Automated derivation of diagnostic criteria for lung cancer using natural language processing on electronic health records: a pilot study.

Background: The digitisation of healthcare records has generated vast amounts of unstructured data, presenting opportunities for improvements in disease diagnosis when clinical coding falls short, such as in the recording of patient symptoms. This study presents an approach using natural language processing to extract clinical concepts from free-text which are used to automatically form diagnostic criteria for lung cancer from unstructured secondary-care data.

Methods: Patients aged 40 and above who underwent a chest x-ray (CXR) between 2016 and 2022 were included.

Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.

Background: Pneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) radiation pneumonitis (RP), and infective pneumonitis (IP) is crucial for swift, appropriate, and tailored management to achieve optimal patient outcomes. However, correct diagnosis is often challenging, owing to overlapping clinical presentations and radiological patterns.

A Multicentric, Retrospective, Real-world Study on Immune-related Adverse Events in Patients with Advanced Non-small Cell Lung Cancers Treated with Pembrolizumab Monotherapy.

Aims: We present 7 years of clinical experience with single-agent pembrolizumab immune checkpoint inhibitor immunotherapy in non-small cell lung cancers (NSCLC) from four UK cancer centres.

Materials And Methods: This multi-institutional retrospective cohort study included 226 metastatic NSCLC patients. Outcomes were number and severity of immune-related adverse events (irAEs), median progression-free survival (mPFS) and median overall survival (mOS).

Multimodality local consolidative treatment versus conventional care of advanced lung cancer after first-line systemic anti-cancer treatment: study protocol for the RAMON multicentre randomised controlled trial with an internal pilot.

Introduction: Lung cancer is the most common cause of cancer death worldwide and most patients present with extensive disease. One-year survival is improving but remains low (37%) despite novel systemic anti-cancer treatments forming the current standard of care. Although new therapies improve survival, most patients have residual disease after treatment, and little is known on how best to manage it.

Pericardial Fluid Analysis in Diagnosis and Prognosis of Patients Who Underwent Pericardiocentesis.

In this study, we aimed to examine the diagnostic yield of pericardial fluid biochemistry and cytology and their prognostic significance in patients with percutaneously drained pericardial effusions, with and without malignancy. This is a single-center, retrospective study of patients who underwent pericardiocentesis between 2010 and 2020. Data were extracted from electronic patient records, including procedural information, underlying diagnosis, and laboratory results.