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.
