Rebecca J. Beyth

Screening for prostate cancer: systematic review and meta-analysis of randomised controlled trials

Objective To examine the evidence on the benefits and harms of screening for prostate cancer. Design Systematic review and meta-analysis of randomised controlled trials. Data sources Electronic databases including Medline, Embase, CENTRAL, abstract proceedings, and reference lists up to July 2010. Review methods Included studies were randomised controlled trials comparing screening by prostate specific antigen with or without digital rectal examination versus no screening. Data abstraction and assessment of methodological quality with the GRADE approach was assessed by two independent reviewers and verified by the primary investigator. Mantel-Haenszel and inverse variance estimates were calculated and pooled under a random effects model expressing data as relative risks and 95% confidence intervals. Results Six randomised controlled trials with a total of 387 286 participants that met inclusion criteria were analysed. Screening was associated with an increased probability of receiving a diagnosis of prostate cancer (relative risk 1.46, 95% confidence interval 1.21 to 1.77; P<0.001) and stage I prostate cancer (1.95, 1.22 to 3.13; P=0.005). There was no significant effect of screening on death from prostate cancer (0.88, 0.71 to 1.09; P=0.25) or overall mortality (0.99, 0.97 to 1.01; P=0.44). All trials had one or more substantial methodological limitations. None provided data on the effects of screening on participants’ quality of life. Little information was provided about potential harms associated with screening. Conclusions The existing evidence from randomised controlled trials does not support the routine use of screening for prostate cancer with prostate specific antigen with or without digital rectal examination.

Self-monitoring of oral anticoagulation: systematic review and meta-analysis of individual patient data

BACKGROUND Uptake of self-testing and self-management of oral anticoagulation [corrected] has remained inconsistent, despite good evidence of their effectiveness. To clarify the value of self-monitoring of oral anticoagulation, we did a meta-analysis of individual patient data addressing several important gaps in the evidence, including an estimate of the effect on time to death, first major haemorrhage, and thromboembolism. METHODS We searched Ovid versions of Embase (1980-2009) and Medline (1966-2009), limiting searches to randomised trials with a maximally sensitive strategy. We approached all authors of included trials and requested individual patient data: primary outcomes were time to death, first major haemorrhage, and first thromboembolic event. We did prespecified subgroup analyses according to age, type of control-group care (anticoagulation-clinic care vs primary care), self-testing alone versus self-management, and sex. We analysed patients with mechanical heart valves or atrial fibrillation separately. We used a random-effect model method to calculate pooled hazard ratios and did tests for interaction and heterogeneity, and calculated a time-specific number needed to treat. FINDINGS Of 1357 abstracts, we included 11 trials with data for 6417 participants and 12,800 person-years of follow-up. We reported a significant reduction in thromboembolic events in the self-monitoring group (hazard ratio 0·51; 95% CI 0·31-0·85) but not for major haemorrhagic events (0·88, 0·74-1·06) or death (0·82, 0·62-1·09). Participants younger than 55 years showed a striking reduction in thrombotic events (hazard ratio 0·33, 95% CI 0·17-0·66), as did participants with mechanical heart valve (0·52, 0·35-0·77). Analysis of major outcomes in the very elderly (age ≥85 years, n=99) showed no significant adverse effects of the intervention for all outcomes. INTERPRETATION Our analysis showed that self-monitoring and self-management of oral coagulation is a safe option for suitable patients of all ages. Patients should also be offered the option to self-manage their disease with suitable health-care support as back-up. FUNDING UK National Institute for Health Research (NIHR) Technology Assessment Programme, UK NIHR National School for Primary Care Research.

Voices of African American, Caucasian, and Hispanic surrogates on the burdens of end-of-life decision making.

