Assessment of Advanced Diagnostic Bronchoscopy Outcomes for Peripheral Lung Lesions: A Delphi Consensus Definition of Diagnostic Yield and Recommendations for Patient-centered Study Designs. An Official American Thoracic Society/American College of Chest Physicians Research Statement

Background: Advanced diagnostic bronchoscopy targeting the lung periphery has developed at an accelerated pace over the last two decades, whereas evidence to support introduction of innovative technologies has been variable and deficient. A major gap relates to variable reporting of diagnostic yield, in addition to limited comparative studies. Objectives: To develop a research framework to standardize the evaluation of advanced diagnostic bronchoscopy techniques for peripheral lung lesions. Specifically, we aimed for consensus on a robust definition of diagnostic yield, and we propose potential study designs at various stages of technology development. Methods: Panel members were selected for their diverse expertise. Workgroup meetings were conducted in virtual or hybrid format. The cochairs subsequently developed summary statements, with voting proceeding according to a modified Delphi process. The statement was cosponsored by the American Thoracic Society and the American College of Chest Physicians. Results: Consensus was reached on 15 statements on the definition of diagnostic outcomes and study designs. A strict definition of diagnostic yield should be used, and studies should be reported according to the STARD (Standards for Reporting Diagnostic Accuracy Studies) guidelines. Clinical or radiographic follow-up may be incorporated into the reference standard definition but should not be used to calculate diagnostic yield from the procedural encounter. Methodologically robust comparative studies, with incorporation of patient-reported outcomes, are needed to adequately assess and validate minimally invasive diagnostic technologies targeting the lung periphery. Conclusions: This American Thoracic Society/American College of Chest Physicians statement aims to provide a research framework that allows greater standardization of device validation efforts through clearly defined diagnostic outcomes and robust study designs. High-quality studies, both industry and publicly funded, can support subsequent health economic analyses and guide implementation decisions in various healthcare settings.

Factors influencing clinician and patient interaction with machine learning-based risk prediction models: a systematic review

Machine learning (ML)-based risk prediction models hold the potential to support the health-care setting in several ways; however, use of such models is scarce. We aimed to review health-care professional (HCP) and patient perceptions of ML risk prediction models in published literature, to inform future risk prediction model development. Following database and citation searches, we identified 41 articles suitable for inclusion. Article quality varied with qualitative studies performing strongest. Overall, perceptions of ML risk prediction models were positive. HCPs and patients considered that models have the potential to add benefit in the health-care setting. However, reservations remain; for example, concerns regarding data quality for model development and fears of unintended consequences following ML model use. We identified that public views regarding these models might be more negative than HCPs and that concerns (eg, extra demands on workload) were not always borne out in practice. Conclusions are tempered by the low number of patient and public studies, the absence of participant ethnic diversity, and variation in article quality. We identified gaps in knowledge (particularly views from under-represented groups) and optimum methods for model explanation and alerts, which require future research.

Impact of the SARS-CoV-2 pandemic on lung cancer survival in England: an analysis of the rapid cancer registration dataset

Early changes in lung cancer care can affect survival. Given the decrease in diagnosis during lockdowns, we calculated their impact on survival using National Lung Cancer Audit data. Percentage survival and HRs for death were compared between 2019 and lockdown periods of 2020. Decreased survival was observed from the first national lockdown onwards and within 90 days of diagnosis. HRs were highest for people diagnosed at the end of 2020 at 1.26 (95% CI 1.20 to 1.32) for death within 90 days and 1.51 (95% CI 1.42 to 1.60) for death between 91 and 270 days. Further work is needed on measures to mitigate this impact.

PET/CT in treatment response assessment in lung cancer. When should it be recommended?

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Different treatment options are now possible both for surgical candidates and for those NSCLC patients deemed not suitable for surgery. Despite the treatments available, only a limited number of less advanced stages are potentially curable, with many patients suffering local recurrence or distant metastases. FDG-PET/CT is commonly used in many centers for post-treatment evaluation, follow-up, or surveillance; Nonetheless, there is no clear consensus regarding the indications in these cases. Based upon the results of a literature review and local expertise from a large lung cancer unit, we built clinical evidence-based recommendations for the use of FDG-PET/CT in response assessment. We found that in general this is not recommended earlier than 3 months from treatment; however, as described in detail the correct timing will also depend upon the type of treatment used. We also present a structured approach to assessing treatment changes when reporting FDG-PET/CT, using visual or quantitative approaches.

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.

The Impact of COVID-19 on Lung Cancer Incidence in England: Analysis of the National Lung Cancer Audit 2019 and 2020 Rapid Cancer Registration Datasets

BACKGROUND

The COVID-19 pandemic has caused significant disruption to health-care services and delivery worldwide. The impact of the pandemic and associated national lockdowns on lung cancer incidence in England have yet to be assessed.

RESEARCH QUESTION

What was the impact of the first year of the COVID-19 pandemic on the incidence and presentation of lung cancer in England?

STUDY DESIGN AND METHODS

In this retrospective observational study, incidence rates for lung cancer were calculated from The National Lung Cancer Audit Rapid Cancer Registration Datasets for 2019 and 2020, using midyear population estimates from the Office of National Statistics as the denominators. Rates were compared using Poisson regression according to time points related to national lockdowns in 2020.

