Post-treatment survival difference between lobectomy and stereotactic ablative radiotherapy in stage I non-small cell lung cancer in England.

BACKGROUND: Approximately 15%-20% of all non-small cell lung cancer (NSCLC) cases present with stage I disease. Surgical resection traditionally offers the best chance of a cure but some patients will not have this treatment due to older age, comorbidities or personal choice. Stereotactic ablative radiotherapy (SABR) has become an established curative intent treatment option for patients who are not selected for or do not choose surgery. The aim of this study is to compare survival at 90 days, 6 months, 1 year and 2 years for patients who received either lobectomy or SABR. METHODS: We used data from the 2015 National Lung Cancer Audit database and linked with Hospital Episode Statistics and the radiotherapy dataset to identify patients with NSCLC stage IA-IB and performance status (PS) 0-2 who underwent surgery or SABR treatment. We assessed the likelihood of death at 90 days, 6 months, 1 year and 2 year after diagnosis and procedure date to observe survival between two patient groups. RESULTS: We identified 2373 patients in our cohort, 476 of whom had SABR. The median difference between date of diagnosis and date of treatment for surgery patients was 17 days while for SABR patients it was 73 days. Increasing age and worsening PS were associated with having SABR rather than surgery. Survival between the two treatment modalities was similar early on but by 1-year people who had surgery did better than those who had SABR (adjusted ORs 2.12, 95% CI 1.35 to 2.31). This difference persisted at 2 years and when the analysis was restricted to patients aged <80 years and with PS 0 or 1 and stage IA only. CONCLUSION: Our analysis suggests that patients who have lobectomy have a better survival compared with SABR patients; however, we found considerable delays in patients receiving SABR which may contribute to poorer long-term outcomes with this treatment option. Reducing these delays should be a key focus in development and reorganisation of services

Assessing eligibility for lung cancer screening using parsimonious ensemble machine learning models: A development and validation study

BACKGROUND: Risk-based screening for lung cancer is currently being considered in several countries; however, the optimal approach to determine eligibility remains unclear. Ensemble machine learning could support the development of highly parsimonious prediction models that maintain the performance of more complex models while maximising simplicity and generalisability, supporting the widespread adoption of personalised screening. In this work, we aimed to develop and validate ensemble machine learning models to determine eligibility for risk-based lung cancer screening. METHODS AND FINDINGS: For model development, we used data from 216,714 ever-smokers recruited between 2006 and 2010 to the UK Biobank prospective cohort and 26,616 high-risk ever-smokers recruited between 2002 and 2004 to the control arm of the US National Lung Screening (NLST) randomised controlled trial. The NLST trial randomised high-risk smokers from 33 US centres with at least a 30 pack-year smoking history and fewer than 15 quit-years to annual CT or chest radiography screening for lung cancer. We externally validated our models among 49,593 participants in the chest radiography arm and all 80,659 ever-smoking participants in the US Prostate, Lung, Colorectal and Ovarian (PLCO) Screening Trial. The PLCO trial, recruiting from 1993 to 2001, analysed the impact of chest radiography or no chest radiography for lung cancer screening. We primarily validated in the PLCO chest radiography arm such that we could benchmark against comparator models developed within the PLCO control arm. Models were developed to predict the risk of 2 outcomes within 5 years from baseline: diagnosis of lung cancer and death from lung cancer. We assessed model discrimination (area under the receiver operating curve, AUC), calibration (calibration curves and expected/observed ratio), overall performance (Brier scores), and net benefit with decision curve analysis. Models predicting lung cancer death (UCL-D) and incidence (UCL-I) using 3 variables-age, smoking duration, and pack-years-achieved or exceeded parity in discrimination, overall performance, and net benefit with comparators currently in use, despite requiring only one-quarter of the predictors. In external validation in the PLCO trial, UCL-D had an AUC of 0.803 (95% CI: 0.783, 0.824) and was well calibrated with an expected/observed (E/O) ratio of 1.05 (95% CI: 0.95, 1.19). UCL-I had an AUC of 0.787 (95% CI: 0.771, 0.802), an E/O ratio of 1.0 (95% CI: 0.92, 1.07). The sensitivity of UCL-D was 85.5% and UCL-I was 83.9%, at 5-year risk thresholds of 0.68% and 1.17%, respectively, 7.9% and 6.2% higher than the USPSTF-2021 criteria at the same specificity. The main limitation of this study is that the models have not been validated outside of UK and US cohorts. CONCLUSIONS: We present parsimonious ensemble machine learning models to predict the risk of lung cancer in ever-smokers, demonstrating a novel approach that could simplify the implementation of risk-based lung cancer screening in multiple settings

