Chapter 3: Cohort life tables by smoking status, removing lung cancer as a cause of death

The potential impact of removing a ban on electronic nicotine delivery systems using the Mexico smoking and vaping model (SAVM)

Objective

To develop the Mexico Smoking and Vaping Model (Mexico SAVM) to estimate cigarette and electronic nicotine delivery systems (ENDS) prevalence and the public health impact of legalizing ENDS use.

Methods

SAVM, a cohort-based discrete-time simulation model, compares two scenarios. The ENDS-Restricted Scenario estimates smoking prevalence and associated mortality outcomes under the current policy of an ENDS ban, using Mexico-specific population projections, death rates, life expectancy, and smoking and e-cigarette prevalence. The ENDS-Unrestricted Scenario projects smoking and vaping prevalence under a hypothetical scenario where ENDS use is allowed. The impact of legalizing ENDS use is estimated as the difference in smoking- and vaping-attributable deaths (SVADs) and life-years lost (LYLs) between the ENDS-Restricted and Unrestricted scenarios.

Results

Compared to a national ENDS ban, The Mexico SAVM projects that legalizing ENDS use could decrease smoking prevalence by 40.1% in males and 30.9% in females by 2049 compared to continuing the national ENDS ban. This reduction in prevalence would save 2.9 (2.5 males and 0.4 females) million life-years and avert almost 106 (91.0 males and 15.5 females) thousand deaths between 2025 and 2049. Public health gains decline by 43% to 59,748 SVADs averted when the switching rate is reduced by half and by 24.3% (92,806 SVADs averted) with a 25% ENDS risk level from that of cigarettes but increased by 24.3% (121,375 SVADs averted) with the 5% ENDS risk.

Conclusions

Mexico SAVM suggests that greater access to ENDS and a more permissive ENDS regulation, simultaneous with strong cigarette policies, would reduce smoking prevalence and decrease smoking-related mortality. The unanticipated effects of an ENDS ban merit closer scrutiny, with further consideration of how specific ENDS restrictions may maximize public health benefits.

The smoking and vaping model, A user-friendly model for examining the country-specific impact of nicotine VAPING product use: application to Germany

BACKGROUND

Simulation models play an increasingly important role in tobacco control. Models examining the impact of nicotine vaping products (NVPs) and smoking tend to be highly specialized and inaccessible. We present the Smoking and Vaping Model (SAVM),a user-friendly cohort-based simulation model, adaptable to any country, that projects the public health impact of smokers switching to NVPs.

METHODS

SAVM compares two scenarios. The No-NVP scenario projects smoking rates in the absence of NVPs using population projections, deaths rates, life expectancy, and smoking prevalence. The NVP scenario models vaping prevalence and its impact on smoking once NVPs became popular. NVP use impact is estimated as the difference in smoking- and vaping-attributable deaths (SVADs) and life-years lost (LYLs) between the No-NVP and NVP scenarios. We illustrate SAVM's adaptation to the German adult ages 18+ population, the Germany-SAVM by adjusting the model using population, mortality, smoking and NVP use data.

RESULTS

Assuming that the excess NVP mortality risk is 5% that of smoking, Germany-SAVM projected 4.7 million LYLs and almost 300,000 SVADs averted associated with NVP use from 2012 to 2060. Increasing the excess NVP mortality risk to 40% with other rates constant resulted in averted 2.8 million LYLs and 200,000 SVADs during the same period.

CONCLUSIONS

SAVM enables non-modelers, policymakers, and other stakeholders to analyze the potential population health effects of NVP use and public health interventions.

Mortality Relative Risks by Smoking, Race/Ethnicity, and Education

INTRODUCTION

The impact of cigarette smoking on mortality is well studied, with estimates of the relative mortality risks for the overall population widely available. However, age-specific mortality estimates for different sociodemographic groups in the U.S. are lacking.

METHODS

Using the 1987-2018 National Health Interview Survey Linked Mortality Files through 2019, all-cause mortality relative risks (RRs) were estimated for current smokers or recent quitters and long-term quitters compared with those for never smokers. Stratified Cox proportional hazards regression models were used to estimate RRs by age, gender, race/ethnicity, and educational attainment. RRs were also assessed for current smokers or recent quitters by smoking intensity and for long-term quitters by years since quitting. The analysis was conducted in 2021-2022.

RESULTS

All-cause mortality RRs among current smokers or recent quitters were generally highest for non-Hispanic White individuals than for never smokers, followed by non-Hispanic Black individuals, and were lowest for Hispanic individuals. RRs varied greatly by educational attainment; generally, higher-education groups had greater RRs associated with smoking than lower-education groups. Conversely, the RRs by years since quitting among long-term quitters did not show clear differences across race/ethnicity and education groups. Age-specific RR patterns varied greatly across racial/ethnic and education groups as well as by gender.

CONCLUSIONS

Age-specific all-cause mortality rates associated with smoking vary considerably by sociodemographic factors. Among high-education groups, lower underlying mortality rates for never smokers result in correspondingly high RR estimates for current smoking. These estimates can be incorporated in modeling analyses to assess tobacco control interventions' impact on smoking-related health disparities between different sociodemographic groups.

Monitoring the Increase in the U.S. Smoking Cessation Rate and its Implication for Future Smoking Prevalence

INTRODUCTION

We calculate the U.S. adult smoking cessation rate for 2014-2019, compare it to the historical trend, and estimate the implication for future smoking prevalence.

METHODS

We repeated an earlier analysis, which examined the cessation rate from 1990-2014, extending the period to 2019. Employing National Health Interview Survey (NHIS) and National Survey on Drug Use and Health (NSDUH) data, we estimated the adult cessation rate in six-year intervals, using weighted non-linear least squares. We then employed a meta-regression model to test whether the cessation rate has increased beyond expectation. We used cessation rate estimates and smoking initiation rate estimates to project smoking prevalence in 2030 and eventual steady-state prevalence.

RESULTS

The annual cessation rate increased 29% using NHIS data (from 4.2% in 2008-2013 to 5.4% in 2014-2019) and 33% with NSDUH data (4.2% to 5.6%). The cessation rate increase accounts for 60% of a smoking prevalence decline in the most recent period exceeding the 1990-2013 predicted trend. The remaining 40% owes to declining smoking initiation. With current initiation and cessation rates, smoking prevalence should fall to 8.3% in 2030 and eventually reach a steady state of 3.53%.

CONCLUSIONS

The smoking cessation rate continued to increase during 2014-2019. NHIS and NSDUH results are practically identical. The larger share (60%) of the smoking prevalence decrease, beyond expectation, attributable to the increased cessation rate is encouraging since the positive health effects of cessation occur much sooner than those derived from declining initiation.