RESULTS

Sixty-four thousand four hundred fifty-seven patients received a diagnosis of lung cancer across 2019 (n = 33,088) and 2020 (n = 31,369). During the first national lockdown, a 26% reduction in lung cancer incidence was observed compared with the equivalent calendar period of 2019 (adjusted incidence rate ratio [IRR], 0.74; 95% CI, 0.71-0.78). This included a 23% reduction in non-small cell lung cancer (adjusted IRR, 0.77; 95% CI, 0.74-0.81) and a 45% reduction in small cell lung cancer (adjusted IRR, 0.55; 95% CI, 0.46-0.65) incidence. Thereafter, incidence rates almost recovered to baseline, without overcompensation (adjusted IRR, 0.96; 95% CI, 0.94-0.98).

INTERPRETATION

The incidence rates of lung cancer in England fell significantly by 26% during the first national lockdown in 2020 and did not compensate later in the year.

The evolution of lung cancer and impact of subclonal selection in TRACERx

Lung cancer is the leading cause of cancer-associated mortality worldwide1. Here we analysed 1,644 tumour regions sampled at surgery or during follow-up from the first 421 patients with non-small cell lung cancer prospectively enrolled into the TRACERx study. This project aims to decipher lung cancer evolution and address the primary study endpoint: determining the relationship between intratumour heterogeneity and clinical outcome. In lung adenocarcinoma, mutations in 22 out of 40 common cancer genes were under significant subclonal selection, including classical tumour initiators such as TP53 and KRAS. We defined evolutionary dependencies between drivers, mutational processes and whole genome doubling (WGD) events. Despite patients having a history of smoking, 8% of lung adenocarcinomas lacked evidence of tobacco-induced mutagenesis. These tumours also had similar detection rates for EGFR mutations and for RET, ROS1, ALK and MET oncogenic isoforms compared with tumours in never-smokers, which suggests that they have a similar aetiology and pathogenesis. Large subclonal expansions were associated with positive subclonal selection. Patients with tumours harbouring recent subclonal expansions, on the terminus of a phylogenetic branch, had significantly shorter disease-free survival. Subclonal WGD was detected in 19% of tumours, and 10% of tumours harboured multiple subclonal WGDs in parallel. Subclonal, but not truncal, WGD was associated with shorter disease-free survival. Copy number heterogeneity was associated with extrathoracic relapse within 1 year after surgery. These data demonstrate the importance of clonal expansion, WGD and copy number instability in determining the timing and patterns of relapse in non-small cell lung cancer and provide a comprehensive clinical cancer evolutionary data resource.

The evolution of non-small cell lung cancer metastases in TRACERx

Metastatic disease is responsible for the majority of cancer-related deaths1. We report the longitudinal evolutionary analysis of 126 non-small cell lung cancer (NSCLC) tumours from 421 prospectively recruited patients in TRACERx who developed metastatic disease, compared with a control cohort of 144 non-metastatic tumours. In 25% of cases, metastases diverged early, before the last clonal sweep in the primary tumour, and early divergence was enriched for patients who were smokers at the time of initial diagnosis. Simulations suggested that early metastatic divergence more frequently occurred at smaller tumour diameters (less than 8 mm). Single-region primary tumour sampling resulted in 83% of late divergence cases being misclassified as early, highlighting the importance of extensive primary tumour sampling. Polyclonal dissemination, which was associated with extrathoracic disease recurrence, was found in 32% of cases. Primary lymph node disease contributed to metastatic relapse in less than 20% of cases, representing a hallmark of metastatic potential rather than a route to subsequent recurrences/disease progression. Metastasis-seeding subclones exhibited subclonal expansions within primary tumours, probably reflecting positive selection. Our findings highlight the importance of selection in metastatic clone evolution within untreated primary tumours, the distinction between monoclonal versus polyclonal seeding in dictating site of recurrence, the limitations of current radiological screening approaches for early diverging tumours and the need to develop strategies to target metastasis-seeding subclones before relapse.

Brain imaging in lung cancer staging: A real-world, multi-centre study of prevalence of brain metastases, impact on treatment and re-modelling of the NICE health economic analysis

INTRODUCTION

In 2019, the National Institute for Health and Care Excellence (NICE) updated their recommendations with respect to brain imaging in the staging of non-small cell lung cancer (NSCLC) based on an analytic cost-effectiveness model using published data and modelling assumptions from committee experts. In this study, we aimed to re-run this model using real-world multi-centre UK data.

MATERIALS AND METHODS

Retrospective data was collected on consecutive patients with radically treatable clinical stage II and III lung cancer from eleven acute NHS Trusts during the calendar year 01/01/2018 to 31/12/2018. Following a written application to the NICE lung cancer guideline committee, we were granted access to the NG122 brain imaging economic model for the purpose of updating the input parameters in line with the real-world findings from this study.

RESULTS

A total of 444 patients had data for analysis. The combined prevalence of occult brain metastases was 6.2% (10/165) in stage II and 6% (17/283) in stage III, compared to 9.5% and 9.3% used in the NICE economic model. 30% of patients with clinical stage III NSCLC and occult BMs on pre-treatment imaging went onto complete the planned curative intent treatment of extracranial disease, 60% completed SRS to the brain and 30% completed WBRT. This compares to 0%, 10% and 0% in the NICE assumptions. The health economic analysis concluded that brain imaging was no longer cost-effective in stage II disease (ICERs £50,023-£115,785) whilst brain imaging remained cost-effective for stage III patients (ICERs 17,000-£22,173), with MRI being the most cost-effective strategy.

