The Impact of Health Care Algorithms on Racial and Ethnic Disparities : A Systematic Review.

BACKGROUND: There is increasing concern for the potential impact of health care algorithms on racial and ethnic disparities. PURPOSE: To examine the evidence on how health care algorithms and associated mitigation strategies affect racial and ethnic disparities. DATA SOURCES: Several databases were searched for relevant studies published from 1 January 2011 to 30 September 2023. STUDY SELECTION: Using predefined criteria and dual review, studies were screened and selected to determine: 1) the effect of algorithms on racial and ethnic disparities in health and health care outcomes and 2) the effect of strategies or approaches to mitigate racial and ethnic bias in the development, validation, dissemination, and implementation of algorithms. DATA EXTRACTION: Outcomes of interest (that is, access to health care, quality of care, and health outcomes) were extracted with risk-of-bias assessment using the ROBINS-I (Risk Of Bias In Non-randomised Studies - of Interventions) tool and adapted CARE-CPM (Critical Appraisal for Racial and Ethnic Equity in Clinical Prediction Models) equity extension. DATA SYNTHESIS: Sixty-three studies (51 modeling, 4 retrospective, 2 prospective, 5 prepost studies, and 1 randomized controlled trial) were included. Heterogenous evidence on algorithms was found to: a) reduce disparities (for example, the revised kidney allocation system), b) perpetuate or exacerbate disparities (for example, severity-of-illness scores applied to critical care resource allocation), and/or c) have no statistically significant effect on select outcomes (for example, the HEART Pathway [history, electrocardiogram, age, risk factors, and troponin]). To mitigate disparities, 7 strategies were identified: removing an input variable, replacing a variable, adding race, adding a non-race-based variable, changing the racial and ethnic composition of the population used in model development, creating separate thresholds for subpopulations, and modifying algorithmic analytic techniques. LIMITATION: Results are mostly based on modeling studies and may be highly context-specific. CONCLUSION: Algorithms can mitigate, perpetuate, and exacerbate racial and ethnic disparities, regardless of the explicit use of race and ethnicity, but evidence is heterogeneous. Intentionality and implementation of the algorithm can impact the effect on disparities, and there may be tradeoffs in outcomes. PRIMARY FUNDING SOURCE: Agency for Healthcare Quality and Research.

Hospitalizations among adults with chronic kidney disease in the United States: A cohort study.

BACKGROUND: Adults with chronic kidney disease (CKD) are hospitalized more frequently than those without CKD, but the magnitude of this excess morbidity and the factors associated with hospitalizations are not well known. METHODS AND FINDINGS: Data from 3,939 participants enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study between 2003 and 2008 at 7 clinical centers in the United States were used to estimate primary causes of hospitalizations, hospitalization rates, and baseline participant factors associated with all-cause, cardiovascular, and non-cardiovascular hospitalizations during a median follow up of 9.6 years. Multivariable-adjusted Poisson regression was used to identify factors associated with hospitalization rates, including demographics, blood pressure, estimated glomerular filtration rate (eGFR), and proteinuria. Hospitalization rates in CRIC were compared with rates in the Nationwide Inpatient Sample (NIS) from 2012. Of the 3,939 CRIC participants, 45.1% were female, and 41.9% identified as non-Hispanic black, with a mean age of 57.7 years, and the mean eGFR is 44.9 ml/min/1.73m2. CRIC participants had an unadjusted overall hospitalization rate of 35.0 per 100 person-years (PY) [95% CI: 34.3 to 35.6] and 11.1 per 100 PY [95% CI: 10.8 to 11.5] for cardiovascular-related causes. All-cause, non-cardiovascular, and cardiovascular hospitalizations were associated with older age (≥65 versus 45 to 64 years), more proteinuria (≥150 to <500 versus <150 mg/g), higher systolic blood pressure (≥140 versus 120 to <130 mmHg), diabetes (versus no diabetes), and lower eGFR (<60 versus ≥60 ml/min/1.73m2). Non-Hispanic black (versus non-Hispanic white) race/ethnicity was associated with higher risk for cardiovascular hospitalization [rate ratio (RR) 1.25, 95% CI: 1.16 to 1.35, p-value < 0.001], while risk among females was lower [RR 0.89, 95% CI: 0.83 to 0.96, p-value = 0.002]. Rates of cardiovascular hospitalizations were higher among those with ≥500 mg/g of proteinuria irrespective of eGFR. The most common causes of hospitalization were related to cardiovascular (31.8%), genitourinary (8.7%), digestive (8.3%), endocrine, nutritional or metabolic (8.3%), and respiratory (6.7%) causes. Hospitalization rates were higher in CRIC than the NIS, except for non-cardiovascular hospitalizations among individuals aged >65 years. Limitations of the study include possible misclassification by diagnostic codes, residual confounding, and potential bias from healthy volunteer effect due to its observational nature. CONCLUSIONS: In this study, we observed that adults with CKD had a higher hospitalization rate than the general population that is hospitalized, and even moderate reductions in kidney function were associated with elevated rates of hospitalization. Causes of hospitalization were predominantly related to cardiovascular disease, but other causes contributed, particularly, genitourinary, digestive, and endocrine, nutritional, and metabolic illnesses. High levels of proteinuria were observed to have the largest association with hospitalizations across a wide range of kidney function levels.

