Time-driven activity-based costing (TDABC) of direct-to-angiography pathway for acute ischemic stroke patients with suspected large vessel occlusion.

INTRODUCTION: Direct-to-angiography (DTA) is a novel care pathway for endovascular treatment (EVT) of acute ischemic stroke (AIS) that has been shown to reduce time-to-treatment and improve clinical outcomes for EVT-eligible patients. The institutional costs of adopting the DTA pathway and the many factors affecting costs have not been studied. In this study, we assess the costs and main cost drivers associated with the DTA pathway compared to the conventional CT pathway for patients presenting with AIS and suspected LVO in the anterior circulation. METHODS: Time driven activity based costing (TDABC) model was used to compare costs of DTA and conventional pathways from the healthcare institution perspective. Process mapping was used to outline all activities and resources (personnel, equipment, materials) needed for each step in both pathways. The cost model was developed using our institutional patient database and average New York state wages for personnel costs. Total, incremental and proportional costs were calculated based on institutional and patient factors affecting the pathways. RESULTS: DTA pathway accrued additional $82,583.61 (9%) in total costs compared to the conventional approach for all AIS patients. For EVT-ineligible patients, the DTA pathway incurred additional $82,964.37 (76%) in total costs compared to the CT pathway. For EVT eligible patients, the total and per-patient costs were greater in the CT pathway by $380.76 (0.04%) and $5.60 (0.04%) respectively. CONCLUSION: As the DTA pathway incurred additional $82,964.37 for EVT-ineligible patients, appropriate patient selection criteria are needed to avoid transferring EVT-ineligible patients to the angiography suite.

A predictive model for lung cancer screening nonadherence in a community setting health-care network.

BACKGROUND: Lung cancer screening (LCS) decreases lung cancer mortality. However, its benefit may be limited by nonadherence to screening. Although factors associated with LCS nonadherence have been identified, to the best of our knowledge, no predictive models have been developed to predict LCS nonadherence. The purpose of this study was to develop a predictive model leveraging a machine learning model to predict LCS nonadherence risk. METHODS: A retrospective cohort of patients who enrolled in our LCS program between 2015 and 2018 was used to develop a model to predict the risk of nonadherence to annual LCS after the baseline examination. Clinical and demographic data were used to fit logistic regression, random forest, and gradient-boosting models that were internally validated on the basis of accuracy and area under the receiver operating curve. RESULTS: A total of 1875 individuals with baseline LCS were included in the analysis, with 1264 (67.4%) as nonadherent. Nonadherence was defined on the basis of baseline chest computed tomography (CT) findings. Clinical and demographic predictors were used on the basis of availability and statistical significance. The gradient-boosting model had the highest area under the receiver operating curve (0.89, 95% confidence interval = 0.87 to 0.90), with a mean accuracy of 0.82. Referral specialty, insurance type, and baseline Lung CT Screening Reporting & Data System (LungRADS) score were the best predictors of nonadherence to LCS. CONCLUSIONS: We developed a machine learning model using readily available clinical and demographic data to predict LCS nonadherence with high accuracy and discrimination. After further prospective validation, this model can be used to identify patients for interventions to improve LCS adherence and decrease lung cancer burden.

Risk Model-Based Lung Cancer Screening : A Cost-Effectiveness Analysis.

