
BD
,
Lee
JS
,
Kozlitina
J
,
Noth
I
,
Devine
MS
,
Glazer
CS
, et al
Effect of telomere length on survival in patients with idiopathic pulmonary fibrosis: an observational cohort study with independent validation
.
Lancet Respir Med
2014
;
2
:
557
65
.
40.
Peffault de Latour
R
,
Calado
RT
,
Busson
M
,
Abrams
J
,
Adoui
N
,
Robin
M
, et al
Age-adjusted recipient pretransplantation telomere length and treatment-related mortality after hematopoietic stem cell transplantation
.
Blood
2012
;
120
:
3353
9
.
41.
Martinez-Delgado
B
,
Yanowsky
K
,
Inglada-Perez
L
,
Domingo
S
,
Urioste
M
,
Osorio
A
, et al
Genetic anticipation is associated with telomere shortening in hereditary breast cancer
.
PLoS Genet
2011
;
7
:
e1002182
.
42.
Yuan
C
,
Morales-Oyarvide
V
,
Babic
A
,
Clish
CB
,
Kraft
P
,
Bao
Y
, et al
Cigarette smoking and pancreatic cancer survival
.
J Clin Oncol
2017
;
35
:
1822
8
.
43.
Yuan
C
,
Bao
Y
,
Wu
C
,
Kraft
P
,
Ogino
S
,
Ng
K
, et al
Prediagnostic body mass index and pancreatic cancer survival
.
J Clin Oncol
2013
;
31
:
4229
34
.
44.
Yuan
C
,
Rubinson
DA
,
Qian
ZR
,
Wu
C
,
Kraft
P
,
Bao
Y
, et al
Survival among patients with pancreatic cancer and long-standing or recent-onset diabetes mellitus
.
J Clin Oncol
2015
;
33
:
29
35
.
45.
Durrleman
S
,
Simon
R
. 
Flexible regression models with cubic splines
.
Stat Med
1989
;
8
:
551
61
.
46.
Makuch
RW
. 
Adjusted survival curve estimation using covariates
.
J Chronic Dis
1982
;
35
:
437
43
.
47.
Ghali
WA
,
Quan
H
,
Brant
R
,
van Melle
G
,
Norris
CM
,
Faris
PD
, et al
Comparison of 2 methods for calculating adjusted survival curves from proportional hazards models
.
JAMA
2001
;
286
:
1494
7
.
48.
Cochran
WG
. 
The combination of estimates from different experiments
.
Biometrics
1954
;
10
:
101
29
.
49.
DerSimonian
R
,
Laird
N
. 
Meta-analysis in clinical trials
.
Control Clin Trials
1986
;
7
:
177
88
.
50.
Codd
V
,
Nelson
CP
,
Albrecht
E
,
Mangino
M
,
Deelen
J
,
Buxton
JL
, et al
Identification of seven loci affecting mean telomere length and their association with disease
.
Nat Genet
2013
;
45
:
422
7
,
427e1–2
.
51.
Pooley
KA
,
Bojesen
SE
,
Weischer
M
,
Nielsen
SF
,
Thompson
D
,
Amin Al Olama
A
, et al
A genome-wide association scan (GWAS) for mean telomere length within the COGS project: identified loci show little association with hormone-related cancer risk
.
Hum Mol Genet
2013
;
22
:
5056
64
.
52.
Kotsopoulos
J
,
Prescott
J
,
De Vivo
I
,
Fan
I
,
McLaughlin
J
,
Rosen
B
, et al
Telomere length and mortality following a diagnosis of ovarian cancer
.
Cancer Epidemiol Biomarkers Prev
2014
;
23
:
2603
6
.
53.
Wang
W
,
Zheng
L
,
Zhou
N
,
Li
N
,
Bulibu
G
,
Xu
C
, et al
Meta-analysis of associations between telomere length and colorectal cancer survival from observational studies
.
Oncotarget
2017
;
8
:
62500
7
.
54.
Ennour-Idrissi
K
,
Maunsell
E
,
Diorio
C
. 
Telomere length and breast cancer prognosis: a systematic review
.
Cancer Epidemiol Biomarkers Prev
2017
;
26
:
3
10
.
55.
Arndt
GM
,
MacKenzie
KL
. 
New prospects for targeting telomerase beyond the telomere
.
Nat Rev Cancer
2016
;
16
:
508
24
.
56.
Hou
L
,
Joyce
BT
,
Gao
T
,
Liu
L
,
Zheng
Y
,
Penedo
FJ
, et al
Blood telomere length attrition and cancer development in the normative aging study cohort
.
EBioMedicine
2015
;
2
:
591
6
.
57.
Bilimoria
KY
,
Bentrem
DJ
,
Ko
CY
,
Ritchey
J
,
Stewart
AK
,
Winchester
DP
, et al
Validation of the 6th edition AJCC pancreatic cancer staging system: report from the National Cancer Database
.
Cancer
2007
;
110
:
738
44
.
58.
Daniali
L
,
Benetos
A
,
Susser
E
,
Kark
JD
,
Labat
C
,
Kimura
M
, et al
Telomeres shorten at equivalent rates in somatic tissues of adults
.
Nat Commun
2013
;
4
:
1597
.
59.
Friedrich
U
,
Griese
E
,
Schwab
M
,
Fritz
P
,
Thon
K
,
Klotz
U
. 
Telomere length in different tissues of elderly patients
.
Mech Ageing Dev
2000
;
119
:
89
99
.
60.
Kimura
M
,
Gazitt
Y
,
Cao
X
,
Zhao
X
,
Lansdorp
PM
,
Aviv
A
. 
Synchrony of telomere length among hematopoietic cells
.
Exp Hematol
2010
;
38
:
854
9
.
61.
Needham
BL
,
Rehkopf
D
,
Adler
N
,
Gregorich
S
,
Lin
J
,
Blackburn
EH
, et al
Leukocyte telomere length and mortality in the National Health and Nutrition Examination Survey, 1999–2002
.
Epidemiology
2015
;
26
:
528
35
.
62.
Carty
CL
,
Kooperberg
C
,
Liu
J
,
Herndon
M
,
Assimes
T
,
Hou
L
, et al
Leukocyte telomere length and risks of incident coronary heart disease and mortality in a racially diverse population of postmenopausal women
.
Arterioscler Thromb Vasc Biol
2015
;
35
:
2225
31
.