Clinical relevance of gene mutations and rearrangements in advanced differentiated thyroid cancer

Background: Tumor genotyping is becoming crucial to optimize the clinical management of patients with advanced differentiated thyroid cancer (DTC); however, its implementation in clinical practice remains undefined. We herein report our single-center experience on molecular advanced DTC testing by next-generation sequencing approach, to better define how and when tumor genotyping can assist clinical decision making. Materials and methods: We retrospectively collected data on all adult patients with advanced DTC who received molecular profiling at the IRCSS Sant'Orsola-Malpighi Hospital from 2008 to 2022. The genetic alterations were correlated with radioactive iodide refractory (RAI-R), RAI uptake/disease status, and time to RAI resistance (TTRR) development. Results: A significant correlation was found between RAI-R development and genetic alterations (P = 0.0001). About 48.7% of RAI-R cases were positive for TERT/TP53 mutations (as both a single event and comutations with other driver gene alterations, such as BRAF mutations, RAS mutations, or gene fusions), while the great majority of RAI-sensitive cases carried gene fusions (41.9%) or were wild type (WT; 41.9%). RAI uptake/disease status and time to TTRR were significantly associated with genetic alterations (P = 0.0001). In particular, DTC with TERT/TP53 mutations as a single event or as comutations displayed a shorter median TTRR of 35.4 months (range 15.0-55.8 months), in comparison to the other molecular subgroups. TERT/TP53 mutations as a single event or as comutations remained independently associated with RAI-R after Cox multivariate analysis (hazard ratio 4.14, 95% CI 1.51-11.32; P = 0.006). Conclusions: Routine testing for genetic alterations should be included as part of the clinical workup, for identifying both the subset of more aggressive tumors and the subset of tumors harboring actionable gene fusions, thus ensuring the appropriate management for all patients with advanced DTC

Association of kidney disease measures with risk of renal function worsening in patients with type 1 diabetes

Background: Albuminuria has been classically considered a marker of kidney damage progression in diabetic patients and it is routinely assessed to monitor kidney function. However, the role of a mild GFR reduction on the development of stage 653 CKD has been less explored in type 1 diabetes mellitus (T1DM) patients. Aim of the present study was to evaluate the prognostic role of kidney disease measures, namely albuminuria and reduced GFR, on the development of stage 653 CKD in a large cohort of patients affected by T1DM. Methods: A total of 4284 patients affected by T1DM followed-up at 76 diabetes centers participating to the Italian Association of Clinical Diabetologists (Associazione Medici Diabetologi, AMD) initiative constitutes the study population. Urinary albumin excretion (ACR) and estimated GFR (eGFR) were retrieved and analyzed. The incidence of stage 653 CKD (eGFR < 60 mL/min/1.73 m2) or eGFR reduction > 30% from baseline was evaluated. Results: The mean estimated GFR was 98 \ub1 17 mL/min/1.73m2 and the proportion of patients with albuminuria was 15.3% (n = 654) at baseline. About 8% (n = 337) of patients developed one of the two renal endpoints during the 4-year follow-up period. Age, albuminuria (micro or macro) and baseline eGFR < 90 ml/min/m2 were independent risk factors for stage 653 CKD and renal function worsening. When compared to patients with eGFR > 90 ml/min/1.73m2 and normoalbuminuria, those with albuminuria at baseline had a 1.69 greater risk of reaching stage 3 CKD, while patients with mild eGFR reduction (i.e. eGFR between 90 and 60 mL/min/1.73 m2) show a 3.81 greater risk that rose to 8.24 for those patients with albuminuria and mild eGFR reduction at baseline. Conclusions: Albuminuria and eGFR reduction represent independent risk factors for incident stage 653 CKD in T1DM patients. The simultaneous occurrence of reduced eGFR and albuminuria have a synergistic effect on renal function worsening

Planning sustainable development through a scenario-based stochastic goal programming model

Most real-world optimization problems involve numerous conflicting criteria, imprecise information estimates and goals, thus the stochastic goal programming method offers an analytical framework to model and solve such problems. In this paper, we develop a stochastic goal programming model with satisfaction function that integrates optimal resource (labor) allocation to simultaneously satisfy conflicting criteria related to economic development, energy consumption, workforce allocation, and greenhouse gas emissions. We validate the model using sectorial data obtained from diverse sources on vital economic sectors for the United Arab Emirates. The results offer significant insights to decision makers for strategic planning decisions and investment allocations towards achieving long term sustainable development goals