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BackgroundEstimation of the risk of malignancy in pulmonary nodules detected by CT is central in clinical management. The use of artificial intelligence (AI) offers an opportunity to improve risk prediction. Here we compare the performance of an AI algorithm, the lung cancer prediction convolutional neural network (LCP-CNN), with that of the Brock University model, recommended in UK guidelines.MethodsA dataset of incidentally detected pulmonary nodules measuring 5–15 mm was collected retrospectively from three UK hospitals for use in a validation study. Ground truth diagnosis for each nodule was based on histology (required for any cancer), resolution, stability or (for pulmonary lymph nodes only) expert opinion. There were 1397 nodules in 1187 patients, of which 234 nodules in 229 (19.3%) patients were cancer. Model discrimination and performance statistics at predefined score thresholds were compared between the Brock model and the LCP-CNN.ResultsThe area under the curve for LCP-CNN was 89.6% (95% CI 87.6 to 91.5), compared with 86.8% (95% CI 84.3 to 89.1) for the Brock model (p≤0.005). Using the LCP-CNN, we found that 24.5% of nodules scored below the lowest cancer nodule score, compared with 10.9% using the Brock score. Using the predefined thresholds, we found that the LCP-CNN gave one false negative (0.4% of cancers), whereas the Brock model gave six (2.5%), while specificity statistics were similar between the two models.ConclusionThe LCP-CNN score has better discrimination and allows a larger proportion of benign nodules to be identified without missing cancers than the Brock model. This has the potential to substantially reduce the proportion of surveillance CT scans required and thus save significant resources.

BackgroundLung cancer outcomes in the UK are worse than in many other developed nations. Symptom awareness campaigns aim to diagnose patients at an earlier stage to improve cancer outcomes.MethodsAn early diagnosis campaign for lung cancer commenced in Leeds, UK in 2011 comprising public and primary-care facing components. Rates of community referral for chest X-ray and lung cancer stage (TNM seventh edition) at presentation were collected from 2008 to 2015. Linear trends were assessed by χ2 test for trend in proportions. Headline figures are presented for the 3 years pre-campaign (2008–2010) and the three most recent years for which data are available during the campaign (2013–2015).FindingsCommunity-ordered chest X-ray rates per year increased from 18 909 in 2008–2010 to 34 194 in 2013–2015 (80.8% increase). A significant stage shift towards earlier stage lung cancer was seen (χ2(1)=32.2, p<0.0001). There was an 8.8 percentage point increase in the proportion of patients diagnosed with stage I/II lung cancer (26.5% pre-campaign vs 35.3% during campaign) and a 9.3% reduction in the absolute number of patients diagnosed with stage III/IV disease (1254 pre-campaign vs 1137 during campaign).InterpretationThis is the largest described lung cancer stage-shift in association with a symptom awareness campaign. A causal link between the campaign and stage-shift cannot be proven but appears plausible. Limitations of the analysis include a lack of contemporary control population.

IntroductionMesothelioma remains a lethal cancer. To date, systemic therapy with pemetrexed and a platinum drug remains the only licensed standard of care. As the median survival for patients with mesothelioma is 12.1 months, surgery is an important consideration to improve survival and/or quality of life. Currently, only two surgical trials have been performed which found that neither extensive (extra-pleural pneumonectomy) or limited (partial pleurectomy) surgery improved survival (although there was some evidence of improved quality of life). Therefore, clinicians are now looking to evaluate pleurectomy decortication, the only radical treatment option left.Methods and analysisThe MARS 2 study is a UK multicentre open parallel group randomised controlled trial comparing the effectiveness and cost-effectiveness of surgery—(extended) pleurectomy decortication—versus no surgery for the treatment of pleural mesothelioma. The study will test the hypothesis that surgery and chemotherapy is superior to chemotherapy alone with respect to overall survival. Secondary outcomes include health-related quality of life, progression-free survival, measures of safety (adverse events) and resource use to 2 years. The QuinteT Recruitment Intervention is integrated into the trial to optimise recruitment.Ethics and disseminationResearch ethics approval was granted by London – Camberwell St. Giles Research Ethics Committee (reference 13/LO/1481) on 7 November 2013. We will submit the results for publication in a peer-reviewed journal.Trial registration numbersISRCTN—ISRCTN44351742 and ClinicalTrials.gov—NCT02040272.

PurposeTo compare qualitative and semi-quantitative PET/CT criteria, and the impact of nodule size on the diagnosis of solitary pulmonary nodules in a prospective multicentre trial.MethodsPatients with an SPN on CT ≥ 8 and ≤ 30 mm were recruited to the SPUTNIK trial at 16 sites accredited by the UK PET Core Lab. Qualitative assessment used a five-point ordinal PET-grade compared to the mediastinal blood pool, and a combined PET/CT grade using the CT features. Semi-quantitative measures included SUVmax of the nodule, and as an uptake ratio to the mediastinal blood pool (SURBLOOD) or liver (SURLIVER). The endpoints were diagnosis of lung cancer via biopsy/histology or completion of 2-year follow-up. Impact of nodule size was analysed by comparison between nodule size tertiles.ResultsThree hundred fifty-five participants completed PET/CT and 2-year follow-up, with 59% (209/355) malignant nodules. The AUCs of the three techniques were SUVmax 0.87 (95% CI 0.83;0.91); SURBLOOD 0.87 (95% CI 0.83; 0.91, p = 0.30 versus SUVmax); and SURLIVER 0.87 (95% CI 0.83; 0.91, p = 0.09 vs. SUVmax). The AUCs for all techniques remained stable across size tertiles (p > 0.1 for difference), although the optimal diagnostic threshold varied by size. For nodules < 12 mm, an SUVmax of 1.75 or visual uptake equal to the mediastinum yielded the highest accuracy. For nodules > 16 mm, an SUVmax ≥ 3.6 or visual PET uptake greater than the mediastinum was the most accurate.ConclusionIn this multicentre trial, SUVmax was the most accurate technique for the diagnosis of solitary pulmonary nodules. Diagnostic thresholds should be altered according to nodule size.Trial registrationISRCTN - ISRCTN30784948. ClinicalTrials.gov - NCT02013063