IMPLICATIONS

The smoking cessation rate in the U.S. continues to increase, accelerating the decline in smoking prevalence. This increase suggests that the Healthy People 2030 goal of 5% adult smoking prevalence, while ambitious, is attainable. Our findings can be used in simulation and statistical models that aim to predict future prevalence and population health effects due to smoking under various scenarios.

Cost-Effectiveness of Four Financial Incentive Programs for Smoking Cessation

Rationale: A trial of four financial incentive programs, conducted at CVS Caremark, a large employer, documented their effectiveness in promoting sustained abstinence from smoking, but their cost-effectiveness is unknown, and the significant up-front cost of the incentives is a deterrent to their adoption. Objectives: To determine the cost-effectiveness of these incentives from the healthcare sector and employer perspectives. Methods: This study examines a decision model built with trial data, supplemented by data from the literature. Life-expectancy gains for quitters were projected on the basis of U.S. life tables. The two individual-oriented programs paid $800 for smoking cessation at 6 months; one required participants to deposit $150 at baseline. Payments in the two group-oriented programs varied with the group's success; again, one required participants to deposit $150. Results: Life-years, quality-adjusted life-years (QALYs), costs (2012 dollars), and cost-effectiveness ratios are described. From the healthcare sector perspective, costs ranged from $3,200 per life-year ($2,500 per QALY) for the competitive deposit program, compared with usual care, to $6,500 per life-year ($5,100 per QALY) for the individual reward program. From the employer perspective, costs ranged from $256,600 per life-year gained for the individual deposit program to $1,711,100 per life-year gained for the individual reward program; the cost per QALY ranged from $65,300 for the competitive deposit program to $128,800 for the individual reward program. Cost-effectiveness from the employer perspective improved with longer decision horizons. Including future medical costs reduced cost-effectiveness from both perspectives. Conclusions: Four financial incentive programs that paid smokers to quit are very cost-effective from the healthcare sector perspective. They are more expensive from the employer perspective but may be cost-effective for employers with longer decision horizons.

Cost-Effectiveness of Smoking Cessation Interventions in the Lung Cancer Screening Setting: A Simulation Study

BACKGROUND

Guidelines recommend offering cessation interventions to smokers eligible for lung cancer screening, but there is little data comparing specific cessation approaches in this setting. We compared the benefits and costs of different smoking cessation interventions to help screening programs select specific cessation approaches.

METHODS

We conducted a societal-perspective cost-effectiveness analysis using a Cancer Intervention and Surveillance Modeling Network model simulating individuals born in 1960 over their lifetimes. Model inputs were derived from Medicare, national cancer registries, published studies, and micro-costing of cessation interventions. We modeled annual lung cancer screening following 2014 US Preventive Services Task Force guidelines plus cessation interventions offered to current smokers at first screen, including pharmacotherapy only or pharmacotherapy with electronic and/or web-based, telephone, individual, or group counseling. Outcomes included lung cancer cases and deaths, life-years saved, quality-adjusted life-years (QALYs) saved, costs, and incremental cost-effectiveness ratios.

RESULTS

Compared with screening alone, all cessation interventions decreased cases of and deaths from lung cancer. Compared incrementally, efficient cessation strategies included pharmacotherapy with either web-based cessation ($555 per QALY), telephone counseling ($7562 per QALY), or individual counseling ($35 531 per QALY). Cessation interventions continued to have costs per QALY well below accepted willingness to pay thresholds even with the lowest intervention effects and was more cost-effective in cohorts with higher smoking prevalence.

CONCLUSION

All smoking cessation interventions delivered with lung cancer screening are likely to provide benefits at reasonable costs. Because the differences between approaches were small, the choice of intervention should be guided by practical concerns such as staff training and availability.

Cost-Effectiveness of Treatment Thresholds for Subsolid Pulmonary Nodules in CT Lung Cancer Screening

Background Guidelines such as the Lung CT Screening Reporting and Data System (Lung-RADS) are available for determining when subsolid nodules should be treated within lung cancer screening programs, but they are based on expert opinion. Purpose To evaluate the cost-effectiveness of varying treatment thresholds for subsolid nodules within a lung cancer screening setting by using a simulation model. Materials and Methods A previously developed model simulated 10 million current and former smokers undergoing CT lung cancer screening who were assumed to have a ground-glass nodule (GGN) at baseline. Nodules were allowed to grow and to develop solid components over time according to a monthly cycle and lifetime horizon. Management strategies generated by varying treatment thresholds, including the solid component size and use of the Brock risk calculator, were tested. For each strategy, average U.S. costs and quality-adjusted life years (QALYs) gained per patient were computed, and the incremental cost-effectiveness ratios (ICERs) of those on the efficient frontier were calculated. One-way and probabilistic sensitivity analyses of results were performed by varying several relevant parameters, such as treatment costs or malignancy growth rates. Results Variants of the Lung-RADS guidelines that did not treat pure GGNs were cost-effective. Strategies based on the Brock risk calculator did not reach the efficient frontier. The strategy with the highest QALYs under a willingness-to-pay threshold of $100 000 per QALY included no treatment of GGNs and a threshold of 4-mm solid component size for treatment of subsolid nodules. This strategy yielded an ICER of $52 993 per QALY (95% CI: 44 407, 64 372). Probabilistic sensitivity analysis showed this was the optimal strategy under a range of parameter variations. Conclusion Treatment of pure ground-glass nodules was not cost-effective. Strategies that use modifications of the Lung CT Screening Reporting and Data System guidelines were cost-effective for treating part-solid nodules; an optimal threshold of 4 mm for the solid component yielded the most quality-adjusted life years. © RSNA, 2021 Online supplemental material is available for this article.

US Nicotine Vaping Product SimSmoke Simulation Model: The Effect of Vaping and Tobacco Control Policies on Smoking Prevalence and Smoking-Attributable Deaths

The public health impact of nicotine vaping products (NVPs) is subject to a complex set of uncertain transitions between NVP and cigarette use. Instead, we apply an indirect method to gauge the impact of NVP use on smoking prevalence and smoking-attributable deaths (SADs) using the well-established SimSmoke tobacco control policy simulation model. Upon validating the model before NVPs were more widely used, we project a No-NVP (i.e., in the absence of NVPs) while controlling for the impact of cigarette-oriented policies. The net impact of NVPs on smoking prevalence is inferred by comparing the projected No-NVP smoking trends to corresponding trends from two US national surveys. Using the TUS-CPS estimates for the period 2012-2018, we estimate that adult smoking prevalence declined in relative terms by 9.7% (95% CI: 7.5-11.7%) for males and 10.7% (95% CI: 9.1-13.0%) for females. Compared to NHIS, smoking prevalence declined by 10.7% (95% CI: 6.8-14.6%) for males and 11.3% (95% CI: 7.4-15.6%) for females. These impacts were confined mainly to ages 18-44. Vaping-related reductions in smoking prevalence were projected to avert nearly 0.4 million SADs between 2012 and 2052. Our analysis indicates that NVP use is associated with substantial reductions in US smoking prevalence among younger adults.

