Association of pre-existing autoimmune diseases in melanoma patients receiving immune checkpoint inhibition with improved survival and increased toxicity.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e21586-e21586
Author(s):  
Nicholas Gulati ◽  
Arda Celen ◽  
Paul Johannet ◽  
Amelia Sawyers ◽  
Min Jae Kim ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Autoimmune Disease ◽  
Autoimmune Diseases ◽  
Immune Checkpoint ◽  
Standard Of Care ◽  
Controlled Clinical Trial ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Before And After ◽  
The Impact

e21586 Background: Immune checkpoint inhibition (ICI) improves progression-free (PFS) and overall survival (OS) for patients with metastatic melanoma (MM), but induces immune-related adverse events (irAEs). Pre-existing autoimmune disease (pre-AI) is considered a relative contraindication due to concerns of inciting autoimmune flare. We here tested the impact of pre-AI on both the survival and irAEs in MM patients treated with ICI. Methods: We examined MM patients treated with ICI who were enrolled in a clinicopathological database at NYULH with protocol-driven prospective follow up. We compiled a comprehensive list of 23 autoimmune diseases and examined the presence of these diseases prior to ICI treatment. We tested the associations between pre-AI and PFS, OS, and irAEs both in univariate and multivariate models. Results: 74/485 (15.3%) patients, who received 718 lines of ICI treatment as either standard of care or in clinical trials, had pre-AI, most commonly asthma (n=42), inflammatory bowel disease (n=9), psoriasis (n=9), rheumatoid arthritis (n=7), and eczema (n=6). In patients receiving ICI as standard of care (n=535), pre-AI was associated with irAEs (P=0.05) as well as with significantly improved PFS (P=0.024) and OS (P=0.007), controlling for patients’ sex, age, stage, ECOG status, and treatment line (1st line versus 2nd or 3rd line). However, no associations were observed between pre-AI and PFS (P=0.2) or irAEs (P=0.54) in the clinical trial group. Conclusions: Our data demonstrate the disparate impact of pre-AI on response and irAEs in standard of care versus the highly controlled clinical trial settings, and underscore the importance of examining the complex interaction between autoimmune disease before and after initiation of ICI. Our data also challenge the notion that clinicians should avoid use of ICI in pre-AI patients. More mechanistic research is needed to understand how to uncouple ICI response from toxicity.

Outcomes in Melanoma Patients Treated with BRAF/MEK-Directed Therapy or Immune Checkpoint Inhibition Stratified by Clinical Trial versus Standard of Care

Oncology ◽  
2017 ◽  
Vol 93 (3) ◽  
pp. 164-176 ◽  
Author(s):  
Chloe Goldman ◽  
Jeremy Tchack ◽  
Eric M. Robinson ◽  
Sung Won Han ◽  
Una Moran ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Immune Checkpoint ◽  
Standard Of Care ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Melanoma Patients

scholarly journals Immune Checkpoint Inhibition and the Prevalence of Autoimmune Disorders Among Patients With Lung and Renal Cancer

2017 ◽  
Vol 16 ◽  
pp. 117693511771252 ◽  
Author(s):  
Sherif M El-Refai ◽  
Joshua D Brown ◽  
Esther P Black ◽  
Jeffery C Talbert
Keyword(s):  
Autoimmune Diseases ◽  
Renal Cancer ◽  
Immune Checkpoint ◽  
Immune Checkpoint Inhibitors ◽  
Checkpoint Inhibitors ◽  
International Classification Of Diseases ◽  
Autoimmune Disorders ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Autoimmune Condition

Purpose: Immune checkpoint inhibition reactivates the immune response against cancer cells in multiple tissue types and has been shown to induce durable responses. However, for patients with autoimmune disorders, their conditions can worsen with this reactivation. We sought to identify, among patients with lung and renal cancer, how many harbor a comorbid autoimmune condition and may be at risk of worsening their condition while on immune checkpoint inhibitors such as nivolumab and pembrolizumab. Methods: An administrative health care claims database, Truven MarketScan, was used to identify patients diagnosed with lung and renal cancer from 2010 to 2013. We assessed patients for diagnosis of autoimmune diseases 1 year prior to or after diagnosis of cancer using International Classification of Diseases, Ninth Revision codes for 41 autoimmune diseases. Baseline characteristics and other comorbid conditions were recorded. Results: More than 25% of patients with both lung and renal cancer had a comorbid autoimmune condition between 2010 and 2013 and were more likely to be women, older, and have more baseline comorbidities. Conclusions: This population presents a dilemma to physicians when deciding to treat with immune checkpoint inhibitors and risk immune-related adverse events. Future evaluation of real-world use of immune checkpoint inhibitors in patients with cancer with autoimmune diseases will be needed.

scholarly journals Clinical impact of COVID-19 on patients with cancer treated with immune checkpoint inhibition

