The incidence of lung cancer amongst primary care chest radiograph referrals; an evaluation of national and local datasets within the UK.

OBJECTIVES: To determine the incidence of lung cancer amongst primary care referrals for investigation with a chest radiograph (CXR). METHOD: Retrospective evaluation of datasets from the national Clinical Practice Research Datalink (CPRD) and from a single large regional centre. Data was extracted for cohorts of consecutive adults aged over 40-yrs for whom a CXR had been performed between 2016 and 2018. Using cancer registry data, the incidence of lung cancer within a two-years of the CXR referral and the variations with age, gender and smoking status were evaluated. RESULTS: A total of 291 294 CXR events were evaluated from the combined datasets. The incidence of lung cancer amongst GP CXR referrals was 1.4% in CPRD with a consistent correlation with increasing age and smoking status. The incidence of lung cancer within two-years of the CXR varied between 0.03% (95%CI 0.0-0.1) amongst never smokers aged 40-45 years to 4.8% (95%CI 4.2-5.5) amongst current-smokers aged 70-75 years. The findings were similar for the single large centre data, although cancer incidence was higher. CONCLUSIONS: A simple estimation and stratification of the risk of lung cancer amongst primary care referrals for investigation with a CXR is possible using age and smoking status. ADVANCES IN KNOWLEDGE: This is the first estimate of the incidence of lung cancer amongst primary care CXR referrals and a demonstration of how the demographic information contained within a request could be used to optimise investigations and interpret test results.

What Is the Accuracy of Clinical Staging for Stage III-Single-station N2 NSCLC? A Multi-Centre UK Study.

Introduction: Single-station N2 (ssN2) versus multi-station N2 has been used as a selection criterion for treatment recommendations between surgical versus non-surgical multimodality treatment in stage III-N2 NSCLC. We hypothesized that clinical staging would be susceptible to upstaging on pathologic staging and, therefore, challenge this practice. Methods: A retrospective study of prospectively collected routine clinical data for patients with stage III-N2 NSCLC that had completed computed tomography (CT), positron emission tomography (PET), and staging endobronchial ultrasound (EBUS) and had been confirmed clinical stage III-ssN2 at multidisciplinary team discussion and went on to complete surgical resection as the first treatment to provide pathologic staging. The study was completed in two cohorts (A) across a single cancer alliance in England (Greater Manchester) January 1, 2015 to December 31, 2018 and (B) across five United Kingdom centers to validate the findings in part A January 1, 2016 to December 31, 2020. Results: A total of 115 patients met the inclusion criteria across cohort A (56 patients) and cohort B (59 patients) across 15 United Kingdom hospitals. The proportion of cases in which clinical stage III-ssN2 was upstaged to pathologic stage III-multi-station N2 was 34% (19 of 56) in cohort A, 32% in cohort B (19 of 59), and 33% across the combined study cohort (38 of 115). Most patients had a single radiologically abnormal lymph node on CT and PET (88%, 105 of 115). In the majority, the reasons for missed N2 disease on staging EBUS were due to inaccessible (stations 5, 6, 8, 9) N2 nodes at EBUS (34%, 13 of 38) and accessible lymph nodes not sampled during staging EBUS as not meeting sampling threshold (40%, 15 of 38) rather than false-negative sampling during EBUS (26%, 10 of 38). Conclusions: During multidisciplinary team discussions, clinicians must be aware that one-third of patients with stage III-ssN2 on the basis of CT, PET, and staging EBUS do not truly have ssN2 and this questions the use of this criterion to define treatment recommendations.

Optimal management of radiation pneumonitis: Findings of an international Delphi consensus study.