CONCLUSION

This re-running of the NICE health economic model with real-world data strongly supports the NICE guideline recommendation for brain imaging prior to curative-intent treatment in stage III lung cancer but questions the cost-effectiveness of CT brain imaging prior to curative-intent treatment in stage II lung cancer.

What is the optimal management of potentially resectable stage III-N2 NSCLC? Results of a fixed-effects network meta-analysis and economic modelling

Introduction

There is a critical need to understand the optimal treatment regimen in patients with potentially resectable stage III-N2 nonsmall cell lung cancer (NSCLC).

Methods

A systematic review of randomised controlled trials was carried out using a literature search including the CDSR, CENTRAL, DARE, HTA, EMBASE and MEDLINE bibliographic databases. Selected trials were used to perform a Bayesian fixed-effects network meta-analysis and economic modelling of treatment regimens relevant to current-day treatment options: chemotherapy plus surgery (CS), chemotherapy plus radiotherapy (CR) and chemoradiotherapy followed by surgery (CRS).

Findings

Six trials were prioritised for evidence synthesis. The fixed-effects network meta-analyses demonstrated an improvement in disease-free survival (DFS) for CRS versus CS and CRS versus CR of 0.34 years (95% CI 0.02-0.65) and 0.32 years (95% CI 0.05-0.58) respectively, over a 5-year period. No evidence of effect was observed in overall survival although point estimates favoured CRS. The probabilities that CRS had a greater mean survival time and greater probability of being alive than the reference treatment of CR at 5 years were 89% and 86% respectively. Survival outcomes for CR and CS were essentially equivalent. The economic model calculated that CRS and CS had incremental cost-effectiveness ratios of £19 000/quality-adjusted life-year (QALY) and £78 000/QALY compared to CR. The probability that CRS generated more QALYs than CR and CS was 94%.

Interpretation

CRS provides an extended time in a disease-free state leading to improved cost-effectiveness over CR and CS in potentially resectable stage III-N2 NSCLC.

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.

Usage of epidermal growth factor mutation testing and impact on treatment patterns in non-small cell lung cancer: An international observational study

OBJECTIVES

Epidermal growth factor receptor (EGFR) mutations (EGFRm) are common oncogene drivers in non-small cell lung cancer (NSCLC). This real-world study explored treatment patterns and time to receive EGFRm test results in patients with advanced EGFRm NSCLC.

METHODS

A cross-sectional medical chart review was completed May-August 2020 in Australia, Canada, Germany, Italy, South Korea, Taiwan, UK, and USA. Eligible patients had advanced NSCLC and a positive EGFRm test result January-December 2017. Data were abstracted from NSCLC diagnosis to end of follow-up (31 March 2020) or patient's death whichever occurred earlier. The index date was the date of EGFRm confirmation.

RESULTS

223 physicians provided data for 1,793 patients. Patients' mean age was 64.7 years, 54 % were male, 30.7 % had no history of smoking. Overall, 78 % of EGFRm test results were received ≤ 2 weeks after request (range of median 7-14 days across countries). Median time from advanced NSCLC diagnosis to EGFRm test result was 18 days (median range 10-22 days across countries). Over a third (37 %) of patients received a systemic treatment prior to EGFRm result; chemotherapy (25 %) and EGFR-TKI (15 %) were most commonly prescribed; post-EGFR test-result was EGFR-TKI (68 %); 80 % of patients initiated EGFR-TKI at any time point post-NSCLC diagnosis. Of those receiving a first-line EGFR-TKI post-EGFRm testing, 84 % received a TKI alone, 12 % in combination with chemotherapy, and 3 % with other treatments. Median time from first-line EGFR-TKI initiation post-EGFRm testing to first subsequent treatment was 19.8 months.

CONCLUSION

Over one-fifth of patients wait >14 days for their EGFRm test results, affecting their likelihood of receiving first-line EGFR-TKI with 20 % of patients never receiving EGFR TKI treatment. There was significant inter-country variability in the proportion of patients receiving EGFR TKIs. Our study highlights the need to improve EGFRm testing turnaround times and treatment initiation across countries.

A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodules

BACKGROUND

Large lung nodules (≥15 mm) have the highest risk of malignancy, and may exhibit important differences in phenotypic or clinical characteristics to their smaller counterparts. Existing risk models do not stratify large nodules well. We aimed to develop and validate an integrated segmentation and classification pipeline, incorporating deep-learning and traditional radiomics, to classify large lung nodules according to cancer risk.

METHODS

502 patients from five U.K. centres were recruited to the large-nodule arm of the retrospective LIBRA study between July 2020 and April 2022. 838 CT scans were used for model development, split into training and test sets (70% and 30% respectively). An nnUNet model was trained to automate lung nodule segmentation. A radiomics signature was developed to classify nodules according to malignancy risk. Performance of the radiomics model, termed the large-nodule radiomics predictive vector (LN-RPV), was compared to three radiologists and the Brock and Herder scores.

FINDINGS

499 patients had technically evaluable scans (mean age 69 ± 11, 257 men, 242 women). In the test set of 252 scans, the nnUNet achieved a DICE score of 0.86, and the LN-RPV achieved an AUC of 0.83 (95% CI 0.77-0.88) for malignancy classification. Performance was higher than the median radiologist (AUC 0.75 [95% CI 0.70-0.81], DeLong p = 0.03). LN-RPV was robust to auto-segmentation (ICC 0.94). For baseline solid nodules in the test set (117 patients), LN-RPV had an AUC of 0.87 (95% CI 0.80-0.93) compared to 0.67 (95% CI 0.55-0.76, DeLong p = 0.002) for the Brock score and 0.83 (95% CI 0.75-0.90, DeLong p = 0.4) for the Herder score. In the international external test set (n = 151), LN-RPV maintained an AUC of 0.75 (95% CI 0.63-0.85). 18 out of 22 (82%) malignant nodules in the Herder 10-70% category in the test set were identified as high risk by the decision-support tool, and may have been referred for earlier intervention.

