Our population-based cohort study showed an excess of cancer incidence risk in people with diabetes. The effect was appreciable only in Type 2 diabetes, while Type 1 diabetes cancer incidence was similar to that of the population without diabetes. Among subjects affected by Type 2 diabetes, association was more relevant for insulin-treated patients, especially for combined therapy users. Compared to previous studies, our study observed smaller overall excess, probably due to the population-based approach related to diabetes registry. It allocated all diabetic subjects to the exposed group, but not limited to patients treated in specialized care centres, as they may represent a selected population suffering from more severe diabetes. Moreover, risk ratios did not substantially decrease when our analysis included only subjects with at least 2 years of diabetes duration. The algorithm used in Reggio Emilia our diabetes registry could detect diabetes subjects since disease onset, thus reducing potential detection bias, i.e. increasing likelihood of cancer diagnosis during diabetes initial assessment and follow up, as some authors assumed .
Nevertheless, we noted that relevant excess for some cancer sites was highly unlikely to be related to random fluctuations. In particular, our study turned out to be consistent with previous studies suggesting an increased cancer incidence for liver [4, 18], pancreas , colon rectum , and bladder  in population with diabetes. Furthermore, we found excess cancer risk for corpus uteri [6, 18], and a suggestion of reduced prostate cancer incidence [9, 18]. Finally, our data suggested an increased risk for ovary and kidney cancer in females, although increased risk for ovary cancer disappeared narrowing the analysis to subjects with at least 2 year diabetes duration.
A recent meta-analysis on diabetes and kidney cancer incidence  has suggested a stronger association in women, although there have been claims that “different proportions of men and women in the studies may in part account for the observed heterogeneity” and that obesity, which is more prevalent in women than men, could be a potential confounder.
As concerns pancreas cancer, the literature showed inconsistent results, and some studies have reported an up 4–5 fold increased risk for diabetic patients, while other studies did not find any increase at all . It must be stressed that studies which could effectively rule out reverse causality, (i.e. cancer increasing the risk of diabetes rather than vice versa) found a moderate increase of pancreas cancer risk in people with diabetes. Our study found an excess risk for pancreas, also restricting the analysis to patients with at least 2 years of diabetes duration, in which case reverse causality overcame.
Association with hypoglycaemic agents
As concerns Type 2 diabetes, we had an opportunity of classifying diabetic population according to antidiabetic treatment during 2009. We observed an increased risk related to increased therapy complexity, an indicator of disease severity. Our results were confirmed by the analysis performed among Type 2 diabetes subjects where we use also time since diagnosis as covariate. Unfortunately, we could not define treatment duration and consequently disentangle the insulin effect on cancer initiation and possible masked worse metabolic conditions (indication bias) or possible close monitoring practice (detection bias), as some authors did . Insulin association was consistent with other studies, which suggested a direct role of exogenous insulin and insulin analogues in carcinogenicity [19,20,21,22]. On the other hand, a direct role of insulin was inconsistent with the absence of any increase in cancer risk in Type 1 diabetes patients, who experienced a much longer use of insulin in their life.
The highest IRR was detected in patients treated with both OHAs and insulin. Such therapeutic regimen is usually followed by patients who cannot reach their glycaemic target with the help of just OHAs, often as a preliminary step before initiating sole insulin therapy . However, it can also be used in patients treated with insulin who gain weight or in patients with low compliance to insulin regimen. These patients may all show unstable and high glycaemic values or a worse metabolic state, so hyperglycaemia could amplify the hyperinsulinemia effect, thus increasing cancer risk.
Only a slight excess risk was observed in untreated Type 2 diabetes subjects, in comparison to drug-treated subjects. Such excess risk cannot be due to insulin or OHAs, rather, it might be confounded or mediated by overweight and obesity, which are well- known risk factors for both diabetes and many type of cancers .
Our study detected an increasing risk for diabetes duration up to 10 years from diagnosis and a subsequent decrease to moderate-higher risk. Our cohort study, which included prevalent cases of diabetes and incident cases of cancer, possibly minimized the so-called indication bias, which was detected by other studies [17, 18] in which follow up started at diabetes onset and tests recommended after a diabetes diagnosis might have increased the probability of detecting prevalent asymptomatic cancers. A decreased relative risk in the last group of diabetic subjects could be due to higher cancer incidence in people with diabetes, leading to a decreased susceptible population. A similar phenomenon of decreased excess risk has been recorded observed for mortality  and for cancer .
Strengths and limits
Strengths are represented by population-based approach thanks to clinically confirmed diabetes registry data, gender approach, including evaluation of heterogeneity between sexes and identification of the type of diabetes, including secondary diabetes, whose causality direction may be difficult to disentangle.
Classification according to patients’ current drug exposure could lead to misclassification. Moreover, we could not evaluate the potential role of some other non-assessed potential confounders, such as different types of insulin used (e.g. insulin analogues vs. human insulin), different mean daily doses of insulin, other drugs taken (e.g., acetylsalicylic acid, statins), glyco-metabolic control, and insulin resistance being present or not.
Nevertheless, the results related to “diet only” and “OHAs only” groups could be unaffected by insulin, and the former also by OHA response. Moreover, our cross-sectional classification of drug exposure was likely to be unaffected by immortal time bias (as we do not set conditions on the exposure duration) and by time-window bias (as we made no use of time dependent variables for exposure).
We did not collect relevant data about other risk factors, in particular positive family history for cancer, smoking, alcohol consumption, physical inactivity, BMI, workplace exposure to toxic substances, etc. We carried out a population-based study and, unlike observational studies of patients using clinical databases, we had limited clinical information on the general population. As regards smoking attitude, our data were confirmed by absence of lung cancer excess. On the other hand, we could not adjust for BMI, although we are well aware that BMI and diabetes could share some mechanisms of cancerogenesis or they could be two rings in the same causal chain. Therefore, further studies should be conducted to analyse possible mediation effect of glucose metabolism in the relationship between BMI and cancer.
As we mainly examined Caucasian race, it was impossible to extend our results to other ethnicities, although our analyses took into account foreign status.
Finally, we considered just 4-year follow up. Such time duration may seem quite short, if compared to time lag from exposure and cancer onset for most cancer sites. Thus, we were mainly concentrated on the effect of diabetes exposure occurred in the years before we started follow up.