New onset diabetes predicts clinical outcomes in patients with pancreatic adenocarcinoma
Original Article

New onset diabetes predicts clinical outcomes in patients with pancreatic adenocarcinoma

Chirayu Mohindroo1, Paul S. Dy1, Suraj P. Hande1, Christopher R. D’Adamo2, Arun Mavanur3,4, Asha Thomas5, Florencia McAllister6,7,8, Ana De Jesus-Acosta9

1Department of Internal Medicine, Sinai Hospital of Baltimore, Baltimore, MD, USA; 2Department of Family and Community Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; 3Department of Surgery, Sinai Hospital of Baltimore, Baltimore, MD, USA; 4Department of Surgery, Johns Hopkins Hospital, Baltimore, MD, USA; 5Division of Endocrinology, Department of Internal Medicine, Sinai Hospital of Baltimore, Baltimore, MD, USA; 6Departments of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 7Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 8Department of Immunology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; 9Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA

Contributions: (I) Conception and design: C Mohindroo, F McAllister, A Thomas, A De Jesus-Acosta, A Mavanur, CR D’Adamo; (II) Administrative support: A Thomas, A De Jesus-Acosta, A Mavanur; (III) Provision of study materials or patients: A Thomas, A Mavanur, C Mohindroo; (IV) Collection and assembly of data: C Mohindroo, PS Dy, SP Hande; (V) Data analysis and interpretation: C Mohindroo, F McAllister, A Thomas, CR D’Adamo, A De Jesus-Acosta, A Mavanur; (VI) Manuscript writing: All authors; (VII) Final approval of manuscript: All authors.

Correspondence to: Ana De Jesus-Acosta, MD. Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, CRB1, 1650 Orleans Street, Rm 488, Baltimore, MD 21287, USA. Email: adejesu1@jhmi.edu.

Background: One percent of pancreatic adenocarcinoma (PDAC) patients are diagnosed with new onset diabetes (NOD) over the age of 50 years within 3 years. Therefore, NOD is a major factor for early diagnosis of PDAC. Research has focused on understanding the differences between NOD and type 2 diabetes, particularly in relation to PDAC. However, conflicting data exists regarding their impact on survival outcomes in PDAC patients. We performed this multi-center study to assess the prevalence and influence of NOD on clinical outcomes in patients with PDAC within a community-based hospital system.

Methods: We conducted a retrospective cohort study of 138 patients with biopsy-proven PDAC with localized/borderline disease (n=70), and metastatic disease (n=68) at three institutions from 2014 to 2021. NOD group consisted of pts diagnosed with diabetes [hemoglobin A1c (HbA1c) >6.5%] or pre-diabetes (HbA1c 5.7–6.4%) within the 3 years prior to PDAC diagnosis. Primary aim of the study was to determine the impact of NOD on clinical outcomes.

Results: A total of 138 patients were included in the study, from which 30 met the criteria for NOD. No significant differences were noted in the demographic and clinical characteristics comparing patients based on NOD history. Comparing survival outcomes, NOD group was associated with worse overall survival (OS) in both the metastatic cohort [n=68, progression-free survival (PFS) 4.6 vs. 7.1 months, P=0.07; OS 7.1 vs. 13.2 months, P=0.01) and the resected cohort (n=40, PFS 8.4 vs. 19.3 months, P=0.04; OS 24.5 vs. 42.3 months, P=0.04). In multivariate analysis, the impact of NOD remained significant for OS and PFS in the resected cohort. Identifying common features amongst the NOD group, we found the entire cohort had a significant reduction in individual body mass index (BMI) 1 year prior to the NOD diagnosis (P=0.006).

Conclusions: NOD is associated with worse survival outcomes in patients with metastatic and resected PDAC. Reduction of BMI prior to diagnosis of NOD, warrants further investigation to be incorporated into the PDAC screening paradigm.