Insulin resistance and chronic kidney disease progression, cardiovascular events, and death: findings from the chronic renal insufficiency cohort study.

BACKGROUND: Insulin resistance contributes to the metabolic syndrome, which is associated with the development of kidney disease. However, it is unclear if insulin resistance independently contributes to an increased risk of chronic kidney disease (CKD) progression or CKD complications. Additionally, predisposing factors responsible for insulin resistance in the absence of diabetes in CKD are not well described. This study aimed to describe factors associated with insulin resistance and characterize the relationship of insulin resistance to CKD progression, cardiovascular events and death among a cohort of non-diabetics with CKD. METHODS: Data was utilized from Chronic Renal Insufficiency Cohort Study participants without diabetes (N = 1883). Linear regression was used to assess associations with insulin resistance, defined using the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). The relationship of HOMA-IR, fasting glucose, hemoglobin A1c (HbA1c), and C-peptide with CKD progression, cardiovascular events, and all-cause mortality was examined with Cox proportional hazards models. RESULTS: Novel positive associations with HOMA-IR included serum albumin, uric acid, and hemoglobin A1c. After adjustment, HOMA-IR was not associated with CKD progression, cardiovascular events, or all-cause mortality. There was a notable positive association of one standard deviation increase in HbA1c with the cardiovascular endpoint (HR 1.16, 95% CI: 1.00-1.34). CONCLUSION: We describe potential determinants of HOMA-IR among a cohort of non-diabetics with mild-moderate CKD. HOMA-IR was not associated with renal or cardiovascular events, or all-cause mortality, which adds to the growing literature describing an inconsistent relationship of insulin resistance with CKD-related outcomes.

Incident Type 2 Diabetes Among Individuals With CKD: Findings From the Chronic Renal Insufficiency Cohort (CRIC) Study.

RATIONALE & OBJECTIVE: Few studies have examined incident type 2 diabetes mellitus (T2DM) in chronic kidney disease (CKD). Our objective was to examine rates of and risk factors for T2DM in CKD, using several alternative measures of glycemic control. STUDY DESIGN: Prospective cohort study. SETTING & PARTICIPANTS: 1,713 participants with reduced glomerular filtration rates and without diabetes at baseline, enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study. PREDICTORS: Measures of kidney function and damage, fasting blood glucose, hemoglobin A1c (HbA1c), HOMA-IR (homeostatic model assessment of insulin resistance), demographics, family history of diabetes mellitus (DM), smoking status, medication use, systolic blood pressure, triglyceride level, high-density lipoprotein cholesterol level, body mass index, and physical activity. OUTCOME: Incident T2DM (defined as fasting blood glucose ≥ 126mg/dL or prescription of insulin or oral hypoglycemic agents). ANALYTICAL APPROACH: Concordance between fasting blood glucose and HbA1c levels was assessed using κ. Cause-specific hazards modeling, treating death and end-stage kidney disease as competing events, was used to predict incident T2DM. RESULTS: Overall T2DM incidence rate was 17.81 cases/1,000 person-years. Concordance between fasting blood glucose and HbA1c levels was low (κ for categorical versions of fasting blood glucose and HbA1c = 13%). Unadjusted associations of measures of kidney function and damage with incident T2DM were nonsignificant (P ≥ 0.4). In multivariable models, T2DM was significantly associated with fasting blood glucose level (P = 0.002) and family history of DM (P = 0.03). The adjusted association of HOMA-IR with T2DM was comparable to that of fasting blood glucose level; the association of HbA1c level was nonsignificant (P ≥ 0.1). Harrell's C for the models ranged from 0.62 to 0.68. LIMITATIONS: Limited number of outcome events; predictors limited to measures taken at baseline. CONCLUSIONS: The T2DM incidence rate among individuals with CKD is markedly higher than in the general population, supporting the need for greater vigilance in this population. Measures of glycemic control and family history of DM were independently associated with incident T2DM.