BackgroundEnd-of-life decisions are frequently made by patients’ surrogates. Race and ethnicity may affect such decision making. Few studies have described how different racial/ethnic groups experience end-of-life surrogate decision making.ObjectivesTo describe the self-reported experience the self-reported experience of African-American, Caucasian, and Hispanic surrogate decision makers of seriously ill patients and to examine the relationship of race, ethnicity, and culture to that experience.DesignPurposive sample to include racial/ethnic minorities in a qualitative study using focus group interviews.ParticipantsThe participants of the study were 44 experienced, mostly female, surrogate decision makers for older veterans.ApproachTranscripts were qualitatively analyzed to identify major themes, with particular attention to themes that might be unique to each of the three groups.ResultsThe experience of burden of end-of-life decision making was similar in all three groups. This burden in its medical, personal, and familial dimensions is compounded by uncertainty about prognosis and the patient’s preferences. Racial/ethnic variations of responses to this burden concerned the physician–family relationship, religion and faith, and past experiences with race/ethnicity concordant versus non-concordant physicians.ConclusionsRegardless of race/ethnicity, surrogates for seriously ill patients appeared to experience increased significant, multidimensional burdens of decision making under conditions of uncertainty about a patient’s preferences. This aspect of the burden of surrogate decision making may not be fully appreciated by physicians. Physicians should identify and be especially attentive to strategies used by surrogates, which may vary by race/ethnicity, to reduce the uncertainty about a patient’s preferences and thus the burden of surrogate decision making to assist them in this difficult process.

