Development and application of an electronic synoptic report for reporting and management of low-dose computed tomography lung cancer screening examination.

BACKGROUND: Interpretation of Low Dose CT scans and protocol driven management of findings is a key aspect of lung cancer screening program performance. Reliable and reproducible methods are needed to communicate radiologists' interpretation to the screening program or clinicians driving management decision. METHODS: We performed an audit of a subset of dictated reports from the PANCAN study to assess for omissions. We developed an electronic synoptic reporting tool for radiologists embedded in a clinical documentation system software. The tool was then used for reporting as part of the Alberta Lung Cancer Screening Study and McGill University Health Centre Pilot Lung Cancer Screening Program. RESULTS: Fifty reports were audited for completeness. At least one omission was noted in 30 (70%) of reports, with a major omission (missing lobe, size, type of nodule in report or actionable incidental finding in recommendation section of report) in 24 (48%). Details of the reporting template and functionality such as automated nodule cancer risk assessment, Lung-RADS category assignment, auto-generated narrative type report as well as personalize participant results letter is provided. A description of the system's performance in its application in 2815 CT reports is then summarized. CONCLUSIONS: We found that narrative type radiologist reports for lung cancer screening CT examinations frequently lacked specific discrete data elements required for management. We demonstrate the successful implementation of a radiology synoptic reporting system for use in lung cancer screening, and the use of this information to drive program management and communications.

USPSTF2013 versus PLCOm2012 lung cancer screening eligibility criteria (International Lung Screening Trial): interim analysis of a prospective cohort study.

BACKGROUND: Lung cancer is a major health problem. CT lung screening can reduce lung cancer mortality through early diagnosis by at least 20%. Screening high-risk individuals is most effective. Retrospective analyses suggest that identifying individuals for screening by accurate prediction models is more efficient than using categorical age-smoking criteria, such as the US Preventive Services Task Force (USPSTF) criteria. This study prospectively compared the effectiveness of the USPSTF2013 and PLCOm2012 model eligibility criteria. METHODS: In this prospective cohort study, participants from the International Lung Screening Trial (ILST), aged 55-80 years, who were current or former smokers (ie, had ≥30 pack-years smoking history or ≤15 quit-years since last permanently quitting), and who met USPSTF2013 criteria or a PLCOm2012 risk threshold of at least 1·51% within 6 years of screening, were recruited from nine screening sites in Canada, Australia, Hong Kong, and the UK. After enrolment, patients were assessed with the USPSTF2013 criteria and the PLCOm2012 risk model with a threshold of at least 1·70% at 6 years. Data were collected locally and centralised. Main outcomes were the comparison of lung cancer detection rates and cumulative life expectancies in patients with lung cancer between USPSTF2013 criteria and the PLCOm2012 model. In this Article, we present data from an interim analysis. To estimate the incidence of lung cancers in individuals who were USPSTF2013-negative and had PLCOm2012 of less than 1·51% at 6 years, ever-smokers in the Prostate Lung Colorectal and Ovarian Cancer Screening Trial (PLCO) who met these criteria and their lung cancer incidence were applied to the ILST sample size for the mean follow-up occurring in the ILST. This trial is registered at ClinicalTrials.gov, NCT02871856. Study enrolment is almost complete. FINDINGS: Between June 17, 2015, and Dec 29, 2020, 5819 participants from the International Lung Screening Trial (ILST) were enrolled on the basis of meeting USPSTF2013 criteria or the PLCOm2012 risk threshold of at least 1·51% at 6 years. The same number of individuals was selected for the PLCOm2012 model as for the USPSTF2013 criteria (4540 [78%] of 5819). After a mean follow-up of 2·3 years (SD 1·0), 135 lung cancers occurred in 4540 USPSTF2013-positive participants and 162 in 4540 participants included in the PLCOm2012 of at least 1·70% at 6 years group (cancer sensitivity difference 15·8%, 95% CI 10·7-22·1%; absolute odds ratio 4·00, 95% CI 1·89-9·44; p<0·0001). Compared to USPSTF2013-positive individuals, PLCOm2012-selected participants were older (mean age 65·7 years [SD 5·9] vs 63·3 years [5·7]; p<0·0001), had more comorbidities (median 2 [IQR 1-3] vs 1 [1-2]; p<0·0001), and shorter life expectancy (13·9 years [95% CI 12·8-14·9] vs 14·8 [13·6-16·0] years). Model-based difference in cumulative life expectancies for those diagnosed with lung cancer were higher in those who had PLCOm2012 risk of at least 1·70% at 6 years than individuals who were USPSTF2013-positive (2248·6 years [95% CI 2089·6-2425·9] vs 2000·7 years [1841·2-2160·3]; difference 247·9 years, p=0·015). INTERPRETATION: PLCOm2012 appears to be more efficient than the USPSTF2013 criteria for selecting individuals to enrol into lung cancer screening programmes and should be used for identifying high-risk individuals who benefit from the inclusion in these programmes. FUNDING: Terry Fox Research Institute, The UBC-VGH Hospital Foundation and the BC Cancer Foundation, the Alberta Cancer Foundation, the Australian National Health and Medical Research Council, Cancer Research UK and a consortium of funders, and the Roy Castle Lung Cancer Foundation for the UK Lung Screen Uptake Trial.

