Interval lung cancer after a negative CT screening examination: CT findings and outcomes in National Lung Screening Trial participants

Lung cancer screening by low-dose CT scan in France: final results of the DEP KP80 study after three rounds

BACKGROUND

In prior randomised controlled trials, lung cancer screening using low-dose computed tomography (LDCT) has been shown to reduce lung cancer mortality and overall mortality. Despite these results, organised screening in France remains a challenge. This study assessed the feasibility and efficacy of lung cancer screening within a real-life context in a French administrative territory.

METHODS

DEP KP80 was a single-arm prospective study. Participants aged between 55 and 74 years, smokers or former smokers of ≥30 pack-years, were recruited. An annual LDCT scan was scheduled and three rounds were performed. Subjects were selected by general practitioners or pulmonologists, who checked the inclusion criteria and prescribed the CT scan.

FINDINGS

Between March 2016 and February 2020, 1254 participants were enrolled. Overall, 945 (75.4%) participants underwent baseline LDCT (T0), 376 (42.8%) completed the first round (T1) and 270 (31%) the second (T2) one. Forty-two lung cancers were diagnosed, 30 cancers (71.4%) were stage I or II and 34 cancers (80.9%) were treated surgically. In this study, the overall positive predictive value for a positive screening was 48% (95% CI 37-59) and the negative predictive value 100% (95% CI 100-100).

INTERPRETATION

This study demonstrated the feasibility and efficacy of lung cancer screening in a real-life context with most lung cancers diagnosed at an early stage and surgically removed. Our results also highlighted the importance of participation in each round, underlining the fact that optimising organisation is a major goal.

FUNDING

Agence Régionale de Santé de Picardie, La Ligue contre le cancer, le Conseil Départemental de la Somme, and AstraZeneca.

The Azygos Esophageal Recess Is Not to Be Missed in Screening Lung Cancer With LDCT

PURPOSE

Lesion overlooking and late diagnostic workup can compromise the efficacy of low-dose CT (LDCT) screening of lung cancer (LC), implying more advanced and less curable disease stages. We hypothesized that the azygos esophageal recess (AER) of the right lower lobe (RLL) might be an area prone to lesion overlooking in LC screening.

MATERIALS AND METHODS

Two radiologists reviewed the LDCT examinations of all the screen-detected incident LCs observed in the active arm of 2 randomized clinical trials: ITALUNG and national lung screening trial. Those in the AER were compared with those in the remainder of the RLL for possible differences in diagnostic lag according to the Lung-RADS 1.1 recommendations, size, stage, and mortality.

RESULTS

Six (11.7%) of 51 screen-detected incident LCs of the RLL were located in the AER. The diagnostic lag time was significantly longer (P=0.046) in the AER LC (mean 14±9 mo) than in the LC in the remaining RLL (mean 7.3±1 mo). Size and stage at diagnosis were not significantly different. All 6 subjects with LC in the AER and 16 (35.5%) of 45 subjects with LC in the remaining RLL (P=0.004) died of LC after a median follow-up of 12 years.

CONCLUSION

Our retrospective study indicates that AER might represent a lung region of the RLL prone to have early LC overlooked due to detection or interpretation errors with possible detrimental consequences for the subject undergoing LC screening.

Navigating the Pitfalls of Lung Cancer Screening: A Case Study on the Risks and Costs of Negative Screenings