INTERPRETATION

The model accurately segments and classifies large lung nodules, and may improve upon existing clinical models.

FUNDING

This project represents independent research funded by: 1) Royal Marsden Partners Cancer Alliance, 2) the Royal Marsden Cancer Charity, 3) the National Institute for Health Research (NIHR) Biomedical Research Centre at the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, 4) the National Institute for Health Research (NIHR) Biomedical Research Centre at Imperial College London, 5) Cancer Research UK (C309/A31316).

The National Lung Cancer Audit: The Impact of COVID-19

Since 2014, the National Lung Cancer Audit (NLCA) has been evaluating the performance of the UK NHS lung cancer services against established standards of care. Prior to the onset of the COVID-19 pandemic, the NLCA's annual reports revealed a steady stream of improvements in early diagnosis, access to surgery, treatment with anti-cancer therapies, input from specialist nursing and survival for patients with lung cancer in the NHS. In January 2022, the NLCA reported on the negative impact COVID-19 has had on all aspects of the lung cancer diagnosis and treatment pathway within the NHS. This article details the fundamental changes made to the NLCA data collection and analysis process during the COVID-19 pandemic and details the negative impact COVID-19 had on NHS lung cancer patient outcomes during 2020.

Utilisation of primary care electronic patient records for identification and targeted invitation of individuals to a lung cancer screening programme

Lung cancer screening (LCS) eligibility is largely determined by tobacco consumption. Primary care smoking data could guide LCS invitation and eligibility assessment. We present observational data from the SUMMIT Study, where individual self-reported smoking status was concordant with primary care records in 75.3%. However, 10.3% demonstrated inconsistencies between historic and most recent smoking status documentation. Quantified tobacco consumption was frequently missing, precluding direct LCS eligibility assessment. Primary care recorded "ever-smoker" status, encompassing both recent and historic documentation, can be used to target LCS invitation. Identifying those with missing or erroneous "never-smoker" smoking status is crucial for equitable invitation to LCS.

Optimising tissue acquisition and the molecular testing pathway for patients with non-small cell lung cancer: A UK expert consensus statement

Targeted therapy against actionable variants has revolutionised the treatment landscape for non-small cell lung cancer (NSCLC). Approximately half of NSCLC adenocarcinomas have an actionable variant, making molecular testing a critical component of the diagnostic process to personalise therapeutic options, optimise clinical outcomes and minimise toxicity. Recently, genomic testing in England has undergone major changes with the introduction of Genomic Laboratory Hubs, designed to consolidate and enhance existing laboratory provision and deliver genomic testing as outlined in the National Genomic Test Directory. Similar changes are ongoing in Scotland, Wales and Northern Ireland. However, multiple challenges exist with current tissue acquisition procedures and the molecular testing pathway in the UK, including quantity and quality of available tissue, adequacy rates, test availability among genomic laboratories, turnaround times, multidisciplinary team communication, and limited guidance and standardisation. The COVID-19 pandemic has added an extra layer of complexity. Herein, we summarise best practice recommendations, based on expert opinion, to overcome existing challenges in the UK. The least invasive biopsy technique should be undertaken with the aim of acquiring the greatest quality and quantity of tissue. Use of sedation should be considered to improve patient experience. Rapid on-site evaluation may also be useful to help guide adequate sampling, and liquid biopsy may be beneficial in some instances. Sample processing should be appropriate to facilitate biomarker testing, in particular, next-generation sequencing for comprehensive genomic information. Steps to optimise tissue utilisation and turnaround times, such as planning of tissue usage, limiting immunohistochemistry, tumour enrichment, and reflex testing at diagnosis, should be implemented. Guidelines for tissue acquisition and sample processing may help to improve sample adequacy to perform downstream testing. Communication among genomic laboratories will help to standardise test availability across England and local auditing could identify further areas for optimisation, including ways to improve turnaround times and adequacy rates.

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.

Telephone risk-based eligibility assessment for low-dose CT lung cancer screening

Eligibility for lung cancer screening (LCS) requires assessment of lung cancer risk, based on smoking history alongside demographic and medical factors. Reliance on individual face-to-face eligibility assessment risks inefficiency and costliness. The SUMMIT Study introduced a telephone-based lung cancer risk assessment to guide invitation to face-to-face LCS eligibility assessment, which significantly increased the proportion of face-to-face attendees eligible for LCS. However, levels of agreement between phone screener and in-person responses were lower in younger individuals and minority ethnic groups. Telephone-based risk assessment is an efficient way to optimise selection for LCS appointments but requires further iteration to ensure an equitable approach.

Association between time-to-treatment and outcomes in non-small cell lung cancer: a systematic review

BACKGROUND

National targets for timely diagnosis and management of a potential cancer are driven in part by the perceived risk of disease progression during avoidable delays. However, it is unclear to what extent time-to-treatment impacts prognosis for patients with non-small cell lung cancer, with previous reviews reporting mixed or apparently paradoxical associations. This systematic review focuses on potential confounders in order to identify particular patient groups which may benefit most from timely delivery of care.