Conventional CT and PET/CT imaging in the evaluation and management of subsolid pulmonary nodules: an overview of the literature and author recommendations

This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

Comorbidity prevalence among cancer patients: a population-based cohort study of four cancers.

BACKGROUND: The presence of comorbidity affects the care of cancer patients, many of whom are living with multiple comorbidities. The prevalence of cancer comorbidity, beyond summary metrics, is not well known. This study aims to estimate the prevalence of comorbid conditions among cancer patients in England, and describe the association between cancer comorbidity and socio-economic position, using population-based electronic health records. METHODS: We linked England cancer registry records of patients diagnosed with cancer of the colon, rectum, lung or Hodgkin lymphoma between 2009 and 2013, with hospital admissions records. A comorbidity was any one of fourteen specific conditions, diagnosed during hospital admission up to 6 years prior to cancer diagnosis. We calculated the crude and age-sex adjusted prevalence of each condition, the frequency of multiple comorbidity combinations, and used logistic regression and multinomial logistic regression to estimate the adjusted odds of having each condition and the probability of having each condition as a single or one of multiple comorbidities, respectively, by cancer type. RESULTS: Comorbidity was most prevalent in patients with lung cancer and least prevalent in Hodgkin lymphoma patients. Up to two-thirds of patients within each of the four cancer patient cohorts we studied had at least one comorbidity, and around half of the comorbid patients had multiple comorbidities. Our study highlighted common comorbid conditions among the cancer patient cohorts. In all four cohorts, the odds of having a comorbidity and the probability of multiple comorbidity were consistently highest in the most deprived cancer patients. CONCLUSIONS: Cancer healthcare guidelines may need to consider prominent comorbid conditions, particularly to benefit the prognosis of the most deprived patients who carry the greater burden of comorbidity. Insight into patterns of cancer comorbidity may inform further research into the influence of specific comorbidities on socio-economic inequalities in receipt of cancer treatment and in short-term mortality

Association between age, deprivation and specific comorbid conditions and the receipt of major surgery in patients with non-small cell lung cancer in England: A population-based study.

INTRODUCTION: We investigated socioeconomic disparities and the role of the main prognostic factors in receiving major surgical treatment in patients with lung cancer in England. METHODS: Our study comprised 31 351 patients diagnosed with non-small cell lung cancer in England in 2012. Data from the national population-based cancer registry were linked to Hospital Episode Statistics and National Lung Cancer Audit data to obtain information on stage, performance status and comorbidities, and to identify patients receiving major surgical treatment. To describe the association between prognostic factors and surgery, we performed two different analyses: one using multivariable logistic regression and one estimating cause-specific hazards for death and surgery. In both analyses, we used multiple imputation to deal with missing data. RESULTS: We showed strong evidence that the comorbidities 'congestive heart failure', 'cerebrovascular disease' and 'chronic obstructive pulmonary disease' reduced the receipt of surgery in early stage patients. We also observed gender differences and substantial age differences in the receipt of surgery. Despite accounting for sex, age at diagnosis, comorbidities, stage at diagnosis, performance status and indication of having had a PET-CT scan, the socioeconomic differences persisted in both analyses: more deprived people had lower odds and lower rates of receiving surgery in early stage lung cancer. DISCUSSION: Comorbidities play an important role in whether patients undergo surgery, but do not completely explain the socioeconomic difference observed in early stage patients. Future work investigating access to and distance from specialist hospitals, as well as patient perceptions and patient choice in receiving surgery, could help disentangle these persistent socioeconomic inequalities