Lung cancer is the leading cause of cancer-related deaths in the United States. Low-dose computed tomography is the preferred screening method for high-risk individuals. However, with a false-negative rate reaching 15%, this method can underestimate disease prevalence and delay necessary treatment. This case examines a 61-year-old female smoker with chronic obstructive pulmonary disease who initially received a negative result from screening. Her imaging findings were categorized as Lung Imaging Reporting and Data System (Lung-RADS) 2 but advanced to small cell lung carcinoma. This progression emphasizes the imperative of thoroughly evaluating screening results and patient history. False-negative results from screenings have profound implications, leading to delayed diagnoses, adversely affecting patient outcomes, and increasing healthcare costs. The necessity for vigilant follow-up enhanced diagnostic precision and transparent communication about limitations is paramount. An economic analysis emphasizes the significant financial impact of diagnosing lung cancer at advanced stages, highlighting the need for timely and accurate diagnostics. Comprehensive strategies, such as physician education, patient awareness, and stringent quality control, are crucial to improving the efficacy of lung cancer screening. Addressing the issue of false negatives is vital for enhancing early detection rates, decreasing healthcare expenses, and advancing patient care in lung cancer management. Continuous evaluation and adjustment of screening protocols are essential to reduce risks and optimize outcomes.

Sybil: A Validated Deep Learning Model to Predict Future Lung Cancer Risk From a Single Low-Dose Chest Computed Tomography

PURPOSE

Low-dose computed tomography (LDCT) for lung cancer screening is effective, although most eligible people are not being screened. Tools that provide personalized future cancer risk assessment could focus approaches toward those most likely to benefit. We hypothesized that a deep learning model assessing the entire volumetric LDCT data could be built to predict individual risk without requiring additional demographic or clinical data.

METHODS

We developed a model called Sybil using LDCTs from the National Lung Screening Trial (NLST). Sybil requires only one LDCT and does not require clinical data or radiologist annotations; it can run in real time in the background on a radiology reading station. Sybil was validated on three independent data sets: a heldout set of 6,282 LDCTs from NLST participants, 8,821 LDCTs from Massachusetts General Hospital (MGH), and 12,280 LDCTs from Chang Gung Memorial Hospital (CGMH, which included people with a range of smoking history including nonsmokers).

RESULTS

Sybil achieved area under the receiver-operator curves for lung cancer prediction at 1 year of 0.92 (95% CI, 0.88 to 0.95) on NLST, 0.86 (95% CI, 0.82 to 0.90) on MGH, and 0.94 (95% CI, 0.91 to 1.00) on CGMH external validation sets. Concordance indices over 6 years were 0.75 (95% CI, 0.72 to 0.78), 0.81 (95% CI, 0.77 to 0.85), and 0.80 (95% CI, 0.75 to 0.86) for NLST, MGH, and CGMH, respectively.

CONCLUSION

Sybil can accurately predict an individual's future lung cancer risk from a single LDCT scan to further enable personalized screening. Future study is required to understand Sybil's clinical applications. Our model and annotations are publicly available.

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Impact of low-dose computed tomography (LDCT) screening on lung cancer-related mortality

BACKGROUND

Lung cancer is the most common cause of cancer-related death in the world, however lung cancer screening has not been implemented in most countries at a population level. A previous Cochrane Review found limited evidence for the effectiveness of lung cancer screening with chest radiography (CXR) or sputum cytology in reducing lung cancer-related mortality, however there has been increasing evidence supporting screening with low-dose computed tomography (LDCT).  OBJECTIVES: To determine whether screening for lung cancer using LDCT of the chest reduces lung cancer-related mortality and to evaluate the possible harms of LDCT screening.

