Efficacy of Risk Prediction Models and Thresholds to Select Patients for Lung Cancer Screening.

PurposeScreening for lung cancer is recommended to reduce lung cancer mortality, but there is no consensus on patient selection for screening in Canada. Risk prediction models are more efficacious than the screening recommendations of the Canadian Task Force on Preventive Health Care (CTFPHC), but it remains to be determined which model and threshold are optimal. MethodsWe retrospectively applied the PLCOm2012, PLCOall2014 and LLPv2 risk prediction models to 120 lung cancer patients from a Canadian province, at risk thresholds of ≥ 1.51% and ≥ 2.00%, to determine screening eligibility at time of diagnosis. OncoSim modelling was used to compare these risk thresholds. ResultsSensitivities of the risk prediction models at a threshold of ≥ 1.51% were similar with 93 (77.5%), 96 (80.0%), and 97 (80.8%) patients selected for screening, respectively. The PLCOm2012 and PLCOall2014 models selected significantly more patients for screening at a ≥ 1.51% threshold. The OncoSim simulation model estimated that the ≥ 1.51% threshold would detect 4 more cancers per 100 000 people than the ≥ 2.00% threshold. All risk prediction models, at both thresholds, achieved greater sensitivity than CTFPHC recommendations, which selected 56 (46.7%) patients for screening. ConclusionCommonly considered lung cancer screening risk thresholds (≥1.51% and ≥2.00%) are more sensitive than the CTFPHC 30-pack-years criterion to detect lung cancer. A lower risk threshold would achieve a larger population impact of lung cancer screening but would require more resources. Patients with limited or no smoking history, young patients, and patients with no history of COPD may be missed regardless of the model chosen.

An Audit of Opportunistic Lung Cancer Screening in a Canadian Province.

OBJECTIVES: Lung cancer is a leading cause of cancer-related death in Canada. Early detection can improve outcomes and despite recommendations from the Canadian Task Force on Preventive Health Care to screen patients who are 55 to 74 years old and have a 30+ pack-year history, formal screening programs are rare in Canada. Our goal was to determine if screening is being performed in a representative Canadian population, if recommendations are being followed, and how screening impacts lung cancer stage at diagnosis and prognosis. METHODS: A retrospective chart review was performed to identify patients either screened for lung cancer or imaged due to lung cancer symptoms in Eastern Newfoundland between 2015 and 2018. Age, smoking history, screening modality, diagnosis, cancer stage, and mortality were recorded. RESULTS: Under 6.0% of the eligible population were screened for lung cancer with only 28.13% meeting age and smoking criteria and being screened appropriately with low-dose CT. However, 70% of patients that had lung cancers found by screening met age and smoking screening criteria. While lung cancer detection rates were similar, screening detected cancer in patients at an earlier stage (50% Stage 1) compared to patients who were not screened (20% Stage 1). Patients who were screened had an improved prognosis. CONCLUSIONS: Physicians are opportunistically screening for lung cancer, but not consistently following screening guidelines. As screening is sensitive, leads to earlier stage diagnosis, and has a mortality benefit, implementation of an organized screening program could increase quality assurance and prevent many lung-cancer related deaths.

Risk Perception Among a Lung Cancer Screening Population.

BACKGROUND: A successful lung cancer screening program requires a patient cohort at sufficient risk of developing cancer who are willing to participate. Among other factors, a patient's lung cancer risk perception may inform their attitudes toward screening and smoking cessation programs. RESEARCH QUESTION: This study analyzed data from the Pan-Canadian Early Detection of Lung Cancer (PanCan) Study to address the following questions: Which factors are associated with the perception of lung cancer risk? Is there an association between risk perception for lung cancer and actual calculated risk? Is there an association between risk perception for lung cancer and the intent to quit smoking? Are there potential targets for lung cancer screening awareness? STUDY DESIGN AND METHODS: The PanCan study recruited current or former smokers aged 50 to 75 years who had at least a 2% risk of developing lung cancer over 6 years to undergo low-dose screening CT. Risk perception and worry about lung cancer were captured on a baseline questionnaire. Cumulative logistic regression analysis was used to assess the relationship between baseline risk variables and both lung cancer risk perception and worry. RESULTS: Among the 2,514 individuals analyzed, a higher perceived risk of lung cancer was positively associated with calculated risk (P = .032). Younger age, being a former smoker, respiratory symptoms, lower FEV1, COPD, and a family history of lung cancer were associated with higher perceived risk. Conversely, a consistent relationship between calculated risk and worry was not identified. There was a positive association between risk perception and lung cancer worry and reported intent to quit smoking. INTERPRETATION: Individuals' lung cancer risk perception correlated positively with calculated risk in a screening population. Promotion of screening programs may benefit from focusing on factors associated with higher risk perception; conversely, harnessing worry seemingly holds less value.