Keywords: Pancreatic adenocarcinoma (PDAC); new onset diabetes (NOD); weight loss; survival

Submitted Jul 25, 2024. Accepted for publication Dec 12, 2024. Published online Feb 26, 2025.

doi: 10.21037/jgo-24-570

Highlight box

Key findings

• New onset diabetes (NOD) is associated with worse outcomes in both resected and metastatic pancreatic adenocarcinoma (PDAC) patients and was an independent prognostic marker in the resected cohort. NOD prior to PDAC diagnosis is often preceded by weight loss.

What is known and what is new?

• Conflicting data exists regarding the role of NOD in PDAC prognosis. Our study found that NOD within 3 years prior to PDAC diagnosis is often indicative of a worse prognosis. Furthermore, these patients may experience a significant reduction in body mass index at the time of NOD diagnosis compared to one year earlier.

What are the implications, and what should change now?

• Prospective studies with larger and more diverse cohorts are needed to determine whether new-onset hyperglycemia prior to PDAC diagnosis can serve as a prognostic marker. Additionally, strategies combining weight loss and NOD should be explored to identify patients at high risk for developing PDAC.

Introduction

Pancreatic adenocarcinoma (PDAC) is one of the most lethal forms of cancer, ranking 3rd among the leading causes of cancer-related deaths in the United States. In 2023, it is estimated 50,550 Americans will die from the disease (1). The 5-year survival rate is only a dismal 11.8% (1). The poor prognosis of PDAC can be attributed to late detection and lack of effective treatment options when the cancer has already spread. Current treatment modalities can slow progression and mildly prolong survival. The standard of care, especially in the advanced stages, is mainly limited to palliative chemotherapy (2).

Risk factors for the development of PDAC include smoking, alcohol consumption, diabetes mellitus (DM) and obesity (3,4). Various studies have shown that DM is more prevalent in patients with PDAC than other cancers or healthy controls (5-7). This is particularly true in patients with a more recent diagnosis (5-7). The pathophysiology is thought to be related to the interference of the tumor with the endocrine function of the pancreas. Among patients older than 50 years and new onset diabetes (NOD), approximately 1% are diagnosed with PDAC within 3 years. The incidence of PDAC in patients with NOD was 2.2-fold higher than in those without pre-existing diabetes (8). Therefore, DM may be both causal and consequential to PDAC.

DM has been associated with worse prognosis in patients with different solid tumors (9,10), but the prognostic impact in patients with PDAC remains controversial (11,12). The results of various studies have been inconsistent (11,12), and these differences may be due to heterogeneous populations being explored including different genetic characteristics, stage, or tumor differentiation as well as with the various definitions of NOD.

Early detection of PDAC has been shown to improve survival (13,14). U.S. Preventive Services Task Force (USPTF)/National Comprehensive Cancer Network (NCCN) now recommend PDAC screening in high-risk individuals based on family history and presence of germline mutations (15,16). DM has not yet been incorporated into the screening paradigm for PDAC (17). NCI has acknowledged studying DM and PDAC has one of the highest research priority areas in the field (18). We conducted a multi-center retrospective cohort study, to understand the prevalence and impact of NOD on clinical outcomes in PDAC patients in a community-based hospital system. Our hypothesis is that NOD would have an impact on survival in PDAC patients. We present this article in accordance with the STROBE reporting checklist (available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-570/rc).

