Phenotyping Patients With Type 2 Diabetes Mellitus and Cancer

Cancer Clinical Trial

— TCPT2023  

Official title:

Type 2 Diabetes Mellitus and Cancer: Phenotyping of Patients at a Third-level Diabetes Centre

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT06299800
• Other study ID #: CE385/2023
• Status: Recruiting
• Start date: February 4, 2024
• Est. completion date: February 4, 2025

Study information

• Verified date: March 2024
• Source: Azienda Ospedaliero Universitaria Maggiore della Carita
• Contact: Flavia Prodam, MD PhD
• Phone: +39 0321 660 693
• Email: flavia.prodam[@]med.uniupo.it
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

Description:

Study design This study is a monocentric retrospective cohort study based on the data available in the Smart Digital Clinic (Meteda Srl) electronic medical record.

Participating centre Surgery of Endocrinology and Diabetology of the SCDU of Novara, University of Eastern Piedmont. Responsible: Prof.ssa Flavia Prodam

Subjects Will be included in the study all patients visited at the Endocrinology and Diabetology surgery of the AOU Major of the Charity of Novara for an initial diagnosis of diabetes mellitus type 2 between 1990 and 2010.

Inclusion criteria

• Legal age

• Diagnosis of type 2 diabetes mellitus Exclusion criteria

• 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

Duration of study: 24 months

Follow-up and events of interest Patients included in the study will be followed from the date of diagnosis of type 2 diabetes mellitus until the date of the last available examination.

During the follow-up, for all patients included, the year of onset of the first cancer after the diagnosis of diabetes and the type of tumor will be detected. From this information it will be possible to calculate the time between the diagnosis of diabetes and the onset of cancer (measured in years).

For patients who have developed a first tumor will also be detected:

1. Recurrence of cancer (year of onset of recurrence)

2. Diagnosis of second tumour not related to primary tumour (year of onset, type of tumour) The diagnosis of cancer will be identified through the extraction system from the electronic medical record Smart Digital Clinic (Meteda Srl), using key words relevant to the area of cancer, identified in the section of the medical history. The key words will be: metastasis, adenocarcinoma, carcinoma, neoplasm, secondary/s, sarcoma, tumor, adenoma, lymphoma, leukemia, glioma, glioblastoma, ependymoma, basalioma, epithelium, melanoma, mesothelioma, cordoma, anaplastic, differentiated, undifferentiated, meningioma, multiple myeloma, small cell carcinoma, timoma, craniopharyngioma, neuroendocrine, LH, LNH, K, GIST, HCC and NET.

Data collection

For each patient, the following variables will be extracted from the Smart Digital Clinic electronic medical record for all visits available after diagnosis, 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 mellitus 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 mellitus;

• Treatment of cancer;

• Family history of cancer; The diagnosis of type 2 diabetes mellitus is confirmed at diabetological centres or, in some cases, by general practitioners who refer patients to specialised diabetological centres. The accuracy of the diagnosis will be confirmed by crossing the Piedmont Diabetic Registry (PDR) and involving a second person to ensure a precise assessment.

BMI categories will be divided into underweight (BMI <18.5 Kg/m2), normal weight (BMI 18.5 - 25 Kg/m2), and overweight (BMI >25 Kg/m2).

With regard to the treatment of type 2 diabetes mellitus, participants will be categorised and grouped for statistical purposes in the following classes:

• Dietary therapy;

• Metformin/Acarbosio;

• Sulfanilurea;

• Metformin + GLP1/ DDPIV inhibitors (DDPIVi) or only GLP1 or only DDPIVi;

• Metformin + SGLT2i inhibitors (SGLT2i) or only SGLT2i;

• Basal insulin + GLP1/DDPIVi +/- Metformin;

• Basal insulin +/- Metformin +/- SGLT2i;

• Insulin basal bolus;

• Basal insulin bolus +/- Metformin +/- SGLT2i. In addition, complications of metabolic pathology will be extracted from the dedicated section of the program, where are systematically recorded and organized, and the diagnosis of which is conducted in accordance with the appropriate guidelines. These complications will be divided into the following categories: vasculopathy, neuropathy, hypertension, heart disease, kidney failure and retinopathy.