Evidence-Based Risk Communication: A Systematic Review

Shared decision making is a collaborative process that allows patients and medical professionals to consider the best scientific evidence available, along with patients values and preferences, to make health care decisions (1). A recent Institute of Medicine report concluded that although people desire a patient experience that includes deep engagement in shared decision making, there are gaps between what patients want and what they get (2). For patients to get the experience they want, providers must effectively communicate evidence about benefits and harms. To improve the decision-making process, the Institute of Medicine recommended development and dissemination of high-quality communication tools (2). New tools, however, must match patients numerical abilities, which are often limited. For example, in one study, as many as 40% of high school graduates could not perform basic numerical operations, such as converting 1% of 1000 to 10 of 1000. This collective statistical illiteracy is a major barrier to the interpretation of health statistics (3). Physicians may also find statistical information difficult to interpret and explain (4). Existing literature about methods of communicating benefits and harms is broad. One review, based on 19 studies, concluded that the choice of a specific graphic is not as important as whether the graphic frames the frequency of an event with a visual representation of the total population in which it occurs (5). Another review, involving a limited literature search, found that comprehension improved when using frequencies (such as 1 in 5) instead of event rates (such as 20%) and using absolute risk reductions (ARRs) instead of relative risk reductions (RRRs) (6). The review did not assess affective outcomes, such as patient satisfaction, and behavioral outcomes, such as changes in decision making. Yet another review identified strong evidence that patients misinterpret RRRs and supported the effectiveness of graphs in communicating harms (7). However, they did not examine the comparative effectiveness of such approaches. More narrowly focused Cochrane reviews examined the communication of risk specific to screening tests (8, 9); numerical presentations, such as ARRs, RRRs, and numbers needed to treat (NNTs) (10); and effects of decision aids (11). An expert commentary about effective risk communication recommended using plain language, icon arrays, and absolute risks and providing time intervals with risk information (12). A group of experts identified 11 key components of risk communication, including presenting numerical estimates in context with evaluative labels, conveying uncertainty, and tailoring estimates (13). The aim of this systematic review is to comprehensively examine the comparative effectiveness of all methods of communicating probabilistic information about benefits and harms to patients to maximize their understanding, satisfaction, and decision-making ability. Methods We developed and followed a plan for the review that included several searches and dual abstraction of study data using standardized abstraction forms. Data Sources and Study Selection We searched PubMed (1966 to March 2014), CINAHL, EMBASE, and the Cochrane Central Register of Controlled Trials (1966 to December 2011) using keywords and structured terms related to the concepts of patients; communication; riskbenefit; and outcomes, such as understanding or comprehension, preferences or satisfaction, and decision making. Supplement 1 shows the detailed search strategy. Supplement 1. Search Strategies We included cross-sectional or prospective, longitudinal trials that were published in English and had an active control group that recruited patients or healthy volunteers and compared any method of communicating probabilistic information with another method. We focused on different methods of communicating the same specific probabilities to eliminate any independent effects that could result from different probabilities being studied (for example, different magnitudes or directions of effect). Studies of personalized risks, which may vary from person to person, were included when participants were randomly assigned. When studies of personalized risks were not randomized, the risks were considered to differ between the groups and were excluded. No limits were placed on study size, location, or duration or on the nature of the communication method. When needed, we reviewed sources specified in the articles, such as Web sites, to directly review the interventions and determine whether probabilistic information was addressed. Studies of medical students, health professionals, and public health or mass media campaigns were excluded. One independent reviewer screened each title and abstract and excluded citations that were not original studies or were unrelated to probabilistic information. Two independent reviewers screened the full text of the remaining citations to identify