Individuals younger than 65 and racial/ethnic minorities have higher odds of CRC when also diagnosed with diabetes. Targeted interventions for these populations, especially regarding screening recommendations, may result in earlier detection of CRC and improved health outcomes.

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BACKGROUND: Smoking cessation rates after stroke and transient ischemic attack are suboptimal, and smoking cessation interventions are underutilized. We performed a cost-effectiveness analysis of smoking cessation interventions in this population. METHODS: We constructed a decision tree and used Markov models that aimed to assess the cost-effectiveness of varenicline, any pharmacotherapy with intensive counseling, and monetary incentives, compared with brief counseling alone in the secondary stroke prevention setting. Payer and societal costs of interventions and outcomes were modeled. The outcomes were recurrent stroke, myocardial infarction, and death using a lifetime horizon. Estimates and variance for the base case (35% cessation), costs and effectiveness of interventions, and outcome rates were imputed from the stroke literature. We calculated incremental cost-effectiveness ratios and incremental net monetary benefits. An intervention was considered cost-effective if the incremental cost-effectiveness ratio was less than the willingness-to-pay threshold of $100 000 per quality-adjusted life-year (QALY) or when the incremental net monetary benefit was positive. Probabilistic Monte Carlo simulations modeled the impact of parameter uncertainty. RESULTS: From the payer perspective, varenicline and pharmacotherapy with intensive counseling were associated with more QALYs (0.67 and 1.00, respectively) at less total lifetime costs compared with brief counseling alone. Monetary incentives were associated with 0.71 more QALYs at an additional cost of $120 compared with brief counseling alone, yielding an incremental cost-effectiveness ratio of $168/QALY. From the societal perspective, all 3 interventions provided more QALYs at less total costs compared with brief counseling alone. In 10 000 Monte Carlo simulations, all 3 smoking cessation interventions were cost-effective in >89% of runs. CONCLUSIONS: For secondary stroke prevention, it is cost-effective and potentially cost-saving to deliver smoking cessation therapy beyond brief counseling alone.

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Background: The detrimental impact of tobacco smoking on brain health is well recognized. Objective: To evaluate whether smoking acts synergistically with hypertension and diabetes to influence cognitive performance. Methods: We performed a cross-sectional analysis using the US National Health and Nutrition Examination Survey. Participants were tested for serum cotinine, a validated cigarette smoking/exposure biomarker, and had standardized blood pressure and hemoglobin A1c measurements. Participants were administered four cognitive tests: Digit Symbol Substitution (DSST), Animal Fluency, Immediate Recall, and Delayed Recall. Multivariable linear regression models adjusted for demographics and confounders evaluated the association of cotinine with cognition. Interaction testing evaluated effect modification by hypertension, diabetes, and their continuous measures (systolic blood pressure and hemoglobin A1c). Results: For 3,007 participants, mean age was 69.4 years; 54% were women. Using cotinine levels, 14.9% of participants were categorized as active smokers. Higher cotinine levels were associated with worse DSST performance when modeling cotinine as a continuous variable (β, -0.70; 95% CI, -1.11, -0.29; p <  0.01) and when categorizing participants as active smokers (β, -5.63; 95% CI, -9.70, -1.56; p <  0.01). Cotinine was not associated with fluency or memory. Effect modification by hypertension and diabetes were absent, except that cotinine was associated with worse Immediate Recall at lower blood pressures. Conclusion: Higher levels of a smoking and secondhand exposure biomarker were associated with worse cognitive performance on a multidomain test. Overall, the relationship of cotinine with cognition was not contingent on or amplified by hypertension or diabetes; smoking is detrimental for brain health irrespective of these comorbidities.

Introduction: The cost effectiveness of smoking-cessation interventions after ischemic stroke and TIA has not been evaluated. We performed a cost-effectiveness analysis of smoking-cessation interventions in this population. Methods: We constructed a decision tree model to compare brief counseling alone to 3 interventions: varenicline, any pharmacotherapy with intensive counseling, and monetary incentives. Direct health care costs of interventions and outcomes were modeled. The outcomes were recurrent stroke, myocardial infarction, and death using a 5-year horizon. Estimates and variance for the base case (42% cessation), costs and effectiveness of interventions, and outcome rates were imputed from the stroke literature. Using standard techniques, we calculated incremental cost-effectiveness ratios (ICER) and net-monetary benefits (NMB). An intervention was considered cost effective if the ICER was less than the standard willingness-to-pay threshold of $100,000 per quality-adjusted life year (QALY) or when the NMB was maximized. Sensitivity analyses and a probabilistic Monte Carlo simulation modeled the impact of parameter uncertainty, including for the base case cessation rate and costs and effectiveness of interventions (TreeAge Pro). Results: All three interventions were cost effective based on the ICER: varenicline - $7,422/QALY, pharmacotherapy with counseling - $14,550/QALY, and monetary incentives - $23,280/QALY. In one-way sensitivity analyses, interventions costing up to $1,729 remained cost-effective. In a two-way sensitivity analysis varying the cost and effectiveness of smoking-cessation interventions, all three interventions were cost effective based on NMB (Figure). In 10,000 Monte Carlo simulations, smoking-cessation interventions were cost effective 90% of the time, as compared to brief counseling alone. Conclusion: Smoking-cessation strategies are cost effective in secondary prevention after stroke and TIA.

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Introduction: We evaluated the association of a cigarette-smoking biomarker with cognitive function, and tested whether smoking acts synergistically with hypertension and diabetes to influence cognition. Methods: We performed a cross-sectional analysis of nationally representative data from the US National Health and Nutrition Examination Survey. From 2011-2014, participants ≥60 years old were given 4 standardized cognitive tests by trained examiners: immediate word recall, delayed word recall, Animal Fluency Test (AFT), and Digit Symbol Substitution Test (DSST) - a multidomain cognitive test. Participants also had 3 consecutive standardized blood pressure measurements and hemoglobin A1c and serum cotinine tests, the latter an accurate biomarker of cigarette smoking/exposure. We used linear regression to evaluate the association of cotinine with cognitive performance. Where an association was found, interaction term testing evaluated effect modification by systolic blood pressure and hemoglobin A1c as continuous measures, and hypertension and diabetes as categorical variables. Models were adjusted for demographics, socioeconomic factors, education, cardiovascular risk factors/disease, alcohol use, and depression. Results: The mean age of 3,244 participants was 69 years and 54% were women. Self-reported current smoking was present in 23%, 77% had hypertension, and 24% had diabetes. In adjusted linear regression models, higher serum cotinine levels were associated with worse performance on the DSST (β, -0.02; 95% CI, -0.03, -0.01; P=0.001), and non-significantly on the AFT (β, -0.003; 95% CI, -0.006, 0.0003; P=0.07), but not immediate or delayed recall. For the DSST, effect modification by systolic blood pressure (P=0.14) and hemoglobin A1c (P=0.39) was not observed. There was also no evidence of effect modification when testing interactions for hypertension and diabetes. Conclusions: Higher levels of a smoking biomarker were associated with worse performance on a multidomain cognitive test at the population level, regardless of hypertension or diabetes. These data demonstrate the detrimental impact of smoking on cognition and underscore the broad importance of promoting smoking cessation to preserve cognitive health.