BACKGROUND: In their 2021 lung cancer screening recommendation update, the U.S. Preventive Services Task Force (USPSTF) evaluated strategies that select people based on their personal lung cancer risk (risk model-based strategies), highlighting the need for further research on the benefits and harms of risk model-based screening. OBJECTIVE: To evaluate and compare the cost-effectiveness of risk model-based lung cancer screening strategies versus the USPSTF recommendation and to explore optimal risk thresholds. DESIGN: Comparative modeling analysis. DATA SOURCES: National Lung Screening Trial; Surveillance, Epidemiology, and End Results program; U.S. Smoking History Generator. TARGET POPULATION: 1960 U.S. birth cohort. TIME HORIZON: 45 years. PERSPECTIVE: U.S. health care sector. INTERVENTION: Annual low-dose computed tomography in risk model-based strategies that start screening at age 50 or 55 years, stop screening at age 80 years, with 6-year risk thresholds between 0.5% and 2.2% using the PLCOm2012 model. OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and cost-effectiveness efficiency frontier connecting strategies with the highest health benefit at a given cost. RESULTS OF BASE-CASE ANALYSIS: Risk model-based screening strategies were more cost-effective than the USPSTF recommendation and exclusively comprised the cost-effectiveness efficiency frontier. Among the strategies on the efficiency frontier, those with a 6-year risk threshold of 1.2% or greater were cost-effective with an ICER less than $100 000 per quality-adjusted life-year (QALY). Specifically, the strategy with a 1.2% risk threshold had an ICER of $94 659 (model range, $72 639 to $156 774), yielding more QALYs for less cost than the USPSTF recommendation, while having a similar level of screening coverage (person ever-screened 21.7% vs. USPSTF's 22.6%). RESULTS OF SENSITIVITY ANALYSES: Risk model-based strategies were robustly more cost-effective than the 2021 USPSTF recommendation under varying modeling assumptions. LIMITATION: Risk models were restricted to age, sex, and smoking-related risk predictors. CONCLUSION: Risk model-based screening is more cost-effective than the USPSTF recommendation, thus warranting further consideration. PRIMARY FUNDING SOURCE: National Cancer Institute (NCI).

Cost-effectiveness of remote robotic mechanical thrombectomy in acute ischemic stroke.

OBJECTIVE: Clinical outcomes following endovascular thrombectomy (EVT) for acute ischemic stroke (AIS) treatment are highly time sensitive. Remote robotic (RR)-EVT systems may be capable of mitigating time delays in patient transfer from a primary stroke center (PSC) to a comprehensive/thrombectomy-capable stroke center. However, health economic evidence is needed to assess the costs and benefits of an RR-EVT system. Therefore, the authors of this study aimed to determine whether performing RR-EVT in suspected AIS patients at a PSC as opposed to standard of care might translate to cost-effectiveness over a lifetime. METHODS: An economic evaluation study was performed from a US healthcare perspective, combining decision analysis and Markov modeling methods over a lifetime horizon to evaluate the cost-effectiveness of RR-EVT in suspected AIS patients at a PSC compared to the standard-of-care approach. Total expected costs and quality-adjusted life-years (QALYs) were estimated. RESULTS: In the cost-effectiveness analysis, RR-EVT yielded greater effectiveness per patient (4.05 vs 3.88 QALYs) and lower costs (US$321,269 vs US$321,397) than the standard-of-care approach. Owing to these lower costs and greater health benefits, RR-EVT was the dominant cost-effective strategy. After initiation of an RR-EVT system, the average costs per year were similar (or slightly reduced), according to this simulation. Sensitivity analyses revealed that RR-EVT remains cost-effective in a wide variety of time delays and cost assumptions. In a one-way sensitivity analysis, RR-EVT remained the most cost-effective strategy when time delays were greater than 2.5 minutes, its complication rate did not exceed 37%, and costs were lower than $54,081. When the cost of the RR-EVT strategy ranged from $19,340 to $54,081 and its complication rate varied from 15% to 37%, the RR-EVT strategy remained the most cost-effective throughout the two ranges. RR-EVT was also the most cost-effective strategy even when its cost doubled (to approximately $40,000) and time delays exceeded 20 minutes. In a probabilistic sensitivity analysis, RR-EVT was the long-term cost-effective strategy in 89.8% of iterations at a willingness-to-pay threshold of $100,000/QALY. CONCLUSIONS: This analysis suggests that RR-EVT as an innovative solution to expedite EVT is cost-effective. An RR-EVT system could potentially extend access to care in underserved communities and rural areas, as well as improve care for socioeconomically disadvantaged populations affected by health inequities.

Cost-effectiveness of endovascular thrombectomy in acute stroke patients with large ischemic core.