Risk of Progression of Nonalbuminuric CKD to End-Stage Kidney Disease in People With Diabetes: The CRIC (Chronic Renal Insufficiency Cohort) Study.

BACKGROUND: Reduced glomerular filtration rate (GFR) in the absence of albuminuria is a common manifestation of chronic kidney disease (CKD) in diabetes. However, the frequency with which it progresses to end-stage kidney disease (ESKD) is unknown. STUDY DESIGN: Multicenter prospective cohort study. SETTING & PARTICIPANTS: We included 1,908 participants with diabetes and reduced GFR enrolled in the Chronic Renal Insufficiency Cohort (CRIC) Study in the United States. PREDICTORS: Urinary albumin and protein excretion. OUTCOMES: Incident ESKD, CKD progression (ESKD or ≥50% reduction in estimated GFR [eGFR] from baseline), and annual rate of decline in kidney function. MEASUREMENTS: ESKD was ascertained by self-report and by linkage to the US Renal Data System. We used Cox proportional hazards modeling to estimate the association of albuminuria and proteinuria with incident ESKD or CKD progression and linear mixed-effects models to assess differences in eGFR slopes among those with and without albuminuria. RESULTS: Mean eGFR at baseline was 41.2mL/min/1.73m2. Normal or mildly increased 24-hour urinary albumin excretion (<30mg/d) at baseline was present in 28% of participants, but in only 5% of those progressing to ESKD. For those with baseline normal or mildly increased albuminuria, moderately increased albuminuria (albumin excretion, 30-299mg/d), and 2 levels of severely increased albuminuria (albumin excretion, 300-999 and ≥1,000mg/d): crude rates of ESKD were 7.4, 34.8, 78.7, and 178.7 per 1,000 person-years, respectively; CKD progression rates were 17.0, 61.4, 130.5, and 295.1 per 1,000 person-years, respectively; and annual rates of eGFR decline were -0.17, -1.35, -2.74, and -4.69mL/min/1.73m2, respectively. LIMITATIONS: We were unable to compare the results with healthy controls. CONCLUSIONS: In people with diabetes with reduced eGFRs, the absence of albuminuria or proteinuria is common and carries a much lower risk for ESKD, CKD progression, or rapid decline in eGFR compared with those with albuminuria or proteinuria. The rate of eGFR decline in normoalbuminuric CKD was similar to that reported for the general diabetic population.

Statistical Methods for Modeling Time-Updated Exposures in Cohort Studies of Chronic Kidney Disease.

When estimating the effect of an exposure on a time-to-event type of outcome, one can focus on the baseline exposure or the time-updated exposures. Cox regression models can be used in both situations. When time-dependent confounding exists, the Cox model with time-updated covariates may produce biased effect estimates. Marginal structural models, estimated through inverse-probability weighting, were developed to appropriately adjust for time-dependent confounding. We review the concept of time-dependent confounding and illustrate the process of inverse-probability weighting. We fit a marginal structural model to estimate the effect of time-updated systolic BP on the time to renal events such as ESRD in the Chronic Renal Insufficiency Cohort. We compare the Cox regression model and the marginal structural model on several attributes (effects estimated, result interpretation, and assumptions) and give recommendations for when to use each method.

Statistical Methods for Recurrent Event Analysis in Cohort Studies of CKD.