eligible articles. Disagreements between the 2 reviewers were resolved by consensus, with a third reviewer arbitrating any unresolved disagreements. Data Extraction and Quality Assessment Two reviewers independently abstracted detailed information about the study population, interventions, primary outcomes, and risk of bias from each included study using a standardized abstraction form, which was developed a priori (Supplement 2). A third reviewer resolved any disagreements. We categorized outcomes in 1 of 3 domains: cognitive (or understanding, such as accuracy in answering questions related to probabilistic information, or general comprehension of the probabilistic information), affective (such as preferences for or satisfaction with the method of communicating probabilistic information), and behavioral (such as real or theoretical decision making). Supplement 2. Abstraction Form Risk of bias in randomized, controlled trials was assessed on the basis of adequacy of randomization, allocation concealment, similarity of study groups at baseline, blinding, equal treatment of groups throughout the study, completeness of follow-up, and intention to treat (participants analyzed in the groups to which they were randomly assigned) (14). Risk of bias in observational studies was assessed with a modified set of criteria adapted from the NewcastleOttawa Scale (15). Data Synthesis and Analysis Data were tabulated, and the frequency of all head-to-head comparisons in studies was assessed to identify clusters of comparisons. In many instances, several interventions were bundled in a single study group (such as event rate plus icon array, or event rate plus natural frequencies plus ARRs). Bundles were not separated or combined with similar interventions because it could not be determined which component of the bundle drove the intervention. Descriptive statistics were used. We decided a priori not to do meta-analysis because of study heterogeneity. We emphasized findings from randomized studies as well as nonrandomized studies when findings were supported by more than 1 study. Role of the Funding Source No funding supported this study. The authors participated within their role on the Evidence-Based Medicine Task Force of the Society of General Internal Medicine. Results The initial search through December 2011 retrieved 22103 citations (16661 from PubMed, 1194 from CINAHL, 2861 from the Cochrane Central Register of Controlled Trials, and 1387 from EMBASE), and 20076 remained after removing duplicates. We updated the PubMed search through 30 March 2014, yielding 6529 additional citations; 5970 remained after removing duplicates, for a total of 26046 citations for review. A total of 630 articles were selected for full-text review and 84 were included, representing 91 unique studies (1699). Reasons for exclusion are noted in Figure 1, and study details are provided in Supplement 3. Figure 1. Summary of evidence search and selection. Supplement 3. Details of All Included Studies Seventy-four (81.3%) of the 91 included studies were randomized trials, most with cross-sectional designs. The median number of participants in randomized trials was 268 (range, 31 to 4685), and the median in all studies was 268 (range, 24 to 16133). Thirty-three studies (36.3%) included patients at specific risk for the target condition of interest. Forty-eight studies (52.7%) presented probabilistic data about benefits of a therapy or intervention (with 7 [14.6%] also presenting harms), 21 (23.1%) presented data only on harms, and 9 (10%) involved screening tests. Forty-nine studies (54.4%) delivered interventions on paper and 39 (42.9%) on a computer, typically over the Internet. The characteristics of study participants are presented in Tables 1 and 2. Table 1. Characteristics of Study Participants Table 2. Proportion of Studies Including Participants at Risk Versus Not at Risk for Target Condition Risk of bias for the included randomized trials was moderate (Figure 2). Randomization was adequate in 32 trials (42.7%), inadequate in 3 (4.0%), and unclear in 40 (53.3%). Allocation concealment was not stated in 55 trials (73.3%). Similarity of groups at baseline was adequate in 37 trials (49.3%) and unclear in 32 (42.7%). Blinding, equal treatment, and intention-to-treat items were similarly difficult to assess from reported information. Figure 2. Risk of bias for randomized, controlled trials (n = 74). Adapted from reference 100. Study Interventions and Comparators A frequency table (heat map) of all study intervention comparisons was created to identify clusters of comparisons (Supplement 4). The heat map represents study group comparisons, so one study may contribute several comparisons. The most commonly studied numerical presentations of data were natural frequencies, defined as the numbers of persons with events juxtaposed with a baseline denominator of persons (for example, 4 out of 100 persons had the outcome); event rates, defined as the proportions of persons wi

