Long-Term Treatment with Telotristat Ethyl in Patients with Carcinoid Syndrome Symptoms: Results from the TELEPATH Study.

INTRODUCTION: Telotristat ethyl is indicated for use in combination with somatostatin analogs (SSAs) to treat carcinoid syndrome (CS) diarrhea uncontrolled by SSAs alone in adults, but long-term safety and efficacy data beyond 48 weeks are needed. OBJECTIVES: The aims of the study were to evaluate the long-term safety and tolerability of telotristat ethyl and its effect on quality of life (QOL) in patients with CS. METHODS: In this phase 3, nonrandomized, multicenter, open-label, long-term extension study (TELEPATH), patients who participated in phase 2 or 3 trials of telotristat ethyl continued treatment at their present dose level (250 or 500 mg thrice daily) for 84 weeks. Safety and tolerability, the primary endpoint, were assessed by monitoring adverse events (AEs), serious AEs, AEs of special interest (AESIs; including liver-related AEs, depression, and gastrointestinal AEs), and deaths. The secondary objective was to evaluate changes in patients' QOL using validated cancer questionnaires and a subjective global assessment of CS symptoms. RESULTS: In 124 patients exposed to telotristat ethyl for a mean of 102.6 ± 53.2 weeks, the type and frequency of AEs were consistent with those reported in previous trials. The occurrence of AESIs was not related to dosage or duration of therapy. Most AEs were mild to moderate in severity, and no deaths were related to telotristat ethyl. QOL scores remained stable, and the majority of patients reported adequate symptom relief throughout the study. CONCLUSIONS: Safety results of TELEPATH support the long-term use of telotristat ethyl in patients with CS diarrhea. Telotristat ethyl was well-tolerated and associated with sustained improvement in QOL scores (NCT02026063).

Ramucirumab Safety in East Asian Patients: A Meta-Analysis of Six Global, Randomized, Double-Blind, Placebo-Controlled, Phase III Clinical Trials.

Purpose Several ramucirumab trials have reported a higher incidence of selected adverse events (AEs) in East Asian (EA) patients with cancer versus non-EA patients. A meta-analysis was conducted across six completed phase III trials to establish the safety parameters of ramucirumab in EA compared with non-EA patients. Materials and Methods Six global, randomized, double-blind, placebo-controlled, phase III registration trials investigating ramucirumab were assessed. Relative risks (RRs) and 95% CIs were calculated for selected all-grade and grade ≥ 3 AEs using fixed-effects and mixed-effects models. Ratio of RR and number needed to harm were calculated for AEs (all grade and grade ≥ 3) between EA and non-EA patients. Results Of 4,996 randomly assigned patients receiving ramucirumab or placebo, 802 (16.1%) were EA (ramucirumab, n = 411; placebo, n = 391) and 4,194 were non-EA (ramucirumab, n = 2,337; placebo, n = 1,857). Patient baseline characteristics were generally balanced between treatment arms in EA and non-EA patients, excluding sex and body weight. Grade ≥ 3 AEs possibly associated with ramucirumab, which were increased in EA versus non-EA patients, included neutropenia (42.1% v 25.5%, respectively) and proteinuria (3.9% v 0.6%, respectively). There was an increase in the RR of several grade ≥ 3 AEs, including hypertension and proteinuria, in ramucirumab-treated EA and non-EA patients compared with placebo. The ratio of RR revealed no significant differences between EA and non-EA patients for all-grade and grade ≥ 3 AEs. Conclusion Despite the enhanced propensity of selected AEs in EA patients relative to non-EA patients, there were no substantial differences in the RR for AEs possibly associated with ramucirumab in these phase III trials.

Unsupervised Discovery of Emphysema Subtypes in a Large Clinical Cohort.

Emphysema is one of the hallmarks of Chronic Obstructive Pulmonary Disorder (COPD), a devastating lung disease often caused by smoking. Emphysema appears on Computed Tomography (CT) scans as a variety of textures that correlate with disease subtypes. It has been shown that the disease subtypes and textures are linked to physiological indicators and prognosis, although neither is well characterized clinically. Most previous computational approaches to modeling emphysema imaging data have focused on supervised classification of lung textures in patches of CT scans. In this work, we describe a generative model that jointly captures heterogeneity of disease subtypes and of the patient population. We also describe a corresponding inference algorithm that simultaneously discovers disease subtypes and population structure in an unsupervised manner. This approach enables us to create image-based descriptors of emphysema beyond those that can be identified through manual labeling of currently defined phenotypes. By applying the resulting algorithm to a large data set, we identify groups of patients and disease subtypes that correlate with distinct physiological indicators.