Cardiovascular events, such as hospitalizations because of congestive heart failure, often occur repeatedly in patients with CKD. Many studies focus on analyses of the first occurrence of these events, and discard subsequent information. In this article, we review a number of statistical methods for analyzing ordered recurrent events of the same type, including Poisson regression and three commonly used survival models that are extensions of Cox proportional hazards regression. We illustrate the models by analyzing data from the Chronic Renal Insufficiency Cohort Study to identify risk factors for congestive heart failure hospitalizations in patients with CKD. We show that recurrent event analyses provide additional insights about the data compared with a standard survival analysis of time to the first event.

Analytic Considerations for Repeated Measures of eGFR in Cohort Studies of CKD.

Repeated measures of various biomarkers provide opportunities for us to enhance understanding of many important clinical aspects of CKD, including patterns of disease progression, rates of kidney function decline under different risk factors, and the degree of heterogeneity in disease manifestations across patients. However, because of unique features, such as correlations across visits and time dependency, these data must be appropriately handled using longitudinal data analysis methods. We provide a general overview of the characteristics of data collected in cohort studies and compare appropriate statistical methods for the analysis of longitudinal exposures and outcomes. We use examples from the Chronic Renal Insufficiency Cohort Study to illustrate these methods. More specifically, we model longitudinal kidney outcomes over annual clinical visits and assess the association with both baseline and longitudinal risk factors.

Statistical Methods for Cohort Studies of CKD: Survival Analysis in the Setting of Competing Risks.

Survival analysis is commonly used to evaluate factors associated with time to an event of interest (e.g., ESRD, cardiovascular disease, and mortality) among CKD populations. Time to the event of interest is typically observed only for some participants. Other participants have their event time censored because of the end of the study, death, withdrawal from the study, or some other competing event. Classic survival analysis methods, such as Cox proportional hazards regression, rely on the assumption that any censoring is independent of the event of interest. However, in most clinical settings, such as in CKD populations, this assumption is unlikely to be true. For example, participants whose follow-up time is censored because of health-related death likely would have had a shorter time to ESRD, had they not died. These types of competing events that cause dependent censoring are referred to as competing risks. Here, we first describe common circumstances in clinical renal research where competing risks operate and then review statistical approaches for dealing with competing risks. We compare two of the most popular analytical methods used in settings of competing risks: cause-specific hazards models and the Fine and Gray approach (subdistribution hazards models). We also discuss practical recommendations for analysis and interpretation of survival data that incorporate competing risks. To demonstrate each of the analytical tools, we use a study of fibroblast growth factor 23 and risks of mortality and ESRD in participants with CKD from the Chronic Renal Insufficiency Cohort Study.

Statistical Methods for Cohort Studies of CKD: Prediction Modeling.

Prediction models are often developed in and applied to CKD populations. These models can be used to inform patients and clinicians about the potential risks of disease development or progression. With increasing availability of large datasets from CKD cohorts, there is opportunity to develop better prediction models that will lead to more informed treatment decisions. It is important that prediction modeling be done using appropriate statistical methods to achieve the highest accuracy, while avoiding overfitting and poor calibration. In this paper, we review prediction modeling methods in general from model building to assessing model performance as well as the application to new patient populations. Throughout, the methods are illustrated using data from the Chronic Renal Insufficiency Cohort Study.

Effects of tailored risk communications for skin cancer prevention and detection: the PennSCAPE randomized trial.

BACKGROUND: Prevention and early detection measures for melanoma, such as sun avoidance and skin examinations, are important, but are practiced inconsistently. In this replication of the Project SCAPE trial, we sought to determine whether tailored print materials were more effective at improving adherence than generic print materials for patients at increased risk of skin cancer. METHODS: Participants were randomized to receive personalized mailed communications about their skin cancer risk and recommended sun protection, or generic mailings. Participants were Caucasian adults, at moderate or high risk for skin cancer, recruited in outpatient primary care. The main outcomes were overall sun protection behaviors and specific protective behaviors including use of sunscreen, shirt, hat, sunglasses, shade, and sun avoidance; recent sunburns; and skin self-examination and provider skin examination. RESULTS: One hundred ninety-two (93.2%) subjects completed the study. Six outcome variables showed significant intervention condition effects in mixed effects models: overall sun protection behavior (P = 0.025); sunscreen use (P = 0.026); use of sunglasses (P = 0.011); sunburns in the past three months (P = 0.033); recency of last skin self-exam (P = 0.017); and frequency of skin exams by health care provider (P = 0.016). CONCLUSIONS: Relative to generic communications, tailored risk communications resulted in improved adherence to six skin cancer protective behaviors, including a composite sun protection behavior measure, sunburns, and health care provider skin examinations. IMPACT: Tailored interventions can be more effective in improving patient prevention behaviors than nontailored, generic information for patients at moderate to high risk of skin cancer.