Chronic obstructive pulmonary disease prevalence and prediction in a high-risk lung cancer screening population.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is an underdiagnosed condition sharing risk factors with lung cancer. Lung cancer screening may provide an opportunity to improve COPD diagnosis. Using Pan-Canadian Early Detection of Lung Cancer (PanCan) study data, the present study sought to determine the following: 1) What is the prevalence of COPD in a lung cancer screening population? 2) Can a model based on clinical and screening low-dose CT scan data predict the likelihood of COPD? METHODS: The single arm PanCan study recruited current or former smokers age 50-75 who had a calculated risk of lung cancer of at least 2% over 6 years. A baseline health questionnaire, spirometry, and low-dose CT scan were performed. CT scans were assessed by a radiologist for extent and distribution of emphysema. With spirometry as the gold standard, logistic regression was used to assess factors associated with COPD. RESULTS: Among 2514 recruited subjects, 1136 (45.2%) met spirometry criteria for COPD, including 833 of 1987 (41.9%) of those with no prior diagnosis, 53.8% of whom had moderate or worse disease. In a multivariate model, age, current smoking status, number of pack-years, presence of dyspnea, wheeze, participation in a high-risk occupation, and emphysema extent on LDCT were all statistically associated with COPD, while the overall model had poor discrimination (c-statistic = 0.627 (95% CI of 0.607 to 0.650). The lowest and the highest risk decile in the model predicted COPD risk of 27.4 and 65.3%. CONCLUSIONS: COPD had a high prevalence in a lung cancer screening population. While a risk model had poor discrimination, all deciles of risk had a high prevalence of COPD, and spirometry could be considered as an additional test in lung cancer screening programs. TRIAL REGISTRATION: (Clinical Trial Registration: ClinicalTrials.gov, number NCT00751660 , registered September 12, 2008).

Trial marketing in the Pan-Canadian Early Detection of Lung Cancer Study.

BACKGROUND: Recruitment to clinical trials is suboptimal, increasing costs, and delaying the potential implementation of clinical advances. Among other barriers, the lack of marketing experience among trialists may limit recruitment. In this observational study, in the context of the Pan-Canadian Early Detection of Lung Cancer Trial, we assessed the value of a motivational survey of study participants in planning a tailored advertising campaign and analysed the value of individual components of advertising in generating telephone calls to the study and recruited subjects. METHODS: The Pan-Canadian Early Detection of Lung Cancer Trial was a single arm study assessing risk modelling for lung cancer screening by low-dose computed tomography scan and autofluorescence bronchoscopy. Individuals were recruited to eight sites across Canada without a central marketing plan. On contact with the study, individuals reported how they heard about the study according to a predefined list. One site, the Juravinski Cancer Centre, worked with a marketing expert to develop a survey to assess participant motivations, source of study awareness, and personal habits. The survey was used to develop a media campaign for recruitment. Media events were collected from all sites. The primary analysis assessed the number of telephone contacts and recruited subjects associated with various media factors. Individual print media characteristics were assessed for their effect on recruitment. RESULTS: At all sites, 7059 individuals contacted the study, and 2537 were eligible and recruited. Among 52 individuals completing the Juravinski Cancer Centre survey, motivation included concern for personal risk of lung cancer (71%), followed by desire to contribute to a cure (67%), followed by personal knowledge of a person with lung cancer (50%). Most reported hearing of the study from the newspaper (58%) despite no print ad yet being distributed. With survey input, a newsprint campaign was executed. The number of media events varied by site (median: 13, range: 3-28). Among all recruits, 56.4% reported referral by newspaper followed by family/friend (14%). Telephone contacts and recruited subjects per event varied significantly by site, while unpaid media events appeared superior to paid events. Print media characteristics associated with increased telephone contacts and recruitment included use of a rational appeal (vs a mixed rational-emotional), less use of white space, and larger headline font. CONCLUSION: A survey of trial candidates provides useful information regarding personal motivation, media use, and lifestyle. Unpaid media events appear superior in generating recruitment, while print media may be superior to radio and television in selecting eligible recruits. The utility of individual print media characteristics appears to differ from the commercial advertising literature. Further research on marketing in clinical trials is encouraged to improve recruitment ( ClinicalTrials.gov registration: NCT00751660, https://clinicaltrials.gov/ct2/show/NCT00751660 ).

