Novel Autologous Dendritic Cell Therapy AVT001 for Type 1 Diabetes.

Background: CD8+ T regulatory (Treg) cells that recognize the nonclassical class 1b molecule Qa-1/human leukocyte antigen E (Q/E CD8+ Treg cells) are important in maintaining self-tolerance. We sought to investigate the role that these T cells play in type 1 diabetes (T1D) pathogenesis and whether an intervention targeting this mechanism may delay T1D progression.

Methods: We conducted a phase 1/2, randomized, double-blind, placebo-controlled trial of the autologous dendritic cell therapy AVT001 that included participants at least 16 years of age, within 1 year of T1D diagnosis, and with ex vivo evidence of a defect in Q/E CD8+ Treg function.

Canakinumab with and without pembrolizumab in patients with resectable non-small-cell lung cancer: CANOPY-N study design.

Canakinumab is a human IgGκ monoclonal antibody, with high affinity and specificity for IL-1β. The Canakinumab Anti-Inflammatory Thrombosis Outcome Study (CANTOS) trial, evaluating canakinumab for cardiovascular disease, provided the first signal of the potential of IL-1β inhibition on lung cancer incidence reduction. Here, we describe the rationale and design for CANOPY-N, a randomized Phase II trial evaluating IL-1β inhibition with or without immune checkpoint inhibition as neoadjuvant treatment in patients with non-small-cell lung cancer.

Safety and efficacy of the combination of sonidegib and ruxolitinib in myelofibrosis: a phase 1b/2 dose-finding study.

The sonidegib and ruxolitinib combination was assessed in an open-label study in JAK inhibitor-naive patients with myelofibrosis (MF). The primary objective of phase 1b was to establish the maximum tolerated dose (MTD) and/or recommended phase 2 dose (RP2D) and phase 2 was to assess spleen volume reduction at weeks 24 and 48. Fifty patients were enrolled.

Long-term efficacy and safety of ruxolitinib versus best available therapy in polycythaemia vera (RESPONSE): 5-year follow up of a phase 3 study.

Background: Polycythaemia vera is a myeloproliferative neoplasm characterised by excessive proliferation of erythroid, myeloid, and megakaryocytic components in the bone marrow due to mutations in the Janus kinase 2 (JAK2) gene. Ruxolitinib, a JAK 1 and JAK 2 inhibitor, showed superiority over best available therapy in a phase 2 study in patients with polycythaemia vera who were resistant to or intolerant of hydroxyurea. We aimed to compare the long-term safety and efficacy of ruxolitinib with best available therapy in patients with polycythaemia vera who were resistant to or intolerant of hydroxyurea.

Long-term survival in patients treated with ruxolitinib for myelofibrosis: COMFORT-I and -II pooled analyses.

Background: Myelofibrosis (MF) is associated with a variety of burdensome symptoms and reduced survival compared with age-/sex-matched controls. This analysis evaluated the long-term survival benefit with ruxolitinib, a Janus kinase (JAK)1/JAK2 inhibitor, in patients with intermediate-2 (int-2) or high-risk MF.

Methods: This was an exploratory analysis of 5-year data pooled from the phase 3 COMFORT-I and -II trials.

Phase I Study of the Pan-PI3K Inhibitor Buparlisib in Adult Chinese Patients with Advanced Solid Tumors.

Background/aim: The phosphatidylinositol-3-kinase (PI3K) signaling pathway is frequently activated in cancer. Buparlisib (BKM120), an oral pan-PI3K inhibitor, inhibits proliferation of human cancer in preclinical models. Studies of buparlisib in Western and Japanese adults with advanced solid tumors established a recommended dose of 100 mg/day and showed an acceptable safety profile and evidence of efficacy.

A new diagnostic accuracy measure and cut-point selection criterion.

Most diagnostic accuracy measures and criteria for selecting optimal cut-points are only applicable to diseases with binary or three stages. Currently, there exist two diagnostic measures for diseases with general k stages: the hypervolume under the manifold and the generalized Youden index. While hypervolume under the manifold cannot be used for cut-points selection, generalized Youden index is only defined upon correct classification rates.

Confidence Interval Estimation for Sensitivity to the Early Diseased Stage Based on Empirical Likelihood.

Many disease processes can be divided into three stages: the non-diseased stage: the early diseased stage, and the fully diseased stage. To assess the accuracy of diagnostic tests for such diseases, various summary indexes have been proposed, such as volume under the surface (VUS), partial volume under the surface (PVUS), and the sensitivity to the early diseased stage given specificity and the sensitivity to the fully diseased stage (P2). This paper focuses on confidence interval estimation for P2 based on empirical likelihood.

Confidence interval estimation of the difference between two sensitivities to the early disease stage.

Although most of the statistical methods for diagnostic studies focus on disease processes with binary disease status, many diseases can be naturally classified into three ordinal diagnostic categories, that is normal, early stage, and fully diseased. For such diseases, the volume under the ROC surface (VUS) is the most commonly used index of diagnostic accuracy. Because the early disease stage is most likely the optimal time window for therapeutic intervention, the sensitivity to the early diseased stage has been suggested as another diagnostic measure.

Parametric and non-parametric confidence intervals of the probability of identifying early disease stage given sensitivity to full disease and specificity with three ordinal diagnostic groups.

In practice, there exist many disease processes with three ordinal disease classes, that is, the non-diseased stage, the early disease stage, and the fully diseased stage. Because early disease stage is likely the best time window for treatment interventions, it is important to have diagnostic tests that have good diagnostic ability to discriminate the early disease stage from the other two stages. In this paper, we present both parametric and non-parametric approaches for confidence interval estimation of probability of detecting early disease stage given the true classification rates for non-diseased group and diseased group, namely, the specificity and the sensitivity to full disease.