Identification of predictive factors of diabetic ketoacidosis in type 1 diabetes using a subgroup discovery algorithm.

Aim: To identify predictive factors for diabetic ketoacidosis (DKA) by retrospective analysis of registry data and the use of a subgroup discovery algorithm.

Materials And Methods: Data from adults and children with type 1 diabetes and more than two diabetes-related visits were analysed from the Diabetes Prospective Follow-up Registry. Q-Finder, a supervised non-parametric proprietary subgroup discovery algorithm, was used to identify subgroups with clinical characteristics associated with increased DKA risk.

Q-Finder: An Algorithm for Credible Subgroup Discovery in Clinical Data Analysis - An Application to the International Diabetes Management Practice Study.

Addressing the heterogeneity of both the outcome of a disease and the treatment response to an intervention is a mandatory pathway for regulatory approval of medicines. In randomized clinical trials (RCTs), confirmatory subgroup analyses focus on the assessment of drugs in predefined subgroups, while exploratory ones allow a posteriori the identification of subsets of patients who respond differently. Within the latter area, subgroup discovery (SD) data mining approach is widely used-particularly in precision medicine-to evaluate treatment effect across different groups of patients from various data sources (be it from clinical trials or real-world data).

MMS19 as a potential predictive marker of adjuvant chemotherapy benefit in resected non-small cell lung cancer.

Background: Resectable non-small cell lung cancer (NSCLC) treatment options most often consist of surgical resection along with adjuvant chemotherapy (ACT). The benefit of ACT however is modest and is accompanied by important side effects.

Objective: One central quest in the field is therefore the identification of a predictive marker of the response to ACT.

Radiographic analysis of the sagittal alignment and balance of the spine in asymptomatic subjects.

Background: There is an increasing recognition of the clinical importance of the sagittal plane alignment of the spine. A prospective study of several radiographic parameters of the sagittal profile of the spine was conducted to determine the physiological values of these parameters, to calculate the variations of these parameters according to epidemiological and morphological data, and to study the relationships among all of these parameters.

Methods: Sagittal radiographs of the head, spine, and pelvis of 300 asymptomatic volunteers, made with the subject standing, were evaluated.

[Validation of a tool to measure pelvic and spinal parameters of sagittal balance].

Purpose Of The Study: Parameters determining sagittal balance are essential for optimal analysis and treatment of many spinal disorders. The purpose of this work was to validate a software designed to measure the principal parameters involved in sagittal balance of the spine.

Material And Methods: Six parameters (lumbar lordosis, thoracic kyphosis, sagittal tilt at T9, pelvic index, pelvic tilt, slope of the sacrum) were measured on lateral views of the spine from 100 healthy volunteers free of any spinal disease.