The Public Health Gains Had Cigarette Companies Chosen to Sell Very Low Nicotine Cigarettes

INTRODUCTION

The U.S. Food and Drug Administration (FDA) has proposed lowering the nicotine content of cigarettes to a minimally addictive level to increase smoking cessation and reduce initiation. This study has two aims: (1) to determine when cigarette manufacturers had the technical capability to reduce cigarette nicotine content and (2) to estimate the lost public health benefits of implementing a standard in 1965, 1975, or 1985.

METHODS

To determine the technical capability of cigarette companies, we reviewed public patents and internal cigarette company business records using the Truth Tobacco Industry Documents. To evaluate the impact of a very low nicotine content cigarette (VLNC) standard on smoking attributable deaths (SADs) and life-years lost (LYLs), we applied a validated (CISNET) model that uses past smoking data, along with estimates of the potential impact of VLNCs derived from expert elicitation.

RESULTS

Cigarette manufacturers recognized that cigarettes were deadly and addictive before 1964. Manufacturers have had the technical capability to lower cigarette nicotine content for decades. Our model projected that a standard implemented in 1965 could have averted 21 million SADs (54% reduction) and 272 million LYLs (64% reduction) from 1965 to 2064, a standard implemented in 1975 could have averted 18.9 million SADs and 245.4 million LYLs from 1975 to 2074, and a standard implemented in 1985 could have averted 16.3 million SADs and 211.5 million LYLs from 1985 to 2084.

CONCLUSIONS

Millions of premature deaths could have been averted if companies had only sold VLNCs decades ago. FDA should act immediately to implement a VLNC standard.

IMPLICATIONS

Prior research has shown that a mandated reduction in the nicotine content of cigarettes could reduce the prevalence of smoking and improve public health. Here we report that cigarette manufacturers have had the ability to voluntarily implement such a standard for decades. We use a well-validated model to demonstrate that millions of smoking attributable deaths and life-years lost would have been averted if the industry had implemented such a standard.

Public health implications of vaping in the USA: the smoking and vaping simulation model

Background

Nicotine vaping products (NVPs) are increasingly popular worldwide. They may provide public health benefits if used as a substitute for smoking, but may create public health harms if used as a gateway to smoking or to discourage smoking cessation. This paper presents the Smoking and Vaping Model (SAVM), a user-friendly model which estimates the public health implications of NVPs in the USA.

Methods

SAVM adopts a cohort approach. We derive public health implications by comparing smoking- and NVP-attributable deaths and life-years lost under a No-NVP and an NVP Scenario. The No-NVP Scenario projects current, former, and never smoking rates via smoking initiation and cessation rates, with their respective mortality rates. The NVP Scenario allows for smoking- and NVP-specific mortality rates, switching from cigarette to NVP use, separate NVP and smoking initiation rates, and separate NVP and smoking cessation rates. After validating the model against recent US survey data, we present the base model with extensive sensitivity analyses.

Results

The SAVM projects that under current patterns of US NVP use and substitution, NVP use will translate into 1.8 million premature smoking- and vaping-attributable deaths avoided and 38.9 million life-years gained between 2013 and 2060. When the NVP relative risk is set to 5%, the results are sensitive to the level of switching and smoking cessation rates and to a lesser extent smoking initiation rates. When the NVP relative risk is raised to 40%, the public health gains in terms of averted deaths and LYL are reduced by 42% in the base case, and the results become much more sensitive to variations in the base case parameters.

Discussion

Policymakers, researchers, and other public health stakeholders can apply the SAVM to estimate the potential public health impact of NVPs in their country or region using their own data sources. In developing new simulation models involving NVPs, it will be important to conduct extensive sensitivity analysis and continually update and validate with new data.

Conclusion

The SAVM indicates the potential benefits of NVP use. However, given the uncertainty surrounding model parameters, extensive sensitivity analysis becomes particularly important.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12963-021-00250-7.

Prediction of COPD risk accounting for time-varying smoking exposures

RATIONALE

Chronic Obstructive Pulmonary Disease (COPD) is the fourth leading cause of death in the United States. Studies have primarily assessed the relationship between smoking on COPD risk focusing on summary measures, like smoking status.

OBJECTIVE

Develop a COPD risk prediction model incorporating individual time-varying smoking exposures.

METHODS

The Nurses' Health Study (N = 86,711) and the Health Professionals Follow-up Study (N = 39,817) data was used to develop a COPD risk prediction model. Data was randomly split in 50-50 samples for model building and validation. Cox regression with time-varying covariates was used to assess the association between smoking duration, intensity and year-since-quit and self-reported COPD diagnosis incidence. We evaluated the model calibration as well as discriminatory accuracy via the Area Under the receiver operating characteristic Curve (AUC). We computed 6-year risk of COPD incidence given various individual smoking scenarios.

RESULTS

Smoking duration, year-since-quit (if former smokers), sex, and interaction of sex and smoking duration are significantly associated with the incidence of diagnosed COPD. The model that incorporated time-varying smoking variables yielded higher AUCs compared to models using only pack-years. The AUCs for the model were 0.80 (95% CI: 0.74-0.86) and 0.73 (95% CI: 0.70-0.77) for males and females, respectively.

CONCLUSIONS

Utilizing detailed smoking pattern information, the model predicts COPD risk with better accuracy than models based on only smoking summary measures. It might serve as a tool for early detection programs by identifying individuals at high-risk for COPD.

Modeling smoking-attributable mortality among adults with major depression in the United States

Tobacco-related health disparities disproportionately affect smokers with major depression (MD). Although tobacco simulation models have been applied to general populations, to date they have not considered populations with a comorbid mental health condition. We developed and calibrated a simulation model of smoking and MD comorbidity for the US adult population using the 2005-2018 National Surveys on Drug Use and Health. We use this model to evaluate trends in smoking prevalence, smoking-attributable mortality and life-years lost among adults with MD, and changes in smoking prevalence by mental health status from 2018 to 2060. The model integrates known interaction effects between smoking initiation and cessation, and MD onset and recurrence. We show that from 2018 to 2060, smoking prevalence will continue declining among those with current MD. In the absence of intervention, people with MD will be increasingly disproportionately affected by smoking compared to the general population; our model shows that the smoking prevalence ratio between those with current MD and those without a history of MD increases from 1.54 to 2.42 for men and from 1.81 to 2.73 for women during this time period. From 2018 to 2060, approximately 484,000 smoking-attributable deaths will occur among adults with current MD, leading to 11.3 million life-years lost. Ambitious tobacco control efforts could alter this trajectory. With aggressive public health efforts, up to 264,000 of those premature deaths could be avoided, translating into 7.5 million life years gained. This model can compare the relative health gains across different intervention strategies for smokers with MD.