Methods

Patients and NOD status

This was a retrospective cohort study. We identified 138 patients with biopsy-proven PDAC, which included the following two groups: (I) localized disease (resectable, borderline resectable and locally advanced unresectable PDAC) (n=70); and (II) patients with metastatic disease (n=68). The patients included in the analysis were diagnosed and/or treated for resectable or metastatic disease at the Lifebridge Health System’s three hospitals (Sinai Hospital of Baltimore, Northwest Hospital and Carroll County Hospital) between 2018 and 2021. We reviewed the patients’ medical records and retrospectively collected data on patient demographics, NOD status, tumor characteristics and treatment characteristics, and survival data, including progression, death, and last follow-up dates. The NOD group was defined as patients with an hemoglobin A1c (HbA1c) level of more than 6.5% (diabetes) or between 5.7% and 6.4% (prediabetes), or with a physician-documented NOD within 3 years prior to their PDAC diagnosis (19). The weight and height of the patients were recorded at 6 months and 1 year prior to the NOD diagnosis (plus/minus 3 months). For the survival analysis, patients from group 1 were included under the resected cohort who underwent surgery. As not all patients with localized/borderline disease undergo surgery due to progression. All patients were followed up until death or data lock (December 2021 for both cohorts). Only patients with complete survival data were included in the study. The study protocol was submitted to the Institutional Review Board of Lifebridge Health System, which oversees all three participating hospitals, and it granted an exemption. As a result, informed patient consent was not required. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Statistical analysis

Patients’ characteristics were summarized according to the NOD status and compared using the Fisher or Chi-squared test for categorical data and the Wilcoxon rank-sum test for continuous data. The frequencies and percentages were reported for categorical variables, and summary statistics such as the median, minimum, and maximum were provided for continuous data (such as age). Overall survival (OS) was defined as the time from diagnosis to death from any cause, and patients were censored to the date of their last follow-up. Progression-free survival (PFS) was defined as the time from surgery to progression or death, whichever occurred first, in patients who underwent surgery, and as the time from first-line chemotherapy to progression or death, whichever occurred first, in the metastatic group. Kaplan-Meier curves were used to estimate the survival distributions by NOD status, and the log-rank and Gehan-Breslow-Wilcoxon test were used to test the difference in survival distributions between treatment groups. Univariate and multivariable Cox proportional hazard models were used to determine the effects of potential risk factors and NOD status variables on OS and PFS. Hazard ratios (HRs) and 95% confidence intervals (CIs) were provided. All tests were two-sided, and P values less than 0.05 were considered statistically significant. Clinically important and statistically significant variables were included in the multivariable models for the multivariate analysis. All analyses were conducted using SAS OnDemand for Academics and GraphPad (San Diego, CA, USA) software.

Results

Patient demographics and clinical characteristics

A total of 138 patients were included in the study, of which 30 met the criteria for NOD. The mean age of the NOD group was 70 years, compared to 69 years for the non-NOD group. Fifty percent of the patients in the NOD group were male, compared to 46% in the other group. The majority of patients in both groups were White: 60% in the NOD group and 54% in the non-NOD group. In terms of tumor location, most patients in both groups (67%) had tumors in the head/uncinate process of the pancreas. Overall, 51% of the patients had localized disease, with 36% in the NOD group. Forty-nine percent of the patients had metastatic disease, with 63% in the NOD group. The majority of patients received first-line chemotherapy, either FOLFIRINOX (49%), with 57% in the NOD group, or gemcitabine-based regimen (51%), including 43% in the NOD group. Forty patients underwent surgery, including 17% in the NOD group. Overall, no significant differences were noted between the two groups, as summarized in Table 1.

Table 1

Baseline characteristics of both resectable and metastatic pancreatic ductal adenocarcinoma cohorts

Variable Total (n=138) NOD (n=30) Non-NOD (n=108) P value
Age (years), mean (SD) 69.61 (10.87) 70.15 (9.58) 69.46 (11.24) 0.32
Sex, n [%] 0.83
   Male 65 [47] 15 [50] 50 [46]
   Female 73 [53] 15 [50] 58 [54]
Race, n [%] 0.70
   White 76 [55] 18 [60] 58 [54]
   Black 49 [35] 10 [33] 39 [36]
   Others 13 [9] 2 [7] 11 [10]
Hispanic, n [%] 1 [1] 0 1 [1] 0.99
Site of disease, n [%] 0.52
   Head/uncinate process 92 [67] 20 [67] 72 [67]
   Body/neck 16 [12] 5 [17] 11 [10]
   Tail 30 [22] 5 [17] 25 [23]
Stage, n [%] 0.10
   Localized 70 [51] 11 [36] 59 [55]
   Metastatic 68 [49] 19 [63] 49 [45]
Type of chemotherapy received, n [%] 0.40
   FOLFRINOX 65 [49] 17 [57] 48 [47]
   Gemcitabine-based 67 [51] 13 [43] 54 [53]
Surgery, n [%] 40 [29] 5 [17] 35 [32] 0.11

NOD, new onset diabetes; SD, standard deviation.

