Anna Rauseo

Development and validation of a predicting model of all-cause mortality in patients with type 2 diabetes.

OBJECTIVE To develop and validate a parsimonious model for predicting short-term all-cause mortality in patients with type 2 diabetes mellitus (T2DM). RESEARCH DESIGN AND METHODS Two cohorts of patients with T2DM were investigated. The Gargano Mortality Study (GMS, n = 679 patients) was the training set and the Foggia Mortality Study (FMS, n = 936 patients) represented the validation sample. GMS and FMS cohorts were prospectively followed up for 7.40 ± 2.15 and 4.51 ± 1.69 years, respectively, and all-cause mortality was registered. A new forward variable selection within a multivariate Cox regression was implemented. Starting from the empty model, each step selected the predictor that, once included into the multivariate Cox model, yielded the maximum continuous net reclassification improvement (cNRI). The selection procedure stopped when no further statistically significant cNRI increase was detected. RESULTS Nine variables (age, BMI, diastolic blood pressure, LDL cholesterol, triglycerides, HDL cholesterol, urine albumin-to-creatinine ratio, and antihypertensive and insulin therapy) were included in the final predictive model with a C statistic of 0.88 (95% CI 0.82–0.94) in the GMS and 0.82 (0.76–0.87) in the FMS. Finally, we used a recursive partition and amalgamation algorithm to identify patients at intermediate and high mortality risk (hazard ratio 7.0 and 24.4, respectively, as compared with those at low risk). A web-based risk calculator was also developed. CONCLUSIONS We developed and validated a parsimonious all-cause mortality equation in T2DM, providing also a user-friendly web-based risk calculator. Our model may help prioritize the use of available resources for targeting aggressive preventive and treatment strategies in a subset of very high-risk individuals.

Association of the Q121 Variant of ENPP1 Gene With Decreased Kidney Function Among Patients With Type 2 Diabetes

BACKGROUND Insulin resistance has a role in diabetic kidney complications. The K121Q (lysine to glutamine substitution at amino acid 121, encoded by single-nucleotide polymorphism rs1044498) variant of the ectonucleotide pyrophosphatase/phosphodiesterase gene (ENPP1) has been associated with insulin resistance and related vascular complications in patients with type 2 diabetes (T2D) in many, although not all, studies. This study investigated whether the ENPP1 Q121 variant modulates the risk of decreased glomerular filtration rate (GFR) in patients with T2D. STUDY DESIGN Cross-sectional study. SETTING & PARTICIPANTS 2 diabetes units from Italy (in Gargano and Padua) and 1 from the United States (Boston, MA) recruited a total of 1,392 patients with T2D. PREDICTOR The ENPP1 Q121 variant. MEASUREMENTS Estimated GFR from serum creatinine, urinary albumin excretion, blood pressure, hemoglobin A(1c), triglycerides, total cholesterol, and high-density lipoprotein cholesterol. OUTCOMES Decreased GFRs (ie, estimated GFR <60 mL/min/1.73 m(2)). RESULTS In the Gargano and Boston populations, according to the dominant model of inheritance, Q121 carriers (ie, individual with either KQ or QQ alleles) had an increased risk of decreased GFR: odds ratios (ORs) of 1.69 (95% confidence interval [CI], 1.1 to 2.6) and 1.50 (95% CI, 1.0 to 2.2), respectively. In the Padua set, the association was in the same direction, but did not reach formal statistical significance (OR, 1.77; 95% CI, 0.7 to 4.5). When the 3 studies were pooled, Q121 carriers showed an increased risk of decreased GFR (OR, 1.58; 95% CI, 1.2 to 2.1; P = 0.002). Also, pooled mean differences in absolute GFRs were different across genotype groups, with Q121 carriers showing lower GFRs compared with KK individuals (P = 0.04). LIMITATIONS P values not approaching a genome-wide level of significance. CONCLUSIONS Our data suggest that patients with T2D carrying the ENPP1 Q121 variant are at increased risk of decreased GFR.