Evidence-based risk communication

Shared decision making is a collaborative process that allows patients and medical professionals to consider the best scientific evidence available, along with patients values and preferences, to make health care decisions (1). A recent Institute of Medicine report concluded that although people desire a patient experience that includes deep engagement in shared decision making, there are gaps between what patients want and what they get (2). For patients to get the experience they want, providers must effectively communicate evidence about benefits and harms. To improve the decision-making process, the Institute of Medicine recommended development and dissemination of high-quality communication tools (2). New tools, however, must match patients numerical abilities, which are often limited. For example, in one study, as many as 40% of high school graduates could not perform basic numerical operations, such as converting 1% of 1000 to 10 of 1000. This collective statistical illiteracy is a major barrier to the interpretation of health statistics (3). Physicians may also find statistical information difficult to interpret and explain (4). Existing literature about methods of communicating benefits and harms is broad. One review, based on 19 studies, concluded that the choice of a specific graphic is not as important as whether the graphic frames the frequency of an event with a visual representation of the total population in which it occurs (5). Another review, involving a limited literature search, found that comprehension improved when using frequencies (such as 1 in 5) instead of event rates (such as 20%) and using absolute risk reductions (ARRs) instead of relative risk reductions (RRRs) (6). The review did not assess affective outcomes, such as patient satisfaction, and behavioral outcomes, such as changes in decision making. Yet another review identified strong evidence that patients misinterpret RRRs and supported the effectiveness of graphs in communicating harms (7). However, they did not examine the comparative effectiveness of such approaches. More narrowly focused Cochrane reviews examined the communication of risk specific to screening tests (8, 9); numerical presentations, such as ARRs, RRRs, and numbers needed to treat (NNTs) (10); and effects of decision aids (11). An expert commentary about effective risk communication recommended using plain language, icon arrays, and absolute risks and providing time intervals with risk information (12). A group of experts identified 11 key components of risk communication, including presenting numerical estimates in context with evaluative labels, conveying uncertainty, and tailoring estimates (13). The aim of this systematic review is to comprehensively examine the comparative effectiveness of all methods of communicating probabilistic information about benefits and harms to patients to maximize their understanding, satisfaction, and decision-making ability. Methods We developed and followed a plan for the review that included several searches and dual abstraction of study data using standardized abstraction forms. Data Sources and Study Selection We searched PubMed (1966 to March 2014), CINAHL, EMBASE, and the Cochrane Central Register of Controlled Trials (1966 to December 2011) using keywords and structured terms related to the concepts of patients; communication; riskbenefit; and outcomes, such as understanding or comprehension, preferences or satisfaction, and decision making. Supplement 1 shows the detailed search strategy. Supplement 1. Search Strategies We included cross-sectional or prospective, longitudinal trials that were published in English and had an active control group that recruited patients or healthy volunteers and compared any method of communicating probabilistic information with another method. We focused on different methods of communicating the same specific probabilities to eliminate any independent effects that could result from different probabilities being studied (for example, different magnitudes or directions of effect). Studies of personalized risks, which may vary from person to person, were included when participants were randomly assigned. When studies of personalized risks were not randomized, the risks were considered to differ between the groups and were excluded. No limits were placed on study size, location, or duration or on the nature of the communication method. When needed, we reviewed sources specified in the articles, such as Web sites, to directly review the interventions and determine whether probabilistic information was addressed. Studies of medical students, health professionals, and public health or mass media campaigns were excluded. One independent reviewer screened each title and abstract and excluded citations that were not original studies or were unrelated to probabilistic information. Two independent reviewers screened the full text of the remaining citations to identify eligible articles. Disagreements between the 2 reviewers were resolved by consensus, with a third reviewer arbitrating any unresolved disagreements. Data Extraction and Quality Assessment Two reviewers independently abstracted detailed information about the study population, interventions, primary outcomes, and risk of bias from each included study using a standardized abstraction form, which was developed a priori (Supplement 2). A third reviewer resolved any disagreements. We categorized outcomes in 1 of 3 domains: cognitive (or understanding, such as accuracy in answering questions related to probabilistic information, or general comprehension of the probabilistic information), affective (such as preferences for or satisfaction with the method of communicating probabilistic information), and behavioral (such as real or theoretical decision making). Supplement 2. Abstraction Form Risk of bias in randomized, controlled trials was assessed on the basis of adequacy of randomization, allocation concealment, similarity of study groups at baseline, blinding, equal treatment of groups throughout the study, completeness of follow-up, and intention to treat (participants analyzed in the groups to which they were randomly assigned) (14). Risk of bias in observational studies was assessed with a modified set of criteria adapted from the NewcastleOttawa Scale (15). Data Synthesis and Analysis Data were tabulated, and the frequency of all head-to-head comparisons in studies was assessed to identify clusters of comparisons. In many instances, several interventions were bundled in a single study group (such as event rate plus icon array, or event rate plus natural frequencies plus ARRs). Bundles were not separated or combined with similar interventions because it could not be determined which component of the bundle drove the intervention. Descriptive statistics were used. We decided a priori not to do meta-analysis because of study heterogeneity. We emphasized findings from randomized studies as well as nonrandomized studies when findings were supported by more than 1 study. Role of the Funding Source No funding supported this study. The authors participated within their role on the Evidence-Based Medicine Task Force of the Society of General Internal Medicine. Results The initial search through December 2011 retrieved 22103 citations (16661 from PubMed, 1194 from CINAHL, 2861 from the Cochrane Central Register of Controlled Trials, and 1387 from EMBASE), and 20076 remained after removing duplicates. We updated the PubMed search through 30 March 2014, yielding 6529 additional citations; 5970 remained after removing duplicates, for a total of 26046 citations for review. A total of 630 articles were selected for full-text review and 84 were included, representing 91 unique studies (1699). Reasons for exclusion are noted in Figure 1, and study details are provided in Supplement 3. Figure 1. Summary of evidence search and selection. Supplement 3. Details of All Included Studies Seventy-four (81.3%) of the 91 included studies were randomized trials, most with cross-sectional designs. The median number of participants in randomized trials was 268 (range, 31 to 4685), and the median in all studies was 268 (range, 24 to 16133). Thirty-three studies (36.3%) included patients at specific risk for the target condition of interest. Forty-eight studies (52.7%) presented probabilistic data about benefits of a therapy or intervention (with 7 [14.6%] also presenting harms), 21 (23.1%) presented data only on harms, and 9 (10%) involved screening tests. Forty-nine studies (54.4%) delivered interventions on paper and 39 (42.9%) on a computer, typically over the Internet. The characteristics of study participants are presented in Tables 1 and 2. Table 1. Characteristics of Study Participants Table 2. Proportion of Studies Including Participants at Risk Versus Not at Risk for Target Condition Risk of bias for the included randomized trials was moderate (Figure 2). Randomization was adequate in 32 trials (42.7%), inadequate in 3 (4.0%), and unclear in 40 (53.3%). Allocation concealment was not stated in 55 trials (73.3%). Similarity of groups at baseline was adequate in 37 trials (49.3%) and unclear in 32 (42.7%). Blinding, equal treatment, and intention-to-treat items were similarly difficult to assess from reported information. Figure 2. Risk of bias for randomized, controlled trials (n = 74). Adapted from reference 100. Study Interventions and Comparators A frequency table (heat map) of all study intervention comparisons was created to identify clusters of comparisons (Supplement 4). The heat map represents study group comparisons, so one study may contribute several comparisons. The most commonly studied numerical presentations of data were natural frequencies, defined as the numbers of persons with events juxtaposed with a baseline denominator of persons (for example, 4 out of 100 persons had the outcome); event rates, defined as the proportions of persons wi

