Screening and Initiating Supportive Care in Patients With Heart Failure.

Background: Patients with heart failure (HF) experience a major symptom burden and an overall reduction of quality of life. However, supportive care (SC) remains an under-utilized resource for these patients. Among the many existing barriers to integrating SC into routine care, identifying patients with SC needs remains challenging. The Kansas City Cardiomyopathy Questionnaire (KCCQ) is an important predictor of SC needs in patients with HF. Methods and Results: We used the shortened version KCCQ-12 as a screening tool for SC need in our ambulatory HF patient population using a KCCQ-12 summary score of <29 as the cut-off. Of the 456 patients who completed the KCCQ-12, 41 (9%) were predicted to have SC needs. Demographics, medical history, biochemical parameters, echocardiographic assessment and medical treatment were similar between the two groups of patients. However, patients with KCCQ-12 <29 were more symptomatic based on both New York Heart Association (NYHA) classification and American Heart Association (AHA) staging with a higher prevalence of depression. We established a multidisciplinary SC clinic and the profile and outcomes of patients with SC needs that were referred and followed at our SC clinic were also evaluated. Twenty-three patients were referred to our SC clinic: 2 died before being seen, 1 refused SC and 20 received SC. Of these 20 patients, 11 died and 9 are currently being followed. Median survival after starting the SC clinic is 3 months. In the original SC cohort of 23, 17 patients had available KCCQ-12 summary scores. However, only 6 out of 17 (35%) had KCCQ-12 scores <29, indicating the need for additional assessment tools in this patient population. Conclusions: The magnitude of unmet supportive care needs in patients with HF is significant. While the KCCQ-12 questionnaire is a useful tool to identify patients with SC, serial clinical evaluation, establishment of a SC clinic and prompt referral are essential for patients needing supportive care.

A Phase 2/3 Multicenter, Randomized, Open-Label Study to Compare the Efficacy and Safety of Lenalidomide Versus Investigator's Choice in Patients with Relapsed or Refractory Diffuse Large B-Cell Lymphoma.

Purpose: Randomized, multicenter, open-label, phase 2/3 trial investigating lenalidomide versus investigator's choice (IC) in relapsed/refractory diffuse large B-cell lymphoma (DLBCL).Experimental Design: Patients with DLBCL who received ≥2 prior therapies were stratified by DLBCL subtype [germinal center B-cell (GCB) vs. non-GCB; determined by immunohistochemistry (IHC)] and then randomized 1:1 to lenalidomide (25 mg/day, 21 days of 28-day cycle) or IC (gemcitabine, rituximab, etoposide, or oxaliplatin). Crossover to lenalidomide was permitted for IC-treated patients with radiologically confirmed progressive disease. The primary endpoint was overall response rate (ORR). Progression-free survival (PFS), overall survival, and subtype analysis [GCB vs. activated B-cell (ABC)] using gene expression profiling (GEP) were exploratory endpoints.Results: Stage 1: 102 DLBCL patients (by IHC: non-GCB, n = 54; GCB, n = 48) received ≥1 dose of lenalidomide or IC. Hematologic treatment-emergent adverse events with lenalidomide versus IC included neutropenia (42.6%; 36.4%), anemia (33.3%; 47.3%), thrombocytopenia (24.1%; 43.6%), and leukopenia (5.6%; 12.7%), respectively. Overall, lenalidomide-treated patients had an ORR of 27.5% versus 11.8% in IC (ORRs were similar regardless of IHC-defined DLBCL subtype). Median PFS was increased in patients receiving lenalidomide (13.6 weeks) versus IC (7.9 weeks; P = 0.041), with greater improvements in non-GCB patients (15.1 vs. 7.1 weeks, respectively; P = 0.021) compared with GCB (10.1 vs. 9.0 weeks, respectively; P = 0.550).Conclusions: The clinical benefit of lenalidomide monotherapy in DLBCL patients was more evident in the non-GCB subtype. Exploratory analyses suggest that this preferential benefit was more pronounced in the GEP-defined ABC population, demonstrating a need for additional studies of lenalidomide in DLBCL using GEP subtyping. Clin Cancer Res; 23(15); 4127-37. ©2017 AACR.

Optimal design of experiments with anticipated pattern of missing observations.

We propose a general method of designing an experiment when there are potentially failing trials. We use polynomial models and the Michaelis-Menten model as examples and construct different types of optimal designs under a broad class of response probability functions. We show that the usual optimal designs, that assume all observations are available at the end of the experiment, can be quite inefficient if the anticipated missingness pattern is not accounted for at the design stage. We also investigate robustness properties of the proposed designs to specification of their nominal values and the response probability functions.