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.

Reporting net survival in populations: a sensitivity analysis in lung cancer demonstrates the differential implications of reporting relative survival and cause-specific survival

Background

Net survival is commonly quantified as relative survival (observed survival among lung cancer patients versus expected survival among the general population) and cause-specific survival (lung cancer–specific survival among lung cancer patients). These approaches have drastically different assumptions; hence, failure to distinguish between them results in significant implications for study findings. We quantified the differences between relative and cause-specific survival when reporting net survival of patients with non-small cell lung cancer (NSCLC).

Methods

Cases of NSCLC diagnosed between 2004 and 2014 were extracted from the Surveillance, Epidemiology, and End Results database. The net survival of each stage-by-age stratum was expressed as cause-specific survival (Kaplan-Meier approach) and relative survival (Ederer II approach); percentage-point (pp) differences between the survival estimates were quantified up to 10 years postdiagnosis.

Results

Analyses included 263,894 cases. Cause-specific survival estimates were higher than relative survival estimates across all strata. Although the differences were negligible at 1 year postdiagnosis, they increased with increasing years of follow-up, up to 9.3 pp at 10 years (eg, aged 60–74 with stage I disease: 53.0% vs 43.7%). Differences in survival estimates between the methods also increased by increasing age groups (eg, at 10 years postdiagnosis: 5.1 pp for ages 18–44, 8.8 pp for ages 45–59, and 9.3 pp for ages 60–74) but decreased drastically for those aged ≥75 (3.1 pp).

Conclusion

Relative survival and cause-specific survival are not interchangeable. The type of survival estimate used in cancer studies should be specified, particularly for long-term survival.

Differences in Cancer Survival with Relative versus Cause-Specific Approaches: An Update Using More Accurate Life Tables

BACKGROUND

We investigated differences in net cancer survival (survival observed if the only possible cause of death was the cancer under study) estimated using new approaches for relative survival (RS) and cause-specific survival (CSS).

METHODS

We used SEER data for patients diagnosed in 2000 to 2013, followed-up through December 31, 2014. For RS, we used new life tables accounting for geography and socio-economic status. For CSS, we used the SEER cause of death algorithm for attributing cancer-specific death. Estimates were compared by site, age, stage, race, and time since diagnosis.

RESULTS

Differences between 5-year RS and CSS were generally small. RS was always higher in screen-detectable cancers, for example, female breast (89.2% vs. 87.8%) and prostate (98.5% vs. 93.7%) cancers; differences increased with age or time since diagnosis. CSS was usually higher in the remaining cancer sites, particularly those related to specific risk factors, for example, cervix (70.9% vs. 68.3%) and liver (20.7% vs. 17.1%) cancers. For most cancer sites, the gap between estimates was smaller with more advanced stage.Conclusion: RS is the preferred approach to report cancer survival from registry data because cause of death may be inaccurate, particularly for older patients and long-term survivors as comorbidities increase challenges in determining cause of death. However, CSS proved to be more reliable in patients diagnosed with localized disease or cancers related to specific risk factors as general population life tables may not capture other causes of mortality.

IMPACT

Different approaches for net survival estimation should be considered depending on cancer under study.

Predicting the Epidemiological Dynamics of Lung Cancer in Japan

While the prevalence of smoking has steadily declined over time, the absolute numbers of lung cancer cases and deaths have continued to increase in Japan. We employed a simple mathematical model that describes the relationship between demographic dynamics and smoking prevalence to predict future epidemiological trends of lung cancer by age and sex. Never-smokers, smokers, and ex-smokers were assumed to experience different hazard of lung cancer, and the model was parameterized using data from 2014 and before, as learning data, and a future forecast was obtained from 2015 onwards. The maximum numbers of lung cancer cases and deaths in men will be 76,978 (95% confidence interval (CI): 76,630⁻77,253) and 63,284 (95% CI: 62,991⁻63507) in 2024, while those in women will be 42,838 (95% CI: 42,601⁻43,095) and 32,267 (95% CI: 32,063⁻32,460) in 2035 and 2036, respectively. Afterwards, the absolute numbers of cases and deaths are predicted to decrease monotonically. Our compartmental modeling approach is well suited to predicting lung cancer in Japan with dynamic ageing and drastic decline in smoking prevalence. The predicted burden is useful for anticipating demands for diagnosis, treatment, and care in the healthcare sector.

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.

Lung Cancer Mortality Associated With Smoking and Smoking Cessation Among People Living With HIV in the United States

Importance

Lung cancer has become a leading cause of death among people living with human immunodeficiency virus (HIV) (PLWH). Over 40% of PLWH in the United States smoke cigarettes; HIV independently increases the risk of lung cancer.

Objective

To project cumulative lung cancer mortality by smoking exposure among PLWH in care.

Design

Using a validated microsimulation model of HIV, we applied standard demographic data and recent HIV/AIDS epidemiology statistics with specific details on smoking exposure, combining smoking status (current, former, or never) and intensity (heavy, moderate, or light). We stratified reported mortality rates attributable to lung cancer and other non-AIDS-related causes by smoking exposure and accounted for an HIV-conferred independent risk of lung cancer. Lung cancer mortality risk ratios (vs never smokers) for male and female current moderate smokers were 23.6 and 24.2, respectively, and for those who quit smoking at age 40 years were 4.3 and 4.5. In sensitivity analyses, we accounted for nonadherence to antiretroviral therapy (ART) and for a range of HIV-conferred risks of death from lung cancer and from other non-AIDS-related diseases (eg, cardiovascular disease).

Main Outcomes and Measures

Cumulative lung cancer mortality by age 80 years (stratified by sex, age at entry to HIV care, and smoking exposure); total expected lung cancer deaths, accounting for nonadherence to ART.

Results

Among 40-year-old men with HIV, estimated cumulative lung cancer mortality for heavy, moderate, and light smokers who continued to smoke was 28.9%, 23.0%, and 18.8%, respectively; for those who quit smoking at age 40 years, it was 7.9%, 6.1%, and 4.3%; and for never smokers, it was 1.6%. Among women, the corresponding mortality for current smokers was 27.8%, 20.9%, and 16.6%; for former smokers, it was 7.5%, 5.2%, and 3.7%; and for never smokers, it was 1.2%. ART-adherent individuals who continued to smoke were 6 to 13 times more likely to die from lung cancer than from traditional AIDS-related causes, depending on sex and smoking intensity. Due to greater AIDS-related mortality risks, individuals with incomplete ART adherence had higher overall mortality but lower lung cancer mortality. Applying model projections to the approximately 644 200 PLWH aged 20 to 64 in care in the United States, 59 900 (9.3%) are expected to die from lung cancer if smoking habits do not change.