METHODS

Medline, EMBASE and Cochrane databases were searched for publications between January 2012 and October 2020, correlating timeliness in secondary care pathways to patient outcomes. The protocol is registered with PROSPERO (the International Prospective Register of Systematic Reviews; ID 99239). Prespecified factors (demographics, performance status, histology, stage and treatment) are examined through narrative synthesis.

RESULTS

Thirty-seven articles were included. All but two were observational. Timely care was generally associated with a worse prognosis in those with advanced stage disease (6/8 studies) but with better outcomes for patients with early-stage disease treated surgically (9/12 studies). In one study, patients with squamous cell carcinoma referred for stereotactic ablative radiotherapy benefited more from timely care, compared with patients with adenocarcinoma. One randomised controlled trial supported timeliness as being advantageous in those with stage I-IIIA disease.

CONCLUSION

There are limitations to the available evidence, but observed trends suggest timeliness to be of particular importance in surgical candidates. In more advanced disease, survival trends are likely outweighed by symptom burden, performance status or clinical urgency dictating timeliness of treatment.

Frailty in Patients With Lung Cancer: A Systematic Review and Meta-Analysis

BACKGROUND

Previous studies regarding the prevalence of frailty in patients with lung cancer and mortality in frail patients with lung cancer are inconsistent and require clarification.

RESEARCH QUESTION

What is the prevalence and impact of frailty in patients with lung cancer?

STUDY DESIGN AND METHODS

This systematic review and meta-analysis used a combination of free-text terms and medical subject headings terms, according to the database requirements in MEDLINE/PubMed, Scopus, and Cochrane Library from inception until November 15, 2020.

RESULTS

A total of 2,571 articles were identified, and 16 articles involving 4,183 patients were included for study. The prevalence of frailty in lung cancer was 45% (95% CI, 28-61; I² = 99.5%; P < .0001). In patients with lung cancer, frailty was associated with an increased hazard ratio for mortality (hazard ratio, 3.01; 95% CI, 1.77-5.10; P < .001).

INTERPRETATION

The prevalence of frailty in lung cancer is 45%, which has a significant negative impact on survival of patients with lung cancer. These results highlight the importance of measuring frailty, which provides important prognostic information, and may provide opportunities for interventions to improve outcomes in patients with lung cancer.

Ninety-day mortality following lung cancer surgery: outcomes from the English national clinical outcomes audit

Accurately explaining perioperative mortality and risk to patients is an essential part of shared decision making. In the case of lung cancer surgery, the currently available multivariable mortality prediction tools perform poorly, and could mislead patients. Using data from 2004 to 2012, this group has previously produced data tables for 90-day postoperative mortality, to be used as a communication aid in the consenting process. Using National Lung Cancer Clinical Outcomes audit data from 2017 to 2018, we have produced updated early mortality tables, to reflect current thoracic surgery practice.

Biomarker Testing for People With Advanced Lung Cancer in England

Introduction

Optimal management of people with advanced NSCLC depends on accurate identification of predictive markers. Yet, real-world data in this setting are limited. We describe the impact, timeliness, and outcomes of molecular testing for patients with advanced NSCLC and good performance status in England.

Methods

In collaboration with Public Health England, patients with stages IIIB to IV NSCLC, with an Eastern Cooperative Oncology Group performance status of 0 to 2, in England, between June 2017 and December 2017, were identified. All English hospitals were invited to record information.

Results

A total of 60 of 142 invited hospitals in England participated in this study and submitted data on 1157 patients. During the study period, 83% of patients with advanced adenocarcinoma underwent molecular testing for three recommended predictive biomarkers (EGFR, ALK, and programmed death-ligand 1). A total of 80% of patients with nonsquamous carcinomas on whom biomarker testing was performed had adequate tissue for analysis on initial sampling. First-line treatment with a tyrosine kinase inhibitor was received by 71% of patients with adenocarcinoma and a sensitizing EGFR mutation and by 59% of those with an ALK translocation. Of patients with no driver mutation and a programmed death-ligand 1 expression of greater than or equal to 50%, 47% received immunotherapy.

Conclusions

We present a comprehensive data set for molecular testing in England. Although molecular testing is well established in England, timeliness and uptake of targeted therapies should be improved.

COVID-19 and the multidisciplinary care of patients with lung cancer: an evidence-based review and commentary

Delivering lung cancer care during the COVID-19 pandemic has posed significant and ongoing challenges. There is a lack of published COVID-19 and lung cancer evidence-based reviews, including for the whole patient pathway. We searched for COVID-19 and lung cancer publications and brought together a multidisciplinary group of stakeholders to review and comment on the evidence and challenges. A rapid review of the literature was undertaken up to 28 October 2020, producing 144 papers, with 113 full texts screened. We focused on new primary data collection (qualitative or quantitative evidence) and excluded case reports, editorials and commentaries. Following exclusions, 15 published papers were included in the review and are summarised. They included one qualitative paper and 14 quantitative studies (surveys or cohort studies), with a total of 2295 lung cancer patients data included (mean study size 153 patients; range 7-803). Review of current evidence and commentary included awareness and help-seeking; lung cancer screening; primary care assessment and referral; diagnosis and treatment in secondary care, including oncology and surgery; patient experience and palliative care. Cross-cutting themes and challenges were identified using qualitative methods for patients, healthcare professionals and service delivery, with a clear need for continued studies to guide evidence-based decision-making.