Health-related quality of life and anxiety in the PAN-CAN lung cancer screening cohort.

OBJECTIVES: The impact of lung cancer screening with low-dose chest CT (LDCT) on participants' anxiety levels and health-related quality of life (HRQoL) is an important consideration in the implementation of such programmes. We aimed to describe changes in anxiety and HRQoL in a high-risk Canadian cohort undergoing LDCT lung cancer screening. METHODS: 2537 subjects who had 2% or greater lung cancer risk over 6 years using a risk prediction tool were recruited from eight centres across Canada in the Pan-Canadian Early Detection of Lung Cancer Study (2008-2010). We compared HRQoL and anxiety levels before and after screening of 1237 participants with LDCT (excluding a subset of 1300 participants who also underwent autofluorescence bronchoscopy screening), as well as after investigations performed because of a positive screening examination. The 12-item short-form Physical and Mental Component Scales (SF-12), EQ-5D-3L scores and State Trait Anxiety Inventory-State anxiety were used at each assessment. RESULTS: Overall, there were no clinically significant differences in HRQoL outcomes between baseline and each of the survey time points following initial screening. No mean change in anxiety in the overall cohort was noted following baseline LDCT, but more participants had clinically significant increase in anxiety versus decrease after baseline screening (increase >minimal clinically important difference (MCID) (n=180) vs decrease >MCID (n=50), p<0.001). This finding persisted but to a lesser degree at the 12 month time point (increase >MCID (n=146) vs decrease >MCID (n=87), p<0.001). CONCLUSIONS: CT screening for lung cancer has no major overall impact on HRQoL among participants, although a minority of participants (number-needed-to-harm=7 after baseline screening and 18 at 1 year) demonstrated clinically significant increased anxiety levels. TRIALREGISTRATION NUMBER: NCT00751660; Results.

Top 100 Cited articles on Radiation Exposure in Medical Imaging: A Bibliometric Analysis.

BACKGROUND: Bibliometric analyses by highest number of citations can help researchers and funding agencies in determining the most influential articles in a field. The main objective of this analysis was to identify the top 100 cited articles addressing radiation exposure from medical imaging and assess their characteristics. METHODS: Relevant articles were extracted from the Scopus database after a systematic search by researchers using an iteratively defined Boolean search string. Subsequently, exclusion criteria were applied. A list of top 100 articles was prepared, and articles were ranked according to the citations they had received. No time restriction was applied. Descriptive statistics of the data were compiled. RESULTS: The top-cited articles were published from 1970-2013, with the most articles published in 2009 and 2010 (12 articles in each year). The citations ranged from 107-1888 with a median of 272. Manuscripts from our top-cited list originated from 20 different countries, with contributions made by 158 authors and 160 organizations. Eighty-eight percent of studies evaluated patient-related radiation exposure, 7% health care workers, and 5% both or were not specified. Thirty-two percent of studies examined adult populations, 14% pediatric, and 54% included both populations or did not specify. Seventy-two percent of studies were dedicated to Computed Tomography, 8% to radiography/fluoroscopy, 9% to interventional procedures, 4% to nuclear medicine, and 7% to a combination of 2 or more modalities. CONCLUSION: The top 100 cited articles in medical imaging related to radiation exposure are diverse, originating from many countries with numerous contributing authors. The most common topics covered involve CT and adult patients. The recent peak in the most-highly cited articles (2010) suggests that increased attention has been devoted to this field in recent years. Based on these results, it would appear that research on radiation exposure in medical imaging is poised to continue expanding.

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.

Reducing Wait Time for Lung Cancer Diagnosis and Treatment: Impact of a Multidisciplinary, Centralized Referral Program.