Lung cancer diagnosis and staging with endobronchial ultrasound-guided transbronchial needle aspiration compared with conventional approaches: an open-label, pragmatic, randomised controlled trial

SummaryBackgroundThe diagnosis and staging of lung cancer is an important process that identifies treatment options and guides disease prognosis. We aimed to assess endobronchial ultrasound-guided transbronchial needle aspiration as an initial investigation technique for patients with suspected lung cancer.MethodsIn this open-label, multicentre, pragmatic, randomised controlled trial, we recruited patients who had undergone a CT scan and had suspected stage I to IIIA lung cancer, from six UK centres and randomly assigned them to either endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) or conventional diagnosis and staging (CDS), for further investigation and staging. If a target node could not be accessed by EBUS-TBNA, then endoscopic ultrasound-guided fine needle aspiration (EUS-FNA) was allowed as an alternative procedure. Randomisation was stratified according to the presence of mediastinal lymph nodes measuring 1 cm or more in the short axis and by recruiting centre. We used a telephone randomisation method with permuted blocks of four generated by a computer. Because of the nature of the intervention, masking of participants and consenting investigators was not possible. The primary endpoint was the time-to-treatment decision after completion of the diagnostic and staging investigations and analysis was by intention-to-diagnose. This trial is registered with ClinicalTrials.gov, number NCT00652769.FindingsBetween June 10, 2008, and July 4, 2011, we randomly allocated 133 patients to treatment: 66 to EBUS-TBNA and 67 to CDS (one later withdrew consent). Two patients from the EBUS-TBNA group underwent EUS-FNA. The median time to treatment decision was shorter with EBUS-TBNA (14 days; 95% CI 14–15) than with CDS (29 days; 23–35) resulting in a hazard ratio of 1·98, (1·39–2·82, p<0·0001). One patient in each group had a pneumothorax from a CT-guided biopsy sample; the patient from the CDS group needed intercostal drainage and was admitted to hospital.InterpretationTransbronchial needle aspiration guided by endobronchial ultrasound should be considered as the initial investigation for patients with suspected lung cancer, because it reduces the time to treatment decision compared with conventional diagnosis and staging techniques.FundingUK Medical Research Council

How should performance in EBUS mediastinal staging in lung cancer be measured?

There has been a paradigm shift in mediastinal staging algorithms in non-small cell lung cancer over the last decade in the United Kingdom (UK). This has seen endoscopic nodal staging (predominantly endobronchial ultrasound, EBUS) almost replace surgical staging (predominantly mediastinoscopy) as the pathological staging procedure of first choic

Whole-body MRI compared with standard pathways for staging metastatic disease in lung and colorectal cancer: the Streamline diagnostic accuracy studies.