BACKGROUND: Evidence has shown that endovascular thrombectomy (EVT) treatment improves clinical outcomes. Yet, its benefit remains uncertain in patients with large established infarcts as defined by ASPECTS (Alberta Stroke Program Early CT Score) <6. This study evaluates the cost-effectiveness of EVT, compared with standard care (SC), in acute ischemic stroke (AIS) patients with ASPECTS 3-5. METHODS: An economic evaluation study was performed combining a decision tree and Markov model to estimate lifetime costs (2021 US$) and quality-adjusted life years (QALYs) of AIS patients with ASPECTS 3-5. Incremental cost-effectiveness ratios (ICERs), net monetary benefits (NMBs), and deterministic one-way and two-way sensitivity analyses were performed. Probabilistic sensitivity analyses were also performed to evaluate the robustness of our model. RESULTS: Compared with SC, the cost-effectiveness analyses revealed that EVT yields higher lifetime benefits (2.20 QALYs vs 1.41 QALYs) with higher lifetime healthcare cost per patient ($285 861 vs $272 954). The difference in health benefits between EVT and SC was 0.79 QALYs, equivalent to 288 additional days of healthy life per patient. Even though EVT is more costly than SC alone, it is still cost-effective given better outcomes with ICER of $16 239/QALY. The probabilistic sensitivity analyses indicated that EVT was the most cost-effective strategy in 98.8% (9882 of 10 000) of iterations at the willingness-to-pay threshold of $100 000 per QALY. CONCLUSIONS: The results of this study suggest that EVT is cost-effective in AIS patients with a large ischemic core (ASPECTS 3-5), compared with SC alone over the patient's lifetime.

Factors Associated With Lung Cancer Screening Adherence Among Patients With Negative Baseline CT Results in a Community Health Care Setting.

PURPOSE: Lung cancer screening (LCS) decreases lung cancer mortality; however, that reduction depends upon screening adherence. The purpose of this study was to determine factors associated with adherence rate for LCS among patients with negative baseline CT results in a multi-integrated health care network. METHODS: A retrospective analysis was conducted among patients with negative baseline CT results in a multi-integrated health care network LCS program between January 2015 and January 2020. The two outcomes were adherence for the first and second subsequent LCS studies. Negative baseline result was defined as a Lung CT Screening Reporting and Data System score 0, 1, or 2. Adherence was defined as undergoing a follow-up study within 11 to 15 months of a prior scan. Multivariable logistic regression was used to determine significant predictors of adherence, adjusting for patient demographics, median household income (on the basis of geocoding ZIP codes from the US Census Bureau), smoking history, screening sites, and provider specialty. RESULTS: A total of 30.7% (512 of 1,668) and 16.3% (270 of 1,660) of patients were adherent for the first two annual subsequent screens, respectively. First-year adherence was higher among former smokers and varied by site and provider specialty. Second-year adherence was higher among former smokers and varied by site, provider specialty, and pack-years smoked. CONCLUSIONS: Adherence to LCS in a multihospital integrated health care network was poor and even lower at year 2. The identified factors associated with adherence may serve as targets to increase LCS adherence and decrease lung cancer mortality.

Evaluation of direct-to-angiography suite (DTAS) and conventional clinical pathways in stroke care: a simulation study.

BACKGROUND: Rapid time to reperfusion is essential to minimize morbidity and mortality in acute ischemic stroke due to large vessel occlusion (LVO). We aimed to evaluate the workflow times when utilizing a direct-to-angiography suite (DTAS) pathway for patients with suspected stroke presenting at a comprehensive stroke center compared with a conventional CT pathway. METHODS: We developed a discrete-event simulation (DES) model to evaluate DTAS workflow timelines compared with a conventional CT pathway, varying the admission NIHSS score treatment eligibility criteria. Model parameters were estimated based on 2 year observational data from our institution. Sensitivity analyses of simulation parameters were performed to assess the impact of patient volume and baseline utilization of angiography suites on workflow times utilizing DTAS. RESULTS: Simulation modeling of stroke patients (SimStroke) demonstrated door-to-reperfusion time savings of 0.2-3.5 min (p=0.05) for a range of DTAS eligibility criteria (ie, last known well to arrival <6 hours and National Institutes of Health Stroke Scale ≥6-11), when compared with the conventional stroke care pathway. Sensitivity analyses revealed that DTAS time savings is highly dependent on baseline utilization of angiography suites. CONCLUSIONS: The results of the SimStroke model showed comparable time intervals for door-to-reperfusion for DTAS compared with a conventional stroke care pathway. However, the DTAS pathway was very sensitive to baseline angiography suite utilization, with even a 10% increase eliminating the advantages of DTAS compared with the conventional pathway. Given the minimal time savings modeled here, further investigation of implementing the DTAS pathway in clinical care is warranted.