Resected cohort

Initial analysis of the KM curves showed that patients in the NOD cohort had worse outcomes compared to the non-NOD group. The median OS in the NOD group was 24.5 months, compared to 42.3 months in the non-NOD group (P=0.04) with a HR of 5.04 (95% CI: 1.0–25.2) (Figure 1A). Similarly, the median PFS in the NOD group was 8.4 months, compared to 19.3 months in the non-NOD group (P=0.04), with a HR of 5.08 (95% CI: 1.0–25.6) (Figure 1B).

Figure 1 Kaplan-Meier survival curves of resectable and metastatic PDAC cohorts according to NOD status. OS (A) and PFS (B) in resectable cohort. OS (C) and PFS (D) in metastatic cohort. PDAC, pancreatic adenocarcinoma; NOD, new onset diabetes; PFS, progression free survival; OS, overall survival.

To further understand our findings, we carried out a univariate analysis (Table 2) of possible confounding factors (gender, age, race, tumor size, nodal involvement, perineural invasion, lymphovascular invasion, and long-standing diabetes), which revealed NOD as trending towards significance for both OS (P=0.05) and PFS (P=0.06). Multivariate modeling (Table 3) further revealed that NOD was independently associated with worse OS (P=0.049) and PFS (P=0.03).

Table 2

Univariate analysis of the OS and PFS in the resectable cohorts

Prognostic factor OS PFS
HR (95% CI) P value HR (95% CI) P value
Gender (female vs. male) 1.48 (0.67–3.28) 0.96 1.02 (0.49–2.13) 0.95
Age (<68 vs. ≥68 years) 0.75 (0.35–1.63) 0.47 1.26 (0.6–2.64) 0.52
Race (White vs. non-White) 0.91 (0.4–2.04) 0.82 0.85 (0.39–1.85) 0.68
Tumor size (T1/T2 vs. T3/T4) 1.05 (0.41–2.47) 0.97 1.03 (0.47–2.26) 0.93
Nodal status (N0 vs. N1/N2) 0.45 (0.17–1.16) 0.09 0.59 (0.23–1.49) 0.27
Perineural invasion 1.2 (0.4–3.58) 0.73 1.24 (0.42–3.66) 0.68
Lymphovascular invasion 0.72 (0.29–1.74) 0.46 0.93 (0.4–2.13) 0.86
Microscopic margins (R1 vs. R0) 0.58 (0.07–4.45) 0.6 N/A
NOD 2.84 (0.95–8.46) 0.05 2.81 (0.93–8.44) 0.06
Long standing diabetes 0.67 (0.29–1.52) 0.34 0.6 (0.27–1.35) 0.22

OS, overall survival; PFS, progression-free survival; HR, hazard ratio; CI, confidence interval; NOD, new onset diabetes; N/A, not applicable.

Table 3

Multivariate analysis of the OS and PFS in resectable cohorts

Prognostic factor OS PFS
HR (95% CI) P value HR (95% CI) P value
Age (<68 vs. ≥68 years) 1.29 (0.44–3.79) 0.63 2.66 (0.81–8.72) 0.11
Tumor size (T1/T2 vs. T3/T4) 0.95 (0.31–2.89) 0.93 1.64 (0.52–5.18) 0.39
Nodal status (N0 vs. N1/N2) 0.34 (0.1–1.1) 0.07 0.35 (0.1–1.18) 0.09
Perineural invasion 3.31 (0.55–19.79) 0.19 1.63 (0.38–6.9) 0.51
Lymphovascular invasion 0.49 (0.16–1.46) 0.20 0.9 (0.34–2.36) 0.84
NOD 8.1 (1.0–65.7) 0.049 9.34 (1.23–70.83) 0.03

OS, overall survival; PFS, progression-free survival; HR, hazard ratio; CI, confidence interval; NOD, new onset diabetes.

