Estimating long-term effectiveness of lung cancer screening in the Mayo CT screening study

A Survey on Artificial Intelligence in Pulmonary Imaging

Over the last decade, deep learning (DL) has contributed a paradigm shift in computer vision and image recognition creating widespread opportunities of using artificial intelligence in research as well as industrial applications. DL has been extensively studied in medical imaging applications, including those related to pulmonary diseases. Chronic obstructive pulmonary disease, asthma, lung cancer, pneumonia, and, more recently, COVID-19 are common lung diseases affecting nearly 7.4% of world population. Pulmonary imaging has been widely investigated toward improving our understanding of disease etiologies and early diagnosis and assessment of disease progression and clinical outcomes. DL has been broadly applied to solve various pulmonary image processing challenges including classification, recognition, registration, and segmentation. This paper presents a survey of pulmonary diseases, roles of imaging in translational and clinical pulmonary research, and applications of different DL architectures and methods in pulmonary imaging with emphasis on DL-based segmentation of major pulmonary anatomies such as lung volumes, lung lobes, pulmonary vessels, and airways as well as thoracic musculoskeletal anatomies related to pulmonary diseases.

Deep Q-networks with web-based survey data for simulating lung cancer intervention prediction and assessment in the elderly: a quantitative study

BACKGROUND

Lung cancer screening and intervention might be important to help detect lung cancer early and reduce the mortality, but little was known about lung cancer intervention strategy associated with intervention effect for preventing lung cancer. We employed Deep Q-Networks (DQN) to respond to this gap. The aim was to quantitatively predict lung cancer optimal intervention strategy and assess intervention effect in aged 65 years and older (the elderly).

METHODS

We screened lung cancer high risk with web-based survey data and conducted simulative intervention. DQN models were developed to predict optimal intervention strategies to prevent lung cancer in elderly men and elderly women separately. We assessed the intervention effects to evaluate the optimal intervention strategy.

RESULTS

Proposed DQN models quantitatively predicted and assessed lung cancer intervention. DQN models performed well in five stratified groups (elderly men, elderly women, men, women and the whole population). Stopping smoking and extending quitting smoking time were optimal intervention strategies in elderly men. Extending quitting time and reducing smoked cigarettes number were optimal intervention strategies in elderly women. In elderly men and women, the maximal reductions of lung cancer incidence were 31.81% and 24.62% separately. Lung cancer incidence trend was deduced from the year of 1984 to 2050, which predicted that the difference of lung cancer incidence between elderly men and women might be significantly decreased after thirty years quitting time.

CONCLUSIONS

We quantitatively predicted optimal intervention strategy and assessed lung cancer intervention effect in the elderly through DQN models. Those might improve intervention effects and reasonably prevent lung cancer.

Biomarkers and Lung Cancer Early Detection: State of the Art

Simple Summary

Lung cancer is the leading cause of cancer death worldwide. Detecting lung malignancies promptly is essential for any anticancer treatment to reduce mortality and morbidity, especially in high-risk individuals. The use of liquid biopsy to detect circulating biomarkers such as RNA, microRNA, DNA, proteins, autoantibodies in the blood, as well as circulating tumor cells (CTCs), can substantially change the way we manage lung cancer patients by improving disease stratification using intrinsic molecular characteristics, identification of therapeutic targets and monitoring molecular residual disease. Here, we made an update on recent developments in liquid biopsy-based biomarkers for lung cancer early diagnosis, and we propose guidelines for an accurate study design, execution, and data interpretation for biomarker development.

Abstract

Lung cancer burden is increasing, with 2 million deaths/year worldwide. Current limitations in early detection impede lung cancer diagnosis when the disease is still localized and thus more curable by surgery or multimodality treatment. Liquid biopsy is emerging as an important tool for lung cancer early detection and for monitoring therapy response. Here, we reviewed recent advances in liquid biopsy for early diagnosis of lung cancer. We summarized DNA- or RNA-based biomarkers, proteins, autoantibodies circulating in the blood, as well as circulating tumor cells (CTCs), and compared the most promising studies in terms of biomarkers prediction performance. While we observed an overall good performance for the proposed biomarkers, we noticed some critical aspects which may complicate the successful translation of these biomarkers into the clinical setting. We, therefore, proposed a roadmap for successful development of lung cancer biomarkers during the discovery, prioritization, and clinical validation phase. The integration of innovative minimally invasive biomarkers in screening programs is highly demanded to augment lung cancer early detection.

A Structured Program Maximizes Benefit of Lung Cancer Screening in an Area of Endemic Histoplasmosis

BACKGROUND

Lung cancer screening with low-dose computed tomography has demonstrated at least a 20% decrease in lung cancer-specific mortality, but has the potential harm of unnecessary invasive procedures due to false positive results. We report the outcomes of a structured multi-disciplinary lung cancer screening program in an area of endemic histoplasmosis.

METHODS

A retrospective review of patients undergoing lung cancer screening from December 2012 to March 2019 was conducted. Findings suspicious for lung cancer were presented at a multidisciplinary thoracic tumor board. Patients were assigned to interval imaging follow-up, additional diagnostic imaging, or referral for an invasive procedure. Invasive procedures were then compared between benign and malignant pathologies.

RESULTS

4087 scans were done on 2129 patients. 372 (9.1%) were suspicious and presented at a multidisciplinary thoracic tumor board. Ultimately 108 procedures were done: 55 bronchoscopies, seven percutaneous biopsies, and 46 operations. 25 patients (1.2%) underwent bronchoscopy resulting in benign pathology, significantly associated with an indication of an endobronchial lesion (p=0.01). All percutaneous biopsies revealed malignancy. Five patients (0.2%) who underwent resection had benign disease. Lung cancer was diagnosed in 67 patients (3.1% of the entire cohort), 46 of which were stage I/II.

CONCLUSIONS

Lung cancer screening in a structured, multidisciplinary program successfully identifies patients with early-stage lung cancer with limited unnecessary surgical interventions. Isolated endobronchial lesions should undergo short interval imaging follow up to avoid bronchoscopy for benign disease. Future studies to minimize unnecessary procedures could incorporate biomarkers and advanced imaging analysis into risk assessment models.

Lung Nodule Detection based on Faster R-CNN Framework

BACKGROUND

Lung cancer is a worldwide high-risk disease, and lung nodules are the main manifestation of early lung cancer. Automatic detection of lung nodules reduces the workload of radiologists, the rate of misdiagnosis and missed diagnosis. For this purpose, we propose a Faster R-CNN algorithm for the detection of these lung nodules.

METHOD

Faster R-CNN algorithm can detect lung nodules, and the training set is used to prove the feasibility of this technique. In theory, parameter optimization can improve network structure, as well as detection accuracy.

RESULT

Through experiments, the best parameters are that the basic learning rate is 0.001, step size is 70,000, attenuation coefficient is 0.1, the value of Dropout is 0.5, and the value of Batch Size is 64. Compared with other networks for detecting lung nodules, the optimized and improved algorithm proposed in this paper generally improves detection accuracy by more than 20% when compared with the other traditional algorithms.

CONCLUSION

Our experimental results have proved that the method of detecting lung nodules based on Faster R-CNN algorithm has good accuracy and therefore, presents potential clinical value in lung disease diagnosis. This method can further assist radiologists, and also for researchers in the design and development of the detection system for lung nodules.