Impact on quality of life from multimodality treatment for lung cancer: a randomised controlled feasibility trial of surgery versus no surgery as part of multimodality treatment in potentially resectable stage III-N2 NSCLC (the PIONEER trial)

Introduction

Optimal treatment for ‘potentially resectable’ stage III-N2 non-small cell lung cancer (NSCLC) requires multimodality treatment: local treatment (surgery or radiotherapy) and systemic anticancer therapy. There is no clear evidence of superiority for survival between the two approaches and little research has explored quality of life (QOL). This study will inform the design of a phase III randomised trial of surgery versus no surgery as part of multimodality treatment for stage III-N2 NSCLC with QOL as a primary outcome.

Methods and analysis

Patient participants will be randomised to receive multimodality treatment (1) with surgery OR (2) without surgery. The Quintet Recruitment Intervention will be used to maximise recruitment. Eligible patients will have ‘potentially resectable’ N2 NSCLC and have received a multidisciplinary team recommendation for multimodality treatment. Sixty-six patients and their carers will be recruited from 8 UK centres. Patient/carer QOL questionnaires will be administered at baseline, weeks 6, 9, 12 and month 6. Semistructured interviews will be conducted. Quantitative data will be analysed descriptively and qualitative data will be analysed using framework analysis.

Ethics and dissemination

Ethical approval has been obtained. Results will be disseminated via publications, national bodies and networks, and patient and public involvement groups.

Trial registration

NCT04540757

Navigating Diagnostic and Treatment Decisions in Non-Small Cell Lung Cancer: Expert Commentary on the Multidisciplinary Team Approach

Non-small cell lung cancer (NSCLC) accounts for approximately one in five cancer-related deaths, and management requires increasingly complex decision making by health care professionals. Many centers have therefore adopted a multidisciplinary approach to patient care, using the expertise of various specialists to provide the best evidence-based, personalized treatment. However, increasingly complex disease staging, as well as expanded biomarker testing and multimodality management algorithms with novel therapeutics, have driven the need for multifaceted, collaborative decision making to optimally guide the overall treatment process. To keep up with the rapidly evolving treatment landscape, national-level guidelines have been introduced to standardize patient pathways and ensure prompt diagnosis and treatment. Such strategies depend on efficient and effective communication between relevant multidisciplinary team members and have both improved adherence to treatment guidelines and extended patient survival. This article highlights the value of a multidisciplinary approach to diagnosis and staging, treatment decision making, and adverse event management in NSCLC. IMPLICATIONS FOR PRACTICE: This review highlights the value of a multidisciplinary approach to the diagnosis and staging of non-small cell lung cancer (NSCLC) and makes practical suggestions as to how multidisciplinary teams (MDTs) can be best deployed at individual stages of the disease to improve patient outcomes and effectively manage common adverse events. The authors discuss how a collaborative approach, appropriately leveraging the diverse expertise of NSCLC MDT members (including specialist radiation and medical oncologists, chest physicians, pathologists, pulmonologists, surgeons, and nursing staff) can continue to ensure optimal per-patient decision making as treatment options become ever more specialized in the era of biomarker-driven therapeutic strategies.

Interventional Pulmonology: A Brave New World

Interventional pulmonology is a dynamic and evolving field in respiratory medicine. Advances have improved the ability to diagnose and manage diseases of the airways. A shift toward early detection of malignant disease has generated a focus on innovative diagnostic techniques. With patient populations living longer with malignant and benign diseases, the role for interventional bronchoscopy has grown. In cancer groups, novel immunotherapies have improved the prospects of clinical outcomes and reignited a focus on optimizing patient performance status to enable access to anticancer therapy. This review discusses current and emerging diagnostic modalities and therapeutic approaches available to manage airway diseases.

Lung Screen Uptake Trial: results from a single lung cancer screening round

The Lung Screen Uptake Trial tested a novel invitation strategy to improve uptake and reduce socioeconomic and smoking-related inequalities in lung cancer screening (LCS) participation. It provides one of the first UK-based 'real-world' LCS cohorts. Of 2012 invited, 1058 (52.6%) attended a 'lung health check'. 768/996 (77.1%) in the present analysis underwent a low-dose CT scan. 92 (11.9%) and 33 (4.3%) participants had indeterminate pulmonary nodules requiring 3-month and 12-month surveillance, respectively; 36 lung cancers (4.7%) were diagnosed (median follow-up: 1044 days). 72.2% of lung cancers were stage I/II and 79.4% of non-small cell lung cancer had curative-intent treatment.

Predictors of patient preference for either whole body magnetic resonance imaging (WB-MRI) or CT/ PET-CT for staging colorectal or lung cancer

INTRODUCTION

Whole body magnetic resonance imaging (WB-MRI) may be more efficient in staging cancers, but can be harder for patients to tolerate. We examined predictors of patient preference for WB-MRI vs. CT/ PET-CT for staging colorectal or lung cancer.

METHODS

Patients recruited prospectively to two multicentre trials comparing diagnostic accuracy of WB-MRI with standard staging scans were sent two questionnaires: the first, administered at trial registration, captured demographics, educational level and comorbidities; the second, administered after staging completion, measured emotional distress (GHQ-12), positive mood (PANAS), perceived scan burden, patients' beliefs about WB-MRI, and preference for either WB-MRI or CT (colorectal trial), WB-MRI or PET-CT (lung trial). Preference for WB-MRI or CT/ PET-CT was analysed using logistic regression.

