Phenotyping Patients With Type 2 Diabetes Mellitus and Cancer

NCT06299800 | Recruiting

• 1 other identifier: CE385/2023
• Study Type: observational
• Target: 779
• Locations: 1 country
• Sites: 1

Brief Summary

Recent research has highlighted the significant relationship between type 2 diabetes mellitus and cancer, both prevalent and impactful on global health. The intrinsic correlation arises from shared metabolic processes, particularly a systemic and chronic inflammatory state driven by factors like obesity, dyslipidemia, and hyperglycemia. This leads to the creation of a self-sustaining microenvironment known as meta-inflammation, promoting cancer development through DNA damage, oxidative stress, and the influence of hormones like leptin. The hyperglycemic environment in diabetes contributes to cancer development, supporting the Warburg effect and insulin-related mechanisms. This study aims to identify risk factors associated with diabetes that impact tumor development and progression, crucial for guiding effective preventive strategies in clinical practice. Primary objective of the study: \- identify the risk factors affecting the occurrence of cancer in the population affected by type 2 diabetes mellitus; Secondary objectives of the study:

• description of the demographic, clinical and first-line therapy characteristics of patients diagnosed with type 2 diabetes mellitus;
• assess risk factors for recurrence, presence of a second tumour not related to the first and the presence of both events in patients who have had a tumor within 10 years of diagnosis of diabetes;
• assess the relationship between the characteristics of patients and the time to the onset of cancer.

Conditions

Diabetes Mellitus, Type 2; Cancer

Keywords

cancer; diabetes mellitus type 2

Outcome Measures

Primary Outcomes (4)

• Smoking assessment at first visit

  identify the risk factors affecting the occurrence of cancer in the population affected by type 2 diabetes mellitus: During the first examination, the history of each patient was investigated, evaluating whether they were smokers, non-smokers or ex smokers

  Assessment of data at time 0 (first clinical visit)

• Alcool consumption at first visit

  identify the risk factors influencing the onset of cancer in the population affected by type 2 diabetes mellitus: During the first examination, the history of each patient was studied, assessing whether I consume alcohol and in what amount. \<1 alcohol unit or greater than 2 alcohol units were used as cutoffs to subdivide the patients considered.

  Assessment of data at time 0 (first clinical visit)

• BMI assessment at first visit

  identify the risk factors influencing the onset of cancer in the population affected by type 2 diabetes mellitus: During the first examination, the history of each patient was studied, measuring weight and height to calculate the BMI of each patient. The ranges considered are: underweight \<18.5, normal weight 18.5-25 and overweight \>25.

  Assessment of data at time 0 (first clinical visit)

• Glycated assessment at first visit

  identify the risk factors influencing the onset of cancer in the population affected by type 2 diabetes mellitus: During the first examination, the history of each patient was studied, measuring the glycate of each patient. The considered cutoff is \< or equal to 8%, where 8% is the limit for glycemic decompensation.

  Assessment of data at time 0 (first clinical visit)

Secondary Outcomes (4)

• First-line therapy characteristics assessment at first visit

  Assessment of data at time 0 (first clinical visit)

• Primary outcomes and recurrence or presence of a secondary tumor

  Assessment of data at time 0 (first clinical visit)

• Relationship between patients characteristics and the time onset of cancer considering anthropometric and biochemical data

  Assessment of data at time 0 (first clinical visit)

• Tumour characterization in the considered population, detected at the first clinical visit

  Assessment of data at time 0 (first clinical visit)

Study Arms (1)

Diabetes mellitus type 2 and cancer

779 patients with cancer and diagnosis of type 2 diabetes mellitus diagnosed between 1990 and 2010

Other: phenotyping of patients followed at a third-level diabetes centre with cancer

Interventions

phenotyping of patients followed at a third-level diabetes centre with cancer OTHER

Collection of the following data for each patient enrolled, where possible: * Gender and age; * Smoking habits and alcohol consumption (units per day); * Weight and body mass index (BMI) at first (T0) and last visit (T1); * Given by the diagnosis of type 2 diabetes mellitus; * Treatment of type 2 diabetes at T0 and T1; * Levels of glycated hemoglobin (hba1c) at T0 and T1, mean hba1c and mean fasting blood sugar; * Creatinine clearance at T0 and T1; * Liver enzymes at T0 and T1: alanine aminotransferase (ALT) and aspartate aminotransferase (AST); * T0 and T1 lipid profile: low density lipoproteins (LDL-c) and triglycerides (TG); * Complications of type 2 diabetes; * Treatment of cancer; * Family history of cancer.

Diabetes mellitus type 2 and cancer

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Probability Sample

Study Population

779 patients with diabetes mellitus type 2 and with at least 18 years old.