2021 ◽  
Vol 9 (1) ◽  
pp. e001931
Author(s):  
Aljosja Rogiers ◽  
Ines Pires da Silva ◽  
Chiara Tentori ◽  
Carlo Alberto Tondini ◽  
Joseph M Grimes ◽  
...  
Keyword(s):  
Immune Checkpoint ◽  
Primary Objective ◽  
Adverse Outcomes ◽  
Severe Illness ◽  
Checkpoint Inhibition ◽  
Immune Checkpoint Inhibition ◽  
Factors Associated ◽  
Patients With Cancer ◽  
Increased Risk ◽  
The Impact

BackgroundPatients with cancer who are infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are more likely to develop severe illness and die compared with those without cancer. The impact of immune checkpoint inhibition (ICI) on the severity of COVID-19 illness is unknown. The aim of this study was to investigate whether ICI confers an additional risk for severe COVID-19 in patients with cancer.MethodsWe analyzed data from 110 patients with laboratory-confirmed SARS-CoV-2 while on treatment with ICI without chemotherapy in 19 hospitals in North America, Europe and Australia. The primary objective was to describe the clinical course and to identify factors associated with hospital and intensive care (ICU) admission and mortality.FindingsThirty-five (32%) patients were admitted to hospital and 18 (16%) died. All patients who died had advanced cancer, and only four were admitted to ICU. COVID-19 was the primary cause of death in 8 (7%) patients. Factors independently associated with an increased risk for hospital admission were ECOG ≥2 (OR 39.25, 95% CI 4.17 to 369.2, p=0.0013), treatment with combination ICI (OR 5.68, 95% CI 1.58 to 20.36, p=0.0273) and presence of COVID-19 symptoms (OR 5.30, 95% CI 1.57 to 17.89, p=0.0073). Seventy-six (73%) patients interrupted ICI due to SARS-CoV-2 infection, 43 (57%) of whom had resumed at data cut-off.InterpretationCOVID-19–related mortality in the ICI-treated population does not appear to be higher than previously published mortality rates for patients with cancer. Inpatient mortality of patients with cancer treated with ICI was high in comparison with previously reported rates for hospitalized patients with cancer and was due to COVID-19 in almost half of the cases. We identified factors associated with adverse outcomes in ICI-treated patients with COVID-19.

scholarly journals Predictive Monitoring: IMPact in Acute Care Cardiology Trial (PM-IMPACCT) - A Randomized Clinical Trial Protocol (Preprint)

2021 ◽  
Author(s):  
Jess Keim-Malpass ◽  
Sarah J Ratcliffe ◽  
Liza P Moorman ◽  
Matthew T Clark ◽  
Katy N Krahn ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Acute Care ◽  
Predictive Analytics ◽  
Healthcare Providers ◽  
Standard Of Care ◽  
Clinical Deterioration ◽  
Controlled Clinical Trial ◽  
Randomized Controlled ◽  
Icu Transfer ◽  
The Impact

BACKGROUND Patients on acute care wards who deteriorate and are emergently transferred to intensive care units have poor outcomes. Early identification of decompensating patients might allow for earlier clinical intervention and reduced morbidity and mortality. Advances in bedside continuous predictive analytics monitoring (i.e., artificial intelligence (AI)-based risk prediction) make complex data easily available to healthcare providers, and can provide early warning of potentially catastrophic clinical events. We present a dynamic, visual predictive analytics monitoring tool that integrates real-time bedside telemetric physiologic data into robust clinical models to estimate and communicate risk of imminent events. This tool, CoMET (Continuous Monitoring of Event Trajectories), has been shown in retrospective observational studies to predict clinical decompensation on the acute care ward. There is a need to more definitively study this advanced predictive analytics or AI monitoring system in a prospective, randomized controlled clinical trial. OBJECTIVE The goal of this trial is to determine the impact of an AI-based visual risk analytic, CoMET, on: (1) improving patient outcomes related to clinical deterioration, (2) response time to proactive clinical action, and (3) costs to the healthcare system. METHODS We propose a cluster randomized controlled trial (NCT04359641) to test the impact of displaying CoMET on an acute care cardiology and cardiothoracic surgery hospital floor. The number of admissions to a room undergoing cluster-randomization is estimated to be 10,424 over the 20-month study period. Cluster randomization based on bed number occurs every 2 months. The intervention cluster will have the CoMET score displayed (along with standard of care), while the usual care group receives standard of care only. RESULTS The primary outcome will be hours free from events of clinical deterioration. Hours of acute clinical events are defined as time when one or more of the following occur: emergent ICU transfer, emergent surgery prior to ICU transfer, cardiac arrest prior to ICU transfer, emergent intubation, or death. The clinical trial began randomization in January 2021. CONCLUSIONS Very few AI-based health analytics are translated from algorithm to real-world use. This study will use robust prospective, randomized controlled clinical trial methodology to assess the effectiveness of an advanced AI predictive analytics monitoring system incorporating real-time telemetric data for identifying clinical deterioration on acute care wards. This analysis will strengthen the ability of healthcare organizations to evolve as learning health systems, which apply bioinformatics data to improve patient outcomes by incorporating AI into knowledge tools that are successfully integrated into clinical practice by healthcare providers. CLINICALTRIAL Clinical trials identifier: NCT04359641