A Cost-Effectiveness Analysis of Lung Cancer Screening With Low-Dose Computed Tomography and a Diagnostic Biomarker.

Background: The Lung Computed Tomography Screening Reporting and Data System (Lung-RADS) reduces the false-positive rate of lung cancer screening but introduces prolonged periods of uncertainty for indeterminate findings. We assess the cost-effectiveness of a screening program that assesses indeterminate findings earlier via a hypothetical diagnostic biomarker introduced in place of Lung-RADS 3 and 4A guidelines. Methods: We evaluated the performance of the US Preventive Services Task Force (USPSTF) recommendations on lung cancer screening with and without a hypothetical noninvasive diagnostic biomarker using a validated microsimulation model. The diagnostic biomarker assesses the malignancy of indeterminate nodules, replacing Lung-RADS 3 and 4A guidelines, and is characterized by a varying sensitivity profile that depends on nodules' size, specificity, and cost. We tested the robustness of our findings through univariate sensitivity analyses. Results: A lung cancer screening program per the USPSTF guidelines that incorporates a diagnostic biomarker with at least medium sensitivity profile and 90% specificity, that costs $250 or less, is cost-effective with an incremental cost-effectiveness ratio lower than $100 000 per quality-adjusted life year, and improves lung cancer-specific mortality reduction while requiring fewer screening exams than the USPSTF guidelines with Lung-RADS. A screening program with a biomarker costing $750 or more is not cost-effective. The health benefits accrued and costs associated with the screening program are sensitive to the disutility of indeterminate findings and specificity of the biomarker, respectively. Conclusions: Lung cancer screening that incorporates a diagnostic biomarker, in place of Lung-RADS 3 and 4A guidelines, could improve the cost-effectiveness of the screening program and warrants further investigation.

Cost-effectiveness Evaluation of the 2021 US Preventive Services Task Force Recommendation for Lung Cancer Screening.

IMPORTANCE: The US Preventive Services Task Force (USPSTF) issued its 2021 recommendation on lung cancer screening, which lowered the starting age for screening from 55 to 50 years and the minimum cumulative smoking exposure from 30 to 20 pack-years relative to its 2013 recommendation. Although costs are expected to increase because of the expanded screening eligibility criteria, it is unknown whether the new guidelines for lung cancer screening are cost-effective. OBJECTIVE: To evaluate the cost-effectiveness of the 2021 USPSTF recommendation for lung cancer screening compared with the 2013 recommendation and to explore the cost-effectiveness of 6 alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years and an ending age for screening of 80 years but varied the starting ages for screening (50 or 55 years) and the number of years since smoking cessation (≤15, ≤20, or ≤25). DESIGN, SETTING, AND PARTICIPANTS: A comparative cost-effectiveness analysis using 4 independently developed microsimulation models that shared common inputs to assess the population-level health benefits and costs of the 2021 recommended screening strategy and 6 alternative screening strategies compared with the 2013 recommended screening strategy. The models simulated a 1960 US birth cohort. Simulated individuals entered the study at age 45 years and were followed up until death or age 90 years, corresponding to a study period from January 1, 2005, to December 31, 2050. EXPOSURES: Low-dose computed tomography in lung cancer screening programs with a minimum cumulative smoking exposure of 20 pack-years. MAIN OUTCOMES AND MEASURES: Incremental cost-effectiveness ratio (ICER) per quality-adjusted life-year (QALY) of the 2021 vs 2013 USPSTF lung cancer screening recommendations as well as 6 alternative screening strategies vs the 2013 USPSTF screening strategy. Strategies with a mean ICER lower than $100 000 per QALY were deemed cost-effective. RESULTS: The 2021 USPSTF recommendation was estimated to be cost-effective compared with the 2013 recommendation, with a mean ICER of $72 564 (range across 4 models, $59 493-$85 837) per QALY gained. The 2021 recommendation was not cost-effective compared with 6 alternative strategies that used the 20 pack-year criterion. Strategies associated with the most cost-effectiveness included those that expanded screening eligibility to include a greater number of former smokers who had not smoked for a longer duration (ie, ≤20 years and ≤25 years since smoking cessation vs ≤15 years since smoking cessation). In particular, the strategy that screened former smokers who quit within the past 25 years and began screening at age 55 years was associated with screening coverage closest to that of the 2021 USPSTF recommendation yet yielded greater cost-effectiveness, with a mean ICER of $66 533 (range across 4 models, $55 693-$80 539). CONCLUSIONS AND RELEVANCE: This economic evaluation found that the 2021 USPSTF recommendation for lung cancer screening was cost-effective; however, alternative screening strategies that maintained a minimum cumulative smoking exposure of 20 pack-years but included individuals who quit smoking within the past 25 years may be more cost-effective and warrant further evaluation.