BACKGROUND: A multidisciplinary, centralized referral program was established at our institution in 2014 to reduce delays in lung cancer diagnosis and treatment following diagnostic imaging observed with the traditional, primary care provider-led referral process. The main objectives of this retrospective cohort study were to determine if referral to a Thoracic Triage Panel (TTP): 1) expedites lung cancer diagnosis and treatment initiation; and 2) leads to more appropriate specialist consultation. METHODS: Patients with a diagnosis of lung cancer and initial diagnostic imaging between March 1, 2015, and February 29, 2016, at a Memorial University-affiliated tertiary care centre in St John's, Newfoundland, were identified and grouped according to whether they were referred to the TTP or managed through a traditional referral process. Wait times (in days) from first abnormal imaging to biopsy and treatment initiation were recorded. Statistical analysis was performed using the Wilcoxon rank-sum test. RESULTS: A total of 133 patients who met inclusion criteria were identified. Seventy-nine patients were referred to the TTP and 54 were managed by traditional means. There was a statistically significant reduction in median wait times for patients referred to the TTP. Wait time from first abnormal imaging to biopsy decreased from 61.5 to 36.0 days (P < .0001). Wait time from first abnormal imaging to treatment initiation decreased from 118.0 to 80.0 days (P < .001). The percentage of specialist consultations that led to treatment was also greater for patients referred to the TTP. CONCLUSIONS: A collaborative, centralized intake and referral program helps to reduce wait time for diagnosis and treatment of lung cancer.

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.

The Cost-Effectiveness of High-Risk Lung Cancer Screening and Drivers of Program Efficiency.

INTRODUCTION: Lung cancer risk prediction models have the potential to make programs more affordable; however, the economic evidence is limited. METHODS: Participants in the National Lung Cancer Screening Trial (NLST) were retrospectively identified with the risk prediction tool developed from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. The high-risk subgroup was assessed for lung cancer incidence and demographic characteristics compared with those in the low-risk subgroup and the Pan-Canadian Early Detection of Lung Cancer Study (PanCan), which is an observational study that was high-risk-selected in Canada. A comparison of high-risk screening versus standard care was made with a decision-analytic model using data from the NLST with Canadian cost data from screening and treatment in the PanCan study. Probabilistic and deterministic sensitivity analyses were undertaken to assess uncertainty and identify drivers of program efficiency. RESULTS: Use of the risk prediction tool developed from the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial with a threshold set at 2% over 6 years would have reduced the number of individuals who needed to be screened in the NLST by 81%. High-risk screening participants in the NLST had more adverse demographic characteristics than their counterparts in the PanCan study. High-risk screening would cost $20,724 (in 2015 Canadian dollars) per quality-adjusted life-year gained and would be considered cost-effective at a willingness-to-pay threshold of $100,000 in Canadian dollars per quality-adjusted life-year gained with a probability of 0.62. Cost-effectiveness was driven primarily by non-lung cancer outcomes. Higher noncurative drug costs or current costs for immunotherapy and targeted therapies in the United States would render lung cancer screening a cost-saving intervention. CONCLUSIONS: Non-lung cancer outcomes drive screening efficiency in diverse, tobacco-exposed populations. Use of risk selection can reduce the budget impact, and screening may even offer cost savings if noncurative treatment costs continue to rise.

Computer Vision Tool and Technician as First Reader of Lung Cancer Screening CT Scans.

OBJECTIVES: To implement a cost-effective low-dose computed tomography (LDCT) lung cancer screening program at the population level, accurate and efficient interpretation of a large volume of LDCT scans is needed. The objective of this study was to evaluate a workflow strategy to identify abnormal LDCT scans in which a technician assisted by computer vision (CV) software acts as a first reader with the aim to improve speed, consistency, and quality of scan interpretation. METHODS: Without knowledge of the diagnosis, a technician reviewed 828 randomly batched scans (136 with lung cancers, 556 with benign nodules, and 136 without nodules) from the baseline Pan-Canadian Early Detection of Lung Cancer Study that had been annotated by the CV software CIRRUS Lung Screening (Diagnostic Image Analysis Group, Nijmegen, The Netherlands). The scans were classified as either normal (no nodules ≥1 mm or benign nodules) or abnormal (nodules or other abnormality). The results were compared with the diagnostic interpretation by Pan-Canadian Early Detection of Lung Cancer Study radiologists. RESULTS: The overall sensitivity and specificity of the technician in identifying an abnormal scan were 97.8% (95% confidence interval: 96.4-98.8) and 98.0% (95% confidence interval: 89.5-99.7), respectively. Of the 112 prevalent nodules that were found to be malignant in follow-up, 92.9% were correctly identified by the technician plus CV compared with 84.8% by the study radiologists. The average time taken by the technician to review a scan after CV processing was 208 ± 120 seconds. CONCLUSIONS: Prescreening CV software and a technician as first reader is a promising strategy for improving the consistency and quality of screening interpretation of LDCT scans.

Plasma pro-surfactant protein B and lung function decline in smokers.