Therapeutic goal attainment in patients with hypertension and dyslipidemia

Background:Recent guidelines emphasize the need to assess and treat overall risk for cardiovascular disease through the concomitant management of multiple risk factors. We sought to ascertain treatment patterns and attainment of therapeutic goals in patients with isolated and concomitant hypertension and dyslipidemia, both with and without diabetes mellitus (DM) and symptomatic cardiovascular disease. Methods:Inception cohorts of more than 41,000 newly diagnosed hypertension and dyslipidemia patients from 6 medical centers of the south-central Veterans Affairs health care system were evaluated. Treatment patterns and goal attainment for low-density lipoprotein cholesterol (LDL-C; Third Report of the National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults guidelines: <160, <130, or ≤100 mg/dL depending on risk factors) and blood pressure (BP; Joint National Committee 6: <140/90 or <130/85 mm Hg depending on risk factors) were measured at 1 year. Separate analyses were conducted in patients with and without DM and symptomatic cardiovascular disease. Results:Treatment rates in patients with and without DM and symptomatic disease ranged from 46.6% to 71.3% in patients with hypertension only, from 31.5% to 64.1% in patients with dyslipidemia only, and from 64.3% to 91.3% in patients with both conditions. Among asymptomatic patients, 40.6% of nondiabetics and 20.6% of patients with DM with isolated hypertension reached BP targets. Attainment of LDL-C goals was slightly higher and reached 52.8% among patients with DM with concomitant hypertension. Among symptomatic patients, attainment of all goals was <40% for all groups. The proportion of asymptomatic patients with concomitant disease reaching goal for both BP and LDL-C was 24.4% among nondiabetics and 15.4% among patients with DM; these proportions decreased to 13.6% and 13.4% respectively, among patients with symptomatic cardiovascular disease. Conclusions:The majority of patients were receiving pharmacological treatment of hypertension and dyslipidemia, yet attainment of therapeutic goals was generally <50%. Further work is needed to determine factors related to improvement in management and outcomes of patients with multiple cardiovascular risk factors.

Cardiovascular Disease and Cognitive Decline in Postmenopausal Women: Results From the Women's Health Initiative Memory Study

Background Data on cardiovascular diseases (CVD) and cognitive decline are conflicting. Our objective was to investigate if CVD is associated with an increased risk for cognitive decline and to examine whether hypertension, diabetes, or adiposity modify the effect of CVD on cognitive functioning. Methods and Results Prospective follow‐up of 6455 cognitively intact, postmenopausal women aged 65 to 79 years old enrolled in the Womens Health Initiative Memory Study (WHIMS). CVD was determined by self‐report. For cognitive decline, we assessed the incidence of mild cognitive impairment (MCI) or probable dementia (PD) via modified mini‐mental state examination (3 MS) score, neurocognitive, and neuropsychiatric examinations. The median follow‐up was 8.4 years. Women with CVD tended to be at increased risk for cognitive decline compared with those free of CVD (hazard ratio [HR], 1.29; 95% CI: 1.00, 1.67). Women with myocardial infarction or other vascular disease were at highest risk (HR, 2.10; 95% CI: 1.40, 3.15 or HR, 1.97; 95% CI: 1.34, 2.87). Angina pectoris was moderately associated with cognitive decline (HR 1.45; 95% CI: 1.05, 2.01) whereas no significant relationships were found for atrial fibrillation or heart failure. Hypertension and diabetes increased the risk for cognitive decline in women without CVD. Diabetes tended to elevate the risk for MCI/PD in women with CVD. No significant trend was seen for adiposity. Conclusions CVD is associated with cognitive decline in elderly postmenopausal women. Hypertension and diabetes, but not adiposity, are associated with a higher risk for cognitive decline. More research is warranted on the potential of CVD prevention for preserving cognitive functioning.