Metastatic cohort

Similar to the resected cohort, NOD was associated with worse outcomes in the metastatic cohort. The median OS in the NOD group was 7.1 months, compared to 13.2 months in the non-NOD group (P=0.01) (Figure 1C). The median PFS in the NOD group was 4.6 months, compared to 7.1 months in the non-NOD group (P=0.07) (Figure 1D). However, these results were determined using the Gehan-Breslow technique, as the KM curves crossed towards the end, making them incompatible with the log-rank test or Cox proportional analysis. The following phenomenon has also been observed in immunotherapy regimens, where the effect of therapy might not be constant throughout the survival (20).

Considering that the first-line chemotherapy regimen can have a considerable impact on survival in the metastatic cohort, we then performed a subgroup analysis based on type of first line chemotherapy. In both the FOLFIRINOX subgroup (OS 8.8 vs. 12.6 months, P=0.36) and the gemcitabine-based subgroup (OS 6.8 vs. 10.4 months, P=0.21), NOD was associated with a trend towards worse prognosis although not statistically significant (Figure S1).

Characterization of the NOD group

Considering that NOD can be an early sign for PDAC, we aimed to identify common features in the NOD group. 65% of the patients were asymptomatic from any symptoms related to PDAC malignancy. Mean time of diagnosis of the NOD was 6.6 months prior to PDAC diagnosis, 61% of the patients had a reduction in weight 6 months prior to NOD diagnosis, 21% had a weight loss 1 year prior to NOD diagnosis. Thirty percent of the patients had a family history of DM, 57% had a history of smoking in the cohort. About 57% of the patients met the criteria for DM and 43% of the patients met the criteria for pre-DM. The mean HbA1c of the cohort was 7.25%, and 46% of the patients progressed to DM from pre-DM. No significant differences were observed when the NOD group was stratified into localized and metastatic cohort in the above-described characteristics as shown in Table S1. Considering the patients had weight loss, we further examined the change in body mass index (BMI) at 6 months and 1 year prior to the diagnosis of NOD. The entire cohort had a significant reduction in the individual BMI at 1 year (P=0.006), but not at 6 months (P=0.17) (Figure S2).

Discussion

Although, it is known that diabetes is a risk factor of PDAC, its impact on survival outcomes is less established. In this study, we show NOD preceding the diagnosis of PDAC is associated with worse outcomes in both the metastatic and resected cohorts, in a community hospital-based setting.

Similar to our study, Hank et al. (21), Li et al. (22), Alpertunga et al. (23) have shown the effect of hyperglycemia being associated with worse clinical outcomes. However, the definition of NOD was variable and the effect was only limited to certain cohorts. In our study, we chose 3 years as the cut-off for NOD based on studies showing that individuals diagnosed with NOD have a 6–8-fold higher risk of being diagnosed with PDAC within 3 years of first meeting glycemic criteria for NOD, with a 3-year incidence of PDAC being ~1% (8). Furthermore, hyperglycemia was associated with worse outcomes in both resected and metastatic cohorts. Robust clinical and preclinical evidence can explain hyperglycemia leading to worse outcomes. Large clinical studies have shown diabetic patients have larger tumors, higher rates of lymph node involvement, and perineural invasion (21,24). Another study showed, that an elevated preoperative HbA1c is often associated with failure to complete neoadjuvant therapy and surgery (25). Consistent with prior studies this effect is seen with NOD rather than long-standing diabetes (22,23).