SEARCH METHODS

We performed the search in collaboration with the Information Specialist of the Cochrane Lung Cancer Group and included the Cochrane Lung Cancer Group Trial Register, Cochrane Central Register of Controlled Trials (CENTRAL, the Cochrane Library, current issue), MEDLINE (accessed via PubMed) and Embase in our search. We also searched the clinical trial registries to identify unpublished and ongoing trials. We did not impose any restriction on language of publication. The search was performed up to 31 July 2021.  SELECTION CRITERIA: Randomised controlled trials (RCTs) of lung cancer screening using LDCT and reporting mortality or harm outcomes.  DATA COLLECTION AND ANALYSIS: Two review authors were involved in independently assessing trials for eligibility, extraction of trial data and characteristics, and assessing risk of bias of the included trials using the Cochrane RoB 1 tool. We assessed the certainty of evidence using GRADE. Primary outcomes were lung cancer-related mortality and harms of screening. We performed a meta-analysis, where appropriate, for all outcomes using a random-effects model. We only included trials in the analysis of mortality outcomes if they had at least 5 years of follow-up. We reported risk ratios (RRs) and hazard ratios (HRs), with 95% confidence intervals (CIs) and used the I2 statistic to investigate heterogeneity.  MAIN RESULTS: We included 11 trials in this review with a total of 94,445 participants. Trials were conducted in Europe and the USA in people aged 40 years or older, with most trials having an entry requirement of ≥ 20 pack-year smoking history (e.g. 1 pack of cigarettes/day for 20 years or 2 packs/day for 10 years etc.). One trial included male participants only. Eight trials were phase three RCTs, with two feasibility RCTs and one pilot RCT. Seven of the included trials had no screening as a comparison, and four trials had CXR screening as a comparator. Screening frequency included annual, biennial and incrementing intervals. The duration of screening ranged from 1 year to 10 years. Mortality follow-up was from 5 years to approximately 12 years.  None of the included trials were at low risk of bias across all domains. The certainty of evidence was moderate to low across different outcomes, as assessed by GRADE. In the meta-analysis of trials assessing lung cancer-related mortality, we included eight trials (91,122 participants), and there was a reduction in mortality of 21% with LDCT screening compared to control groups of no screening or CXR screening (RR 0.79, 95% CI 0.72 to 0.87; 8 trials, 91,122 participants; moderate-certainty evidence). There were probably no differences in subgroups for analyses by control type, sex, geographical region, and nodule management algorithm. Females appeared to have a larger lung cancer-related mortality benefit compared to males with LDCT screening. There was also a reduction in all-cause mortality (including lung cancer-related) of 5% (RR 0.95, 95% CI 0.91 to 0.99; 8 trials, 91,107 participants; moderate-certainty evidence).  Invasive tests occurred more frequently in the LDCT group (RR 2.60, 95% CI 2.41 to 2.80; 3 trials, 60,003 participants; moderate-certainty evidence). However, analysis of 60-day postoperative mortality was not significant between groups (RR 0.68, 95% CI 0.24 to 1.94; 2 trials, 409 participants; moderate-certainty evidence).  False-positive results and recall rates were higher with LDCT screening compared to screening with CXR, however there was low-certainty evidence in the meta-analyses due to heterogeneity and risk of bias concerns. Estimated overdiagnosis with LDCT screening was 18%, however the 95% CI was 0 to 36% (risk difference (RD) 0.18, 95% CI -0.00 to 0.36; 5 trials, 28,656 participants; low-certainty evidence). Four trials compared different aspects of health-related quality of life (HRQoL) using various measures. Anxiety was pooled from three trials, with participants in LDCT screening reporting lower anxiety scores than in the control group (standardised mean difference (SMD) -0.43, 95% CI -0.59 to -0.27; 3 trials, 8153 participants; low-certainty evidence). There were insufficient data to comment on the impact of LDCT screening on smoking behaviour.  AUTHORS' CONCLUSIONS: The current evidence supports a reduction in lung cancer-related mortality with the use of LDCT for lung cancer screening in high-risk populations (those over the age of 40 with a significant smoking exposure). However, there are limited data on harms and further trials are required to determine participant selection and optimal frequency and duration of screening, with potential for significant overdiagnosis of lung cancer. Trials are ongoing for lung cancer screening in non-smokers.

Screening for Lung Cancer With Low-Dose Computed Tomography: Updated Evidence Report and Systematic Review for the US Preventive Services Task Force

IMPORTANCE

Lung cancer is the leading cause of cancer-related death in the US.

OBJECTIVE

To review the evidence on screening for lung cancer with low-dose computed tomography (LDCT) to inform the US Preventive Services Task Force (USPSTF).

DATA SOURCES

MEDLINE, Cochrane Library, and trial registries through May 2019; references; experts; and literature surveillance through November 20, 2020.

