Purpose: Retrospective studies have identified a link between the average set-up error of lung cancer patients treated with image-guided radiotherapy (IGRT) and survival. The IGRT protocol was subsequently changed to reduce the action threshold. In this study, we use a Bayesian approach to evaluate the clinical impact of this change to practice using routine 'real-world' patient data.

Methods And Materials: Two cohorts of NSCLC patients treated with IGRT were compared: pre-protocol change (N = 780, 5 mm action threshold) and post-protocol change (N = 411, 2 mm action threshold). Survival models were fitted to each cohort and changes in the hazard ratios (HR) associated with residual set-up errors was assessed. The influence of using an uninformative and a skeptical prior in the model was investigated.

Results: Following the reduction of the action threshold, the HR for residual set-up error towards the heart was reduced by up to 10%. Median patient survival increased for patients with set-up errors towards the heart, and remained similar for patients with set-up errors away from the heart. Depending on the prior used, a residual hazard ratio may remain.

Conclusions: Our analysis found a reduced hazard of death and increased survival for patients with residual set-up errors towards versus away from the heart post-protocol change. This study demonstrates the value of a Bayesian approach in the assessment of technical changes in radiotherapy practice and supports the consideration of adopting this approach in further prospective evaluations of changes to clinical practice.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.radonc.2022.09.009DOI Listing

Publication Analysis

Top Keywords

action threshold
16
set-up errors
16
residual set-up
12
changes radiotherapy
8
set-up error
8
patients treated
8
bayesian approach
8
post-protocol change
8
patients set-up
8
errors heart
8

Similar Publications

Background: As China's "Internet + Health" initiative advances, the digital economy significantly influences the quality of medical and health services. However, there is a research gap concerning the digital economy's specific impacts, mechanisms, and marginal effects on these services. This gap impedes a comprehensive understanding of the digital economy's potential in healthcare.

View Article and Find Full Text PDF

Importance: Active surveillance (AS) for patients with prostate cancer (PC) often includes fixed repeat prostate biopsies that do not account for the varying risk of reclassification to significant disease. Given the invasive nature and potential complications of biopsies, a personalized approach is needed to balance the burden of biopsies with the risk of missing disease progression.

Objective: To develop and externally validate a dynamic model that predicts an individual's risk of PC reclassification during AS.

View Article and Find Full Text PDF

Background: Fast-acting Sub-perception Therapy (FAST) is a novel spinal cord stimulation (SCS) modality delivering paresthesia-free pain relief. Our study evaluated the longer-term, real-world impact of FAST on chronic pain.

Research Design And Methods: As part of a multicenter, real-world, consecutive case series, we retrospectively identified patients who used FAST-SCS and analyzed their data.

View Article and Find Full Text PDF

Informing Risk Hotspots and Critical Mitigations for Rainstorms Using Machine Learning: Evidence from 268 Chinese Cities.

Environ Sci Technol

January 2025

State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing 210023, China.

Climate change is exacerbating rainstorms, increasing the risk of flooding and threatening urban sustainability, which could undermine climate action. Here, we propose a machine learning-based framework to assess heterogeneous risks and identify critical mitigation measures for rainstorms across 268 Chinese cities. Nighttime light serves as a proxy for urban functionality, and meteorological, socio-economic, and infrastructural factors are incorporated to uncover underlying impact mechanisms.

View Article and Find Full Text PDF

The Accuracy of Cardiac Surface Conduction Velocity Measurements.

JACC Clin Electrophysiol

December 2024

The Hull Family Cardiac Fibrillation Management Laboratory, Toronto General Hospital, University Health Network, Toronto, Ontario, Canada.

Background: Conduction velocity (CV) is a measure of the health of myocardial tissue. It can be measured by taking differences in local activation times from intracardiac electrodes. Several factors introduce error into the measurement, among which ignoring the 3-dimensional aspect is a major detriment.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!