A Systematic Review of the Quality of Evidence of Ablative Therapy for Small Renal Masses

PURPOSE We critically assessed the methodological and reporting quality of published studies of ablative techniques for small renal masses. MATERIALS AND METHODS We performed a systematic PubMed® and EMBASE® literature search from January 1966 to March 2010 to identify all full text, original research publications on ablative therapy for renal masses. Six reviewers working independently in 3 teams performed duplicate data abstraction using Strengthening the Reporting of Observational Studies in Epidemiology criteria, which were pilot tested in a separate sample. RESULTS A total of 117 original research publications published in a 15-year period (1995 to 2009) met eligibility criteria. No randomized, controlled trials were identified. All studies were observational and 88.9% had 1 arm with no comparison group. Median sample size was 18 patients (IQR 5.5, 40.0) and 53.8% of studies included 20 or fewer patients. Median followup was 14.0 months (IQR 8.0, 23.8) and only 19.7% of studies had an average followup of greater than 24 months. Of the studies 20.5% mentioned the number of operators involved and only 6.0% provided information on their experience level. Of the studies 66.7% addressed the recurrence rate. Disease specific and overall survival was reported in only 15.4% and 16.2% of studies, respectively. CONCLUSIONS The published literature on the therapeutic efficacy of ablative therapy for renal masses is largely limited to uncontrolled, 1-arm observational studies. In the absence of higher quality evidence ablative therapy outside research studies should be limited to select patients who are not candidates for surgical intervention.

Racial and Ethnic Differences in the Treatment of Seriously Ill Patients: A Comparison of African-American, Caucasian and Hispanic Veterans

BACKGROUND No national data exist regarding racial/ethnic differences in the use of interventions for patients at the end of life. OBJECTIVES To test whether among 3 cohorts of hospitalized seriously ill veterans with cancer, noncancer or dementia the use of common life-sustaining treatments differed significantly by race/ethnicity. DESIGN Retrospective cohort study during fiscal years 1991-2002. PATIENTS Hospitalized veterans >55 years, defined clinically as at high-risk for 6-month mortality, not by decedent data. MEASUREMENTS Utilization patterns by race/ethnicity for 5 life-sustaining therapies. Logistic regression models evaluated differences among Caucasians, African Americans and Hispanics, controlling for age, disease severity and clustering of patients within Veterans Affairs (VA) medical centers. RESULTS Among 166,059 veterans, both differences and commonalities across diagnostic cohorts were found. African Americans received more or the same amount of end-of-life treatments across disease cohorts, except for less resuscitation [OR = 0.84 (0.77-0.92), p = 0.002] and mechanical ventilation [OR = 0.89 (0.85-0.94), p < or = 0.0001] in noncancer patients. Hispanics were 36% (cancer) to 55% (noncancer) to 88% (dementia) more likely to receive transfusions than Caucasians (p < 0.0001). They received similar rates as Caucasians for all other interventions in all other groups, except for 161% higher likelihood for mechanical ventilation in patients with dementia. Increased end-of-life treatments for both minority groups were most pronounced in the dementia cohort. Differences demonstrated a strong interaction with the disease cohort. CONCLUSIONS Differences in level of end-of-life treatments were disease specific and bidirectional for African Americans. In the absence of generally accepted, evidence-based standards for end-of-life care, these differences may or may not constitute disparities.

Appropriate use of myocardial perfusion imaging in a veteran population: profit motives and professional liability concerns.

calate niacin use, specifically Niaspan in the United States, with its prominent “intervention-style” ads.11 Our study is limited in that we did not have access to patient-level data to determine whether niacin prescribing was clinically appropriate. Our study only evaluated the prescription niacin market; niacin use likely exceeds our estimates since some niacin products can be purchased over the counter. In conclusion, our study shows that prescription niacin sales are substantial and growing, even in the absence of contemporary supportive trial evidence. The discordance between sales and evidence should be a focus of professional dialogue about the role of this medication in the medical armamentarium.