STUDY SELECTION

English-language studies of screening with LDCT, accuracy of LDCT, risk prediction models, or treatment for early-stage lung cancer.

DATA EXTRACTION AND SYNTHESIS

Dual review of abstracts, full-text articles, and study quality; qualitative synthesis of findings. Data were not pooled because of heterogeneity of populations and screening protocols.

MAIN OUTCOMES AND MEASURES

Lung cancer incidence, lung cancer mortality, all-cause mortality, test accuracy, and harms.

RESULTS

This review included 223 publications. Seven randomized clinical trials (RCTs) (N = 86 486) evaluated lung cancer screening with LDCT; the National Lung Screening Trial (NLST, N = 53 454) and Nederlands-Leuvens Longkanker Screenings Onderzoek (NELSON, N = 15 792) were the largest RCTs. Participants were more likely to benefit than the US screening-eligible population (eg, based on life expectancy). The NLST found a reduction in lung cancer mortality (incidence rate ratio [IRR], 0.85 [95% CI, 0.75-0.96]; number needed to screen [NNS] to prevent 1 lung cancer death, 323 over 6.5 years of follow-up) with 3 rounds of annual LDCT screening compared with chest radiograph for high-risk current and former smokers aged 55 to 74 years. NELSON found a reduction in lung cancer mortality (IRR, 0.75 [95% CI, 0.61-0.90]; NNS to prevent 1 lung cancer death of 130 over 10 years of follow-up) with 4 rounds of LDCT screening with increasing intervals compared with no screening for high-risk current and former smokers aged 50 to 74 years. Harms of screening included radiation-induced cancer, false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, and increases in distress. For every 1000 persons screened in the NLST, false-positive results led to 17 invasive procedures (number needed to harm, 59) and fewer than 1 person having a major complication. Overdiagnosis estimates varied greatly (0%-67% chance that a lung cancer was overdiagnosed). Incidental findings were common, and estimates varied widely (4.4%-40.7% of persons screened).

CONCLUSIONS AND RELEVANCE

Screening high-risk persons with LDCT can reduce lung cancer mortality but also causes false-positive results leading to unnecessary tests and invasive procedures, overdiagnosis, incidental findings, increases in distress, and, rarely, radiation-induced cancers. Most studies reviewed did not use current nodule evaluation protocols, which might reduce false-positive results and invasive procedures for false-positive results.

False-Negative Results in Lung Cancer Screening-Evidence and Controversies

Identifying false-negative cases is an important quality metric in lung cancer screening, but it has been infrequently and variably reported in previous studies. Although as a proportion of all screening participants, false-negative cases are uncommon, such cases may constitute a substantial proportion of all lung cancers diagnosed (up to 15%) within a screening program. This article reviews the impact and causes of false-negative lung cancer screening tests, including those related to radiologic evaluation, nodule management protocols, and management decisions made by multidisciplinary teams. Following a review of data from international screening studies, this article discusses the controversies within the screening literature surrounding the definition and classification of a false-negative lung cancer screening test and how data on false-negative rates should be captured and recorded. Challenges, such as avoiding overly cautious surveillance of lung nodules while minimizing overdiagnosis and investigation of indolent or benign lesions, are considered. Finally, the advantages and disadvantages of different approaches to dealing with false-negative results in lung cancer screening are discussed.

Incidence Lung Cancer after a Negative CT Screening in the National Lung Screening Trial: Deep Learning-Based Detection of Missed Lung Cancers

