Mixtures of skew-t distributions offer a flexible choice for model-based clustering. A mixture model of this sort can be implemented using a variety of formulations of the skew-t distribution. Herein we develop a mixture of skew-t factor analyzers model for clustering of high-dimensional data using a flexible formulation of the skew-t distribution. Methodological details of our approach, which represents an extension of the mixture of factor analyzers model to a flexible skew-t distribution, are outlined and details of parameter estimation are provided. Clustering results are illustrated and compared to an alternative formulation of the mixture of skew-t factor analyzers model as well as the mixture of factor analyzers model.

The addition of PR and HER2 to NPI increases its 5-year prognostic accuracy. The iNPI can be considered as a clinically useful tool for stratification of patients with breast cancer receiving standard of care.

Background Children with advanced cancer experience symptoms despite access to quality care. Symptom research has previously relied upon retrospective designs and parent proxy rather than prospective measurement with self-report. Objective This study evaluated the feasibility of electronic data collection in children with advanced cancer using self-report of symptom frequency, severity, and distress. Methods A multisite prospective cohort design was used for this study. Children who were 7 to 18 years of age and English-speaking and had a diagnosis of advanced cancer were included. Symptom frequency, severity, and level of distress were measured every 2 weeks. Results Forty-six children completed 563 of 622 (91%) administered electronic symptom assessments. Pain, fatigue, nausea, and sleeping difficulties were the most reported symptoms across all assessments and during the last 12 weeks of life. Symptoms with the highest composite scores included pain, fatigue, nausea, and sleeping difficulties. During the last 12 weeks of life, pain, fatigue, diarrhea, and sleeping difficulties had the highest composite scores. When the domains of frequency, severity, and distress were compared between groups, children reported significantly higher frequency of pain and eating difficulty during the last 12 weeks of life. Conclusions Electronic data collection is a feasible way to evaluate the constellation of symptoms. Children with advanced cancer continue to experience physical and psychological symptoms, especially during the last 12 weeks of life despite quality care. Implications for Practice Assessment of symptom domains, including frequency, severity, and distress when symptoms are present may allow clinicians to better understand and manage symptoms of most concern to the patient.