You may qualify if:

• Legal age
• Diagnosis of type 2 diabetes mellitus

You may not qualify if:

• Diagnosis of cancer before diagnosis of type 2 diabetes
• Diagnosis of diabetes secondary to other diseases
• Diagnosis of diabetes secondary to other drugs
• Diagnosis of diabetes following surgery

Sponsors & Collaborators

• Azienda Ospedaliero Universitaria Maggiore della Carita: lead

Study Sites (1)

SCDU Endocrinology, AOU Ospedale Maggiore della Carità

Novara, 28100, Italy

RECRUITING

Related Publications (11)

• Fu Z, Gilbert ER, Liu D. Regulation of insulin synthesis and secretion and pancreatic Beta-cell dysfunction in diabetes. Curr Diabetes Rev. 2013 Jan 1;9(1):25-53.

  PMID: 22974359 BACKGROUND

• Rojas A, Schneider I, Lindner C, Gonzalez I, Morales MA. Association between diabetes and cancer. Current mechanistic insights into the association and future challenges. Mol Cell Biochem. 2023 Aug;478(8):1743-1758. doi: 10.1007/s11010-022-04630-x. Epub 2022 Dec 24.

  PMID: 36565361 BACKGROUND

• Cignarelli A, Genchi VA, Caruso I, Natalicchio A, Perrini S, Laviola L, Giorgino F. Diabetes and cancer: Pathophysiological fundamentals of a 'dangerous affair'. Diabetes Res Clin Pract. 2018 Sep;143:378-388. doi: 10.1016/j.diabres.2018.04.002. Epub 2018 Apr 19.

  PMID: 29679627 BACKGROUND

• Francisco V, Pino J, Campos-Cabaleiro V, Ruiz-Fernandez C, Mera A, Gonzalez-Gay MA, Gomez R, Gualillo O. Obesity, Fat Mass and Immune System: Role for Leptin. Front Physiol. 2018 Jun 1;9:640. doi: 10.3389/fphys.2018.00640. eCollection 2018.

  PMID: 29910742 BACKGROUND

• Chiefari E, Mirabelli M, La Vignera S, Tanyolac S, Foti DP, Aversa A, Brunetti A. Insulin Resistance and Cancer: In Search for a Causal Link. Int J Mol Sci. 2021 Oct 15;22(20):11137. doi: 10.3390/ijms222011137.

  PMID: 34681797 BACKGROUND

• Yakar S, Leroith D, Brodt P. The role of the growth hormone/insulin-like growth factor axis in tumor growth and progression: Lessons from animal models. Cytokine Growth Factor Rev. 2005 Aug-Oct;16(4-5):407-20. doi: 10.1016/j.cytogfr.2005.01.010.

  PMID: 15886048 BACKGROUND

• Mao Z, Zhang W. Role of mTOR in Glucose and Lipid Metabolism. Int J Mol Sci. 2018 Jul 13;19(7):2043. doi: 10.3390/ijms19072043.

  PMID: 30011848 BACKGROUND

• Saxton RA, Sabatini DM. mTOR Signaling in Growth, Metabolism, and Disease. Cell. 2017 Mar 9;168(6):960-976. doi: 10.1016/j.cell.2017.02.004.

  PMID: 28283069 BACKGROUND

• Laplante M, Sabatini DM. mTOR signaling in growth control and disease. Cell. 2012 Apr 13;149(2):274-93. doi: 10.1016/j.cell.2012.03.017.

  PMID: 22500797 BACKGROUND

• Shlomai G, Neel B, LeRoith D, Gallagher EJ. Type 2 Diabetes Mellitus and Cancer: The Role of Pharmacotherapy. J Clin Oncol. 2016 Dec 10;34(35):4261-4269. doi: 10.1200/JCO.2016.67.4044. Epub 2016 Nov 7.

  PMID: 27903154 BACKGROUND

• Cho NH, Shaw JE, Karuranga S, Huang Y, da Rocha Fernandes JD, Ohlrogge AW, Malanda B. IDF Diabetes Atlas: Global estimates of diabetes prevalence for 2017 and projections for 2045. Diabetes Res Clin Pract. 2018 Apr;138:271-281. doi: 10.1016/j.diabres.2018.02.023. Epub 2018 Feb 26.

  PMID: 29496507 BACKGROUND

MeSH Terms

Conditions

Diabetes Mellitus, Type 2; Neoplasms

Condition Hierarchy (Ancestors)

Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Study Officials

• Flavia Prodam, MD PhD

  AOU Maggiore della Carità di Novara

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Flavia Prodam, MD PhD

CONTACT

+39 0321 660 693; flavia.prodam@med.uniupo.it

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Professor

Study Record Dates

• First Submitted: February 13, 2024
• First Posted: March 8, 2024
• Study Start: February 4, 2024
• Primary Completion: February 4, 2025
• Study Completion: February 4, 2025
• Last Updated: March 8, 2024

Record last verified: 2024-03

Locations

IT (1)