Conclusions and Relevance

Those PLWH who adhere to ART but smoke are substantially more likely to die from lung cancer than from AIDS-related causes.

Potential deaths averted in USA by replacing cigarettes with e-cigarettes

Introduction

US tobacco control policies to reduce cigarette use have been effective, but their impact has been relatively slow. This study considers a strategy of switching cigarette smokers to e-cigarette use (‘vaping’) in the USA to accelerate tobacco control progress.

Methods

A Status Quo Scenario, developed to project smoking rates and health outcomes in the absence of vaping, is compared with Substitution models, whereby cigarette use is largely replaced by vaping over a 10-year period. We test an Optimistic and a Pessimistic Scenario, differing in terms of the relative harms of e-cigarettes compared with cigarettes and the impact on overall initiation, cessation and switching. Projected mortality outcomes by age and sex under the Status Quo and E-Cigarette Substitution Scenarios are compared from 2016 to 2100 to determine public health impacts.

Findings

Compared with the Status Quo, replacement of cigarette by e-cigarette use over a 10-year period yields 6.6 million fewer premature deaths with 86.7 million fewer life years lost in the Optimistic Scenario. Under the Pessimistic Scenario, 1.6 million premature deaths are averted with 20.8 million fewer life years lost. The largest gains are among younger cohorts, with a 0.5 gain in average life expectancy projected for the age 15 years cohort in 2016.

Conclusions

The tobacco control community has been divided regarding the role of e-cigarettes in tobacco control. Our projections show that a strategy of replacing cigarette smoking with vaping would yield substantial life year gains, even under pessimistic assumptions regarding cessation, initiation and relative harm.

Biases in Individualized Cost-effectiveness Analysis: Influence of Choices in Modeling Short-Term, Trial-Based, Mortality Risk Reduction and Post-Trial Life Expectancy

BACKGROUND

The benefits and costs of a treatment are typically heterogeneous across individual patients. Randomized clinical trials permit the examination of individualized treatment benefits over the trial horizon but extrapolation to lifetime horizon usually involves combining trial-based individualized estimates of short-term risk reduction with less detailed (less granular) population life tables. However, the underlying assumption of equal post-trial life expectancy for low- and high-risk patients of the same sex and age is unrealistic. We aimed to study the influence of unequal granularity between models of short-term risk reduction and life expectancy on individualized estimates of cost-effectiveness of aggressive thrombolysis for patients with an acute myocardial infarction.

METHODS

To estimate life years gained, we multiplied individualized estimates of short-term risk reduction either with less granular and with equally granular post-trial life expectancy estimates. Estimates of short-term risk reduction were obtained from GUSTO trial data (30,510 patients) using logistic regression analysis with treatment, sex, and age as predictor variables. Life expectancy estimates were derived from sex- and age-specific US life tables.

RESULTS

Based on sex- and age-specific, short-term risk reductions but average population life expectancy (less granularity), we found that aggressive thrombolysis was cost-effective (incremental cost-effectiveness ratio below $50,000) for women above age 49 y and men above age 53 y (92% and 69% of the population, respectively). Considering sex- and age-specific short-term mortality risk reduction and correspondingly sex- and age-specific life expectancy (equal granularity), aggressive thrombolysis was cost-effective for men above age 45 y and women above age 50 y (95% and 76% of the population, respectively).

CONCLUSIONS

Failure to model short-term risk reduction and life expectancy at an equal level of granularity may bias our estimates of individualized cost-effectiveness and misallocate resources.

Smoking and the Reduced Life Expectancy of Individuals With Serious Mental Illness

INTRODUCTION

People with serious mental illness experience substantially reduced life expectancy, likely due in part to their higher smoking rates relative to the general population. However, the extent to which smoking affects their life expectancy, independent of mental illness, is unknown. This study quantifies the potential contribution of smoking to reduced life expectancy among individuals with serious psychological distress (SPD), a measure that screens for serious mental illness in national surveys.

METHODS

A cohort of 328,110 U.S. adults was examined using the 1997-2009 National Health Interview Surveys linked to the 2011 National Death Index. Cox models were used to estimate mortality hazard ratios for current smoking, former smoking, and SPD and construct life tables by smoking and SPD status. The smoking-attributable fraction of deaths by SPD status was calculated. Analyses were conducted in 2015.

RESULTS

Among those with SPD, being a current smoker doubles the risk of death. Current smokers with SPD lose 14.9 years of life relative to never smokers without SPD. Among never smokers, having SPD reduces life expectancy by 5.3 years. Thus, smoking may account for up to two thirds of the difference in life expectancy between smokers with SPD and never smokers without SPD. One third of deaths among those with SPD can be attributed to smoking.

CONCLUSIONS

The life expectancy difference between current smokers with SPD and never smokers without SPD is primarily due to smoking. Aiding individuals with serious mental illness to avoid smoking will translate into sizeable gains in life expectancy.

Trends in Subpopulations at High Risk for Lung Cancer

INTRODUCTION

Two-thirds of patients in the United States with newly diagnosed lung cancer would not meet the current U.S. Preventive Services Task Force (USPSTF) screening criteria, which suggests a need for amendment of the definition of high risk. To provide evidence of additional high-risk subpopulations and estimated gains and losses from using different criteria for screening eligibility, we conducted a two-step study using three cohorts.

METHODS

The two prospective cohorts comprised 5988 patients in whom primary lung cancer was diagnosed between 1997 and 2011 (the hospital cohort) and 850 defined-community residents (the community cohort); the retrospective cohort consisted of the population of Olmsted County, Minnesota, which was observed for 28 years (1984-2011). Subgroups of patients with lung cancer who might have been identified using additional determinates were estimated and compared between the community and hospital cohorts. The findings were supported by indirect comparative projections of two ratios: benefit to harm and cost to effectiveness.

RESULTS

Former cigarette smokers who had a smoking history of 30 or more pack-years and 15 to 30 quit-years and were 55 to 80 years old formed the largest subgroup not meeting the current screening criteria; they constituted 12% of the hospital cohort and 17% of community cohort. Using the expanded criteria suggested by our study may add 19% more CT examinations for detecting 16% more cases when compared with the USPSTF criteria. Meanwhile, the increases in false-positive results, overdiagnosis, and radiation-related lung cancer deaths are 0.6%, 0.1%, and 4.0%, respectively.

CONCLUSIONS

Current USPSTF screening criteria exclude many patients who are at high risk for development of lung cancer. Including individuals who are younger than 81 years, have a smoking history of 30 or more pack-years, and have quit for 15 to 30 years may significantly increase the number of cases of non-overdiagnosed screen-detected lung cancer, does not significantly add to the number of false-positive cases, and saves more lives with an acceptable amount of elevated exposure to radiation and cost.