Two-Year Follow-Up of a Randomized Controlled Study of Integrated Smoking Cessation in a Lung Cancer Screening Program.

INTRODUCTION: Smoking cessation activities incorporated into lung cancer screening programs have been broadly recommended, but studies to date have not exhibited increased quit rates associated with cessation programs in this setting. We aimed to determine the long-term effectiveness of smoking cessation counseling in smokers presenting for lung cancer screening. METHODS: This was a randomized control trial of an intensive, telephone-based smoking cessation counseling intervention incorporating lung cancer screening results versus usual care (information pamphlet). This analysis reports on the long-term impact (24-mo) of the intervention on abstinence from smoking. RESULTS: A total of 337 active smokers who participated in the screening study were randomized to active smoking cessation counseling (n = 171) or control arm (n = 174) and completed a 24-month assessment. The 30-day smoking abstinence rates at 24 months postrandomization was 18.3% and 21.4% in the control and intervention arms, respectively-a 3.1% difference (95% confidence interval: -5.4 to 11.6, p = 0.48). No statistically significant differences in the 7-day abstinence, the use of pharmacologic cessation aids, nicotine replacement therapies, nor intent to quit in the following 30 days were noted (p > 0.05). The abstinence rates at 24-months were higher overall than at 12-months (19.9% versus 13.3%, p < 0.001), and smoking intensity was lower than at baseline for ongoing smokers. CONCLUSIONS: A telephone-based smoking cessation counseling intervention incorporating lung cancer screening results did not result in increased long-term cessation rates versus written information alone in unselected smokers undergoing lung cancer screening. Overall, quit rates were high and continued to improve throughout participation in the screening program. (ClinicalTrials.govNCT02431962).

Protein polyglutamylation catalyzed by the bacterial calmodulin-dependent pseudokinase SidJ.

Pseudokinases are considered to be the inactive counterparts of conventional protein kinases and comprise approximately 10% of the human and mouse kinomes. Here, we report the crystal structure of the Legionella pneumophila effector protein, SidJ, in complex with the eukaryotic Ca2+-binding regulator, calmodulin (CaM). The structure reveals that SidJ contains a protein kinase-like fold domain, which retains a majority of the characteristic kinase catalytic motifs. However, SidJ fails to demonstrate kinase activity. Instead, mass spectrometry and in vitro biochemical analyses demonstrate that SidJ modifies another Legionella effector SdeA, an unconventional phosphoribosyl ubiquitin ligase, by adding glutamate molecules to a specific residue of SdeA in a CaM-dependent manner. Furthermore, we show that SidJ-mediated polyglutamylation suppresses the ADP-ribosylation activity. Our work further implies that some pseudokinases may possess ATP-dependent activities other than conventional phosphorylation.