Association of invitation to lung cancer screening and tobacco use outcomes in a VA demonstration project

A potential unintended consequence of lung cancer screening (LCS) is an adverse effect on smoking behaviors. This has been difficult to assess in previous randomized clinical trials. Our goal was to determine whether cessation and relapse behaviors differ between Veterans directly invited (DI) to participate in LCS compared to usual care (UC). We conducted a longitudinal survey of tobacco use outcomes among Veterans (Minneapolis VA) from 2014 to 2015, randomized (2:1) to DI versus UC and stratified by baseline smoking status (current/former). Within the DI group, we explored differences between those who did and did not choose to undergo LCS. A total of 979 patients (n = 660 DI, n = 319 UC) returned the survey at a median of 484 days. Among current smokers (n = 488), smoking abstinence rates and cessation attempts did not differ between DI and UC groups. More baseline smokers in DI were non-daily smokers at follow-up compared to those in UC (25.3% vs 15.6%, OR 1.97 95%CI 1.15–3.36). A significant proportion of former smokers at baseline relapsed, with 17% overall indicating past 30-day smoking. This did not differ between arms. Of those invited to LCS, smoking outcomes did not significantly differ between those who chose to be screened (161/660) versus not. This randomized program evaluation of smoking behaviors in the context of invitation to LCS observed no adverse or beneficial effects on tobacco cessation or relapse among participants invited to LCS, or among those who completed screening. As LCS programs scale and spread nationally, effective cessation programs will be essential.

All-cause mortality versus cancer-specific mortality as outcome in cancer screening trials: A review and modeling study

BACKGROUND

All-cause mortality has been suggested as an end-point in cancer screening trials in order to avoid biases in attributing the cause of death. The aim of this study was to investigate which sample size and follow-up is needed to find a significant reduction in all-cause mortality.

METHODS

A literature review was conducted to identify previous studies that modeled the effect of screening on all-cause mortality. Microsimulation modeling was used to simulate breast cancer, lung cancer, and colorectal cancer screening trials. Model outputs were: cancer-specific deaths, all-cause deaths, and life-years gained per year of follow-up.

RESULTS

There were large differences between the evaluated cancers. For lung cancer, when 40 000 high-risk people are randomized to each arm, a significant reduction in all-cause mortality could be expected between 11 and 13 years of follow-up. For breast cancer, a significant reduction could be found between 16 and 26 years of follow-up for a sample size of over 300 000 women in each arm. For colorectal cancer, 600 000 persons in each arm were required to be followed for 15-20 years. Our systematic literature review identified seven papers, which showed highly similar results to our estimates.

CONCLUSION

Cancer screening trials are able to demonstrate a significant reduction in all-cause mortality due to screening, but require very large sample sizes. Depending on the cancer, 40 000-600 000 participants per arm are needed to demonstrate a significant reduction. The reduction in all-cause mortality can only be detected between specific years of follow-up, more limited than the timeframe to detect a reduction in cancer-specific mortality.

Smoking and Lung Cancer Mortality in the United States From 2015 to 2065: A Comparative Modeling Approach

BACKGROUND

Tobacco control efforts implemented in the United States since the 1960s have led to considerable reductions in smoking and smoking-related diseases, including lung cancer.

OBJECTIVE

To project reductions in tobacco use and lung cancer mortality from 2015 to 2065 due to existing tobacco control efforts.

DESIGN

Comparative modeling approach using 4 simulation models of the natural history of lung cancer that explicitly relate temporal smoking patterns to lung cancer rates.

SETTING

U.S. population, 1964 to 2065.

PARTICIPANTS

Adults aged 30 to 84 years.

MEASUREMENTS

Models were developed using U.S. data on smoking (1964 to 2015) and lung cancer mortality (1969 to 2010). Each model projected lung cancer mortality by smoking status under the assumption that current decreases in smoking would continue into the future (status quo trends). Sensitivity analyses examined optimistic and pessimistic scenarios.

RESULTS

Under the assumption of continued decreases in smoking, age-adjusted lung cancer mortality was projected to decrease by 79% between 2015 and 2065. Concomitantly, and despite the expected growth, aging, and longer life expectancy of the U.S. population, the annual number of lung cancer deaths was projected to decrease from 135 000 to 50 000 (63% reduction). However, 4.4 million deaths from lung cancer are still projected to occur in the United States from 2015 to 2065, with about 20 million adults aged 30 to 84 years continuing to smoke in 2065.

LIMITATION

Projections assumed no changes to tobacco control efforts in the future and did not explicitly consider the potential effect of lung cancer screening.

CONCLUSION

Tobacco control efforts implemented since the 1960s will continue to reduce lung cancer rates well into the next half-century. Additional prevention and cessation efforts will be required to sustain and expand these gains to further reduce the lung cancer burden in the United States.

PRIMARY FUNDING SOURCE

National Cancer Institute.

A Decision Analysis of Follow-up and Treatment Algorithms for Nonsolid Pulmonary Nodules

Purpose To evaluate management strategies and treatment options for patients with ground-glass nodules (GGNs) by using decision-analysis models. Materials and Methods A simulation was developed for 1 000 000 hypothetical patients with GGNs undergoing follow-up per the Lung Imaging Reporting and Data System (Lung-RADS) recommendations. The initial age range was 55-75 years (mean, 64 years). Nodules could grow and develop solid components over time. Clinically significant malignancy rates were calibrated to data from the National Lung Screening Trial. Annual versus 3-year-interval follow-up of Lung-RADS category 2 nodules was compared, and different treatment strategies were tested (stereotactic body radiation therapy, surgery, and no therapy). Results Overall, 2.3% (22 584 of 1 000 000) of nodules were clinically significant malignancies; 6.3% (62 559 of 1 000 000) of nodules were treated. Only 30% (18 668 of 62 559) of Lung-RADS category 4B or 4X nodules were clinically significant malignancies. The risk of clinically significant malignancy for persistent nonsolid nodules after baseline was higher than Lung-RADS estimates for categories 2 and 3 (3% vs <1% and 1%-2%, respectively). Overall survival (OS) at 10 years was 72% (527 827 of 737 306; 95% confidence interval [CI]: 71%, 72%) with annual follow-up and 71% (526 507 of 737 306; 95% CI: 71%, 72%) with 3-year-interval follow-up (P < .01). At 10 years, OS among patients whose nodules progressed to Lung-RADS category 4B or 4X was 80% after radiation therapy (49 945 of 62 559; 95% CI: 80%, 80%), 79% after surgery (49 139 of 62 559; 95% CI: 78%, 79%), and 74% after no therapy (46 512 of 62 559; 95% CI: 74%, 75%) (P < .01). Conclusion Simulation modeling suggests that the follow-up interval for evaluating ground-glass nodules can be increased from 1 year to 3 years with minimal change in outcomes. Stereotactic body radiation therapy demonstrated the best outcomes compared with lobectomy and with no therapy for nonsolid nodules. © RSNA, 2018 Online supplemental material is available for this article.

Benefits and harms of lung cancer screening in HIV-infected individuals with CD4+ cell count at least 500 cells/μl

OBJECTIVE

Lung cancer is the leading cause of non-AIDS-defining cancer deaths among HIV-infected individuals. Although lung cancer screening with low-dose computed tomography (LDCT) is endorsed by multiple national organizations, whether HIV-infected individuals would have similar benefit as uninfected individuals from lung cancer screening is unknown. Our objective was to determine the benefits and harms of lung cancer screening among HIV-infected individuals.