We aimed to analyse the CT examinations of the previous screening round (CTprev) in NLST participants with incidence lung cancer and evaluate the value of DL-CAD in detection of missed lung cancers. Thoracic radiologists reviewed CTprev in participants with incidence lung cancer, and a DL-CAD analysed CTprev according to NLST criteria and the lung CT screening reporting & data system (Lung-RADS) classification. We calculated patient-wise and lesion-wise sensitivities of the DL-CAD in detection of missed lung cancers. As per the NLST criteria, 88% (100/113) of CTprev were positive and 74 of them had missed lung cancers. The DL-CAD reported 98% (98/100) of the positive screens as positive and detected 95% (70/74) of the missed lung cancers. As per the Lung-RADS classification, 82% (93/113) of CTprev were positive and 60 of them had missed lung cancers. The DL-CAD reported 97% (90/93) of the positive screens as positive and detected 98% (59/60) of the missed lung cancers. The DL-CAD made false positive calls in 10.3% (27/263) of controls, with 0.16 false positive nodules per scan (41/263). In conclusion, the majority of CTprev in participants with incidence lung cancers had missed lung cancers, and the DL-CAD detected them with high sensitivity and a limited false positive rate.

Recent developments in advanced diagnostic bronchoscopy

The field of bronchoscopy is advancing rapidly. Minimally invasive diagnostic approaches are replacing more aggressive surgical ones for the diagnosis and staging of lung cancer. Evolving diagnostic modalities allow early detection and serve as an adjunct to early treatment, ideally influencing patient outcomes. In this review, we will elaborate on recent bronchoscopic developments as well as some promising investigational tools and approaches in development. We aim to offer a concise overview of the significant advances in the field of advanced bronchoscopy and to put them into clinical context. We will also address potential complications and current diagnostic challenges associated with sampling central and peripheral lung lesions.

Low-Dose CT Screening for Lung Cancer: Evidence from 2 Decades of Study

Lung cancer remains the overwhelmingly greatest cause of cancer death in the United States, accounting for more annual deaths than breast, prostate, and colon cancer combined. Accumulated evidence since the mid to late 1990s, however, indicates that low-dose CT screening of high-risk patients enables detection of lung cancer at an early stage and can reduce the risk of dying from lung cancer. CT screening is now a recommended clinical service in the United States, subject to guidelines and reimbursement requirements intended to standardize practice and optimize the balance of benefits and risks. In this review, the evidence on the effectiveness of CT screening will be summarized and the current guidelines and standards will be described in the context of knowledge gained from lung cancer screening studies. In addition, an overview of the potential advances that may improve CT screening will be presented, and the need to better understand the performance in clinical practice outside of the research trial setting will be discussed. © RSNA, 2020.

Lung Cancer Screening, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology

Lung cancer is the leading cause of cancer-related mortality in the United States and worldwide. Early detection of lung cancer is an important opportunity for decreasing mortality. Data support using low-dose computed tomography (LDCT) of the chest to screen select patients who are at high risk for lung cancer. Lung screening is covered under the Affordable Care Act for individuals with high-risk factors. The Centers for Medicare & Medicaid Services (CMS) covers annual screening LDCT for appropriate Medicare beneficiaries at high risk for lung cancer if they also receive counseling and participate in shared decision-making before screening. The complete version of the NCCN Guidelines for Lung Cancer Screening provides recommendations for initial and subsequent LDCT screening and provides more detail about LDCT screening. This manuscript focuses on identifying patients at high risk for lung cancer who are candidates for LDCT of the chest and on evaluating initial screening findings.

Radiologist performance in the detection of lung cancer using CT

AIM

To measure the level of radiologists' performance in lung cancer detection, and to explore radiologists' performance in cancer specialised and non-specialised centres.

MATERIALS AND METHODS

Thirty radiologists read 60 chest computed tomography (CT) examinations. Thirty cases had surgically or biopsy-proven lung cancer and 30 were cancer-free cases. The cancer cases were validated by four expert radiologists who located the malignant lung nodules. Reader performance was evaluated by calculating sensitivity, location sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve (AUC). In addition, sensitivity at fixed specificity (0.794) was computed from each reader's estimated ROC curve.