RESULTS

Baseline and post-staging questionnaires were completed by 97 and 107 patients, respectively. Overall, 56/107 (52%) preferred WB-MRI over standard scans and were more likely to have no additional comorbidities, higher positive mood, greater awareness of potential benefits of WB-MRI and lower levels of perceived WB-MRI scan burden. In adjusted analyses, only awareness of potential WB-MRI benefits remained a significant predictor (OR: 1.516, 95% CIs 1.006-2.284, P = 0.047). Knowledge that WB-MRI does not use radiation predicted preference (adjusted OR: 3.018, 95% CIs 1.099-8.288, P = 0.032), although only 45/107 (42%) patients were aware of this attribute.

CONCLUSIONS

A small majority of patients undergoing staging of colorectal or lung cancer prefer WB-MRI to CT/ PET-CT. Raising awareness of the potential benefits of WB-MRI, notably lack of ionizing radiation, could influence preference.

Effect of delays in the 2-week-wait cancer referral pathway during the COVID-19 pandemic on cancer survival in the UK: a modelling study

BACKGROUND

During the COVID-19 lockdown, referrals via the 2-week-wait urgent pathway for suspected cancer in England, UK, are reported to have decreased by up to 84%. We aimed to examine the impact of different scenarios of lockdown-accumulated backlog in cancer referrals on cancer survival, and the impact on survival per referred patient due to delayed referral versus risk of death from nosocomial infection with severe acute respiratory syndrome coronavirus 2.

METHODS

In this modelling study, we used age-stratified and stage-stratified 10-year cancer survival estimates for patients in England, UK, for 20 common tumour types diagnosed in 2008-17 at age 30 years and older from Public Health England. We also used data for cancer diagnoses made via the 2-week-wait referral pathway in 2013-16 from the Cancer Waiting Times system from NHS Digital. We applied per-day hazard ratios (HRs) for cancer progression that we generated from observational studies of delay to treatment. We quantified the annual numbers of cancers at stage I-III diagnosed via the 2-week-wait pathway using 2-week-wait age-specific and stage-specific breakdowns. From these numbers, we estimated the aggregate number of lives and life-years lost in England for per-patient delays of 1-6 months in presentation, diagnosis, or cancer treatment, or a combination of these. We assessed three scenarios of a 3-month period of lockdown during which 25%, 50%, and 75% of the normal monthly volumes of symptomatic patients delayed their presentation until after lockdown. Using referral-to-diagnosis conversion rates and COVID-19 case-fatality rates, we also estimated the survival increment per patient referred.

FINDINGS

Across England in 2013-16, an average of 6281 patients with stage I-III cancer were diagnosed via the 2-week-wait pathway per month, of whom 1691 (27%) would be predicted to die within 10 years from their disease. Delays in presentation via the 2-week-wait pathway over a 3-month lockdown period (with an average presentational delay of 2 months per patient) would result in 181 additional lives and 3316 life-years lost as a result of a backlog of referrals of 25%, 361 additional lives and 6632 life-years lost for a 50% backlog of referrals, and 542 additional lives and 9948 life-years lost for a 75% backlog in referrals. Compared with all diagnostics for the backlog being done in month 1 after lockdown, additional capacity across months 1-3 would result in 90 additional lives and 1662 live-years lost due to diagnostic delays for the 25% backlog scenario, 183 additional lives and 3362 life-years lost under the 50% backlog scenario, and 276 additional lives and 5075 life-years lost under the 75% backlog scenario. However, a delay in additional diagnostic capacity with provision spread across months 3-8 after lockdown would result in 401 additional lives and 7332 life-years lost due to diagnostic delays under the 25% backlog scenario, 811 additional lives and 14 873 life-years lost under the 50% backlog scenario, and 1231 additional lives and 22 635 life-years lost under the 75% backlog scenario. A 2-month delay in 2-week-wait investigatory referrals results in an estimated loss of between 0·0 and 0·7 life-years per referred patient, depending on age and tumour type.

INTERPRETATION

Prompt provision of additional capacity to address the backlog of diagnostics will minimise deaths as a result of diagnostic delays that could add to those predicted due to expected presentational delays. Prioritisation of patient groups for whom delay would result in most life-years lost warrants consideration as an option for mitigating the aggregate burden of mortality in patients with cancer.

FUNDING

None.

Prevalence, Symptom Burden, and Underdiagnosis of Chronic Obstructive Pulmonary Disease in a Lung Cancer Screening Cohort