Hyperglycemia can also promote epithelial-mesenchymal transition and proliferation of PDAC cells, via hydrogen peroxide (26), epidermal growth factor and epidermal growth factor receptor (EGF-EGFR) pathway (27) and transforming growth factor beta (TGF-β) signaling pathways (28). Another study showed that elevated blood glucose can suppress the cytotoxic effects of natural killer (NK) cells in PDAC cells utilizing the AMP-activated protein kinase-Bmi1-GATA2-MHC class I chain related molecules A/B, contributing to an immunosuppressive tumor microenvironment (TME) (29). Another explanation is based on the Warburg effect, hyperglycemia can upregulate aerobic glycolysis, which can further lead to impaired T cell function (30,31). Recent studies have shown that tumor/gut microbiome can impact survival in PDAC patients (32-34), diabetes has also been shown to be associated with dysbiosis (35). Furthermore, diabetes-induced dysbiosis can lead to resistance to chemotherapy, in PDAC mouse models (36). Overall, taken in context to our findings, support that hyperglycemia is associated with poor prognosis in PDAC.

Currently NCCN/USPTF recommend screening individuals at high risk for PDAC (15,17). However, NOD is yet to be incorporated into the paradigm of PDAC screening, as a strategy solely based on NOD has shown not to be cost-effective. In our study, we identify weight loss preceding NOD, as a common factor seen in the NOD cohort. Hence, PDAC screening strategies could potentially incorporate weight loss along with NOD to form a “sieve” identifying a higher-risk group more suitable for screening. The phenomenon is now being integrated into PDAC screening programs. Furthermore, our preliminary results showed that NOD was correlated with the presence of focal lesions in the pancreas in individuals at high risk for developing PDAC (37).

Our study had several limitations. Firstly, it was a retrospective study with a relatively small cohort. Secondly, the results cannot be directly applied to all racial and ethnic groups, as our study was enriched with the White population. Thirdly, the documented weight in the NOD cohort, was not exactly at the prespecified intervals and some variables were missing due to the retrospective nature of the study. Another limitation was the crossing of survival curves in the metastatic cohort, while NOD was associated with worse outcomes, we could not apply the traditional Cox proportional hazards for multivariate modeling. Our survival analysis was limited to a 3-year follow-up period. Given that the resected PDAC population can have a survival rate of approximately 40%, extended follow-up will be essential for future studies to capture the long-term outcomes.

Conclusions

In conclusion, NOD was associated with worse outcomes in PDAC patients, hence representing an important prognostic marker. NOD is often preceded by weight loss, a combination of them could identify a higher risk population which would benefit from PDAC screening. Larger studies with a more diverse cohort are needed to further validate these findings.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-570/rc

Data Sharing Statement: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-570/dss

Peer Review File: Available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-570/prf

Funding: None.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-24-570/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study protocol was submitted to the Institutional Review Board of Lifebridge Health System, which oversees all three participating hospitals, and it granted an exemption. As a result, informed patient consent was not required. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013).