RESULTS

The radiologists had a mean sensitivity of 0.749, sensitivity at fixed specificity of 0.744, location sensitivity of 0.666, specificity of 0.81 and AUC of 0.846. Radiologists in the specialised and non-specialised cancer centres had the following (specialised, non-specialised) pairs of values: sensitivity=(0.80, 0.719); sensitivity for fixed 0.794 specificity=(0.752, 0.740); location sensitivity=(0.712, 0.637); specificity=(0.794, 0.82) and AUC=(0.846, 0.846).

CONCLUSION

The efficacy of radiologists was comparable to other studies. Furthermore, AUC outcomes were similar for specialised and non-specialised cancer centre radiologists, suggesting they have similar discriminatory ability and that the higher sensitivity and lower specificity for specialised-centre radiologists can be attributed to them being less conservative in interpreting case images.

Long-Term Active Surveillance of Screening Detected Subsolid Nodules is a Safe Strategy to Reduce Overtreatment

INTRODUCTION

Lung cancer presenting as subsolid nodule (SSN) can show slow growth, hence treating SSN is controversial. Our aim was to determine the long-term outcome of subjects with unresected SSNs in lung cancer screening.

METHODS

Since 2005, the Multicenter Italian Lung Detection (MILD) screening trial implemented active surveillance for persistent SSN, as opposed to early resection. Presence of SSNs was related to diagnosis of cancer at the site of SSN, elsewhere in the lung, or in the body. The risk of overall mortality and lung cancer mortality was tested by Cox proportional hazards model.

RESULTS

SSNs were found in 16.9% (389 of 2303) of screenees. During 9.3 ± 1.2 years of follow-up, the hazard ratio of lung cancer diagnosis in subjects with SSN was 6.77 (95% confidence interval: 3.39-13.54), with 73% (22 of 30) of cancers not arising from SSN (median time to diagnosis 52 months from SSN). Lung cancer-specific mortality in subjects with SSN was significantly increased (hazard ratio = 3.80; 95% confidence interval: 1.24-11.65) compared to subjects without lung nodules. Lung cancer arising from SSN did not lead to death within the follow-up period.

CONCLUSIONS

Subjects with SSN in the MILD cohort showed a high risk of developing lung cancer elsewhere in the lung, with only a minority of cases arising from SSN, and never representing the cause of death. These results show the safety of active surveillance for conservative management of SSN until signs of solid component growth and the need for prolonged follow-up because of high risk of other cancers.

Lung cancer screening: nodule identification and characterization

The accurate identification and characterization of small pulmonary nodules at low-dose CT is an essential requirement for the implementation of effective lung cancer screening. Individual reader detection performance is influenced by nodule characteristics and technical CT parameters but can be improved by training, the application of CT techniques, and by computer-aided techniques. However, the evaluation of nodule detection in lung cancer screening trials differs from the assessment of individual readers as it incorporates multiple readers, their inter-observer variability, reporting thresholds, and reflects the program accuracy in identifying lung cancer. Understanding detection and interpretation errors in screening trials aids in the implementation of lung cancer screening in clinical practice. Indeed, as CT screening moves to ever lower radiation doses, radiologists must be cognisant of new technical challenges in nodule assessment. Screen detected lung cancers demonstrate distinct morphological features from incidentally or symptomatically detected lung cancers. Hence characterization of screen detected nodules requires an awareness of emerging concepts in early lung cancer appearances and their impact on radiological assessment and malignancy prediction models. Ultimately many nodules remain indeterminate, but further imaging evaluation can be appropriate with judicious utilization of contrast enhanced CT or MRI techniques or functional evaluation by PET-CT.

Missed Lung Cancer

The chest radiograph is one of the most commonly used imaging studies and is the modality of choice for initial evaluation of many common clinical scenarios. Over the last two decades, chest computed tomography has been increasingly used for a wide variety of indications, including respiratory illnesses, trauma, oncologic staging, and more recently lung cancer screening. Diagnostic radiologists should be familiar with the common causes of missed lung cancers on imaging studies in order to avoid detection and interpretation errors. Failure to detect these lesions can potentially have serious implications for both patients as well as the interpreting radiologist.