The effect of the transfemoral prosthetic socket interface designs on skeletal motion and socket comfort: A randomized clinical trial

2020 ◽  
Vol 44 (3) ◽  
pp. 145-154 ◽  
Author(s):  
Jason Kahle ◽  
Rebecca Maria Miro ◽  
Loi T Ho ◽  
Michael Porter ◽  
Derek J Lura ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Repeated Measures ◽  
Weight Bearing ◽  
Standard Of Care ◽  
Vertical Movement ◽  
Full Weight Bearing ◽  
Controlled Clinical Trial ◽  
Current Standard ◽  
Prosthetic Socket ◽  
The Impact

Background: The most crucial aspect of a prosthesis is the socket, as it will directly determine gait stability and quality. The current standard of care ischial ramus containment socket is reported to increase coronal stability through gait; however, socket discomfort is the primary complaint among prosthetic users. Objectives: The purpose of this study is to compare ischial ramus containment to alternatives in the transfemoral amputee population. All subjects were fit with three different sockets: traditional ischial ramus containment, a dynamic socket, and a sub-ischial. In this study, authors hypothesized socket skeletal motion would be equivalent across interventions. Study Design: Single-blind, repeated-measures, three-period randomized crossover clinical trial. Methods: Outcome measures were socket comfort score and skeletal motion, viewed coronally with X-ray measuring the position of the skeleton in relationship to the socket in full weight-bearing and full un-loading. Results: The mean age was 38.2 and mean Amputee Mobility Predictor score was 40. Mean vertical movement, horizontal movement, single limb prosthetic stance, mean femoral adduction in swing and stance, and median socket comfort score were not statistically different. Conclusion: The socket design did not significantly effect skeletal motion and socket comfort. All socket designs are suitable depending on the patient-centric preferences and prosthetist skill set. Clinical relevance The comfort of the standard of care transfemoral amputation socket has been widely reported as problematic. A comparison of alternative designs in a controlled clinical trial environment will assist the clinician in understanding the impact of design regarding skeletal motion and comfort. Users could benefit from alternatives applied in clinical practice.

scholarly journals Empirical Treatment Against Cytomegalovirus and Tuberculosis in HIV-Infected Infants with Severe Pneumonia: Study Protocol for a Multicenter, an Open-Label Randomized Controlled Clinical Trial

2021 ◽  
Author(s):  
Alfredo Tagarro ◽  
Cinta Moraleda ◽  
Sara Dominguez ◽  
Pui-Ying Iroh Tam ◽  
Christopher William Buck ◽  
...  
Keyword(s):  
Clinical Trial ◽  
Severe Pneumonia ◽  
Standard Of Care ◽  
Empirical Treatment ◽  
Controlled Clinical Trial ◽  
African Countries ◽  
Clinical Trial Registry ◽  
Open Label ◽  
Secondary Endpoints ◽  
The Impact

Abstract Background Pneumonia is the primary cause of death among HIV-infected children in Africa, with mortality rates as high as 35-40% in infants hospitalized with severe pneumonia. Bacterial pathogens and Pneumocystis jirovecii are well known causes of pneumonia-related death, but other important causes such as cytomegalovirus (CMV) and tuberculosis (TB) remain under-recognized and under-treated.The immune response elicited by CMV may be associated with the risk of developing TB and TB disease progression, and CMV may accelerate disease caused both by HIV and TB. Minimally invasive autopsies confirm that CMV and TB are unrecognized causes of death in children wit HIV. CMV and TB may also co-infect the same child. The aim of this study is to compare the impact on 15-day and 1-year mortality of empirical treatment against TB and CMV plus standard of care (SoC) versus SoC in HIV-infected infants with severe pneumonia. Methods This is a Phase II-III, open-label randomized factorial (2x2) clinical trial, conducted in six African countries. The trial has four arms. Infants from 28 to 365 days of age HIV-infected and hospitalized with severe pneumonia will be randomized (1:1:1:1) to i) SoC, ii) valganciclovir iii) TB-T and iv) TB-T plus valganciclovir. The primary endpoint of the study is all-cause mortality, focusing on the short term (up to 15-days) and long-term (up to 1-year) mortality. Secondary endpoints include repeat hospitalization, duration of oxygen therapy during initial admission, severe and notable adverse events, adverse reactions, CMV and TB prevalence at enrolment, TB incidence, CMV viral load reduction, and evaluation of diagnostic tests such as GeneXpert Ultra on fecal and nasopharyngeal aspirate samples and urine TB-LAM.Discussion Given the challenges in diagnosing CMV and TB in children and results from previous autopsy studies that show high rates of poly-infection in HIV-infected infants with respiratory disease, , this study aims to evaluate a new approach including empirical treatment of CMV and TB for this patient population. The potential downsides of empirical treatment of these conditions including toxicity, and medication interactions, which will be evaluated with pharmacokinetics substudies. Trial Registration: ClinicalTrials.gov, NCT03915366, Universal Trial Number U111-1231-4736, Pan African Clinical Trial Registry PACTR201994797961340.

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