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

References

  1. Siegel RL, Miller KD, Wagle NS, et al. Cancer statistics, 2023. CA Cancer J Clin 2023;73:17-48. [Crossref] [PubMed]
  2. Berlin J. Cancers of the Pancreas Update 2023. Clin Colorectal Cancer 2023;22:1. [Crossref] [PubMed]
  3. Maisonneuve P, Lowenfels AB. Epidemiology of pancreatic cancer: an update. Dig Dis 2010;28:645-56. [Crossref] [PubMed]
  4. McAuliffe JC, Christein JD. Type 2 diabetes mellitus and pancreatic cancer. Surg Clin North Am 2013;93:619-27. [Crossref] [PubMed]
  5. Aggarwal G, Kamada P, Chari ST. Prevalence of diabetes mellitus in pancreatic cancer compared to common cancers. Pancreas 2013;42:198-201. [Crossref] [PubMed]
  6. Chari ST, Leibson CL, Rabe KG, et al. Pancreatic cancer-associated diabetes mellitus: prevalence and temporal association with diagnosis of cancer. Gastroenterology 2008;134:95-101. [Crossref] [PubMed]
  7. Pannala R, Leirness JB, Bamlet WR, et al. Prevalence and clinical profile of pancreatic cancer-associated diabetes mellitus. Gastroenterology 2008;134:981-7. [Crossref] [PubMed]
  8. Chari ST, Leibson CL, Rabe KG, et al. Probability of pancreatic cancer following diabetes: a population-based study. Gastroenterology 2005;129:504-11. [Crossref] [PubMed]
  9. Li W, Zhang X, Sang H, et al. Effects of hyperglycemia on the progression of tumor diseases. J Exp Clin Cancer Res 2019;38:327. [Crossref] [PubMed]
  10. Wu CH, Wu TY, Li CC, et al. Impact of diabetes mellitus on the prognosis of patients with oral squamous cell carcinoma: a retrospective cohort study. Ann Surg Oncol 2010;17:2175-83. [Crossref] [PubMed]
  11. De Souza A, Irfan K, Masud F, et al. Diabetes Type 2 and Pancreatic Cancer: A History Unfolding. JOP 2016;17:144-8. [PubMed]
  12. Li D. Diabetes and pancreatic cancer. Mol Carcinog 2012;51:64-74. [Crossref] [PubMed]
  13. Yamaguchi A, Kato N, Sugata S, et al. Effectiveness of Abdominal Ultrasonography for Improving the Prognosis of Pancreatic Cancer during Medical Checkup: A Single Center Retrospective Analysis. Diagnostics (Basel) 2022;12:2913. [Crossref] [PubMed]
  14. Blackford AL, Canto MI, Dbouk M, et al. Pancreatic Cancer Surveillance and Survival of High-Risk Individuals. JAMA Oncol 2024;10:1087-96. [Crossref] [PubMed]
  15. Lucas AL, Kastrinos F. Screening for Pancreatic Cancer. JAMA 2019;322:407-8. [Crossref] [PubMed]
  16. Network NCC. NCCN Clinical Practice Guidelines in Oncology (NCCN Guidelines®) Genetic/Familial High-Risk Assessment: Breast, Ovarian, and Pancreatic Version 3.2023: NCCN; 2023. Available online: https://www.nccn.org/professionals/physician_gls/pdf/genetics_bop.pdf
  17. Maitra A, Sharma A, Brand RE, et al. A Prospective Study to Establish a New-Onset Diabetes Cohort: From the Consortium for the Study of Chronic Pancreatitis, Diabetes, and Pancreatic Cancer. Pancreas 2018;47:1244-8. [Crossref] [PubMed]
  18. Institute NC. Scientific Framework for Pancreatic Ductal Adenocarcinoma (PDAC) 2014. Available online: https://deainfo.nci.nih.gov/advisory/ctac/workgroup/pc/pdacframework.pdf
  19. Sharma A, Kandlakunta H, Nagpal SJS, et al. Model to Determine Risk of Pancreatic Cancer in Patients With New-Onset Diabetes. Gastroenterology 2018;155:730-739.e3. [Crossref] [PubMed]
  20. Castañon E, Sanchez-Arraez A, Alvarez-Manceñido F, et al. Critical reappraisal of phase III trials with immune checkpoint inhibitors in non-proportional hazards settings. Eur J Cancer 2020;136:159-68. [Crossref] [PubMed]