PURPOSE: Radiation pneumonitis (RP) is a dose-limiting toxicity for patients undergoing radiotherapy (RT) for lung cancer, however, the optimal practice for diagnosis, management, and follow-up for RP remains unclear. We thus sought to establish expert consensus recommendations through a Delphi Consensus study. METHODS: In Round 1, open questions were distributed to 31 expert clinicians treating thoracic malignancies. In Round 2, participants rated agreement/disagreement with statements derived from Round 1 answers using a 5-point Likert scale. Consensus was defined as ≥ 75 % agreement. Statements that did not achieve consensus were modified and re-tested in Round 3. RESULTS: Response rate was 74 % in Round 1 (n = 23/31; 17 oncologists, 6 pulmonologists); 82 % in Round 2 (n = 19/23; 15 oncologists, 4 pulmonologists); and 100 % in Round 3 (n = 19/19). Thirty-nine of 65 Round 2 statements achieved consensus; a further 10 of 26 statements achieved consensus in Round 3. In Round 2, there was agreement that risk stratification/mitigation includes patient factors; optimal treatment planning; the basis for diagnosis of RP; and that oncologists and pulmonologists should be involved in treatment. For uncomplicated radiation pneumonitis, an equivalent to 60 mg oral prednisone per day, with consideration of gastroprotection, is a typical initial regimen. However, in this study, no consensus was achieved for dosing recommendation. Initial steroid dose should be administered for a duration of 2 weeks, followed by a gradual, weekly taper (equivalent to 10 mg prednisone decrease per week). For severe pneumonitis, IV methylprednisolone is recommended for 3 days prior to initiating oral corticosteroids. Final consensus statements included that the treatment of RP should be multidisciplinary, the uncertainty of whether pneumonitis is drug versus radiation-induced, and the importance risk stratification, especially in the scenario of interstitial lung disease. CONCLUSIONS: This Delphi study achieved consensus recommendations and provides practical guidance on diagnosis and management of RP.

Treating Tobacco Dependency in National Health Service Workers in Greater Manchester: An Evaluation of a Bespoke Digital Service.

Introduction: Treating tobacco dependency in National Health Service (NHS) workers delivers substantial benefits at an individual, population, and health care system level. We report the outcomes from the Greater Manchester Integrated Care Partnership's tobacco dependency treatment program for NHS workers which includes 6-months' access to behavioral support and 12 weeks of treatment through a digital application. Methods: Aggregate results for all participants across the program from January 1, 2022, to September 1, 2023, are reported including a deep-dive evaluation of 300 participants recruited to provide chemically validated outcomes. Results: A total of 1567 NHS workers participated in the program within the evaluation period, completing 24,048 sessions with specialist advisors within the application, ordering 18,710 nicotine vape liquids, 6927 nicotine patches, and 297 short-acting nicotine products. Users reported achieving 89,464 smoke-free days, 1,258,069 less cigarettes smoked, and a financial saving of £622,231. The deep-dive evaluation revealed a CO-verified 12-week abstinence rate of 37% (111 of 300). Conclusion: This evaluation provides assurance of clinical effectiveness within a bespoke digital tobacco dependency treatment program for NHS workers across an Integrated Care Partnership.

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. METHODS: In this multi-centre study of 455 patients, we used machine learning with radiomic features extracted from chest CT imaging to develop and validate five models to distinguish CIP and RP from COVID-19, non-COVID-19 infective pneumonitis, and each other. Model performance was compared to that of two radiologists. RESULTS: Models to distinguish RP from COVID-19, CIP from COVID-19 and CIP from non-COVID-19 IP out-performed radiologists (test set AUCs of 0.92 vs 0.8 and 0.8; 0.68 vs 0.43 and 0.4; 0.71 vs 0.55 and 0.63 respectively). Models to distinguish RP from non-COVID-19 IP and CIP from RP were not superior to radiologists but demonstrated modest performance, with test set AUCs of 0.81 and 0.8 respectively. The CIP vs RP model performed less well on patients with prior exposure to both ICI and radiotherapy (AUC 0.54), though the radiologists also had difficulty distinguishing this test cohort (AUC values 0.6 and 0.6). CONCLUSION: Our results demonstrate the potential utility of such tools as a second or concurrent reader to support oncologists, radiologists, and chest physicians in cases of diagnostic uncertainty. Further research is required for patients with exposure to both ICI and thoracic radiotherapy.