Plasma pro-surfactant protein B (pro-SFTPB) levels have recently been shown to predict the development of lung cancer in current and ex-smokers, but the ability of pro-SFTPB to predict measures of chronic obstructive pulmonary disease (COPD) severity is unknown. We evaluated the performance characteristics of pro-SFTPB as a biomarker of lung function decline in a population of current and ex-smokers. Plasma pro-SFTPB levels were measured in 2503 current and ex-smokers enrolled in the Pan-Canadian Early Detection of Lung Cancer Study. Linear regression was performed to determine the relationship of pro-SFTPB levels to changes in forced expiratory volume in 1 s (FEV1) over a 2-year period as well as to baseline FEV1 and the burden of emphysema observed in computed tomography (CT) scans. Plasma pro-SFTPB levels were inversely related to both FEV1 % predicted (p=0.024) and FEV1/forced vital capacity (FVC) (p<0.001), and were positively related to the burden of emphysema on CT scans (p<0.001). Higher plasma pro-SFTPB levels were also associated with a more rapid decline in FEV1 at 1 year (p=0.024) and over 2 years of follow-up (p=0.004). Higher plasma pro-SFTPB levels are associated with increased severity of airflow limitation and accelerated decline in lung function. Pro-SFTPB is a promising biomarker for COPD severity and progression.

The impact of diagnostic imaging wait times on the prognosis of lung cancer.

OBJECTIVE: This study was performed to determine whether gaps in patient flow from initial lung imaging to computed tomography (CT) guided lung biopsy in patients with non-small cell lung cancer (NSCLC) was associated with a change in tumour size, stage, and thus prognosis. METHODS: All patients who had a CT-guided lung biopsy in 2009 (phase I) and in 2011 (phase II) with a pathologic diagnosis of primary lung cancer (NSCLC) at Eastern Health, Newfoundland, were identified. Dates of initial abnormal imaging, confirmatory CT (if performed), and CT-guided biopsy were recorded, along with tumour size and resulting T stage at each time point. In 2010, wait times for diagnostic imaging at Eastern Health were reduced. The stage and prognosis of NSCLC in 2009 was compared with 2011. RESULTS: In phase 1, there was a statistically significant increase in tumour size (mean difference, 0.67 cm; P < .0001) and stage (P < .0001) from initial image to biopsy. There was a moderate correlation between the time (in days) between the images and change in size (r = 0.33, P = .008) or stage (r = 0.26, P = .036). In phase II, the median wait time from initial imaging to confirmatory CT was reduced to 7.5 days (from 19 days). At this reduced wait time, there was no statistically significant increase in tumour size (mean difference, 0.02; P > .05) or stage (P > .05) from initial imaging to confirmatory CT. CONCLUSIONS: Delays in patient flow through diagnostic imaging resulted in an increase in tumour size and stage, with a negative impact on prognosis of NSCLC. This information contributed to the hiring of additional CT technologists and extended CT hours to decrease the wait time for diagnostic imaging. With reduced wait times, the prognosis of NSCLC was not adversely impacted as patients navigated through diagnostic imaging.

Resource utilization and costs during the initial years of lung cancer screening with computed tomography in Canada.

BACKGROUND: It is estimated that millions of North Americans would qualify for lung cancer screening and that billions of dollars of national health expenditures would be required to support population-based computed tomography lung cancer screening programs. The decision to implement such programs should be informed by data on resource utilization and costs. METHODS: Resource utilization data were collected prospectively from 2059 participants in the Pan-Canadian Early Detection of Lung Cancer Study using low-dose computed tomography (LDCT). Participants who had 2% or greater lung cancer risk over 3 years using a risk prediction tool were recruited from seven major cities across Canada. A cost analysis was conducted from the Canadian public payer's perspective for resources that were used for the screening and treatment of lung cancer in the initial years of the study. RESULTS: The average per-person cost for screening individuals with LDCT was $453 (95% confidence interval [CI], $400-$505) for the initial 18-months of screening following a baseline scan. The screening costs were highly dependent on the detected lung nodule size, presence of cancer, screening intervention, and the screening center. The mean per-person cost of treating lung cancer with curative surgery was $33,344 (95% CI, $31,553-$34,935) over 2 years. This was lower than the cost of treating advanced-stage lung cancer with chemotherapy, radiotherapy, or supportive care alone, ($47,792; 95% CI, $43,254-$52,200; p = 0.061). CONCLUSION: In the Pan-Canadian study, the average cost to screen individuals with a high risk for developing lung cancer using LDCT and the average initial cost of curative intent treatment were lower than the average per-person cost of treating advanced stage lung cancer which infrequently results in a cure.