Evaluation of Alternative Diagnostic Follow-up Intervals for Lung Reporting and Data System Criteria on the Effectiveness of Lung Cancer Screening.

PURPOSE: The ACR developed the Lung CT Screening Reporting and Data System (Lung-RADS) to standardize the diagnostic follow-up of suspicious screening findings. A retrospective analysis showed that Lung-RADS would have reduced the false-positive rate in the National Lung Screening Trial, but the optimal timing of follow-up examinations has not been established. In this study, we assess the effectiveness of alternative diagnostic follow-up intervals on lung cancer screening. METHODS: We used the Lung Cancer Outcome Simulator to estimate population-level outcomes of alternative diagnostic follow-up intervals for Lung-RADS categories 3 and 4A. The Lung Cancer Outcome Simulator is a microsimulation model developed within the Cancer Intervention and Surveillance Modeling Network Consortium to evaluate outcomes of national screening guidelines. Here, among the evaluated outcomes are percentage of mortality reduction, screens performed, lung cancer deaths averted, screen-detected cases, and average number of screens and follow-ups per death averted. RESULTS: The recommended 3-month follow-up interval for Lung-RADS category 4A is optimal. However, for Lung-RADS category 3, a 5-month, instead of the recommended 6-month, follow-up interval yielded a higher mortality reduction (0.08% for men versus 0.05% for women), and a higher number of deaths averted (36 versus 27), a higher number of screen-detected cases (13 versus 7), and a lower number of combined low-dose CTs and diagnostic follow-ups per death avoided (8 versus 5), per one million general population. Sensitivity analysis of nodule progression threshold verifies a higher mortality reduction with a 1-month earlier follow-up for Lung-RADS 3. CONCLUSIONS: One-month earlier diagnostic follow-ups for individuals with Lung-RADS category 3 nodules may result in a higher mortality reduction and warrants further investigation.

Predicting 90-day modified Rankin Scale score with discharge information in acute ischaemic stroke patients following treatment.

OBJECTIVES: To understand variability in modified Rankin Scale scores from discharge to 90 days in acute ischaemic stroke patients following treatment, and examine prediction of 90-day modified Rankin Scale score by using discharge modified Rankin Scale and discharge disposition. MATERIALS AND METHODS: Retrospective analysis of acute ischaemic stroke patients following treatment was performed from January 2016 to March 2020. Data collection included demographic and clinical characteristics and outcomes data (modified Rankin Scale score at discharge, 30 days and 90 days and discharge disposition). Pearson's χ2 test assessed statistical differences in distribution of modified Rankin Scale scores at discharge, 30 days and 90 days. The predictive power of discharge modified Rankin Scale score and disposition quantified the association with 90-day outcome. RESULTS: A total of 280 acute ischaemic stroke patients (65.4% aged ≥65 years, 47.1% female, 60.7% white) were included in the analysis. The modified Rankin Scale score significantly changed between 30 and 90 days from discharge (p<0.001) after remaining stable from discharge to 30 days (p=0.665). The positive and negative predictive values of an unfavourable long-term outcome for discharge modified Rankin Scale scores of 3-5 were 67.7% (95% CI 60.4% to 75.0%) and 82.0% (95% CI 75.1% to 88.8%), and for non-home discharge disposition were 72.4% (95% CI 64.5% to 80.2%) and 74.5% (95% CI 67.8% to 81.3%), respectively. CONCLUSIONS: Discharge modified Rankin Scale score and non-home discharge disposition are good individual predictors of 90-day modified Rankin Scale score for ischaemic stroke patients following treatment.