Application of Lung-Screening Reporting and Data System Versus Pan-Canadian Early Detection of Lung Cancer Nodule Risk Calculation in the Alberta Lung Cancer Screening Study.

BACKGROUND: False-positive scans and resultant needless early recalls can increase harms and reduce cost-effectiveness of low-dose CT (LDCT) lung cancer screening. How LDCT scans are interpreted and classified may impact these metrics. METHODS: The Pan-Canadian Early Detection of Lung Cancer risk calculator was used to determine nodule risk of malignancy on baseline screening LDCTs in the Alberta Lung Cancer Screening Study, which were then classified according to Nodule Risk Classification (NRC) categories and ACR Lung Screening Reporting and Data System (Lung-RADS). Test performance characteristics and early recall rates were compared for each approach. RESULTS: In all, 775 baseline screens were analyzed. After a mean of 763 days (±203) of follow-up, lung cancer was detected in 22 participants (2.8%). No statistically significant differences in sensitivity, specificity, or area under the receiver operator characteristic curve occurred between the NRC and Lung-RADS nodule management approaches. Early recall rates were 9.2% and 9.3% for NRC and Lung-RADS, with the NRC unnecessarily recalling some ground glass nodules, and the Lung-RADS recalling many smaller solid nodules with low risk of malignancy. CONCLUSION: Performances of both the NRC and Lung-RADS in this cohort were very good with a trend to higher sensitivity for the NRC. Early recall rates were less than 10% with each approach, significantly lower than rates using the National Lung Screening Trial cutoffs. Further reductions in early recall rates without compromising sensitivity could be achieved by increasing the NRC threshold to 20% for ground glass nodules or by applying the nodule risk calculator with a 5% threshold to 6- to 10-mm solid nodules under Lung-RADS.

A Randomized Controlled Study of Integrated Smoking Cessation in a Lung Cancer Screening Program.

INTRODUCTION: Smoking cessation activities incorporated into lung cancer screening programs have been broadly recommended, but studies to date have not shown increased quit rates associated with cessation programs in this setting. We aimed to determine the effectiveness of smoking cessation counseling in smokers presenting for lung cancer screening. METHODS: This study is a randomized control trial of an intensive telephone-based smoking cessation counseling intervention incorporating lung cancer screening results versus usual care (information pamphlet). All active smokers enrolled in the Alberta Lung Cancer Screening Study cohort were randomized on a 1:1 ratio with a primary endpoint of self-reported 30-day abstinence at 12 months. RESULTS: A total of 345 active smokers participating in the screening study were randomized to active smoking cessation counseling (n = 171) or control arm (n = 174). Thirty-day smoking abstinence at 12 months post-randomization was noted in 22 of 174 (12.6%) and 24 of 171 (14.0%) of participants in the control and intervention arms, respectively, a 1.4% difference (95% confidence interval: -5.9 to 8.7, p = 0.7). No statistically significant differences in 7-day or point abstinence were noted, nor were differences at 6 months or 24 months. CONCLUSIONS: A telephone-based smoking cessation counseling intervention incorporating lung cancer screening results did not result in increased 12-month cessation rates versus written information alone in unselected smokers undergoing lung cancer screening. Routine referral of all current smokers to counseling-based cessation programs may not improve long-term cessation in this patient cohort. Future studies should specifically focus on this subgroup of older long-term smokers to determine the optimal method of integrating smoking cessation with lung cancer screening (clinicaltrials.govNCT02431962).

Prediction of lung cancer risk at follow-up screening with low-dose CT: a training and validation study of a deep learning method.