DESIGN

We modified an existing simulation model, the Lung Cancer Policy Model, for HIV-infected patients.

DATA SOURCES

Veterans Aging Cohort Study, Kaiser Permanente Northern California HIV Cohort, and medical literature.

TARGET POPULATION

HIV-infected current and former smokers.

TIME HORIZON

Lifetime.

PERSPECTIVE

Population.

INTERVENTION

Annual LDCT screening from ages 45, 50, or 55 until ages 72 or 77 years.

MAIN OUTCOME MEASURES

Benefits assessed included lung cancer mortality reduction and life-years gained; harms assessed included numbers of LDCT examinations, false-positive results, and overdiagnosed cases.

RESULTS OF BASE-CASE ANALYSIS

For HIV-infected patients with CD4 cell count at least 500 cells/μl and 100% antiretroviral therapy adherence, screening using the Centers for Medicare & Medicaid Services criteria (age 55-77, 30 pack-years of smoking, current smoker or quit within 15 years of screening) would reduce lung cancer mortality by 18.9%, similar to the mortality reduction of uninfected individuals. Alternative screening strategies utilizing lower screening age and/or pack-years criteria increase mortality reduction, but require more LDCT examinations.

LIMITATIONS

Strategies assumed 100% screening adherence.

CONCLUSION

Lung cancer screening reduces mortality in HIV-infected patients with CD4 cell count at least 500 cells/μl, with a number of efficient strategies for eligibility, including the current Centers for Medicare & Medicaid Services criteria.

Screening for Lung Cancer

Lung cancer is a global health burden and is among the most common and deadliest of all malignancies worldwide. The goal of screening programs is to detect tumors in earlier, curable stages, consequently reducing disease-specific mortality. The issue of screening has great relevance to thoracic surgeons, who should play a leading role in the debate over screening and its consequences. The burden is on thoracic surgeons to work in a multidisciplinary setting to guide and treat these patients safely and responsibly, ensuring low morbidity and mortality of potential diagnostic or therapeutic interventions.

Population impact of lung cancer screening in the United States: Projections from a microsimulation model

BACKGROUND

Previous simulation studies estimating the impacts of lung cancer screening have ignored the changes in smoking prevalence over time in the United States. Our primary rationale was to perform, to our knowledge, the first simulation study that estimates the health outcomes of lung cancer screening with explicit modeling of smoking trends for the whole US population.

METHODS/FINDINGS

Utilizing a well-validated microsimulation model, we estimated the benefits and harms of an annual low-dose computed tomography screening scenario with a realistic screening adherence rate versus a no-screening scenario for the US population from 2016-2030. The Centers for Medicare and Medicaid Services (CMS) eligibility criteria were applied: age 55-77 years at time of screening, history of at least 30 pack-years of smoking, and current smoker or former smoker with fewer than 15 years since quitting. In the screened population, cumulative mortality reduction was projected to reach 16.98% (95% CI 16.90%-17.07%). Cumulative mortality reduction was estimated to be 3.52% (95% CI 3.50%-3.53%) for the overall study population, with annual mortality reduction peaking at 4.38% (95% CI 4.36%-4.41%) in 2021 and falling to 3.53% (95% CI 3.50%-3.56%) by 2030. Lung cancer screening would save a projected 148,484 life-years (95% CI 147,429-149,540) across the total population through 2030. There were estimated to be 9,054 (95% CI 9,011-9,098) overdiagnosed cases among the 252,429 (95% CI 251,208-253,649) screen-detected lung cancer diagnoses, yielding an overdiagnosis rate of 3.59%. The limitations of our study are that we do not explicitly model race or socioeconomic status and our model was calibrated to data from studies performed in academic centers, both of which may impact the generalizability of our results. We also exclusively model the effects of the CMS guidelines for lung cancer screening and not any other screening strategies.

CONCLUSIONS

The mortality reduction and life-years gained estimated by this study are lower than those of single birth cohort studies. Single cohort studies neglect the changing dynamics of smoking behavior across generations, whereas this study reflects the trend of decreasing smoking prevalence since the 1960s. Maximum benefit could be derived from lung cancer screening through 2021; in later years, mortality reduction due to screening will decline. If a comprehensive screening program is not implemented in the near future, the opportunity to achieve these benefits will have passed.

The relationship between demands for lung cancer screening and the constructs of health belief model: a cross-sectional survey in Hefei, China

The aim of investigation is to explore the relationship between demands for lung cancer screening (LCS) and the constructs derived from the health belief model (HBM) in Hefei. The study collected data about socio-demographics, health beliefs in and demands for LCS during early June to later July 2015. By constructing a LCS demands HBM constructs, it calculated indices of demands for LCS (DSI) and HBM constructs, which include perceived risk (PR) and seriousness (PS) of the cancers; and perceived effectiveness (PE), benefits (PB) and difficulties (PD) of the screening. It also performed descriptive and multivariate regression analysis of the demands and the HBM constructs. The amount of 823 respondents participated and completed the survey. 6.4% of them had ever undertaken LCS, whereas 60.1% of them expressed willingness to accept the service of LCS if it is free. In multiple regression analysis which used weights in calculating the HBM construct indices, education displayed significant positive associations with DSI (p = .044), and most of HBM constructs indices (PSI, PRI, PBI, and PDI) were statistically significant with DSI (p < .05). HBM-based constructs regarding LCS have important effects on demands for the service, and may provide effective paths to cancer screening promotion.

An integrated digital/clinical approach to smoking cessation in lung cancer screening: study protocol for a randomized controlled trial

Background

Delivering effective tobacco dependence treatment that is feasible within lung cancer screening (LCS) programs is crucial for realizing the health benefits and cost savings of screening. Large-scale trials and systematic reviews have demonstrated that digital cessation interventions (i.e. web-based and text message) are effective, sustainable over the long-term, scalable, and cost-efficient. Use of digital technologies is commonplace among older adults, making this a feasible approach within LCS programs. Use of cessation treatment has been improved with models that proactively connect smokers to treatment rather than passive referrals. Proactive referral to cessation treatment has been advanced through healthcare systems changes such as modifying the electronic health record to automatically link smokers to treatment.

Methods

This study evaluates the impact of a proactive enrollment strategy that links LCS-eligible smokers with an evidence-based intervention comprised of a web-based (WEB) program and integrated text messaging (TXT) in a three-arm randomized trial with repeated measures at one, three, six, and 12 months post randomization. The primary outcome is biochemically confirmed abstinence at 12 months post randomization. We will randomize 1650 smokers who present for a clinical LCS to: (1) a usual care control condition (UC) which consists of Ask–Advise–Refer; (2) a digital (WEB + TXT) cessation intervention; or (3) a digital cessation intervention combined with tobacco treatment specialist (TTS) counseling (WEB + TXT + TTS).

Discussion

The scalability and sustainability of a digital intervention may represent the most cost-effective and feasible approach for LCS programs to proactively engage large numbers of smokers in effective cessation treatment. We will also evaluate the impact and cost-effectiveness of adding proven clinical intervention provided by a TTS. We expect that a combined digital/clinical intervention will yield higher quit rates than digital alone, but that it may not be as cost-effective or feasible for LCS programs to implement. This study is innovative in its use of interoperable, digital technologies to deliver a sustainable, scalable, high-impact cessation intervention and to facilitate its integration within clinical practice. It will add to the growing knowledge base about the overall effectiveness of digital interventions and their role in the healthcare delivery system.

