Performance of a multigene genomic classifier and clinical parameters in predicting malignancy in a Southeast Asian cohort of patients with cytologically indeterminate thyroid nodules.

BACKGROUND: Most thyroid nodules are benign. It is important to determine the likelihood of malignancy in such nodules to avoid unnecessary surgery. The primary objective of this study was to characterize the genetic landscape and the performance of a multigene genomic classifier in fine-needle aspiration (FNA) biopsies of cytologically indeterminate thyroid nodules in a Southeast Asian cohort. The secondary objective was to assess the predictive contribution of clinical characteristics to thyroid malignancy. METHODS: This prospective, multicenter, blinded study included 132 patients with 134 nodules. Molecular testing (MT) with ThyroSeq v3 was performed on clinical or ex-vivo FNA samples. Centralized pathology review also was performed. RESULTS: Of 134 nodules, consisting of 61% Bethesda category III, 20% category IV, and 19% category V cytology, and 56% were histologically malignant. ThyroSeq yielded negative results in 37.3% of all FNA samples and in 42% of Bethesda category III-IV cytology nodules. Most positive samples had RAS-like (41.7%), followed by BRAF-like (22.6%), and high-risk (17.9%) alterations. Compared with North American patients, the authors observed a higher proportion of RAS-like mutations, specifically NRAS, in Bethesda categories III and IV and more BRAF-like mutations in Bethesda category III. The test had sensitivity, specificity, negative predictive value, and positive predictive value of 89.6%, 73.7%, 84.0%, and 82.1%, respectively. The risk of malignancy was predicted by positive MT and high-suspicion ultrasound characteristics according to American Thyroid Association criteria. CONCLUSIONS: Even in the current Southeast Asian cohort with nodules that had a high pretest cancer probability, MT could lead to potential avoidance of diagnostic surgery in 42% of patients with Bethesda category III-IV nodules. MT positivity was a stronger predictor of malignancy than clinical parameters.

Personalised Dosing Using the CURATE.AI Algorithm: Protocol for a Feasibility Study in Patients with Hypertension and Type II Diabetes Mellitus.

Chronic diseases typically require long-term management through healthy lifestyle practices and pharmacological intervention. Although efficacious treatments exist, disease control is often sub-optimal leading to chronic disease-related sequela. Poor disease control can partially be explained by the 'one size fits all' pharmacological approach. Precision medicine aims to tailor treatments to the individual. CURATE.AI is a dosing optimisation platform that considers individual factors to improve the precision of drug therapies. CURATE.AI has been validated in other therapeutic areas, such as cancer, but has yet to be applied in chronic disease care. We will evaluate the CURATE.AI system through a single-arm feasibility study (n = 20 hypertensives and n = 20 type II diabetics). Dosing decisions will be based on CURATE.AI recommendations. We will prospectively collect clinical and qualitative data and report on the clinical effect, implementation challenges, and acceptability of using CURATE.AI. In addition, we will explore how to enhance the algorithm further using retrospective patient data. For example, the inclusion of other variables, the simultaneous optimisation of multiple drugs, and the incorporation of other artificial intelligence algorithms. Overall, this project aims to understand the feasibility of using CURATE.AI in clinical practice. Barriers and enablers to CURATE.AI will be identified to inform the system's future development.

The Impact of Frailty, Falls and Cognition on Osteoporosis Management in the Oldest Old.

Data and clinical guidelines on the management of osteoporosis in nonagenarians are lacking. The aim of this study was to assess the characteristics of osteoporosis management and identify any gaps or trends in a cohort of nonagenarians who were newly diagnosed with osteoporosis during an inpatient admission. A retrospective analysis of nonagenarians admitted to the medicine department of a tertiary hospital who were newly diagnosed with osteoporosis based on extracted ICD-10 codes. Baseline demographics, frailty based on the clinical frailty scale, comorbidities, initiation, compliance and adverse effects on osteoporosis medication were analysed. Mean age of the study group was 93.0 ± 2.5 years. There was a high prevalence of frailty (71.7%), cognitive impairment (34.2%) and recurrent falls (30.0%). 82.5% were started on osteoporosis treatment with denosumab (43.4%) being the most prescribed, followed by alendronate (41.4%). Cognitive impairment and male gender were associated with less likelihood of being on osteoporosis treatment on multivariate analysis. Having a previous fracture was associated with a higher likelihood of being on osteoporosis treatment. There was a discontinuation rate of 49.5% with a mean time to discontinuation of 26.3 ± 22.9 months. There was a high rate of osteoporosis treatment in nonagenarians with osteoporosis. The presence of previous fractures was associated with initiation of osteoporosis medications, whereas frailty and falls had no impact on treatment decisions. Cognitive impairment and males were associated with a lower rate of initiation of osteoporosis medication.