Should Never-Smokers at Increased Risk for Lung Cancer Be Screened?

INTRODUCTION

Lung cancer in never-smokers ranks among the 10 most common causes of death due to cancer worldwide and in the United States. However, it is unknown whether never-smokers at elevated risk for developing lung cancer may benefit from lung cancer screening.

METHODS

The MIcrosimulation SCreening ANalysis (MISCAN)-Lung microsimulation model was used to assess the effects of lung cancer screening for simulated cohorts of never-smokers at different levels of relative risk (RR) for lung cancer compared with never-smokers at average risk. The benefits and harms of screening were estimated for each cohort and compared with those of a cohort of ever-smokers eligible for lung cancer screening according to the United States Preventive Services Task Force (USPSTF) criteria.

RESULTS

The relative lung cancer mortality reduction in never-smokers was higher than the USPSTF eligible cohort (37% compared with 32%). However, the number of life-years gained per lung cancer death averted was lower (10.4 compared with 11.9) and the proportion of overdiagnosed cancers was higher (9.6% compared with 8.4%) for never-smokers compared with the USPSTF eligible cohort, as never-smokers are diagnosed at a later age. The estimated number of screens per lung cancer death averted ranged from 6162 for never-smokers at average risk to 151 for never-smokers with an RR of 35 compared with 353 for the USPSTF eligible cohort.

CONCLUSIONS

Never-smokers with RRs of 15 to 35 have similar to better trade-offs between benefits and harms compared with ever-smokers recommended for lung cancer screening by the USPSTF guidelines. For most never-smokers, lung cancer screening is not beneficial.

Gastric adenocarcinoma screening and prevention in the era of new biomarker and endoscopic technologies: a cost-effectiveness analysis

OBJECTIVE

To estimate the cost-effectiveness of noncardia gastric adenocarcinoma (NCGA) screening strategies based on new biomarker and endoscopic technologies.

DESIGN

Using an intestinal-type NCGA microsimulation model, we evaluated the following one-time screening strategies for US men: (1) serum pepsinogen to detect gastric atrophy (with endoscopic follow-up of positive screen results), (2) endoscopic screening to detect dysplasia and asymptomatic cancer (with endoscopic mucosal resection (EMR) treatment for detected lesions) and (3) Helicobacter pylori screening and treatment. Screening performance, treatment effectiveness, cancer and cost data were based on published literature and databases. Subgroups included current, former and never smokers. Outcomes included lifetime cancer risk and incremental cost-effectiveness ratios (ICERs), expressed as cost per quality-adjusted-life-year (QALY) gained.

RESULTS

Screening the general population at age 50 years reduced the lifetime intestinal-type NCGA risk (0.24%) by 26.4% with serum pepsinogen screening, 21.2% with endoscopy and EMR and 0.2% with H. pylori screening/treatment. Targeting current smokers reduced the lifetime risk (0.35%) by 30.8%, 25.5%, and 0.1%, respectively. For all subgroups, serum pepsinogen screening was more effective and more cost-effective than all other strategies, although its ICER varied from $76,000/QALY (current smokers) to $105,400/QALY (general population). Results were sensitive to H. pylori prevalence, screen age and serum pepsinogen test sensitivity. Probabilistic sensitivity analysis found that at a $100,000/QALY willingness-to-pay threshold, the probability that serum pepsinogen screening was preferred was 0.97 for current smokers.

CONCLUSIONS

Although not warranted for the general population, targeting high-risk smokers for serum pepsinogen screening may be a cost-effective strategy to reduce intestinal-type NCGA mortality.

Projected Clinical, Resource Use, and Fiscal Impacts of Implementing Low-Dose Computed Tomography Lung Cancer Screening in Medicare

PURPOSE

The Centers for Medicare and Medicaid Services (CMS) recently issued a national coverage determination that provides reimbursement for low-dose computed tomography (CT) lung cancer screening for enrollees age 55 to 77 years with ≥ 30-pack-year smoking history who currently smoke or quit in the last 15 years. The clinical, resource use, and fiscal impacts of this change in screening coverage policy remain uncertain.

METHODS

We developed a simulation model to forecast the 5-year health outcome impacts of the CMS low-dose CT screening policy in Medicare compared with no screening. The model used data from the National Lung Screening Trial, CMS enrollment statistics and reimbursement schedules, and peer-reviewed literature. Outcomes included counts of screening examinations, patient cases of lung cancer detected, stage distribution, and total and per-enrollee per-month fiscal impact.

RESULTS

Over 5 years, we project that low-dose CT screening will result in 10.7 million more low-dose CT scans, 52,000 more lung cancers detected, and increased overall expenditure of $6.8 billion ($2.22 per Medicare enrollee per month). The most fiscally impactful factors were the average cost-per-screening episode, proportion of enrollees eligible for screening, and cost of treating stage I lung cancer.

CONCLUSION

Low-dose CT screening is expected to increase lung cancer diagnoses, shift stage at diagnosis toward earlier stages, and substantially increase Medicare expenditures over a 5-year time horizon. These projections can inform planning efforts by Medicare administrators, contracted health care providers, and other stakeholders.

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.

Cost-effectiveness of a 14-gene risk score assay to target adjuvant chemotherapy in early stage non-squamous non-small cell lung cancer

Life Technologies has developed a 14-gene molecular assay that provides information about the risk of death in early stage non-squamous non-small cell lung cancer patients after surgery. The assay can be used to identify patients at highest risk of mortality, informing subsequent treatments. The objective of this study was to evaluate the cost-effectiveness of this novel assay. Patients and Methods. We developed a Markov model to estimate life expectancy, quality-adjusted life years (QALYs), and costs for testing versus standard care. Risk-group classification was based on assay-validation studies, and chemotherapy uptake was based on pre- and post-testing recommendations from a study of 58 physicians. We evaluated three chemotherapy-benefit scenarios: moderately predictive (base case), nonpredictive (i.e., the same benefit for each risk group), and strongly predictive. We calculated the incremental cost-effectiveness ratio (ICER) and performed one-way and probabilistic sensitivity analyses. Results. In the base case, testing and standard-care strategies resulted in 6.81 and 6.66 life years, 3.76 and 3.68 QALYs, and $122,400 and $118,800 in costs, respectively. The ICER was $23,200 per QALY (stage I: $29,200 per QALY; stage II: $12,200 per QALY). The ICER ranged from "dominant" to $92,100 per QALY in the strongly predictive and nonpredictive scenarios. The model was most sensitive to the proportion of high-risk patients receiving chemotherapy and the high-risk hazard ratio. The 14-gene risk score assay strategy was cost-effective in 68% of simulations. Conclusion. Our results suggest that the 14-gene risk score assay may be a cost-effective alternative to standard guideline-based adjuvant chemotherapy decision making in early stage non-small cell lung cancer.