Trial registration

ClinicalTrials.gov, NCT03084835. Registered on 9 March 2017.

Electronic supplementary material

The online version of this article (doi:10.1186/s13063-017-2312-x) contains supplementary material, which is available to authorized users.

Evaluating lung cancer screening in China: Implications for eligibility criteria design from a microsimulation modeling approach

More than half of males in China are current smokers and evidence from western countries tells us that an unprecedented number of smoking-attributable deaths will occur as the Chinese population ages. We used the China Lung Cancer Policy Model (LCPM) to simulate effects of computed tomography (CT)-based lung cancer screening in China, comparing the impact of a screening guideline published in 2015 by a Chinese expert group to a version developed for the United States by the U.S. Centers for Medicare & Medicaid Services (CMS). The China LCPM, built using an existing lung cancer microsimulation model, can project population outcomes associated with interventions for smoking-related diseases. After calibrating the model to published Chinese smoking prevalence and lung cancer mortality rates, we simulated screening from 2016 to 2050 based on eligibility criteria from the CMS and Chinese guidelines, which differ by age to begin and end screening, pack-years smoked, and years since quitting. Outcomes included number of screens, mortality reduction, and life-years saved for each strategy. We projected that in the absence of screening, 14.98 million lung cancer deaths would occur between 2016 and 2050. Screening with the CMS guideline would prevent 0.72 million deaths and 5.8 million life-years lost, resulting in 6.58% and 1.97% mortality reduction in males and females, respectively. Screening with the Chinese guideline would prevent 0.74 million deaths and 6.6 million life-years lost, resulting in 6.30% and 2.79% mortality reduction in males and females, respectively. Through 2050, 1.43 billion screens would be required using the Chinese screening strategy, compared to 988 million screens using the CMS guideline. In conclusion, CT-based lung cancer screening implemented in 2016 and based on the Chinese screening guideline would prevent about 20,000 (2.9%) more lung cancer deaths through 2050, but would require about 445 million (44.7%) more screens than the CMS guideline.

Combined Biomarker and Computed Tomography Screening Strategies for Lung Cancer: Projections of Health and Economic Tradeoffs in the US Population

Background: Lung cancer screening with computed tomography (CT) of individuals who meet certain age and smoking history criteria is the current standard-of-care. Methods: Using a published simulation model, we compared outcomes associated with seven biomarker + CT screening strategies to CT screening alone using Centers for Medicare & Medicaid Services eligibility criteria. We assumed that the biomarker had conditionally independent performance; was used for first-line screening in some, or all, individuals screened; and could be extended to Centers for Medicare & Medicaid Services–ineligible smokers. Strategies differed by inclusion criteria (e.g., pack-years) and proportion of individuals for whom CT remained the first-line test. Each model run simulated a combined cohort of one million men and one million women born in 1950. Primary outcomes were cancer-specific mortality reduction and screening costs; biomarker costs were measured relative to CT. Efficiency frontiers identified optimal health and economic tradeoffs. Sensitivity analysis evaluated the stability of results. Results: Standard-of-care screening yielded an 8.3% cancer-specific mortality reduction in the simulated US population (screened + unscreened individuals). For a biomarker test with 75% sensitivity and 95% specificity, mortality reductions across biomarker + CT strategies ranged from 7.0% to 23.9%. If the biomarker’s cost was >0.86× that of CT, standard-of-care screening remained on the efficiency frontier, indicating that health and economic tradeoffs were equally (or more) efficient relative to all biomarker + CT strategies. Biomarker + CT strategy costs were principally driven by biomarker specificity; mortality reduction was driven by sensitivity. Conclusion: Combined biomarker + CT strategies have the potential to improve future lung cancer screening effectiveness in the United States and achieve economic efficiency that is greater than the current standard-of-care.

The UK Lung Cancer Screening Trial: a pilot randomised controlled trial of low-dose computed tomography screening for the early detection of lung cancer

BACKGROUND

Lung cancer kills more people than any other cancer in the UK (5-year survival < 13%). Early diagnosis can save lives. The USA-based National Lung Cancer Screening Trial reported a 20% relative reduction in lung cancer mortality and 6.7% all-cause mortality in low-dose computed tomography (LDCT)-screened subjects.

OBJECTIVES

To (1) analyse LDCT lung cancer screening in a high-risk UK population, determine optimum recruitment, screening, reading and care pathway strategies; and (2) assess the psychological consequences and the health-economic implications of screening.

DESIGN

A pilot randomised controlled trial comparing intervention with usual care. A population-based risk questionnaire identified individuals who were at high risk of developing lung cancer (≥ 5% over 5 years).

SETTING

Thoracic centres with expertise in lung cancer imaging, respiratory medicine, pathology and surgery: Liverpool Heart & Chest Hospital, Merseyside, and Papworth Hospital, Cambridgeshire.

PARTICIPANTS

Individuals aged 50-75 years, at high risk of lung cancer, in the primary care trusts adjacent to the centres.

INTERVENTIONS

A thoracic LDCT scan. Follow-up computed tomography (CT) scans as per protocol. Referral to multidisciplinary team clinics was determined by nodule size criteria.

MAIN OUTCOME MEASURES

Population-based recruitment based on risk stratification; management of the trial through web-based database; optimal characteristics of CT scan readers (radiologists vs. radiographers); characterisation of CT-detected nodules utilising volumetric analysis; prevalence of lung cancer at baseline; sociodemographic factors affecting participation; psychosocial measures (cancer distress, anxiety, depression, decision satisfaction); and cost-effectiveness modelling.

RESULTS

A total of 247,354 individuals were approached to take part in the trial; 30.7% responded positively to the screening invitation. Recruitment of participants resulted in 2028 in the CT arm and 2027 in the control arm. A total of 1994 participants underwent CT scanning: 42 participants (2.1%) were diagnosed with lung cancer; 36 out of 42 (85.7%) of the screen-detected cancers were identified as stage 1 or 2, and 35 (83.3%) underwent surgical resection as their primary treatment. Lung cancer was more common in the lowest socioeconomic group. Short-term adverse psychosocial consequences were observed in participants who were randomised to the intervention arm and in those who had a major lung abnormality detected, but these differences were modest and temporary. Rollout of screening as a service or design of a full trial would need to address issues of outreach. The health-economic analysis suggests that the intervention could be cost-effective but this needs to be confirmed using data on actual lung cancer mortality.

CONCLUSIONS

The UK Lung Cancer Screening (UKLS) pilot was successfully undertaken with 4055 randomised individuals. The data from the UKLS provide evidence that adds to existing data to suggest that lung cancer screening in the UK could potentially be implemented in the 60-75 years age group, selected via the Liverpool Lung Project risk model version 2 and using CT volumetry-based management protocols.

FUTURE WORK

The UKLS data will be pooled with the NELSON (Nederlands Leuvens Longkanker Screenings Onderzoek: Dutch-Belgian Randomised Lung Cancer Screening Trial) and other European Union trials in 2017 which will provide European mortality and cost-effectiveness data. For now, there is a clear need for mortality results from other trials and further research to identify optimal methods of implementation and delivery. Strategies for increasing uptake and providing support for underserved groups will be key to implementation.

