Long-Lasting Therapeutic Response following Treatment with Pembrolizumab in Patients with Non-Small Cell Lung Cancer: A Real-World Experience.

Immune checkpoint inhibitors (ICIs), pembrolizumab in particular, have been shown to be vastly more efficacious than traditional cytotoxic or platinum-based chemotherapies in the treatment of non-small cell lung cancer (NSCLC). While there are plenty of data showing their efficacy and safety profiles, very little exists about the long-term effects of pembrolizumab. We compiled all patients with NSCLC who were treated with pembrolizumab at our institution and had progression-free survival (PFS) of at least 2 years during or after the treatment period. Within this group, we examined the long-term rates of PFS and overall survival (OS), side effect profiles, treatment, and overall disease course up to 60 months after starting treatment. This study included 36 patients with median (range) follow up times from treatment initiation in months as follows: 36 (28-65) overall; 39.5 (28-65) for adenocarcinoma; and 36 (30-58) for squamous cell carcinoma. The median (range) of OS and PFS (months) was comparable for adenocarcinoma, 36 (23-55); and squamous cell carcinoma, 35.5 (28-65). Overall, pembrolizumab shows remarkable long-term safety and efficacy in NSCLC patients. In patients who show an initially strong response and can make it to 24 months of PFS, disease progression after this period seems increasingly unlikely.

Can Dialysis Patients Identify and Diagnose Pulmonary Congestion Using Self-Lung Ultrasound?

BACKGROUND: With the recent developments in automated tools, smaller and cheaper machines for lung ultrasound (LUS) are leading us toward the potential to conduct POCUS tele-guidance for the early detection of pulmonary congestion. This study aims to evaluate the feasibility and accuracy of a self-lung ultrasound study conducted by hemodialysis (HD) patients to detect pulmonary congestion, with and without artificial intelligence (AI)-based automatic tools. METHODS: This prospective pilot study was conducted between November 2020 and September 2021. Nineteen chronic HD patients were enrolled in the Soroka University Medical Center (SUMC) Dialysis Clinic. First, we examined the patient's ability to obtain a self-lung US. Then, we used interrater reliability (IRR) to compare the self-detection results reported by the patients to the observation of POCUS experts and an ultrasound (US) machine with an AI-based automatic B-line counting tool. All the videos were reviewed by a specialist blinded to the performer. We examined their agreement degree using the weighted Cohen's kappa (Kw) index. RESULTS: A total of 19 patients were included in our analysis. We found moderate to substantial agreement between the POCUS expert review and the automatic counting both when the patient performed the LUS (Kw = 0.49 [95% CI: 0.05-0.93]) and when the researcher performed it (Kw = 0.67 [95% CI: 0.67-0.67]). Patients were able to place the probe in the correct position and present a lung image well even weeks from the teaching session, but did not show good abilities in correctly saving or counting B-lines compared to an expert or an automatic counting tool. CONCLUSIONS: Our results suggest that LUS self-monitoring for pulmonary congestion can be a reliable option if the patient's count is combined with an AI application for the B-line count. This study provides insight into the possibility of utilizing home US devices to detect pulmonary congestion, enabling patients to have a more active role in their health care.