Evaluation of the Benefits and Harms of Lung Cancer Screening With Low-Dose Computed Tomography: Modeling Study for the US Preventive Services Task Force.

Importance: The US Preventive Services Task Force (USPSTF) is updating its 2013 lung cancer screening guidelines, which recommend annual screening for adults aged 55 through 80 years who have a smoking history of at least 30 pack-years and currently smoke or have quit within the past 15 years. Objective: To inform the USPSTF guidelines by estimating the benefits and harms associated with various low-dose computed tomography (LDCT) screening strategies. Design, Setting, and Participants: Comparative simulation modeling with 4 lung cancer natural history models for individuals from the 1950 and 1960 US birth cohorts who were followed up from aged 45 through 90 years. Exposures: Screening with varying starting ages, stopping ages, and screening frequency. Eligibility criteria based on age, cumulative pack-years, and years since quitting smoking (risk factor-based) or on age and individual lung cancer risk estimation using risk prediction models with varying eligibility thresholds (risk model-based). A total of 1092 LDCT screening strategies were modeled. Full uptake and adherence were assumed for all scenarios. Main Outcomes and Measures: Estimated lung cancer deaths averted and life-years gained (benefits) compared with no screening. Estimated lifetime number of LDCT screenings, false-positive results, biopsies, overdiagnosed cases, and radiation-related lung cancer deaths (harms). Results: Efficient screening programs estimated to yield the most benefits for a given number of screenings were identified. Most of the efficient risk factor-based strategies started screening at aged 50 or 55 years and stopped at aged 80 years. The 2013 USPSTF-recommended criteria were not among the efficient strategies for the 1960 US birth cohort. Annual strategies with a minimum criterion of 20 pack-years of smoking were efficient and, compared with the 2013 USPSTF-recommended criteria, were estimated to increase screening eligibility (20.6%-23.6% vs 14.1% of the population ever eligible), lung cancer deaths averted (469-558 per 100 000 vs 381 per 100 000), and life-years gained (6018-7596 per 100 000 vs 4882 per 100 000). However, these strategies were estimated to result in more false-positive test results (1.9-2.5 per person screened vs 1.9 per person screened with the USPSTF strategy), overdiagnosed lung cancer cases (83-94 per 100 000 vs 69 per 100 000), and radiation-related lung cancer deaths (29.0-42.5 per 100 000 vs 20.6 per 100 000). Risk model-based vs risk factor-based strategies were estimated to be associated with more benefits and fewer radiation-related deaths but more overdiagnosed cases. Conclusions and Relevance: Microsimulation modeling studies suggested that LDCT screening for lung cancer compared with no screening may increase lung cancer deaths averted and life-years gained when optimally targeted and implemented. Screening individuals at aged 50 or 55 years through aged 80 years with 20 pack-years or more of smoking exposure was estimated to result in more benefits than the 2013 USPSTF-recommended criteria and less disparity in screening eligibility by sex and race/ethnicity.

Risk-Based lung cancer screening: A systematic review.