Finally, as regards cancer pathology, a categorization of treatment will be carried out in three classes: chemotherapy, surgery and radiation therapy.

In addition, the types of cancer will be divided in order to ensure greater homogeneity between groups, including the nervous system, head and neck, thorax, gastrointestinal, gynecological, urinary tract, male genital system, skin, blood, breast, soft tissues, endocrine glands and neuroendocrine tumors. This information will be collected at the diabetes diagnosis visit and at the last visit before the onset of cancer for the subjects experiencing the event and at the last available visit for the remaining subjects.

EXPECTED RESULTS Through this research, the investigators aim to obtain new information on the study population in order to better understand the possible correlation between the two pathologies. This will allow us to identify the risk factors associated with metabolic pathology that can affect the development time of cancer pathologies, as well as to identify those that could contribute to carcinogenesis itself.

This knowledge will allow us to define the role of hyperglycemia, obesity and other factors or behaviors at risk in the field of cancer in order to act with appropriate prevention strategies, thus considering the tumor pathology as one of the possible complications of type 2 diabetes mellitus.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 779
• Est. completion date: February 4, 2025
• Est. primary completion date: February 4, 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• Legal age

• Diagnosis of type 2 diabetes mellitus

Exclusion Criteria:

• 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

Related Conditions & MeSH terms

• Cancer
• Diabetes Mellitus
• Diabetes Mellitus, Type 2

Intervention

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

Locations

Country	Name	City	State
Italy	SCDU Endocrinology, AOU Ospedale Maggiore della Carità	Novara

Sponsors (1)

Lead Sponsor	Collaborator
Azienda Ospedaliero Universitaria Maggiore della Carita

Country where clinical trial is conducted

Italy, 

References & Publications (11)

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. — View Citation

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. Erratum In: Cell. 2017 Apr 6;169(2):361-371. — View Citation

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. — View Citation

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. — View Citation

* Note: There are 11 references in all — Click here to view all references

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	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)
Primary	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)
Primary	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)
Primary	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	First-line therapy characteristics assessment at first visit	Detection of drug therapy given at the first visit considering the medical record. The therapies considered were: Dietotherapy, Metformin/Acarbosio, Sulfanilurea, Metformin + GLP1/DDPIVi or GLP1 alone or DDDPIVi alone, Metformin + SGLT2i or SGLT2i alone, Basal insulin + GLP1/DPIVi +/- Metformin, Basal Insulin +/- Metformin + SGT2i, Insulin Basal Bolus, Insulin Basal Bolus +/- Metformin +/- SGLT2i	Assessment of data at time 0 (first clinical visit)
Secondary	Primary outcomes and recurrence or presence of a secondary tumor	Considering the risk factors measured as primary findings, it was intended to observe a possible association with those who had recurrence or with the development of a secondary tumour unrelated to the first, within 10 years of the diagnosis of diabetes. Detected during first clinical visit signed in the medical record	Assessment of data at time 0 (first clinical visit)
Secondary	Relationship between patients characteristics and the time onset of cancer considering anthropometric and biochemical data	Assess the relationship between the characteristics of patients and the time to the onset of cancer using medical record	Assessment of data at time 0 (first clinical visit)
Secondary	Tumour characterization in the considered population, detected at the first clinical visit	Characterization of tumors: tumors of the nervous system, head neck, thoracic, gastrointestinal, gynecological, urological, male genital, cutaneous, haematological, breast, soft tissue, endocrine glands, neuroendocrine and bone tumors. Detected during first clinical visit considering the medical record.	Assessment of data at time 0 (first clinical visit)