  21. Hank T, Sandini M, Qadan M, et al. Diabetes mellitus is associated with unfavorable pathologic features, increased postoperative mortality, and worse long-term survival in resected pancreatic cancer. Pancreatology 2020;20:125-31. [Crossref] [PubMed]
  22. Li D, Mao Y, Chang P, et al. Impacts of new-onset and long-term diabetes on clinical outcome of pancreatic cancer. Am J Cancer Res 2015;5:3260-9. [PubMed]
  23. Alpertunga I, Sadiq R, Pandya D, et al. Glycemic Control as an Early Prognostic Marker in Advanced Pancreatic Cancer. Front Oncol 2021;11:571855. [Crossref] [PubMed]
  24. Kleeff J, Costello E, Jackson R, et al. The impact of diabetes mellitus on survival following resection and adjuvant chemotherapy for pancreatic cancer. Br J Cancer 2016;115:887-94. [Crossref] [PubMed]
  25. Rajamanickam ES, Christians KK, Aldakkak M, et al. Poor Glycemic Control Is Associated with Failure to Complete Neoadjuvant Therapy and Surgery in Patients with Localized Pancreatic Cancer. J Gastrointest Surg 2017;21:496-505. [Crossref] [PubMed]
  26. Li W, Zhang L, Chen X, et al. Hyperglycemia Promotes the Epithelial-Mesenchymal Transition of Pancreatic Cancer via Hydrogen Peroxide. Oxid Med Cell Longev 2016;2016:5190314. [Crossref] [PubMed]
  27. Han L, Ma Q, Li J, et al. High glucose promotes pancreatic cancer cell proliferation via the induction of EGF expression and transactivation of EGFR. PLoS One 2011;6:e27074. [Crossref] [PubMed]
  28. Rahn S, Zimmermann V, Viol F, et al. Diabetes as risk factor for pancreatic cancer: Hyperglycemia promotes epithelial-mesenchymal-transition and stem cell properties in pancreatic ductal epithelial cells. Cancer Lett 2018;415:129-50. [Crossref] [PubMed]
  29. Duan Q, Li H, Gao C, et al. High glucose promotes pancreatic cancer cells to escape from immune surveillance via AMPK-Bmi1-GATA2-MICA/B pathway. J Exp Clin Cancer Res 2019;38:192. [Crossref] [PubMed]
  30. Cascone T, McKenzie JA, Mbofung RM, et al. Increased Tumor Glycolysis Characterizes Immune Resistance to Adoptive T Cell Therapy. Cell Metab 2018;27:977-987.e4. [Crossref] [PubMed]
  31. Lim SO, Li CW, Xia W, et al. EGFR Signaling Enhances Aerobic Glycolysis in Triple-Negative Breast Cancer Cells to Promote Tumor Growth and Immune Escape. Cancer Res 2016;76:1284-96. [Crossref] [PubMed]
  32. Chandra V, McAllister F. Therapeutic potential of microbial modulation in pancreatic cancer. Gut 2021;70:1419-25. [Crossref] [PubMed]
  33. Mohindroo C, Hasanov M, Rogers JE, et al. Antibiotic use influences outcomes in advanced pancreatic adenocarcinoma patients. Cancer Med 2021;10:5041-50. [Crossref] [PubMed]
  34. Riquelme E, Zhang Y, Zhang L, et al. Tumor Microbiome Diversity and Composition Influence Pancreatic Cancer Outcomes. Cell 2019;178:795-806.e12. [Crossref] [PubMed]
  35. Zhou Z, Sun B, Yu D, et al. Gut Microbiota: An Important Player in Type 2 Diabetes Mellitus. Front Cell Infect Microbiol 2022;12:834485. [Crossref] [PubMed]
  36. Kesh K, Mendez R, Abdelrahman L, et al. Type 2 diabetes induced microbiome dysbiosis is associated with therapy resistance in pancreatic adenocarcinoma. Microb Cell Fact 2020;19:75. [Crossref] [PubMed]
  37. Baydogan S, Mohindroo C, Hasanov M, et al. New-onset diabetes is a predictive risk factor for pancreatic lesions in high-risk individuals: An observational cohort study. Endosc Ultrasound 2024;13:83-8. [Crossref] [PubMed]
Cite this article as: Mohindroo C, Dy PS, Hande SP, D’Adamo CR, Mavanur A, Thomas A, McAllister F, De Jesus-Acosta A. New onset diabetes predicts clinical outcomes in patients with pancreatic adenocarcinoma. J Gastrointest Oncol 2025;16(1):226-233. doi: 10.21037/jgo-24-570

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