Background: Current lung cancer screening guidelines use mean diameter, volume or density of the largest lung nodule in the prior computed tomography (CT) or appearance of new nodule to determine the timing of the next CT. We aimed at developing a more accurate screening protocol by estimating the 3-year lung cancer risk after two screening CTs using deep machine learning (ML) of radiologist CT reading and other universally available clinical information. Methods: A deep machine learning (ML) algorithm was developed from 25,097 participants who had received at least two CT screenings up to two years apart in the National Lung Screening Trial. Double-blinded validation was performed using 2,294 participants from the Pan-Canadian Early Detection of Lung Cancer Study (PanCan). Performance of ML score to inform lung cancer incidence was compared with Lung-RADS and volume doubling time using time-dependent ROC analysis. Exploratory analysis was performed to identify individuals with aggressive cancers and higher mortality rates. Findings: In the PanCan validation cohort, ML showed excellent discrimination with a 1-, 2- and 3-year time-dependent AUC values for cancer diagnosis of 0·968±0·013, 0·946±0·013 and 0·899±0·017. Although high ML score cohort included only 10% of the PanCan sample, it identified 94%, 85%, and 71% of incident and interval lung cancers diagnosed within 1, 2, and 3 years, respectively, after the second screening CT. Furthermore, individuals with high ML score had significantly higher mortality rates (HR=16·07, p<0·001) compared to those with lower risk. Interpretation: ML tool that recognizes patterns in both temporal and spatial changes as well as synergy among changes in nodule and non-nodule features may be used to accurately guide clinical management after the next scheduled repeat screening CT.

Predicting Malignancy Risk of Screen-Detected Lung Nodules-Mean Diameter or Volume.

OBJECTIVE: In lung cancer screening practice low-dose computed tomography, diameter, and volumetric measurement have been used in the management of screen-detected lung nodules. The aim of this study was to compare the performance of nodule malignancy risk prediction tools using diameter or volume and between computer-aided detection (CAD) and radiologist measurements. METHODS: Multivariable logistic regression models were prepared by using data from two multicenter lung cancer screening trials. For model development and validation, baseline low-dose computed tomography scans from the Pan-Canadian Early Detection of Lung Cancer Study and a subset of National Lung Screening Trial (NLST) scans with lung nodules 3 mm or more in mean diameter were analyzed by using the CIRRUS Lung Screening Workstation (Radboud University Medical Center, Nijmegen, the Netherlands). In the NLST sample, nodules with cancer had been matched on the basis of size to nodules without cancer. RESULTS: Both CAD-based mean diameter and volume models showed excellent discrimination and calibration, with similar areas under the receiver operating characteristic curves of 0.947. The two CAD models had predictive performance similar to that of the radiologist-based model. In the NLST validation data, the CAD mean diameter and volume models also demonstrated excellent discrimination: areas under the curve of 0.810 and 0.821, respectively. These performance statistics are similar to those of the Pan-Canadian Early Detection of Lung Cancer Study malignancy probability model with use of these data and radiologist-measured maximum diameter. CONCLUSION: Either CAD-based nodule diameter or volume can be used to assist in predicting a nodule's malignancy risk.

Participant selection for lung cancer screening by risk modelling (the Pan-Canadian Early Detection of Lung Cancer [PanCan] study): a single-arm, prospective study.

