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INTRODUCTION: In a small percentage of patients, pulmonary nodules found on CT scans are early lung cancers. Lung cancer detected at an early stage has a much better prognosis. The British Thoracic Society guideline on managing pulmonary nodules recommends using multivariable malignancy risk prediction models to assist in management. While these guidelines seem to be effective in clinical practice, recent data suggest that artificial intelligence (AI)-based malignant-nodule prediction solutions might outperform existing models. METHODS AND ANALYSIS: This study is a prospective, observational multicentre study to assess the clinical utility of an AI-assisted CT-based lung cancer prediction tool (LCP) for managing incidental solid and part solid pulmonary nodule patients vs standard care. Two thousand patients will be recruited from 12 different UK hospitals. The primary outcome is the difference between standard care and LCP-guided care in terms of the rate of benign nodules and patients with cancer discharged straight after the assessment of the baseline CT scan. Secondary outcomes investigate adherence to clinical guidelines, other measures of changes to clinical management, patient outcomes and cost-effectiveness. ETHICS AND DISSEMINATION: This study has been reviewed and given a favourable opinion by the South Central-Oxford C Research Ethics Committee in UK (REC reference number: 22/SC/0142).Study results will be available publicly following peer-reviewed publication in open-access journals. A patient and public involvement group workshop is planned before the study results are available to discuss best methods to disseminate the results. Study results will also be fed back to participating organisations to inform training and procurement activities. TRIAL REGISTRATION NUMBER: NCT05389774.
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Neoplasias Pulmonares , Nódulos Pulmonares Múltiplos , Humanos , Inteligência Artificial , Neoplasias Pulmonares/diagnóstico por imagem , Neoplasias Pulmonares/patologia , Estudos Multicêntricos como Assunto , Nódulos Pulmonares Múltiplos/diagnóstico por imagem , Nódulos Pulmonares Múltiplos/patologia , Estudos Observacionais como Assunto , Estudos Prospectivos , Tomografia Computadorizada por Raios X/métodos , Reino UnidoRESUMO
Aim: This study retrospectively analyses the impact of the 1st year of the COVID-19 pandemic on route of presentation and staging in lung cancer compared to the 2 years before and after implementation of the Leicester Optimal Lung Cancer Pathway (LOLCP) in Leicester, United Kingdom. Method: Electronic databases and hospital records were used to identify all patients diagnosed with lung cancer in 2018 (pre-LOLCP), 2019 (post-LOLCP), and March 2020-2021 (post-COVID-19 lockdown). Information regarding patient characteristics, performance status, stage, and route of diagnosis was documented and analysed. Emergency presentation was defined as diagnosis of new lung cancer being made after unscheduled attendance to urgent or emergency care facility. Results: Following implementation of the LOLCP pathway, there was a significant decrease in emergency presentations from 26.8 to 19.6% (p = 0.002) with a stage shift from 33.9% early stage disease to 40.3%. These improved outcomes were annulled during the COVID-19 pandemic, with emergency presentations increasing to 38.9% (p < 0.001) and a reduction in early-stage lung cancer diagnoses to 31.5%. There was a 61% decline in 2 week wait referrals but no significant decline in the LOLCP direct-to-CT referrals. Conclusion: We have demonstrated a significant increase in late-stage lung cancer diagnoses and emergency presentations during the first year of the COVID-19 pandemic. The causes for these changes are likely to be multifactorial. The long-term effect on lung cancer mortality remains to be seen and is an important focus of future study.
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COVID-19 , Neoplasias Pulmonares , Humanos , COVID-19/epidemiologia , Neoplasias Pulmonares/epidemiologia , Estadiamento de Neoplasias , Estudos Retrospectivos , Pandemias , Controle de Doenças Transmissíveis , PulmãoRESUMO
BACKGROUND: Hodgkin's Lymphoma (HL) is a rare malignancy characterised histologically by the presence of Reed-Sternberg cells. Diagnosis of lymphomas can be difficult due to broad, non-specific presentations of disease, which can be similar to several other conditions ranging from infective, inflammatory or malignant causes, with one of the most common differentials being tuberculosis (TB). We aim to highlight the diagnostic dilemma of TB versus lymphoma with an atypical presentation of HL and explored areas for further research and improvement with a non-systematic literature review using MEDLINE database and Google Scholar. Written consent was obtained from the patient in compliance with ethical guidelines. CASE PRESENTATION: A 23-year-old Asian female initially presented to rheumatology with over a one-year history of neuropathic pain, alongside abnormal white cell count and inflammatory markers. This was investigated with magnetic resonance imaging resulting in an incidental finding of mediastinal mass and pulmonary infiltrates. An initial diagnosis of TB was made despite testing negative for acid-fast bacilli and anti-tubercular treatment was commenced. Four months later, following clinical deterioration and further investigations, a mediastinal biopsy assisted in diagnosing Stage IV HL. CONCLUSIONS: Lymphoma is often misdiagnosed as TB, prolonging time to treatment and may adversely impact patient prognosis due to disease progression. Existing TB guidelines for smear-negative cases are not clear when to consider alternative diagnoses. In smear-negative TB, lymphoma should be considered as a differential and definitive diagnostic tests such as molecular testing and histological examination of biopsies should be considered earlier in the diagnostic work-up to prevent diagnostic delay.