Lung cancer remains the leading cause of cancer related deaths worldwide. Lung cancer screening using low-dose computed tomography (LDCT) has been shown to reduce lung cancer specific mortality. In 2013, the United States Preventive Services Task Force (USPSTF) recommended annual lung cancer screening with LDCT for smokers aged between 55 years to 80 years, with at least 30 pack-years of smoking exposure that currently smoke or who have quit smoking within 15 years. Risk-based lung cancer screening is an alternative approach that defines screening eligibility based on the personal risk of individuals. Selection of individuals for lung cancer screening based on their personal lung cancer risk has been shown to improve the sensitivity and specificity associated with the eligibility criteria of the screening program as compared to the 2013 USPSTF criteria. Numerous risk prediction models have been developed to estimate the lung cancer risk of individuals incorporating sociodemographic, smoking, and clinical risk factors associated with lung cancer, including age, smoking history, sex, race/ethnicity, personal and family history of cancer, and history of emphysema and chronic obstructive pulmonary disease (COPD), among others. Some risk prediction models include biomarker information, such as germline mutations or protein-based biomarkers as independent risk predictors, in addition to clinical, smoking, and sociodemographic risk factors. While, the majority of lung cancer risk prediction models are suitable for selecting high-risk individuals for lung cancer screening, some risk models have been developed to predict the probability of malignancy of screen-detected solidary pulmonary nodules or to optimize the screening frequency of eligible individuals by incorporating past screening findings. In this systematic review, we provide an overview of existing risk prediction models and their applications to lung cancer screening. We discuss potential strengths and limitations of lung cancer screening using risk prediction models and future research directions.

Disparities of National Lung Cancer Screening Guidelines in the US Population.

BACKGROUND: Current US Preventive Services Task Force (USPSTF) lung cancer screening guidelines are based on smoking history and age (55-80 years). These guidelines may miss those at higher risk, even at lower exposures of smoking or younger ages, because of other risk factors such as race, family history, or comorbidity. In this study, we characterized the demographic and clinical profiles of those selected by risk-based screening criteria but were missed by USPSTF guidelines in younger (50-54 years) and older (71-80 years) age groups. METHODS: We used data from the National Health Interview Survey, the CISNET Smoking History Generator, and results of logistic prediction models to simulate lifetime lung cancer risk-factor data for 100 000 individuals in the 1950-1960 birth cohorts. We calculated age-specific 6-year lung cancer risk for each individual from ages 50 to 90 years using the PLCOm2012 model and evaluated age-specific screening eligibility by USPSTF guidelines and by risk-based criteria (varying thresholds between 1.3% and 2.5%). RESULTS: In the 1950 birth cohort, 5.4% would have been ineligible for screening by USPSTF criteria in their younger ages but eligible based on risk-based criteria. Similarly, 10.4% of the cohort would be ineligible for screening by USPSTF in older ages. Notably, high proportions of blacks were ineligible for screening by USPSTF criteria at younger (15.6%) and older (14.2%) ages, which were statistically significantly greater than those of whites (4.8% and 10.8%, respectively; P < .001). Similar results were observed with other risk thresholds and for the 1960 cohort. CONCLUSIONS: Further consideration is needed to incorporate comprehensive risk factors, including race and ethnicity, into lung cancer screening to reduce potential racial disparities.

A Comparative Modeling Analysis of Risk-Based Lung Cancer Screening Strategies.

BACKGROUND: Risk-prediction models have been proposed to select individuals for lung cancer screening. However, their long-term effects are uncertain. This study evaluates long-term benefits and harms of risk-based screening compared with current United States Preventive Services Task Force (USPSTF) recommendations. METHODS: Four independent natural history models were used to perform a comparative modeling study evaluating long-term benefits and harms of selecting individuals for lung cancer screening through risk-prediction models. In total, 363 risk-based screening strategies varying by screening starting and stopping age, risk-prediction model used for eligibility (Bach, PLCOm2012, or Lung Cancer Death Risk Assessment Tool [LCDRAT]), and risk threshold were evaluated for a 1950 US birth cohort. Among the evaluated outcomes were percentage of individuals ever screened, screens required, lung cancer deaths averted, life-years gained, and overdiagnosis. RESULTS: Risk-based screening strategies requiring similar screens among individuals ages 55-80 years as the USPSTF criteria (corresponding risk thresholds: Bach = 2.8%; PLCOm2012 = 1.7%; LCDRAT = 1.7%) averted considerably more lung cancer deaths (Bach = 693; PLCOm2012 = 698; LCDRAT = 696; USPSTF = 613). However, life-years gained were only modestly higher (Bach = 8660; PLCOm2012 = 8862; LCDRAT = 8631; USPSTF = 8590), and risk-based strategies had more overdiagnosed cases (Bach = 149; PLCOm2012 = 147; LCDRAT = 150; USPSTF = 115). Sensitivity analyses suggest excluding individuals with limited life expectancies (<5 years) from screening retains the life-years gained by risk-based screening, while reducing overdiagnosis by more than 65.3%. CONCLUSIONS: Risk-based lung cancer screening strategies prevent considerably more lung cancer deaths than current recommendations do. However, they yield modest additional life-years and increased overdiagnosis because of predominantly selecting older individuals. Efficient implementation of risk-based lung cancer screening requires careful consideration of life expectancy for determining optimal individual stopping ages.