Probability of cancer in pulmonary nodules detected on first screening CT.

BACKGROUND: Major issues in the implementation of screening for lung cancer by means of low-dose computed tomography (CT) are the definition of a positive result and the management of lung nodules detected on the scans. We conducted a population-based prospective study to determine factors predicting the probability that lung nodules detected on the first screening low-dose CT scans are malignant or will be found to be malignant on follow-up. METHODS: We analyzed data from two cohorts of participants undergoing low-dose CT screening. The development data set included participants in the Pan-Canadian Early Detection of Lung Cancer Study (PanCan). The validation data set included participants involved in chemoprevention trials at the British Columbia Cancer Agency (BCCA), sponsored by the U.S. National Cancer Institute. The final outcomes of all nodules of any size that were detected on baseline low-dose CT scans were tracked. Parsimonious and fuller multivariable logistic-regression models were prepared to estimate the probability of lung cancer. RESULTS: In the PanCan data set, 1871 persons had 7008 nodules, of which 102 were malignant, and in the BCCA data set, 1090 persons had 5021 nodules, of which 42 were malignant. Among persons with nodules, the rates of cancer in the two data sets were 5.5% and 3.7%, respectively. Predictors of cancer in the model included older age, female sex, family history of lung cancer, emphysema, larger nodule size, location of the nodule in the upper lobe, part-solid nodule type, lower nodule count, and spiculation. Our final parsimonious and full models showed excellent discrimination and calibration, with areas under the receiver-operating-characteristic curve of more than 0.90, even for nodules that were 10 mm or smaller in the validation set. CONCLUSIONS: Predictive tools based on patient and nodule characteristics can be used to accurately estimate the probability that lung nodules detected on baseline screening low-dose CT scans are malignant. (Funded by the Terry Fox Research Institute and others; ClinicalTrials.gov number, NCT00751660.).

A Newfoundland cohort of familial and sporadic idiopathic pulmonary fibrosis patients: clinical and genetic features.

BACKGROUND: Idiopathic pulmonary fibrosis (IPF) is an adult-onset Idiopathic Interstitial Pneumonia (IIP) usually diagnosed between age 50 to 70 years. Individuals with Familial Pulmonary Fibrosis (FPF) have at least one affected first or second-degree relative and account for 0.5-20% of cases. METHODS: We ascertained and collected DNA samples from a large population-based cohort of IPF patients from Newfoundland, Canada. For each proband, a family history was documented and medical records were reviewed. Each proband was classified as familial (28 patients) or sporadic (50 patients) and all 78 probands were screened for variants in four highly penetrant, adult-onset PF genes (SFTPC, SFTPA2, TERT,TERC). RESULTS: Seventy-eight IPF probands were enrolled of whom 28 (35.9%) had a positive family history. These 28 familial patients led to the recruitment of an additional 49 affected relatives (total of 77 FPF patients). By age 60 years, 42% of the familial cohort had been diagnosed with PF compared with only 16% of the sporadic patient collection (χ2 = 8.77, p = 0.003). Mean age of diagnosis in the familial group was significantly younger than the sporadic group (61.4 years vs. 66.6 yrs, p = 0.012) with a wider age range of diagnosis (19-92 years compared with 47-82 years). Thirty-three of 77 (42.8%) FPF patients had a tissue diagnosis and all but five had usual interstitial pneumonia histology. Compared with other published case series, the familial IIP histologies were more homogeneous. Three of 28 familial probands (10.7%) and none of the 50 sporadic probands had pathogenic variants in the four genes tested. All three familial probands had mutations in TERT. Other phenotypes associated with telomerase deficiency were present in these families including cirrhosis, bone marrow hypoplasia and premature graying. Telomere length assays were performed on mutation carriers from two families and confirmed telomere-related deficiency. CONCLUSION: The proportion of familial cases in our cohort is higher than any previously reported estimate and we suggest that this is due to the fact that Newfoundland cohort is ethnically homogeneous and drawn from a founder population. In our patient collection, diagnosis with IPF prior to age 45 years predicted familial disease. In two of the three TERT mutation families, the pedigree appearance is consistent with genetic anticipation. In the other 25 FPF families negative for mutations in known PF genes, we did not identify other telomerase associated medical problems (bone marrow dysfunction, cirrhosis) and we hypothesize that there are novel PF genes segregating in our population.