BACKGROUND: Whole-body magnetic resonance imaging is advocated as an alternative to standard pathways for staging cancer. OBJECTIVES: The objectives were to compare diagnostic accuracy, efficiency, patient acceptability, observer variability and cost-effectiveness of whole-body magnetic resonance imaging and standard pathways in staging newly diagnosed non-small-cell lung cancer (Streamline L) and colorectal cancer (Streamline C). DESIGN: The design was a prospective multicentre cohort study. SETTING: The setting was 16 NHS hospitals. PARTICIPANTS: Consecutive patients aged ≥ 18 years with histologically proven or suspected colorectal (Streamline C) or non-small-cell lung cancer (Streamline L). INTERVENTIONS: Whole-body magnetic resonance imaging. Standard staging investigations (e.g. computed tomography and positron emission tomography-computed tomography). REFERENCE STANDARD: Consensus panel decision using 12-month follow-up data. MAIN OUTCOME MEASURES: The primary outcome was per-patient sensitivity difference between whole-body magnetic resonance imaging and standard staging pathways for metastasis. Secondary outcomes included differences in specificity, the nature of the first major treatment decision, time and number of tests to complete staging, patient experience and cost-effectiveness. RESULTS: Streamline C - 299 participants were included. Per-patient sensitivity for metastatic disease was 67% (95% confidence interval 56% to 78%) and 63% (95% confidence interval 51% to 74%) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference in sensitivity of 4% (95% confidence interval -5% to 13%; p = 0.51). Specificity was 95% (95% confidence interval 92% to 97%) and 93% (95% confidence interval 90% to 96%) respectively, a difference of 2% (95% confidence interval -2% to 6%). Pathway treatment decisions agreed with the multidisciplinary team treatment decision in 96% and 95% of cases, respectively, a difference of 1% (95% confidence interval -2% to 4%). Time for staging was 8 days (95% confidence interval 6 to 9 days) and 13 days (95% confidence interval 11 to 15 days) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference of 5 days (95% confidence interval 3 to 7 days). The whole-body magnetic resonance imaging pathway was cheaper than the standard staging pathway: £216 (95% confidence interval £211 to £221) versus £285 (95% confidence interval £260 to £310). Streamline L - 187 participants were included. Per-patient sensitivity for metastatic disease was 50% (95% confidence interval 37% to 63%) and 54% (95% confidence interval 41% to 67%) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference in sensitivity of 4% (95% confidence interval -7% to 15%; p = 0.73). Specificity was 93% (95% confidence interval 88% to 96%) and 95% (95% confidence interval 91% to 98%), respectively, a difference of 2% (95% confidence interval -2% to 7%). Pathway treatment decisions agreed with the multidisciplinary team treatment decision in 98% and 99% of cases, respectively, a difference of 1% (95% confidence interval -2% to 4%). Time for staging was 13 days (95% confidence interval 12 to 14 days) and 19 days (95% confidence interval 17 to 21 days) for whole-body magnetic resonance imaging and standard pathways, respectively, a difference of 6 days (95% confidence interval 4 to 8 days). The whole-body magnetic resonance imaging pathway was cheaper than the standard staging pathway: £317 (95% confidence interval £273 to £361) versus £620 (95% confidence interval £574 to £666). Participants generally found whole-body magnetic resonance imaging more burdensome than standard imaging but most participants preferred the whole-body magnetic resonance imaging staging pathway if it reduced time to staging and/or number of tests. LIMITATIONS: Whole-body magnetic resonance imaging was interpreted by practitioners blinded to other clinical data, which may not fully reflect how it is used in clinical practice. CONCLUSIONS: In colorectal and non-small-cell lung cancer, the whole-body magnetic resonance imaging staging pathway has similar accuracy to standard staging pathways, is generally preferred by patients, improves staging efficiency and has lower staging costs. Future work should address the utility of whole-body magnetic resonance imaging for treatment response assessment. TRIAL REGISTRATION: Current Controlled Trials ISRCTN43958015 and ISRCTN50436483. FUNDING: This project was funded by the NIHR Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 23, No. 66. See the NIHR Journals Library website for further project information

The role of computer-assisted radiographer reporting in lung cancer screening programmes

OBJECTIVES: Successful lung cancer screening delivery requires sensitive, timely reporting of low-dose computed tomography (LDCT) scans, placing a demand on radiology resources. Trained non-radiologist readers and computer-assisted detection (CADe) software may offer strategies to optimise the use of radiology resources without loss of sensitivity. This report examines the accuracy of trained reporting radiographers using CADe support to report LDCT scans performed as part of the Lung Screen Uptake Trial (LSUT). METHODS: In this observational cohort study, two radiographers independently read all LDCT performed within LSUT and reported on the presence of clinically significant nodules and common incidental findings (IFs), including recommendations for management. Reports were compared against a 'reference standard' (RS) derived from nodules identified by study radiologists without CADe, plus consensus radiologist review of any additional nodules identified by the radiographers. RESULTS: A total of 716 scans were included, 158 of which had one or more clinically significant pulmonary nodules as per our RS. Radiographer sensitivity against the RS was 68-73.7%, with specificity of 92.1-92.7%. Sensitivity for detection of proven cancers diagnosed from the baseline scan was 83.3-100%. The spectrum of IFs exceeded what could reasonably be covered in radiographer training. CONCLUSION: Our findings highlight the complexity of LDCT reporting requirements, including the limitations of CADe and the breadth of IFs. We are unable to recommend CADe-supported radiographers as a sole reader of LDCT scans, but propose potential avenues for further research including initial triage of abnormal LDCT or reporting of follow-up surveillance scans. KEY POINTS: • Successful roll-out of mass screening programmes for lung cancer depends on timely, accurate CT scan reporting, placing a demand on existing radiology resources. • This observational cohort study examines the accuracy of trained radiographers using computer-assisted detection (CADe) software to report lung cancer screening CT scans, as a potential means of supporting reporting workflows in LCS programmes. • CADe-supported radiographers were less sensitive than radiologists at identifying clinically significant pulmonary nodules, but had a low false-positive rate and good sensitivity for detection of confirmed cancers