TRIAL REGISTRATION

Current Controlled Trials ISRCTN78513845.

FUNDING

This project was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme and will be published in full in Health Technology Assessment; Vol. 20, No. 40. See the NIHR Journals Library website for further project information.

Evaluating the impacts of screening and smoking cessation programmes on lung cancer in a high-burden region of the USA: a simulation modelling study

OBJECTIVE

While the US Preventive Services Task Force has issued recommendations for lung cancer screening, its effectiveness at reducing lung cancer burden may vary at local levels due to regional variations in smoking behaviour. Our objective was to use an existing model to determine the impacts of lung cancer screening alone or in addition to increased smoking cessation in a US region with a relatively high smoking prevalence and lung cancer incidence.

SETTING

Computer-based simulation model.

PARTICIPANTS

Simulated population of individuals 55 and older based on smoking prevalence and census data from Northeast Pennsylvania.

INTERVENTIONS

Hypothetical lung cancer control from 2014 to 2050 through (1) screening with CT, (2) intensified smoking cessation or (3) a combination strategy.

PRIMARY AND SECONDARY OUTCOME MEASURES

Primary outcomes were lung cancer mortality rates. Secondary outcomes included number of people eligible for screening and number of radiation-induced lung cancers.

RESULTS

Combining lung cancer screening with increased smoking cessation would yield an estimated 8.1% reduction in cumulative lung cancer mortality by 2050. Our model estimated that the number of screening-eligible individuals would progressively decrease over time, indicating declining benefit of a screening-only programme. Lung cancer screening achieved a greater mortality reduction in earlier years, but was later surpassed by smoking cessation.

CONCLUSIONS

Combining smoking cessation programmes with lung cancer screening would provide the most benefit to a population, especially considering the growing proportion of patients ineligible for screening based on current recommendations.

Research Challenges and Opportunities for Clinically Oriented Academic Radiology Departments

Between 2004 and 2012, US funding for the biomedical sciences decreased to historic lows. Health-related research was crippled by receiving only 1/20th of overall federal scientific funding. Despite the current funding climate, there is increased pressure on academic radiology programs to establish productive research programs. Whereas larger programs have resources that can be utilized at their institutions, small to medium-sized programs often struggle with lack of infrastructure and support. To address these concerns, the Association of University Radiologists' Radiology Research Alliance developed a task force to explore any untapped research productivity potential in these smaller radiology departments. We conducted an online survey of faculty at smaller clinically funded programs and found that while they were interested in doing research and felt it was important to the success of the field, barriers such as lack of resources and time were proving difficult to overcome. One potential solution proposed by this task force is a collaborative structured research model in which multiple participants from multiple institutions come together in well-defined roles that allow for an equitable distribution of research tasks and pooling of resources and expertise. Under this model, smaller programs will have an opportunity to share their unique perspective on how to address research topics and make a measureable impact on the field of radiology as a whole. Through a health services focus, projects are more likely to succeed in the context of limited funding and infrastructure while simultaneously providing value to the field.

Personalizing annual lung cancer screening for patients with chronic obstructive pulmonary disease: A decision analysis

BACKGROUND

Lung cancer screening with annual chest computed tomography (CT) is recommended for current and former smokers with a ≥30-pack-year smoking history. Patients with chronic obstructive pulmonary disease (COPD) are at increased risk of developing lung cancer and may benefit from screening at lower pack-year thresholds.

METHODS

We used a previously validated simulation model to compare the health benefits of lung cancer screening in current and former smokers ages 55-80 with ≥30 pack-years with hypothetical programs using lower pack-year thresholds for individuals with COPD (≥20, ≥10, and ≥1 pack-years). Calibration targets for COPD prevalence and associated lung cancer risk were derived using the Framingham Offspring Study limited data set. We performed sensitivity analyses to evaluate the stability of results across different rates of adherence to screening, increased competing mortality risk from COPD, and increased surgical ineligibility in individuals with COPD. The primary outcome was projected life expectancy.

RESULTS

Programs using lower pack-year thresholds for individuals with COPD yielded the highest life expectancy gains for a given number of screens. Highest life expectancy was achieved when lowering the pack-year threshold to ≥1 pack-year for individuals with COPD, which dominated all other screening strategies. These results were stable across different adherence rates to screening and increases in competing mortality risk for COPD and surgical ineligibility.

CONCLUSIONS

Current and former smokers with COPD may disproportionately benefit from lung cancer screening. A lower pack-year threshold for screening eligibility may benefit this high-risk patient population.

Targeted screening of individuals at high risk for pancreatic cancer: results of a simulation model

PURPOSE

To identify when, from the standpoint of relative risk, magnetic resonance (MR) imaging-based screening may be effective in patients with a known or suspected genetic predisposition to pancreatic cancer.

MATERIALS AND METHODS

The authors developed a Markov model of pancreatic ductal adenocarcinoma (PDAC). The model was calibrated to National Cancer Institute Surveillance, Epidemiology, and End Results registry data and informed by the literature. A hypothetical screening strategy was evaluated in which all population individuals underwent one-time MR imaging screening at age 50 years. Screening outcomes for individuals with an average risk for PDAC ("base case") were compared with those for individuals at an increased risk to assess for differential benefits in populations with a known or suspected genetic predisposition. Effects of varying key inputs, including MR imaging performance, surgical mortality, and screening age, were evaluated with a sensitivity analysis. RESULTS In the base case, screening resulted in a small number of cancer deaths averted (39 of 100 000 men, 38 of 100 000 women) and a net decrease in life expectancy (-3 days for men, -4 days for women), which was driven by unnecessary pancreatic surgeries associated with false-positive results. Life expectancy gains were achieved if an individual's risk for PDAC exceeded 2.4 (men) or 2.7 (women) times that of the general population. When relative risk increased further, for example to 30 times that of the general population, averted cancer deaths and life expectancy gains increased substantially (1219 of 100 000 men, life expectancy gain: 65 days; 1204 of 100 000 women, life expectancy gain: 71 days). In addition, results were sensitive to MR imaging specificity and the surgical mortality rate.

CONCLUSION

Although PDAC screening with MR imaging for the entire population is not effective, individuals with even modestly increased risk may benefit.

Lung cancer screening: the European perspective

European studies have contributed significantly to the understanding of lung cancer screening. Smoking within screening, quality of life, nodule management, minimally invasive treatments, cancer prevention programs, and risk models have been extensively investigated by European groups. Mortality data from European screening studies have not been encouraging so far, but long-term results of the NELSON study are eagerly awaited. Investigations on molecular markers of lung cancer are ongoing in Europe; preliminary results suggest they may become an important screening tool in the future.

Computed tomography: revolutionizing the practice of medicine for 40 years

Computed tomography (CT) has had a profound effect on the practice of medicine. Both the spectrum of clinical applications and the role that CT has played in enhancing the depth of our understanding of disease have been profound. Although almost 90 000 articles on CT have been published in peer-reviewed journals over the past 40 years, fewer than 5% of these have been published in Radiology. Nevertheless, these almost 4000 articles have provided a basis for many important medical advances. By enabling a deepened understanding of anatomy, physiology, and pathology, CT has facilitated key advances in the detection and management of disease. This article celebrates this breadth of scientific discovery and development by examining the impact that CT has had on the diagnosis, characterization, and management of a sampling of major health challenges, including stroke, vascular diseases, cancer, trauma, acute abdominal pain, and diffuse lung diseases, as related to key technical advances in CT and manifested in Radiology.

