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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:
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
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:
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:
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:
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Diabetes mellitus type 2 and cancer | 779 patients with cancer and diagnosis of type 2 diabetes mellitus diagnosed between 1990 and 2010 |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| phenotyping of patients followed at a third-level diabetes centre with cancer | Other | Collection of the following data for each patient enrolled, where possible:
|
| Measure | Description | Time Frame |
|---|---|---|
| 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) |
| Measure | Description | Time Frame |
|---|---|---|
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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779 patients with diabetes mellitus type 2 and with at least 18 years old.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Flavia Prodam, MD PhD | Contact | +39 0321 660 693 | flavia.prodam@med.uniupo.it |
| Name | Affiliation | Role |
|---|---|---|
| Flavia Prodam, MD PhD | AOU Maggiore della Carità di Novara | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| SCDU Endocrinology, AOU Ospedale Maggiore della Carità | Recruiting | Novara | 28100 | Italy |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 22974359 | Background | 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. | |
| 36565361 | 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. |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Sep 10, 2023 | Mar 1, 2024 | Prot_SAP_000.pdf |
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| ID | Term |
|---|---|
| D003924 | Diabetes Mellitus, Type 2 |
| D009369 | Neoplasms |
| ID | Term |
|---|---|
| D003920 | Diabetes Mellitus |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
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|
| Assessment of data at time 0 (first clinical visit) |
| 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) |
| 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) |
| 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) |
| 29679627 | 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. |
| 29910742 | 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. |
| 34681797 | 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. |
| 15886048 | 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. |
| 30011848 | 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. |
| 28283069 | 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. |
| 22500797 | 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. |
| 27903154 | 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. |
| 29496507 | 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. |
| D004700 | Endocrine System Diseases |