BACKGROUND: Results from retrospective studies indicate that selecting individuals for low-dose CT lung cancer screening on the basis of a highly predictive risk model is superior to using criteria similar to those used in the National Lung Screening Trial (NLST; age, pack-year, and smoking quit-time). We designed the Pan-Canadian Early Detection of Lung Cancer (PanCan) study to assess the efficacy of a risk prediction model to select candidates for lung cancer screening, with the aim of determining whether this approach could better detect patients with early, potentially curable, lung cancer. METHODS: We did this single-arm, prospective study in eight centres across Canada. We recruited participants aged 50-75 years, who had smoked at some point in their life (ever-smokers), and who did not have a self-reported history of lung cancer. Participants had at least a 2% 6-year risk of lung cancer as estimated by the PanCan model, a precursor to the validated PLCOm2012 model. Risk variables in the model were age, smoking duration, pack-years, family history of lung cancer, education level, body-mass index, chest x-ray in the past 3 years, and history of chronic obstructive pulmonary disease. Individuals were screened with low-dose CT at baseline (T0), and at 1 (T1) and 4 (T4) years post-baseline. The primary outcome of the study was incidence of lung cancer. This study is registered with ClinicalTrials.gov, number NCT00751660. FINDINGS: 7059 queries came into the study coordinating centre and were screened for PanCan risk. 15 were duplicates, so 7044 participants were considered for enrolment. Between Sept 24, 2008, and Dec 17, 2010, we recruited and enrolled 2537 eligible ever-smokers. After a median follow-up of 5·5 years (IQR 3·2-6·1), 172 lung cancers were diagnosed in 164 individuals (cumulative incidence 0·065 [95% CI 0·055-0·075], incidence rate 138·1 per 10 000 person-years [117·8-160·9]). There were ten interval lung cancers (6% of lung cancers and 6% of individuals with cancer): one diagnosed between T0 and T1, and nine between T1 and T4. Cumulative incidence was significantly higher than that observed in NLST (4·0%; p<0·0001). Compared with 593 (57%) of 1040 lung cancers observed in NLST, 133 (77%) of 172 lung cancers in the PanCan Study were early stage (I or II; p<0·0001). INTERPRETATION: The PanCan model was effective in identifying individuals who were subsequently diagnosed with early, potentially curable, lung cancer. The incidence of cancers detected and the proportion of early stage cancers in the screened population was higher than observed in previous studies. This approach should be considered for adoption in lung cancer screening programmes. FUNDING: Terry Fox Research Institute and Canadian Partnership Against Cancer.

Tobacco use and motivation to stop smoking among long-term smokers who are ineligible for lung cancer screening.

BACKGROUND: The importance of smoking cessation interventions in lung cancer screening participants has been highlighted. This study aimed to describe the smoking habits of individuals who were ineligible for lung cancer screening and to investigate whether this encounter may represent an opportunity to reduce tobacco use. METHODS: Ever smokers between the ages of 55 and 80 and ≥1.5% lung cancer risk over 6 years or having smoked ≥30 pack-years and with no more than 15 years of smoking abstinence were eligible to participate in the Alberta Lung Cancer Screening Program (ALCSP). A baseline questionnaire exploring tobacco use was administered to all interested individuals as part of the eligibility determination for the program. RESULTS: Among 504 individuals, 254 (50.4%) met the criteria for the ALCSP and 250 (49.6%) were non-eligible for screening. Non-eligible individuals were slightly younger (mean=60.2 vs. 63.1 years, p-value <0.001), and less likely to be current smokers (26.0% vs. 48.8%, p-value <0.001). Non-eligible smokers had a lower degree of addiction compared to eligible group, as measured by the Fagerström Test of Nicotine Dependence (Median=4.0 vs 6.0, p-value=0.001), but still in the "moderately dependent" range for this test. There were no significant differences in motivation to quit (98.5% vs. 97.6%, p-value=0.689), or motivation to receive help with their quit attempt (89.2% vs. 90.3%, p-value=0.813) between these two groups. Only 7.7% of non-eligible and 2.4% of eligible current smokers were currently in a smoking cessation program. CONCLUSION: A significant proportion of individuals applying to, but not qualifying for a lung cancer screening program are active smokers with significant nicotine dependence. Very few are currently participating in active smoking cessation programs but almost all are interested in quitting and in receiving help with quit attempts. Future studies need to investigate the most effective approaches for smoking cessation in this substantial group of older, long-term smokers, capitalizing on their motivation to receive cessation assistance.