Benefits and harms of computed tomography lung cancer screening strategies: a comparative modeling study for the U.S. Preventive Services Task Force

BACKGROUND

The optimum screening policy for lung cancer is unknown.

OBJECTIVE

To identify efficient computed tomography (CT) screening scenarios in which relatively more lung cancer deaths are averted for fewer CT screening examinations.

DESIGN

Comparative modeling study using 5 independent models.

DATA SOURCES

The National Lung Screening Trial; the Prostate, Lung, Colorectal, and Ovarian Cancer Screening trial; the Surveillance, Epidemiology, and End Results program; and the U.S. Smoking History Generator.

TARGET POPULATION

U.S. cohort born in 1950.

TIME HORIZON

Cohort followed from ages 45 to 90 years.

PERSPECTIVE

Societal.

INTERVENTION

576 scenarios with varying eligibility criteria (age, pack-years of smoking, years since quitting) and screening intervals.

OUTCOME MEASURES

Benefits included lung cancer deaths averted or life-years gained. Harms included CT examinations, false-positive results (including those obtained from biopsy/surgery), overdiagnosed cases, and radiation-related deaths.

RESULTS OF BEST-CASE SCENARIO

The most advantageous strategy was annual screening from ages 55 through 80 years for ever-smokers with a smoking history of at least 30 pack-years and ex-smokers with less than 15 years since quitting. It would lead to 50% (model ranges, 45% to 54%) of cases of cancer being detected at an early stage (stage I/II), 575 screening examinations per lung cancer death averted, a 14% (range, 8.2% to 23.5%) reduction in lung cancer mortality, 497 lung cancer deaths averted, and 5250 life-years gained per the 100,000-member cohort. Harms would include 67,550 false-positive test results, 910 biopsies or surgeries for benign lesions, and 190 overdiagnosed cases of cancer (3.7% of all cases of lung cancer [model ranges, 1.4% to 8.3%]).

RESULTS OF SENSITIVITY ANALYSIS

The number of cancer deaths averted for the scenario varied across models between 177 and 862; the number of overdiagnosed cases of cancer varied between 72 and 426.

LIMITATIONS

Scenarios assumed 100% screening adherence. Data derived from trials with short duration were extrapolated to lifetime follow-up.

CONCLUSION

Annual CT screening for lung cancer has a favorable benefit-harm ratio for individuals aged 55 through 80 years with 30 or more pack-years' exposure to smoking.

PRIMARY FUNDING SOURCE

National Cancer Institute.

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.

Patterns of birth cohort-specific smoking histories, 1965-2009

BACKGROUND

Characterizing the smoking patterns for different birth cohorts is essential for evaluating the impact of tobacco control interventions and predicting smoking-related mortality, but the process of estimating birth cohort smoking histories has received limited attention.

PURPOSE

Smoking history summaries were estimated beginning with the 1890 birth cohort in order to provide fundamental parameters that can be used in studies of cigarette smoking intervention strategies.

METHODS

U.S. National Health Interview Surveys conducted from 1965 to 2009 were used to obtain cross-sectional information on current smoking behavior. Surveys that provided additional detail on history for smokers including age at initiation and cessation and smoking intensity were used to construct smoking histories for participants up to the date of survey. After incorporating survival differences by smoking status, age-period-cohort models with constrained natural splines were used to estimate the prevalence of current, former, and never smokers in cohorts beginning in 1890. This approach was then used to obtain yearly estimates of initiation, cessation, and smoking intensity for the age-specific distribution for each birth cohort. These rates were projected forward through 2050 based on recent trends.

RESULTS

This summary of smoking history shows clear trends by gender, cohort, and age over time. If current patterns persist, a slow decline in smoking prevalence is projected from 2010 through 2040.

CONCLUSIONS

A novel method of generating smoking histories has been applied to develop smoking histories that can be used in micro-simulation models, and has been incorporated in the National Cancer Institute's Smoking History Generator. These aggregate estimates developed by age, gender, and cohort will provide a complete source of smoking data over time.

Tobacco control and the reduction in smoking-related premature deaths in the United States, 1964-2012

IMPORTANCE

January 2014 marks the 50th anniversary of the first surgeon general's report on smoking and health. This seminal document inspired efforts by governments, nongovernmental organizations, and the private sector to reduce the toll of cigarette smoking through reduced initiation and increased cessation.

OBJECTIVE

To model reductions in smoking-related mortality associated with implementation of tobacco control since 1964.

DESIGN, SETTING, AND PARTICIPANTS

Smoking histories for individual birth cohorts that actually occurred and under likely scenarios had tobacco control never emerged were estimated. National mortality rates and mortality rate ratio estimates from analytical studies of the effect of smoking on mortality yielded death rates by smoking status. Actual smoking-related mortality from 1964 through 2012 was compared with estimated mortality under no tobacco control that included a likely scenario (primary counterfactual) and upper and lower bounds that would capture plausible alternatives.

EXPOSURES

National Health Interview Surveys yielded cigarette smoking histories for the US adult population in 1964-2012.

MAIN OUTCOMES AND MEASURES

Number of premature deaths avoided and years of life saved were primary outcomes. Change in life expectancy at age 40 years associated with change in cigarette smoking exposure constituted another measure of overall health outcomes.

RESULTS

In 1964-2012, an estimated 17.7 million deaths were related to smoking, an estimated 8.0 million (credible range [CR], 7.4-8.3 million, for the lower and upper tobacco control counterfactuals, respectively) fewer premature smoking-related deaths than what would have occurred under the alternatives and thus associated with tobacco control (5.3 million [CR, 4.8-5.5 million] men and 2.7 million [CR, 2.5-2.7 million] women). This resulted in an estimated 157 million years (CR, 139-165 million) of life saved, a mean of 19.6 years for each beneficiary (111 million [CR, 97-117 million] for men, 46 million [CR, 42-48 million] for women). During this time, estimated life expectancy at age 40 years increased 7.8 years for men and 5.4 years for women, of which tobacco control is associated with 2.3 years (CR, 1.8-2.5) (30% [CR, 23%-32%]) of the increase for men and 1.6 years (CR, 1.4-1.7) (29% [CR, 25%-32%]) for women.

CONCLUSIONS AND RELEVANCE

Tobacco control was estimated to be associated with avoidance of 8 million premature deaths and an estimated extended mean life span of 19 to 20 years. Although tobacco control represents an important public health achievement, efforts must continue to reduce the effect of smoking on the nation's death toll.