Uptake of invitations to a lung health check offering low-dose CT lung cancer screening among an ethnically and socioeconomically diverse population at risk of lung cancer in the UK (SUMMIT): a prospective, longitudinal cohort study

BACKGROUND: Lung cancer screening with low-dose CT reduces lung cancer mortality, but screening requires equitable uptake from candidates at high risk of lung cancer across ethnic and socioeconomic groups that are under-represented in clinical studies. We aimed to assess the uptake of invitations to a lung health check offering low-dose CT lung cancer screening in an ethnically and socioeconomically diverse cohort at high risk of lung cancer. METHODS: In this multicentre, prospective, longitudinal cohort study (SUMMIT), individuals aged 55-77 years with a history of smoking in the past 20 years were identified via National Health Service England primary care records at practices in northeast and north-central London, UK, using electronic searches. Eligible individuals were invited by letter to a lung health check offering lung cancer screening at one of four hospital sites, with non-responders re-invited after 4 months. Individuals were excluded if they had dementia or metastatic cancer, were receiving palliative care or were housebound, or declined research participation. The proportion of individuals invited who responded to the lung health check invitation by telephone was used to measure uptake. We used univariable and multivariable logistic regression analyses to estimate associations between uptake of a lung health check invitation and re-invitation of non-responders, adjusted for sex, age, ethnicity, smoking, and deprivation score. This study was registered prospectively with ClinicalTrials.gov, NCT03934866. FINDINGS: Between March 20 and Dec 12, 2019, the records of 2 333 488 individuals from 251 primary care practices across northeast and north-central London were screened for eligibility; 1 974 919 (84·6%) individuals were outside the eligible age range, 7578 (2·1%) had pre-existing medical conditions, and 11 962 (3·3%) had opted out of particpation in research and thus were not invited. 95 297 individuals were eligible for invitation, of whom 29 545 (31·0%) responded. Due to the COVID-19 pandemic, re-invitation letters were sent to only a subsample of 4594 non-responders, of whom 642 (14·0%) responded. Overall, uptake was lower among men than among women (odds ratio [OR] 0·91 [95% CI 0·88-0·94]; p<0·0001), and higher among older age groups (1·48 [1·42-1·54] among those aged 65-69 years vs those aged 55-59 years; p<0·0001), groups with less deprivation (1·89 [1·76-2·04] for the most vs the least deprived areas; p<0·0001), individuals of Asian ethnicity (1·14 [1·09-1·20] vs White ethnicity; p<0·0001), and individuals who were former smokers (1·89 [1·83-1·95] vs current smokers; p<0·0001). When ethnicity was subdivided into 16 groups, uptake was lower among individuals of other White ethnicity than among those with White British ethnicity (0·86 [0·83-0·90]), whereas uptake was higher among Chinese, Indian, and other Asian ethnicities than among those with White British ethnicity (1·33 [1·13-1·56] for Chinese ethnicity; 1·29 [1·19-1·40] for Indian ethnicity; and 1·19 [1·08-1·31] for other Asian ethnicity). INTERPRETATION: Inviting eligible adults for lung health checks in areas of socioeconomic and ethnic diversity should achieve favourable participation in lung cancer screening overall, but inequalities by smoking, deprivation, and ethnicity persist. Reminder and re-invitation strategies should be used to increase uptake and the equity of response. FUNDING: GRAIL