OBJECTIVE OF THE STUDY Evaluate the evolution of the therapy’s quality by gender in type 2 diabetes (DM2) in Italy, from 2011 to 2016, considering the new AMD Indicators in a gender perspective and the possible disparity in the drug treatment. DESIGN AND METHODS For the purpose of this analysis, data from the AMD Annals 2018 were used. They refer to patients with DM2, treated in 2016 in 222 diabetology services. This report is based on the analysis of the new 2015 AMD indicators (Audit 2, January 23rd, 2018). The characteristics of the study population and the analysis of the indicators are reported separately for men and women affected by DM2. RESULTS The data of 242,422 men and 184,696 women with DM2 were evaluated. The patients were treated by 222 diabetology services in 2016. The distribution by gender shows the prevalence of males and the one by age shows a general aging of the population and an increased survival, mainly in women (3.6% of men and 6.6% of women with DM2 have an age >85 years). The average number of visits per treatment group was comparable between sexes. Compared to the 2011 evaluation, an improvement was achieved in all the process indicators in both genders, although still slightly better in males. In particular, the evaluation of metabolic control through the monitoring of glycated hemoglobin affects almost all male and female patients (96.9% vs 97%). The percentage of patients monitored for lipid profile, renal function, retinopathy and foot screening is lower. Some parameters were considered intermediate outcome indicators as they predict cardiovascular (CV) risk: the achievement of targets for the main CV risk factors is systematically unfavorable for women with DM2. In particular, women are more obese, have a worse diabetes compensation (especially a worse lipid profile) and a greater frequency of glomerularfiltrate reduction. The average levels of glycosylated hemoglobin were slightly higher in women than in men (7,3% ± 1,3 vs 7,2% ± 1,2), also the average levels of LDL cholesterol (100,2 mg/dl ± 33,4 vs 92,5 mg/dl ± 32,3) and average BMI levels (30,1 kg/m2 ± 6.1 vs 29,2 kg / m2 ± 4,9). In comparison with 2011 data, is noticeable a slight reduction in smokers among males and a slight increase among women (20,5% vs 21,5% in men, 12,2% vs 11,8% in women). Overall, the quality of the therapy (assessed with Q score) has improved over the years, in a similar way for both sexes. About half of the patients, in both sexes, have a Q score >25, therefore adequate levels of therapy. The use of drugs for the control of glycaemia in both genders is similar also for innovative drugs. The use of statins is high in both sexes, slightly in favor of women. The intensity of the therapy for hypertension has improved in both sexes. Hence, the available data does not highlight a problem of under-treatment of women, despite their worst results. Gender data related to micro and macroangiopathic complications show differences in the two sexes, but the quality of the data recording on final outcomes, especially cardiovascular, is still modest. CONCLUSIONS Data analysis shows a significant improvement in the quality of specialistic health care, with greater attention in monitoring CV risk factors and complications, an increase in the percentage of subjects in target and a more intensive use of drugs in both sexes. However, some gaps are still present. The examined data confirm that the cardiovascular risk profile is decidedly unfavorable for women and that the main cardiovascular risk factors control, although improved over the years, remains sub-optimal in women and men. Greater efforts are needed to optimize CV risk factors management in both sexes and to reduce, or better eliminate, differences between genders. These data offer important insights for research, clinical practice and review of guidelines in a gender perspective, taking into account that various factors related to gender, such as genetic/biological aspects, lifestyle, adherence to therapies, psycho-social aspects, in addition to prescriptive differences, can affect the achievement of the various outcomes. KEYWORDS gender; DM2; AMD indicators.