Comparing benefits from many possible computed tomography lung cancer screening programs: extrapolating from the National Lung Screening Trial using comparative modeling

BACKGROUND

The National Lung Screening Trial (NLST) demonstrated that in current and former smokers aged 55 to 74 years, with at least 30 pack-years of cigarette smoking history and who had quit smoking no more than 15 years ago, 3 annual computed tomography (CT) screens reduced lung cancer-specific mortality by 20% relative to 3 annual chest X-ray screens. We compared the benefits achievable with 576 lung cancer screening programs that varied CT screen number and frequency, ages of screening, and eligibility based on smoking.

METHODS AND FINDINGS

We used five independent microsimulation models with lung cancer natural history parameters previously calibrated to the NLST to simulate life histories of the US cohort born in 1950 under all 576 programs. 'Efficient' (within model) programs prevented the greatest number of lung cancer deaths, compared to no screening, for a given number of CT screens. Among 120 'consensus efficient' (identified as efficient across models) programs, the average starting age was 55 years, the stopping age was 80 or 85 years, the average minimum pack-years was 27, and the maximum years since quitting was 20. Among consensus efficient programs, 11% to 40% of the cohort was screened, and 153 to 846 lung cancer deaths were averted per 100,000 people. In all models, annual screening based on age and smoking eligibility in NLST was not efficient; continuing screening to age 80 or 85 years was more efficient.

CONCLUSIONS

Consensus results from five models identified a set of efficient screening programs that include annual CT lung cancer screening using criteria like NLST eligibility but extended to older ages. Guidelines for screening should also consider harms of screening and individual patient characteristics.

Histoplasmosis mimicking primary lung neoplasm

A 70-year-old man, ex-smoker with a 3-pack-year smoking history, presented with a 5-week history of persistent cough. There were no positive findings on clinical examination. The patient's chest X-ray showed a nodular density in the right lung, initially thought to be malignant. After an extensive workup which included CT-guided lung biopsies, bronchoscopies, positron emission tomography scanning, among many other investigations, discussion at the respiratory multidisciplinary team meeting, and a right upper lobe lung resection, a diagnosis of histoplasmosis was performed.

Comparative analysis of 5 lung cancer natural history and screening models that reproduce outcomes of the NLST and PLCO trials

BACKGROUND

The National Lung Screening Trial (NLST) demonstrated that low-dose computed tomography screening is an effective way of reducing lung cancer (LC) mortality. However, optimal screening strategies have not been determined to date and it is uncertain whether lighter smokers than those examined in the NLST may also benefit from screening. To address these questions, it is necessary to first develop LC natural history models that can reproduce NLST outcomes and simulate screening programs at the population level.

METHODS

Five independent LC screening models were developed using common inputs and calibration targets derived from the NLST and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial (PLCO). Imputation of missing information regarding smoking, histology, and stage of disease for a small percentage of individuals and diagnosed LCs in both trials was performed. Models were calibrated to LC incidence, mortality, or both outcomes simultaneously.

RESULTS

Initially, all models were calibrated to the NLST and validated against PLCO. Models were found to validate well against individuals in PLCO who would have been eligible for the NLST. However, all models required further calibration to PLCO to adequately capture LC outcomes in PLCO never-smokers and light smokers. Final versions of all models produced incidence and mortality outcomes in the presence and absence of screening that were consistent with both trials.

CONCLUSIONS

The authors developed 5 distinct LC screening simulation models based on the evidence in the NLST and PLCO. The results of their analyses demonstrated that the NLST and PLCO have produced consistent results. The resulting models can be important tools to generate additional evidence to determine the effectiveness of lung cancer screening strategies using low-dose computed tomography.

Roles of computed tomography and [(18)F]fluorodeoxyglucose-positron emission tomography/computed tomography in the characterization of multiple solitary solid lung nodules

The purpose of this study is to compare the performance of multidetector computed tomography (CT) and positron emission tomography/CT (PET/CT) with [(18)F]fluorodeoxyglucose in the diagnosis of multiple solitary lung nodules in 14 consecutive patients with suspicious lung cancer. CT and PET/CT findings were reviewed by a radiologist and nuclear medicine physician, respectively, blinded to the pathological diagnoses of lung cancer, considering nodule size, shape, and location (CT) and maximum standardized uptake value normalized to body weight (SUVbw max). Nodules were judged malignant or benign. The sensitivity, specificity, and accuracy of the two techniques were compared. CT had a sensitivity, specificity, and accuracy of 93.7, 86.7, and 90.3%, respectively, whereas PET/CT had a sensitivity, specificity, and accuracy of 75, 100, and 87.1%, respectively. Clinical management would have been erroneous in two patients by CT alone and in four patients by PET/CT alone. In one patient, the two techniques misdiagnosed the nodules (2 CT and 1 PET/CT). CT and PET/CT have complimentary roles in characterization of multiple solitary pulmonary nodules. Small nodules are poorly characterized by CT, and small-sized low-SUV malignant nodules are difficult to detect with PET/CT.

Chapter 13: CISNET lung models: comparison of model assumptions and model structures

Sophisticated modeling techniques can be powerful tools to help us understand the effects of cancer control interventions on population trends in cancer incidence and mortality. Readers of journal articles are, however, rarely supplied with modeling details. Six modeling groups collaborated as part of the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) to investigate the contribution of U.S. tobacco-control efforts toward reducing lung cancer deaths over the period 1975-2000. The six models included in this monograph were developed independently and use distinct, complementary approaches toward modeling the natural history of lung cancer. The models used the same data for inputs, and agreed on the design of the analysis and the outcome measures. This article highlights aspects of the models that are most relevant to similarities of or differences between the results. Structured comparisons can increase the transparency of these complex models.

Chapter 9: The MGH-HMS lung cancer policy model: tobacco control versus screening

The natural history model underlying the MGH Lung Cancer Policy Model (LCPM) does not include the two-stage clonal expansion model employed in other CISNET lung models. We used the LCPM to predict numbers of U.S. lung cancer deaths for ages 30-84 between 1975 and 2000 under four scenarios as part of the comparative modeling analysis described in this issue. The LCPM is a comprehensive microsimulation model of lung cancer development, progression, detection, treatment, and survival. Individual-level patient histories are aggregated to estimate cohort or population-level outcomes. Lung cancer states are defined according to underlying disease variables, test results, and clinical events. By simulating detailed clinical procedures, the LCPM can predict benefits and harms attributable to a variety of patient management practices, including annual screening programs. Under the scenario of observed smoking patterns, predicted numbers of deaths from the calibrated LCPM were within 2% of observed over all years (1975-2000). The LCPM estimated that historical tobacco control policies achieved 28.6% (25.2% in men, 30.5% in women) of the potential reduction in U.S. lung cancer deaths had smoking had been eliminated entirely. The hypothetical adoption in 1975 of annual helical CT screening of all persons aged 55-74 with at least 30 pack-years of cigarette exposure to historical tobacco control would have yielded a proportion realized of 39.0% (42.0% in men, 33.3% in women). The adoption of annual screening would have prevented less than half as many lung cancer deaths as the elimination of cigarette smoking.