The association between changes in alternative reinforcers and short-term smoking cessation.

BACKGROUND: While more than 50% of smokers make a serious quit attempt each year, less than 10% quit permanently. Evidence from studies of adolescent smoking and other substances of abuse suggest that alternative reinforcers, a construct of Behavioral Economic Theory, may contribute to the likelihood of smoking cessation in adults. This study examined the behavioral economics of smoking cessation within a smoking cessation clinical trial and evaluated how depressive symptoms and behavioral economic variables are associated with smoking cessation. METHODS: A sample of 469 smokers, enrolled in an effectiveness trial that provided counseling and 8 weeks of 21 mg nicotine patches, was analyzed. Alternative reinforcers (substitute and complementary reinforcers) and depressive symptoms were examined in relation to 7-day point prevalence abstinence, verified with breath carbon monoxide, 8 weeks after the quit date. RESULTS: Controlling for covariates associated with cessation (nicotine dependence, age of smoking initiation, patch adherence), participants who were abstinent at week 8 showed significantly higher substitute reinforcers at all time-points, compared to those who were smoking (p's<.05). Participants who were abstinent at week 8 showed lower complementary reinforcers and depressive symptoms at all time-points, compared to those who were smoking, but significant differences were confined to week 8 (p's<.01). There was no significant interaction between alternative reinforcers and depressive symptoms across the 8 weeks on week 8 abstinence. CONCLUSIONS: These results support continued examination of Behavioral Economic Theory in understanding adult smoking cessation in order to inform future treatments and guidelines.

No untoward effects of smoking cues in anti-smoking public service announcements.

BACKGROUND: Anti-smoking public service announcements (PSAs) often include smoking-related cues; however, visual drug cues can trigger acute cravings that may impede cognitive processing of the anti-smoking message. This experiment evaluated effects of smoking cues in PSAs on smoking urges, immediate smoking behavior, and persuasion measures in daily smokers. METHODS: Three-hundred and eighteen non-treatment seeking smokers completed a single laboratory session during which they viewed sets of PSAs differentiated by presence of smoking cues (central to the PSA's argument, peripheral, or no cues) and argument strength (high versus low). After viewing the PSAs, participants completed self-report measures of smoking urges, attitudes toward quitting, self-efficacy, and intentions to quit smoking. Smoking behavior was recorded during a 1-h ad libitum smoking period immediately following PSA viewing and assessment. RESULTS: There was a significant positive effect of argument strength on attitudes toward quitting smoking (p=0.012). There were no main effects of smoking cues or smoking cue by argument strength interactions on any of the outcome measures. CONCLUSIONS: Visual smoking cues in PSAs do not increase urges to smoke, nor is there evidence that the inclusion of such cues impedes the recall or persuasive effects of anti-smoking arguments.

Melanoma genetic testing, counseling, and adherence to skin cancer prevention and detection behaviors.

BACKGROUND: Little is known about the impact of knowledge of CDKN2A and MC1R genotype on melanoma prevention behaviors like sun avoidance and skin examination in the context of familial melanoma. METHODS: Seventy-three adults with a family history of melanoma were randomly assigned to be offered individualized CDKN2A and MC1R genotyping results in the context of a genetic counseling session, or the standard practice of not being offered counseling or disclosure of genotyping results. Mixed effects or longitudinal logistic models were used to determine whether the intervention affected change in sun protection habits, skin examinations, and perception and beliefs related to melanoma risk, prevention, and genetic counseling. RESULTS: All participants in the intervention group who attended genetic counseling sessions chose to receive their test results. From baseline to follow-up, participants in the intervention group reported an increase in the frequency of skin self-examinations compared with a slight decrease in the control group (P = 0.002). Participants in the intervention group reported a smaller decrease in frequency of wearing a shirt with long sleeves than did participants in the control group (P = 0.047). No effect of the intervention was noted for other outcomes. CONCLUSIONS: Feedback of CDKN2A and MC1R genotype among families without known pathogenic CDKN2A mutations does not seem to decrease sun protection behaviors. IMPACT: While disclosure of CDKN2A and MC1R genotype did not have negative effects on prevention, the benefits of communicating this information remain unclear. The small number of families who tested positive for CDKN2A mutations in this study is a limitation.

