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.

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.

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.

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.

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.

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.

CHRNA4 and tobacco dependence: from gene regulation to treatment outcome.

CONTEXT: Given the probable importance of the alpha4 subunit of the neuronal nicotinic acetylcholine receptor, the gene that codes for this subunit (CHRNA4) represents an excellent starting point for a genetic investigation of smoking behavior. OBJECTIVE: To achieve a better understanding of the role of this gene in the cause and treatment of tobacco dependence, we adopted a transdisciplinary pharmacogenetic approach. DESIGN: Study at the behavioral and clinical levels of analysis. SETTING: Academic research. PARTICIPANTS: Smokers (n = 316) between the ages of 18 and 50 years were recruited from the Denver, Colorado, metropolitan area. MAIN OUTCOME MEASURES: Bioinformatics analyses, cell culture experiments, and analyses of CHRNA4 expression and nicotine binding in postmortem human brain tissue advanced 2 single-nucleotide polymorphisms (rs6122429 and rs2236196). RESULTS: Both single-nucleotide polymorphisms were associated with subjective responses to smoking in the laboratory among 316 smokers. Likewise, among 353 participants in a clinical trial, rs2236196 was associated with smoking cessation outcomes. CONCLUSIONS: Results of analyses ranging from basic biological approaches to clinical outcome data provide consistent evidence that 2 single-nucleotide polymorphisms in CHRNA4 are functional at a biological level and are associated with nicotine dependence phenotypes. This interdisciplinary approach to the genetics of nicotine dependence provides a model for testing how functional genetic variation is translated from changes in messenger RNA and protein to individual differences in behavior and treatment outcome.

Mispredicting and misremembering: patients with renal failure overestimate improvements in quality of life after a kidney transplant.

OBJECTIVE: People tend to overestimate the impact that future events will have on their quality of life. In the case of a medical treatment like kidney transplant, this should result in biased predictions--overestimates of how much the transplant will benefit quality of life. The authors surveyed kidney transplant patients, both before and after transplant, to test whether they would overestimate the benefits of a successful transplant for their quality of life. DESIGN: The authors interviewed 307 patients on a waiting list for cadaveric renal or renal-pancreatic transplant, and 195 patients one year after a successful transplant. A sub sample of patients were interviewed both before and after transplant. MAIN OUTCOME MEASURES: The survey included measures of quality of life, both in terms of an overall estimate (0-100), and across sub domains, including health, employment, and travel. RESULTS: Cross-sectional results suggested that overall quality of life improved after transplant, but the predictions of pretransplant patients overestimated the magnitude of the improvement (p < .01). In addition, patients predicted large improvements in specific life domains that did not change. These results were confirmed in longitudinal, prospective analyses. Additional analyses showed that posttransplant patients recalled their pretransplant quality of life to be much lower than what they had reported at the time. CONCLUSION: Consistent with an impact bias, patients substantially overestimated the benefits of a successful kidney transplant, both in terms of predictions of life after treatment, and in their memories of QOL before the transplant.

CYP2B6 genotype alters abstinence rates in a bupropion smoking cessation trial.

BACKGROUND: CYP2B6 is the primary enzyme involved in bupropion (Zyban; GlaxoSmithKline, Research Triangle Park, North Carolina) metabolism. Genetic polymorphisms in CYP2B6, such as CYP2B6*6, can alter bupropion metabolism and may affect bupropion treatment outcome. METHODS: Subjects participated in a smoking cessation clinical trial of bupropion versus placebo. The main outcome was a 7-day point prevalence abstinence rate measured 10 weeks after the start of treatment (i.e., end of treatment) and at the 6-month follow-up; secondary outcomes were severity of adverse effects, withdrawal, and urge to smoke. Subjects were haplotyped for the CYP2B6*6 variants. RESULTS: Among smokers in the CYP2B6*6 group (CYP2B6*1/*6 or CYP2B6*6/*6 genotype, n = 147, 45% of the population), bupropion produced significantly higher abstinence rates than placebo at the end of treatment (32.5% vs. 14.3%, p = .01) and at the 6-month follow-up (31.2% vs. 12.9%, p = .008). In contrast, bupropion was no more effective than placebo for smokers in the CYP2B6*1 group (CYP2B6*1/*1, n = 179) at the end of treatment (31.0% vs. 31.6%, p = .93) or at the 6-month follow-up (22.0% vs. 21.5%, p = .94). There was a significant genotype by treatment interaction at the end of treatment (odds ratio [OR] = 2.97, confidence interval [CI] = 1.05-8.40, p = .04), which was similar at 6-month follow-up (OR = 2.98, CI = .98-9.06, p = .05). CONCLUSIONS: These data suggest that smokers with the CYP2B6*6 genotype have a higher liability to relapse on placebo and that they may be good candidates for bupropion treatment for smoking cessation.

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.

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.

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: 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.

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.

