Publications by authors named "Robert Beveridge"
Article Synopsis
- - The study analyzed how anthracycline-based neoadjuvant chemotherapy (NAC) affects immune cells' spatial distribution in high-risk soft tissue sarcomas (STS) and how this relates to patient outcomes.
- - Researchers examined various tumor areas for specific immune cells using advanced pathology techniques and created a sarcoma immune index (SIS) to predict disease-free and overall survival rates.
- - Findings revealed that certain immune cell types, particularly PD-1+ and CD20+ B-cells, correlated with prognosis differently based on their locations within the tumor, highlighting NAC's role in altering tumor immune characteristics.
Background: The Complexity INdex in SARComas (CINSARC) is a transcriptional signature derived from the expression of 67 genes involved in mitosis control and chromosome integrity. This study aims to assess CINSARC value of in an independent series of high-risk patients with localized soft tissue sarcoma (STS) treated with preoperative chemotherapy within a prospective, randomized, phase III study (ISG-STS 1001).
Patients And Methods: Patients with available pre-treatment samples, treated with 3 cycles of either standard (ST) preoperative or histotype-tailored (HT) chemotherapy, were scored according to CINSARC (low-risk, C1; high-risk, C2).
Histotype-tailored neoadjuvant chemotherapy versus standard chemotherapy in patients with high-risk soft-tissue sarcomas (ISG-STS 1001): an international, open-label, randomised, controlled, phase 3, multicentre trial.
Lancet Oncol
June 2017
Background: Previous trials from our group suggested an overall survival benefit with five cycles of adjuvant full-dose epirubicin plus ifosfamide in localised high-risk soft-tissue sarcoma of the extremities or trunk wall, and no difference in overall survival benefit between three cycles versus five cycles of the same neoadjuvant regimen. We aimed to show the superiority of the neoadjuvant administration of histotype-tailored regimen to standard chemotherapy.
Methods: For this international, open-label, randomised, controlled, phase 3, multicentre trial, patients were enrolled from 32 hospitals in Italy, Spain, France, and Poland.
Objective: To determine the inter-observer agreement on triage assignment by first-time users with diverse training and background using the Canadian Emergency Department Triage and Acuity Scale (CTAS).
Methods: Twenty emergency care providers (5 physicians, 5 nurses, 5 Basic Life Support paramedics and 5 Advanced Life Support paramedics) at a large urban teaching hospital participated in the study. Observers used the 5-level CTAS to independently assign triage levels for 42 case scenarios abstracted from actual emergency department patient presentations.
Objective: To assess the performance of the newly implemented Canadian Emergency Department Triage and Acuity Scale (CTAS) triage system in a redesigned 200-bed community hospital emergency department (ED) and to evaluate the predictive validity of CTAS in this setting.
Methods: Triage system performance was analyzed on the basis of 4 quality indicators: time to triage; triage duration; proportion of patients who left without being seen by a physician; and waiting time to nurse and physician, stratified by triage level and reported as fractile response rates. The predictive validity of CTAS was evaluated by investigating the relationship between CTAS level, hospitalization index, ED length of stay (LOS) and diagnostic test utilization.
Background: Few assessments of the costs and benefits of reducing acute cardiorespiratory morbidity related to air pollution have employed a comprehensive, explicit approach to capturing the full societal value of reduced morbidity.
Methods: We used empirical data on the duration and severity of episodes of cardiorespiratory disease as inputs to complementary models of cost of treatment, lost productivity, and willingness to pay to avoid acute cardiorespiratory morbidity outcomes linked to air pollution in epidemiological studies. A Monte Carlo estimation procedure was utilized to propagate uncertainty in key inputs and model parameters.