Graphic warning labels in cigarette advertisements: recall and viewing patterns.

BACKGROUND: The Family Smoking Prevention and Control Act gave the U.S. Food and Drug Administration (FDA) legal authority to mandate graphic warning labels on cigarette advertising and packaging. The FDA requires that these graphic warning labels be embedded into cigarette advertising and packaging by September 2012. PURPOSE: The aim of this study was to examine differences in recall and viewing patterns of text-only versus graphic cigarette warning labels and the association between viewing patterns and recall. METHODS: Participants (current daily smokers; N=200) were randomized to view a cigarette advertisement with either text-only or graphic warning labels. Viewing patterns were measured using eye-tracking, and recall was later assessed. Sessions were conducted between November 2008 and November 2009. Data analysis was conducted between March 2011 and July 2011. RESULTS: There was a significant difference in percentage correct recall of the warning label between those in the text-only versus graphic warning label condition, 50% vs 83% (χ(2)=23.74, p=0.0001). Time to first viewing of the graphic warning label text and dwell time duration (i.e., time spent looking) on the graphic image were significantly associated with correct recall. Warning labels that drew attention more quickly and resulted in longer dwell times were associated with better recall. CONCLUSIONS: Graphic warning labels improve smokers' recall of warning and health risks; these labels do so by drawing and holding attention.

Association of the nicotine metabolite ratio and CHRNA5/CHRNA3 polymorphisms with smoking rate among treatment-seeking smokers.

INTRODUCTION: Genome-wide association studies have linked single-nucleotide polymorphisms (SNPs) in the CHRNA5/A3/B4 gene cluster with heaviness of smoking. The nicotine metabolite ratio (NMR), a measure of the rate of nicotine metabolism, is associated with the number of cigarettes per day (CPD) and likelihood of cessation. We tested the potential interacting effects of these two risk factors on CPD. METHODS: Pretreatment data from three prior clinical trials were pooled for analysis. One thousand and thirty treatment seekers of European ancestry with genotype data for the CHRNA5/A3/B4 SNPs rs578776 and rs1051730 and complete data for NMR and CPD at pretreatment were included. Data for the third SNP, rs16969968, were available for 677 individuals. Linear regression models estimated the main and interacting effects of genotype and NMR on CPD. RESULTS: We confirmed independent associations between the NMR and CPD as well as between the SNPs rs16969968 and rs1051730 and CPD. We did not detect a significant interaction between NMR and any of the SNPs examined. CONCLUSIONS: This study demonstrates the additive and independent association of the NMR and SNPs in the CHRNA5/A3/B4 gene cluster with smoking rate in treatment-seeking smokers.

Mouse model predicts effects of smoking and varenicline on event-related potentials in humans.

BACKGROUND: Nicotine alters auditory event-related potentials (ERPs) in rodents and humans and is an effective treatment for smoking cessation. Less is known about the effects of the partial nicotine agonist varenicline on ERPs. METHODS: We measured the effects of varenicline and nicotine on the mouse P20 and varenicline and smoking on the human P50 in a paired-click task. Eighteen mice were tested following nicotine, varenicline, and their combination. One hundred and fourteen current smokers enrolled in a placebo-controlled within-subject crossover study to test the effects of varenicline during smoking and abstinence. Thirty-two subjects participated in the ERP study, with half receiving placebo first and half varenicline first (VP). RESULTS: Nicotine and varenicline enhanced mouse P20 amplitude, while nicotine improved P20 habituation by selectively increasing the first-click response. Similar to mice, abstinence reduced P50 habituation relative to smoking by reducing the first-click response. There was no effect of varenicline on P50 amplitude during abstinence across subjects. However, there was a significant effect of medication order on P50 amplitude during abstinence. Subjects in the PV group displayed reduced P50 during abstinence, which was blocked by varenicline. However, subjects in the VP group did not display abstinence-induced P50 reduction. CONCLUSIONS: Data suggest that smoking improves sensory processing. Varenicline mimics amplitude changes associated with nicotine and smoking but fails to alter habituation. The effect of medication order suggests a possible carryover effect from the previous arm. This study supports the predictive validity of ERPs in mice as a marker of drug effects in human studies.