Rationale: Individuals eligible for lung cancer screening (LCS) by low-dose computed tomography (LDCT) are also at risk of chronic obstructive pulmonary disease (COPD) due to age and smoking exposure. Whether the LCS episode is useful for early detection of COPD is not well established.Objectives: To explore associations between symptoms, comorbidities, spirometry, and emphysema in participants enrolled in the Lung Screen Uptake Trial.Methods: This cross-sectional study was a prespecified analysis nested within Lung Screen Uptake Trial, which was a randomized study testing the impact of differing invitation materials on attendance of 60- to 75-year-old smokers and ex-smokers to a "lung health check" between November 2015 and July 2017. Participants with a smoking history ≥30 pack-years and who quit ≤15 years ago, or meeting a lung cancer risk of ≥1.51% via the Prostate Lung Colorectal Ovarian model or ≥2.5% via the Liverpool Lung Project model, were offered LDCT. COPD was defined and classified according to the GOLD (Global Initiative for Obstructive Lung Disease) criteria using prebronchodilator spirometry. Analyses included the use of descriptive statistics, chi-square tests to examine group differences, and univariable and multivariable logistic regression to explore associations between symptom prevalence, airflow limitation, and visually graded emphysema.Results: A total of 560 of 986 individuals included in the analysis (57%) had prebronchodilator spirometry consistent with COPD; 67% did not have a prior history of COPD and were termed "undiagnosed." Emphysema prevalence in those with known and "undiagnosed" COPD was 73% and 68%, respectively. A total of 32% of those with "undiagnosed COPD" had no emphysema on LDCT. Inhaler use and symptoms were more common in the "known" than the "undiagnosed" COPD group (63% vs. 33% with persistent cough [P < 0.001]; 73% vs. 33% with dyspnea [P < 0.001]). Comorbidities were common in all groups. Adjusted odds ratio (aOR) of respiratory symptoms were more significant for airflow obstruction (aOR GOLD 1 and 2, 1.57; confidence interval [CI], 1.14-2.17; aOR GOLD 3 and 4, 4.6; CI, 2.17-9.77) than emphysema (aOR mild, 1.12; CI, 0.81-1.55; aOR moderate, 1.33; CI, 0.85-2.09; aOR severe, 4.00; CI, 1.57-10.2).Conclusions: There is high burden of "undiagnosed COPD" and emphysema in LCS participants. Adding spirometry findings to the LDCT enhances identification of individuals with COPD.Clinical trial registered with www.clinicaltrials.gov (NCT02558101).

Lung Screen Uptake Trial (LSUT): Randomized Controlled Clinical Trial Testing Targeted Invitation Materials

Rationale: Low uptake of low-dose computed tomography (LDCT) lung cancer screening, particularly by current smokers of a low socioeconomic position, compromises effectiveness and equity.Objectives: To compare the effect of a targeted, low-burden, and stepped invitation strategy versus control on uptake of hospital-based Lung Health Check appointments offering LDCT screening.Methods: In a two-arm, blinded, between-subjects, randomized controlled trial, 2,012 participants were selected from 16 primary care practices using these criteria: 1) aged 60 to 75 years, 2) recorded as a current smoker within the last 7 years, and 3) no prespecified exclusion criteria contraindicating LDCT screening. Both groups received a stepped sequence of preinvitation, invitation, and reminder letters from their primary care practitioner offering prescheduled appointments. The key manipulation was the accompanying leaflet. The intervention group's leaflet targeted psychological barriers and provided low-burden information, mimicking the concept of the U.K. Ministry of Transport's annual vehicle test ("M.O.T. For Your Lungs").Measurements and Main Results: Uptake was 52.6%, with no difference between intervention (52.3%) and control (52.9%) groups in unadjusted (odds ratio [OR], 0.98; 95% confidence interval [CI], 0.82-1.16) or adjusted (OR, 0.98; 95% CI, 0.82-1.17) analyses. Current smokers were less likely to attend (adjusted OR, 0.70; 95% CI, 0.56-0.86) than former smokers. Socioeconomic deprivation was significantly associated with lower uptake for the control group only (P < 0.01).Conclusions: The intervention did not improve uptake. Regardless of trial arm, uptake was considerably higher than previous clinical and real-world studies, particularly given that the samples were predominantly lower socioeconomic position smokers. Strategies common to both groups, including a Lung Health Check approach, could represent a minimum standard.Clinical trial registered with www.clinicaltrials.gov (NCT02558101) and registered prospectively with the International Standard Registered Clinical/Social Study (N21774741).

Patient deprivation and perceived scan burden negatively impact the quality of whole-body MRI

AIM

To evaluate the association between the image quality of cancer staging whole-body magnetic resonance imaging (WB-MRI) and patient demographics, distress, and perceived scan burden.

MATERIALS AND METHODS

A sample of patients recruited prospectively to multicentre trials comparing WB-MRI with standard scans for staging lung and colorectal cancer were invited to complete two questionnaires. The baseline questionnaire, administered at recruitment, collated data on demographics, distress and co-morbidity. The follow-up questionnaire, completed after staging investigations, measured perceived WB-MRI scan burden (scored 1 low to 7 high). WB-MRI anatomical coverage, and technical quality was graded by a radiographic technician and grading combined to categorise the scan as "optimal", "sub-optimal" or "degraded". A radiologist categorised 30 scans to test interobserver agreement. Data were analysed using the chi-square, Fisher's exact, t-tests, and multinomial regression.

RESULTS

One hundred and fourteen patients were included in the study (53 lung, 61 colorectal; average age 65.3 years, SD=11.8; 66 men [57.9%]). Overall, 45.6% (n=52), scans were classified as "optimal" quality, 39.5% (n=45) "sub-optimal", and 14.9% (n=17) as "degraded". In adjusted analyses, greater deprivation level and higher patient-reported scan burden were both associated with a higher likelihood of having a sub-optimal versus an optimal scan (odds ratio [OR]: 4.465, 95% confidence interval [CI]: 1.454 to 13.709, p=0.009; OR: 1.987, CI: 1.153 to 3.425, p=0.013, respectively). None of the variables predicted the likelihood of having a degraded scan.

CONCLUSIONS

Deprivation and patients' perceived experience of the WB-MRI are related to image quality. Tailored protocols and individualised patient management before and during WB-MRI may improve image quality.

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.