Longitudinal multistage model for lung cancer incidence, mortality, and CT detected indolent and aggressive cancers

It is currently not known whether most lung cancers detected by computerized tomography (CT) screening are aggressive and likely to be fatal if left untreated, or if a sizable fraction are indolent and unlikely to cause death during the natural lifetime of the individual. We developed a longitudinal biologically-based model of the relationship between individual smoking histories and the probability for lung cancer incidence, CT screen detection, lung cancer mortality, and other-cause mortality. The longitudinal model relates these different outcomes to an underlying lung cancer disease pathway and an effective other-cause mortality pathway, which are both influenced by the individual smoking history. The longitudinal analysis provides additional information over that available if these outcomes were analyzed separately, including testing if the number of CT detected and histologically-confirmed lung cancers is consistent with the expected number of lung cancers "in the pipeline". We assume indolent nodules undergo Gompertz growth and are detectable by CT, but do not grow large enough to contribute significantly to symptom-based lung cancer incidence or mortality. Likelihood-based model calibration was done jointly to data from 6878 heavy smokers without asbestos exposure in the control (placebo) arm of the Carotene and Retinol Efficacy Trial (CARET); and to 3,642 heavy smokers with comparable smoking histories in the Pittsburgh Lung Screening Study (PLuSS), a single-arm prospective trial of low-dose spiral CT screening for diagnosis of lung cancer. Model calibration was checked using data from two other single-arm prospective CT screening trials, the New York University Lung Cancer Biomarker Center (NYU) (n=1,021), and Moffitt Cancer Center (Moffitt) cohorts (n=677). In the PLuSS cohort, we estimate that at the end of year 2, after the baseline and first annual CT exam, that 33.0 (26.9, 36.9)% of diagnosed lung cancers among females and 7.0 (4.9,11.7)% among males were overdiagnosed due to being indolent cancers. At the end of the PLuSS study, with maximum follow-up of 5.8 years, we estimate that due to early detection by CT and limited follow-up, an additional 2.2 (2.0,2.4)% of all diagnosed cancers among females and 7.1 (6.7,8.0)% among males would not have been diagnosed in the absence of CT screening. We also find a higher apparent cure rate for lung cancer among CARET females than males, consistent with the larger indolent fraction of CT detected and histologically confirmed lung cancers among PLuSS females. This suggests that there are significant gender differences in the aggressiveness of lung cancer. Females may have an inherently higher proportion of indolent lung cancers than males, or aggressive lung cancers may be brought into check by the immune system more frequently among females than males.

Using radiation risk models in cancer screening simulations: important assumptions and effects on outcome projections

PURPOSE

To evaluate the effect of incorporating radiation risk into microsimulation (first-order Monte Carlo) models for breast and lung cancer screening to illustrate effects of including radiation risk on patient outcome projections.

MATERIALS AND METHODS

All data used in this study were derived from publicly available or deidentified human subject data. Institutional review board approval was not required. The challenges of incorporating radiation risk into simulation models are illustrated with two cancer screening models (Breast Cancer Model and Lung Cancer Policy Model) adapted to include radiation exposure effects from mammography and chest computed tomography (CT), respectively. The primary outcome projected by the breast model was life expectancy (LE) for BRCA1 mutation carriers. Digital mammographic screening beginning at ages 25, 30, 35, and 40 years was evaluated in the context of screenings with false-positive results and radiation exposure effects. The primary outcome of the lung model was lung cancer-specific mortality reduction due to annual screening, comparing two diagnostic CT protocols for lung nodule evaluation. The Metropolis-Hastings algorithm was used to estimate the mean values of the results with 95% uncertainty intervals (UIs).

RESULTS

Without radiation exposure effects, the breast model indicated that annual digital mammography starting at age 25 years maximized LE (72.03 years; 95% UI: 72.01 years, 72.05 years) and had the highest number of screenings with false-positive results (2.0 per woman). When radiation effects were included, annual digital mammography beginning at age 30 years maximized LE (71.90 years; 95% UI: 71.87 years, 71.94 years) with a lower number of screenings with false-positive results (1.4 per woman). For annual chest CT screening of 50-year-old females with no follow-up for nodules smaller than 4 mm in diameter, the lung model predicted lung cancer-specific mortality reduction of 21.50% (95% UI: 20.90%, 22.10%) without radiation risk and 17.75% (95% UI: 16.97%, 18.41%) with radiation risk.

CONCLUSION

Because including radiation exposure risk can influence long-term projections from simulation models, it is important to include these risks when conducting modeling-based assessments of diagnostic imaging.

Impact of reduced tobacco smoking on lung cancer mortality in the United States during 1975-2000

BACKGROUND

Considerable effort has been expended on tobacco control strategies in the United States since the mid-1950s. However, we have little quantitative information on how changes in smoking behaviors have impacted lung cancer mortality. We quantified the cumulative impact of changes in smoking behaviors that started in the mid-1950s on lung cancer mortality in the United States over the period 1975-2000.

METHODS

A consortium of six groups of investigators used common inputs consisting of simulated cohort-wise smoking histories for the birth cohorts of 1890 through 1970 and independent models to estimate the number of US lung cancer deaths averted during 1975-2000 as a result of changes in smoking behavior that began in the mid-1950s. We also estimated the number of deaths that could have been averted had tobacco control been completely effective in eliminating smoking after the Surgeon General's first report on Smoking and Health in 1964.

RESULTS

Approximately 795,851 US lung cancer deaths were averted during the period 1975-2000: 552,574 among men and 243,277 among women. In the year 2000 alone, approximately 70,218 lung cancer deaths were averted: 44,135 among men and 26,083 among women. However, these numbers are estimated to represent approximately 32% of lung cancer deaths that could have potentially been averted during the period 1975-2000, 38% of the lung cancer deaths that could have been averted in 1991-2000, and 44% of lung cancer deaths that could have been averted in 2000.

CONCLUSIONS

Our results reflect the cumulative impact of changes in smoking behavior since the 1950s. Despite a large impact of changing smoking behaviors on lung cancer deaths, lung cancer remains a major public health problem. Continued efforts at tobacco control are critical to further reduce the burden of this disease.

Screening for lung cancer: challenges for the thoracic surgeon

Lung cancer is a global health burden and is among the most common and deadly of all malignancies worldwide. Early detection of resectable and potentially curable disease may reduce the overall death rate from lung cancer. However, at the present time, screening for lung cancer is not recommended by most clinical societies and health care agencies in the United States. This article discusses the history of, and rationale for, lung cancer screening, addresses optimization of screening protocols, and describes our current approach for the evaluation of small pulmonary nodules referred for surgical management.

Clinical application of pharmacokinetic analysis as a biomarker of solitary pulmonary nodules: dynamic contrast-enhanced MR imaging

The purpose of this study is to evaluate perfusion indices and pharmacokinetic parameters in solitary pulmonary nodules (SPNs). Thirty patients of 34 enrolled with SPNs (15-30 mm) were evaluated in this study. T1 and T2-weighted structural images and 2D turbo FLASH perfusion images were acquired with shallow free breathing. B-spline nonrigid image registration and optimization by χ² test against pharmacokinetic model curve were performed on dynamic contrast-enhanced MRI. This allowed voxel-by-voxel calculation of k(ep) , the rate constant for tracer transport to and from plasma and the extravascular extracellular space. Mean transit time, time-to-peak, initial slope, and maximum enhancement (E(max) ) were calculated from time-intensity curves fitted to a gamma variate function. After blinded data analysis, correlation with tissue histology from surgical resection or biopsy samples was performed. Histologic evaluation revealed 25 malignant and five benign SPNs. All benign SPNs had k(ep) < 1.0 min⁻¹. Nineteen of 25 (76%) malignant SPNs showed k(ep) > 1.0 min⁻¹. Sensitivity to diagnose malignant SPNs at a cutoff of k(ep) = 1.0 min⁻¹ was 76%, specificity was 100%, positive predictive value was 100%, negative predictive value was 45%, and accuracy was 80%. Of all indices studied, k(ep) was the most significant in differentiating malignant from benign SPNs.