Contribution of H. pylori and smoking trends to US incidence of intestinal-type noncardia gastric adenocarcinoma: a microsimulation model

BACKGROUND

Although gastric cancer has declined dramatically in the US, the disease remains the second leading cause of cancer mortality worldwide. A better understanding of reasons for the decline can provide important insights into effective preventive strategies. We sought to estimate the contribution of risk factor trends on past and future intestinal-type noncardia gastric adenocarcinoma (NCGA) incidence.

METHODS AND FINDINGS

We developed a population-based microsimulation model of intestinal-type NCGA and calibrated it to US epidemiologic data on precancerous lesions and cancer. The model explicitly incorporated the impact of Helicobacter pylori and smoking on disease natural history, for which birth cohort-specific trends were derived from the National Health and Nutrition Examination Survey (NHANES) and National Health Interview Survey (NHIS). Between 1978 and 2008, the model estimated that intestinal-type NCGA incidence declined 60% from 11.0 to 4.4 per 100,000 men, <3% discrepancy from national statistics. H. pylori and smoking trends combined accounted for 47% (range = 30%-58%) of the observed decline. With no tobacco control, incidence would have declined only 56%, suggesting that lower smoking initiation and higher cessation rates observed after the 1960s accelerated the relative decline in cancer incidence by 7% (range = 0%-21%). With continued risk factor trends, incidence is projected to decline an additional 47% between 2008 and 2040, the majority of which will be attributable to H. pylori and smoking (81%; range = 61%-100%). Limitations include assuming all other risk factors influenced gastric carcinogenesis as one factor and restricting the analysis to men.

CONCLUSIONS

Trends in modifiable risk factors explain a significant proportion of the decline of intestinal-type NCGA incidence in the US, and are projected to continue. Although past tobacco control efforts have hastened the decline, full benefits will take decades to be realized, and further discouragement of smoking and reduction of H. pylori should be priorities for gastric cancer control efforts.

Derivation of background mortality by smoking and obesity in cancer simulation models

BACKGROUND

Simulation models designed to evaluate cancer prevention strategies make assumptions on background mortality-the competing risk of death from causes other than the cancer being studied. Researchers often use the U.S. life tables and assume homogeneous other-cause mortality rates. However, this can lead to bias because common risk factors such as smoking and obesity also predispose individuals for deaths from other causes such as cardiovascular disease.

METHODS

We obtained calendar year-, age-, and sex-specific other-cause mortality rates by removing deaths due to a specific cancer from U.S. all-cause life tables. Prevalence across 12 risk factor groups (3 smoking [never, past, and current smoker] and 4 body mass index [BMI] categories [<25, 25-30, 30-35, 35+ kg/m(2)]) were estimated from national surveys (National Health and Nutrition Examination Surveys [NHANES] 1971-2004). Using NHANES linked mortality data, we estimated hazard ratios for death by BMI/smoking using a Poisson regression model. Finally, we combined these results to create 12 sets of BMI and smoking-specific other-cause life tables for U.S. adults aged 40 years and older that can be used in simulation models of lung, colorectal, or breast cancer.

RESULTS

We found substantial differences in background mortality when accounting for BMI and smoking. Ignoring the heterogeneity in background mortality in cancer simulation models can lead to underestimation of competing risk of deaths for higher-risk individuals (e.g., male, 60-year old, white obese smokers) by as high as 45%.

CONCLUSION

Not properly accounting for competing risks of death may introduce bias when using simulation modeling to evaluate population health strategies for prevention, screening, or treatment. Further research is warranted on how these biases may affect cancer-screening strategies targeted at high-risk individuals.

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 8: The FHCRC lung cancer model

As a member of the Cancer Intervention and Surveillance Modeling Network (CISNET), the lung cancer (LC) group at Fred Hutchinson Cancer Research Center (FHCRC) developed a model for evaluating U.S. lung cancer mortality trends and the impact of changing tobacco consumption. Model components include a biologically based two-stage clonal expansion (TSCE) model; a smoking simulator to generate smoking histories and other cause mortality; and adjustments for period and birth cohort to improve calibration to U.S. LC mortality. The TSCE model was first calibrated to five substantial cohorts: British doctors, American Cancer Society CPS-I and CPS-II, Health Professionals' Follow-Up Study (HPFS), and Nurses' Health Study (NHS). The NHS and HPFS cohorts included the most detailed smoking histories and were chosen to represent the effects of smoking on U.S. LC mortality. The calibrated TSCE model and smoking simulator were used to simulate U.S. LC mortality. Further adjustments were necessary to account for unknown factors. This provided excellent fits between simulated and observed U.S. LC mortality for ages 30-84 and calendar years 1975-2000. The FHCRC LC model may be used to study the effects of public health information on U.S. LC trends and the impact of tobacco control policy. For example, we estimated that over 500,000 males and 200,000 females avoided LC death between 1975 and 2000 due to increasing awareness since the mid 1950s of the harmful effects of smoking. We estimated that 1.1 million male and 0.6 million female LC deaths were avoidable if smokers quit smoking in 1965.

Chapter 1:The impact of the reduction in tobacco smoking on U.S. lung cancer mortality, 1975-2000: an introduction to the problem

To better understand the contribution of cigarette smoking, and its changing role in lung cancer, this article provides an introduction to a special issue of Risk Analysis, which considers the relationship between smoking and lung cancer death rates during the period 1975-2000 for U.S. men and women aged 30-84 years. Six models are employed, which are part of a consortium of lung cancer modelers funded by National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET). Starting with birth-cohort-specific smoking histories derived from National Health Interview Surveys, three scenarios are modeled: Actual Tobacco Control (observed trends in smoking), Complete Tobacco Control (a counterfactual lower bound on smoking rates that could have been achieved had all smoking ceased after the first Surgeon General's report in 1964), and No Tobacco Control (a counterfactual upper bound on smoking rates if smoking patterns that prevailed before the first studies in the 1950s began to inform the public about the hazards of smoking). Using these three scenarios and the lung cancer models, the number and percentage of lung cancer deaths averted from 1975-2000, among all deaths that could have been averted if tobacco control efforts been immediate and perfect, can be estimated. The variability of the results across multiple models provides a measure of the robustness of the results to model assumptions and structure. The results provide not only a portrait of the achieved impact of tobacco control on lung cancer mortality, but also the bounds of what still needs to be achieved.

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.

Chapter 5: Actual and counterfactual smoking prevalence rates in the U.S. population via microsimulation

The smoking history generator (SHG) developed by the National Cancer Institute simulates individual life/smoking histories that serve as inputs for the Cancer Intervention and Surveillance Modeling Network (CISNET) lung cancer models. In this chapter, we review the SHG inputs, describe its outputs, and outline the methodology behind it. As an example, we use the SHG to simulate individual life histories for individuals born between 1890 and 1984 for each of the CISNET smoking scenarios and use those simulated histories to compute the corresponding smoking prevalence over the period 1975-2000.