Role of functional genetic variation in the dopamine D2 receptor (DRD2) in response to bupropion and nicotine replacement therapy for tobacco dependence: results of two randomized clinical trials.

Although bupropion and nicotine replacement therapy (NRT) are efficacious tobacco dependence treatments, there is substantial interindividual variability in therapeutic response and most smokers relapse. Pharmacogenetics research may improve treatment outcomes by identifying genetic variants predictive of therapeutic response. We investigated the roles of two functional genetic variants in the dopamine D2 receptor (DRD2) gene in response to pharmacotherapy for tobacco dependence among participants in two randomized clinical trials with a 6-month follow-up period: a double-blind placebo-controlled trial of bupropion (n=414) and an open label trial of transdermal nicotine vs nicotine nasal spray (n=368). At the end of the treatment phase, a statistically significant (p=0.01) interaction between the DRD2 - 141C Ins/Del genotype and treatment indicated a more favorable response to bupropion among smokers homozygous for the Ins C allele compared to those carrying a Del C allele. By contrast, smokers carrying the Del C allele had statistically significantly (p=0.006) higher quit rates on NRT compared to those homozygous for the Ins C allele, independent of NRT type. The C957T variant was also associated (p=0.03) with abstinence following NRT. These results suggest that bupropion may be the preferred pharmacologic treatment for smokers homozygous for the DRD2 - 141 Ins C allele, while NRT may be more beneficial for those who carry the Del C allele. Study findings require confirmation in additional larger samples before they are applied in practice.

In a mailed physician survey, questionnaire length had a threshold effect on response rate.

OBJECTIVE: To examine the association between questionnaire length and response rate in a mailed survey of generalist physicians randomly selected from the American Medical Association master file. STUDY DESIGN AND SETTING: In a pilot study, otherwise similar questionnaires of 30 different lengths (849 to 1,867 words) were mailed to 192 physicians in April 1999. In the main study, questionnaires of 16 different lengths (564 to 988 words) were mailed to 1,700 physicians between June 1999 and January 2000. RESULTS: In the pilot study, response rate decreased from 60% for questionnaires 849 words in length to 16.7% for questionnaires over 1,800 words in length. Logistic regression revealed an odds ratio of 0.887 (95%CI 0.813, 0.968; p=0.006) for word count, expressed in units of 100 words. In the main study, response rate varied between 51.5% and 71.4%. Logistic regression showed no association between response and word count (OR 0.988; 95%CI 0.896, 1.090; p=0.81). CONCLUSION: There appears to have been a threshold in these studies of approximately 1,000 words. Questionnaires above the threshold had lower response rates than those below it (38.0% vs. 59.4%).

Ignorance of hedonic adaptation to hemodialysis: a study using ecological momentary assessment.

Healthy people generally underestimate the self-reported well-being of people with disabilities and serious illnesses. The cause of this discrepancy is in dispute, and the present study provides evidence for 2 causes. First, healthy people fail to anticipate hedonic adaptation to poor health. Using an ecological momentary assessment measure of mood, the authors failed to find evidence that hemodialysis patients are less happy than healthy nonpatients are, suggesting that they have largely, if not completely, adapted to their condition. In a forecasting task, healthy people failed to anticipate this adaptation. Second, although controls understated their own mood in both an estimation task and a recall task, patients were quite accurate in both tasks. This relative negativity in controls' estimates of their own moods could also contribute to their underestimation of the moods and overall well-being of patients.

Naltrexone reduces the relative reinforcing value of nicotine in a cigarette smoking choice paradigm.

RATIONALE: Human behavioral pharmacology studies can examine how medications that target different neurotransmitter systems influence different aspects of smoking. Naltrexone and bupropion have been shown to alter ad lib smoking behavior; however, medication effects on nicotine reward in a cigarette choice paradigm have yet to be investigated. OBJECTIVE: This study explored the effects of an acute dose of naltrexone, bupropion, or placebo on the relative reinforcing value of nicotine from cigarette smoking using new nicotine and de-nicotinized (Quest, 0.6 and 0.05 mg = "denicotinized") cigarettes. METHODS: In a double-blind, within-subjects design, 26 dependent smokers participated in three experimental cigarette smoking sessions following pretreatment with either naltrexone (50 mg), bupropion (300 mg), or placebo. After medication administration and 2 h of monitored deprivation from cigarettes and food, participants rated their responses to the initial exposure to the cigarettes and then participated in four choice sessions over a 2-h period during which they could take four puffs from either cigarette. RESULTS: The relative reinforcing value of nicotine, as measured by the number of nicotine puffs chosen out of 16, was significantly lower following naltrexone compared to placebo. There were no effects of an acute dose of bupropion on nicotine choices. CONCLUSIONS: These results suggest that naltrexone may reduce the relative reinforcing effects of nicotine via cigarette smoking and support ongoing investigation of opioid antagonists as potential smoking cessation pharmacotherapies.