Cost-effectiveness of computed tomography screening for lung cancer in the United States

INTRODUCTION

A randomized trial has demonstrated that lung cancer screening reduces mortality. Identifying participant and program characteristics that influence the cost-effectiveness of screening will help translate trial results into benefits at the population level.

METHODS

Six U.S. cohorts (men and women aged 50, 60, or 70 years) were simulated in an existing patient-level lung cancer model. Smoking histories reflected observed U.S. patterns. We simulated lifetime histories of 500,000 identical individuals per cohort in each scenario. Costs per quality-adjusted life-year gained ($/QALY) were estimated for each program: computed tomography screening; stand-alone smoking cessation therapies (4-30% 1-year abstinence); and combined programs.

RESULTS

Annual screening of current and former smokers aged 50 to 74 years costs between $126,000 and $169,000/QALY (minimum 20 pack-years of smoking) or $110,000 and $166,000/QALY (40 pack-year minimum), when compared with no screening and assuming background quit rates. Screening was beneficial but had a higher cost per QALY when the model included radiation-induced lung cancers. If screen participation doubled background quit rates, the cost of annual screening (at age 50 years, 20 pack-year minimum) was below $75,000/QALY. If screen participation halved background quit rates, benefits from screening were nearly erased. If screening had no effect on quit rates, annual screening costs more but provided fewer QALYs than annual cessation therapies. Annual combined screening/cessation therapy programs at age 50 years costs $130,500 to $159,700/QALY, when compared with annual stand-alone cessation.

CONCLUSIONS

The cost-effectiveness of computed tomography screening will likely be strongly linked to achievable smoking cessation rates. Trials and further modeling should explore the consequences of relationships between smoking behaviors and screen participation.

Computer disease simulation models: integrating evidence for health policy

Computer disease simulation models are increasingly being used to evaluate and inform health care decisions across medical disciplines. The aim of researchers who develop these models is to integrate and synthesize short-term outcomes and results from multiple sources to predict the long-term clinical outcomes and costs of different health care strategies. Policy makers, in turn, can use the predictions generated by disease models together with other evidence to make decisions related to health care practices and resource utilization. Models are particularly useful when the existing evidence does not yield obvious answers or does not provide answers to the questions of greatest interest, such as questions about the relative cost-effectiveness of different practices. This review focuses on models used to inform decisions about imaging technology, discussing the role of disease models for health policy development and providing a foundation for understanding the basic principles of disease modeling. This manuscript draws from the collective computed tomographic colonography modeling experience, reviewing 10 published investigations of the clinical effectiveness and cost-effectiveness of computed tomographic colonography relative to colonoscopy. The discussion focuses on implications of different modeling assumptions and difficulties that may be encountered when evaluating the quality of models. This underscores the importance of forging stronger collaborations between researchers who develop disease models and radiologists, to ensure that policy-level models accurately represent the experience of everyday clinical practices.

Lung cancer risk prediction to select smokers for screening CT--a model based on the Italian COSMOS trial

Screening with low-dose helical computed tomography (CT) has been shown to significantly reduce lung cancer mortality but the optimal target population and time interval to subsequent screening are yet to be defined. We developed two models to stratify individual smokers according to risk of developing lung cancer. We first used the number of lung cancers detected at baseline screening CT in the 5,203 asymptomatic participants of the COSMOS trial to recalibrate the Bach model, which we propose using to select smokers for screening. Next, we incorporated lung nodule characteristics and presence of emphysema identified at baseline CT into the Bach model and proposed the resulting multivariable model to predict lung cancer risk in screened smokers after baseline CT. Age and smoking exposure were the main determinants of lung cancer risk. The recalibrated Bach model accurately predicted lung cancers detected during the first year of screening. Presence of nonsolid nodules (RR = 10.1, 95% CI = 5.57-18.5), nodule size more than 8 mm (RR = 9.89, 95% CI = 5.84-16.8), and emphysema (RR = 2.36, 95% CI = 1.59-3.49) at baseline CT were all significant predictors of subsequent lung cancers. Incorporation of these variables into the Bach model increased the predictive value of the multivariable model (c-index = 0.759, internal validation). The recalibrated Bach model seems suitable for selecting the higher risk population for recruitment for large-scale CT screening. The Bach model incorporating CT findings at baseline screening could help defining the time interval to subsequent screening in individual participants. Further studies are necessary to validate these models.

A serum circulating miRNA diagnostic test to identify asymptomatic high-risk individuals with early stage lung cancer

Lung cancer is the first cause of cancer mortality worldwide, and its early detection is currently the main available strategy to improve disease prognosis. While early diagnosis can be successfully achieved through tomography-based population screenings in high-risk individuals, simple methodologies are needed for effective cancer prevention programs. We developed a test, based on the detection of 34 microRNAs (miRNAs) from serum, that could identify patients with early stage non-small cell lung carcinomas (NSCLCs) in a population of asymptomatic high-risk individuals with 80% accuracy. The signature could assign disease probability accurately either in asymptomatic or symptomatic patients, is able to distinguish between benign and malignant lesions, and to capture the onset of the malignant disease in individual patients over time. Thus, our test displays a number of features of clinical relevance that project its utility in programs for the early detection of NSCLC.

Clarifying differences in natural history between models of screening: the case of colorectal cancer

BACKGROUND

Microsimulation models are important decision support tools for screening. However, their complexity makes them difficult to understand and limits realization of their full potential. Therefore, it is important to develop documentation that clarifies their structure and assumptions. The authors demonstrate this problem and explore a solution for natural history using 3 independently developed colorectal cancer screening models.

METHODS

The authors first project effectiveness and cost-effectiveness of colonoscopy screening for the 3 models (CRC-SPIN, SimCRC, and MISCAN). Next, they provide a conventional presentation of each model, including information on structure and parameter values. Finally, they report the simulated reduction in clinical cancer incidence following a one-time complete removal of adenomas and preclinical cancers for each model. They call this new measure the maximum clinical incidence reduction (MCLIR).

RESULTS

Projected effectiveness varies widely across models. For example, estimated mortality reduction for colonoscopy screening every 10 years from age 50 to 80 years, with surveillance in adenoma patients, ranges from 65% to 92%. Given only conventional information, it is difficult to explain these differences, largely because differences in structure make parameter values incomparable. In contrast, the MCLIR clearly shows the impact of model differences on the key feature of natural history, the dwell time of preclinical disease. Dwell times vary from 8 to 25 years across models and help explain differences in projected screening effectiveness.

CONCLUSIONS

The authors propose a new measure, the MCLIR, which summarizes the implications for predicted screening effectiveness of differences in natural history assumptions. Including the MCLIR in the standard description of a screening model would improve the transparency of these models.