Convergent evidence that choline acetyltransferase gene variation is associated with prospective smoking cessation and nicotine dependence.

The ability to quit smoking is heritable, yet few genetic studies have investigated prospective smoking cessation. We conducted a systems-based genetic association analysis in a sample of 472 treatment-seeking smokers of European ancestry after 8 weeks of transdermal nicotine therapy for smoking cessation. The genotyping panel included 169 single-nucleotide polymorphisms (SNPs) in 7 nicotinic acetylcholine receptor subunit genes and 4 genes in the endogenous cholinergic system. The primary outcome was smoking cessation (biochemically confirmed) at the end of treatment. SNPs clustered in the choline acetyltransferase (ChAT) gene were individually identified as nominally significant, and a 5-SNP haplotype (block 6) in ChAT was found to be significantly associated with quitting success. Single SNPs in ChAT haplotype block 2 were also associated with pretreatment levels of nicotine dependence in this cohort. To replicate associations of SNPs in haplotype blocks 2 and 6 of ChAT with nicotine dependence in a non-treatment-seeking cohort, we used data from an independent community-based sample of 629 smokers representing 200 families of European ancestry. Significant SNP and haplotype associations were identified for multiple measures of nicotine dependence. Although the effect sizes in both cohorts are modest, converging data across cohorts and phenotypes suggest that ChAT may be involved in nicotine dependence and ability to quit smoking. Additional sequencing and characterization of ChAT may reveal functional variants that contribute to nicotine dependence and smoking cessation.

Working memory deficits predict short-term smoking resumption following brief abstinence.

As many as one-half of smokers relapse in the first week following a quit attempt, and subjective reports of cognitive deficits in early abstinence are associated with increased relapse risk. This study examined whether objective cognitive performance after 3 days of abstinence predicts smoking resumption in a 7-day simulated quit attempt. Sixty-seven treatment-seeking smokers received either varenicline or placebo (randomized double-blind) for 21 days. Following medication run-up (days 1-10), there was a 3-day mandatory (biochemically confirmed) abstinence period (days 11-13) during which working memory (Letter-N-Back Task) and sustained attention (Continuous Performance Task) were assessed (day 13). Participants were then exposed to a scheduled smoking lapse and instructed to try to remain abstinent for the next 7 days (days 15-21). Poorer cognitive performance (slower correct reaction time on Letter-N-Back task) during abstinence predicted more rapid smoking resumption among those receiving placebo (p=0.038) but not among those receiving varenicline. These data lend further support for the growing recognition that cognitive deficits involving working memory are a core symptom of nicotine withdrawal and a potential target for the development of pharmacological and behavioral treatments.

Experimental evaluation of antitobacco PSAs: effects of message content and format on physiological and behavioral outcomes.

INTRODUCTION: Antitobacco media campaigns using public service announcements (PSAs) have shown promise in reducing smoking initiation and increasing intentions to quit. Research on what makes an effective PSA has had mixed outcomes. The present study tested the effects of specific message features in antitobacco PSAs, using theory-based physiological and self-report outcomes. METHODS: PSAs were categorized as high or low in message sensation value (MSV) and strength of argument and presented to 200 current smokers in a 2 x 2 factorial design. Physiological responses-specifically, heart rate, skin conductance, zygomaticus major, and corrugator supercilii-were assessed while participants viewed the PSAs. Beliefs, attitudes, efficacy, norms, and intentions to quit were assessed immediately following viewing. RESULTS: Corrugator activity was significantly greater in the high MSV condition. Among those low in sensation seeking, low MSV PSAs elicited higher self-efficacy, whereas the reverse was true for high sensation seekers. High MSV PSAs elicited higher negative beliefs in low sensation seekers. Adding physiological measures to a model predicting intention to quit did not improve the explained variance. DISCUSSION: The present study represents the first comprehensive theory-based experimental investigation of the effects of different features of antitobacco PSAs and provides a framework for future research in identifying effective features of such PSAs. Results illustrate the importance of considering individual differences, characterizing both PSA content and format, and outcome and response measures when evaluating antitobacco PSAs.