Cost-Effectiveness Analysis of Lung Cancer Screening in the United States: A Comparative Modeling Study.

Background: Recommendations vary regarding the maximum age at which to stop lung cancer screening: 80 years according to the U.S. Preventive Services Task Force (USPSTF), 77 years according to the Centers for Medicare & Medicaid Services (CMS), and 74 years according to the National Lung Screening Trial (NLST). Objective: To compare the cost-effectiveness of different stopping ages for lung cancer screening. Design: By using shared inputs for smoking behavior, costs, and quality of life, 4 independently developed microsimulation models evaluated the health and cost outcomes of annual lung cancer screening with low-dose computed tomography (LDCT). Data Sources: The NLST; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; SEER (Surveillance, Epidemiology, and End Results) program; Nurses' Health Study and Health Professionals Follow-up Study; and U.S. Smoking History Generator. Target Population: Current, former, and never-smokers aged 45 years from the 1960 U.S. birth cohort. Time Horizon: 45 years. Perspective: Health care sector. Intervention: Annual LDCT according to NLST, CMS, and USPSTF criteria. Outcome Measures: Incremental cost-effectiveness ratios (ICERs) with a willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY). Results of Base-Case Analysis: The 4 models showed that the NLST, CMS, and USPSTF screening strategies were cost-effective, with ICERs averaging $49 200, $68 600, and $96 700 per QALY, respectively. Increasing the age at which to stop screening resulted in a greater reduction in mortality but also led to higher costs and overdiagnosis rates. Results of Sensitivity Analysis: Probabilistic sensitivity analysis showed that the NLST and CMS strategies had higher probabilities of being cost-effective (98% and 77%, respectively) than the USPSTF strategy (52%). Limitation: Scenarios assumed 100% screening adherence, and models extrapolated beyond clinical trial data. Conclusion: All 3 sets of lung cancer screening criteria represent cost-effective programs. Despite underlying uncertainty, the NLST and CMS screening strategies have high probabilities of being cost-effective. Primary Funding Source: CISNET (Cancer Intervention and Surveillance Modeling Network) Lung Group, National Cancer Institute.

Assessment of occupational safety risks in Floridian solid waste systems using Bayesian analysis.

Safety risks embedded within solid waste management systems continue to be a significant issue and are prevalent at every step in the solid waste management process. To recognise and address these occupational hazards, it is necessary to discover the potential safety concerns that cause them, as well as their direct and/or indirect impacts on the different types of solid waste workers. In this research, our goal is to statistically assess occupational safety risks to solid waste workers in the state of Florida. Here, we first review the related standard industrial codes to major solid waste management methods including recycling, incineration, landfilling, and composting. Then, a quantitative assessment of major risks is conducted based on the data collected using a Bayesian data analysis and predictive methods. The risks estimated in this study for the period of 2005-2012 are then compared with historical statistics (1993-1997) from previous assessment studies. The results have shown that the injury rates among refuse collectors in both musculoskeletal and dermal injuries have decreased from 88 and 15 to 16 and three injuries per 1000 workers, respectively. However, a contrasting trend is observed for the injury rates among recycling workers, for whom musculoskeletal and dermal injuries have increased from 13 and four injuries to 14 and six injuries per 1000 workers, respectively. Lastly, a linear regression model has been proposed to identify major elements of the high number of musculoskeletal and dermal injuries.