Lisa R. Shugarman

Meta-analysis: surgical treatment of obesity.

Context The effectiveness of surgical therapy in the treatment of obesity is unclear. Contribution Many published studies of obesity surgery have significant limitations, and case series make up much of the evidence. Evidence is complicated by the heterogeneity of procedures studied. However, surgery can result in substantial amounts of weight loss (20 to 30 kg) for markedly obese individuals. One cohort study documented weight loss for 8 years with associated improvements in comorbid conditions, such as diabetes. Complications of surgery appear to occur in about 20% of patients. Implications Those considering surgical treatment for obesity should understand that, although patients who have surgery can lose substantial amounts of weight, the evidence base for these treatments is limited. The Editors The prevalence of obesity in the United States is reaching epidemic proportions. An estimated 30% of individuals met the criteria for obesity in 19992002 (1, 2), and many industrialized countries have seen similar increases. The health consequences of obesity include heart disease, diabetes, hypertension, hyperlipidemia, osteoarthritis, and sleep apnea (3-7). Weight loss of 5% to 10% has been associated with marked reductions in the risk for these chronic diseases and with reducing the incidence of diabetes (8-14). The increasing numbers of obese individuals have led to intensified interest in surgical treatments to achieve weight loss, and a variety of surgical procedures have been used (Figure 1). Bariatric surgery was first performed in 1954 with the introduction of the jejunoileal bypass, which bypasses a large segment of small intestine by connecting proximal small intestine to distal small intestine. With this procedure, weight loss occurs secondary to malabsorption from reduction of upstream pancreatic and biliary contents. However, diarrhea and nutritional deficiencies were common, and this procedure was discontinued because of the complication of irreversible hepatic cirrhosis. With the development of surgical staplers came the introduction of gastroplasty procedures by Gomez in 1981 (15) and Mason in 1982 (16). In these early procedures, the upper portion of the stomach was stapled into a small gastric pouch with an outlet (that is, a stoma) to the remaining distal stomach, which limited the size of the meal and induced early satiety. These procedures were prone to staple-line breakdown or stoma enlargement and were modified in turn by the placement of a band around the stoma (vertical banded gastroplasty). Figure 1. Surgical procedures. The first gastric bypass was reported in 1967 by Mason and Ito (17). It combined the creation of a small gastric pouch with bypassing a portion of the upper small intestine. Additional modifications resulted in the Roux-en-Y gastric bypass (RYGB), a now common operation that involves stapling the upper stomach into a 30-mL pouch and creating an outlet to the downstream small intestine. The new food limb joins with the biliopancreatic intestine after a short distance. This procedure, performed laparoscopically or by using an open approach, generates weight loss by limiting gastric capacity, causing mild malabsorption, and inducing hormonal changes. A second common technique, particularly outside of the United States, is the laparoscopic adjustable gastric band. This device is positioned around the uppermost portion of the stomach and can be adjusted to allow tailoring of the stoma outlet, which controls the rate of emptying of the pouch and meal capacity. Another procedure, preferred by a number of surgeons, is the biliopancreatic bypass, which combines a limited gastrectomy with a long Roux limb intestinal bypass that creates a small common channel (that is, an intestine where food and biliopancreatic contents mix). This procedure can be combined with a duodenal switch, which maintains continuity of the proximal duodenum with the stomach and uses a long limb Roux-en-Y bypass to create a short common distal channel. These latter 2 procedures generate weight loss primarily through malabsorption. Recent worldwide survey data from 2002 and 2003 show that gastric bypass is the most commonly performed weight loss procedure (65.1%) (18). Slightly more than half of gastric bypasses are done laparoscopically. Overall, 24% of cases are laparoscopic adjustable band procedures; 5.4% are vertical banded gastroplasties; and 4.9% are biliopancreatic diversion, with or without the duodenal switch. In California, the number of bariatric cases increased 6-fold between 1996 and 2000 (19), from 1131 cases to 6304; an estimated 140000 procedures were performed in the United States in 2004. With this escalation in the number of procedures, there have been reports of high postoperative complication rates (20-24). Because of these reports and the increasing use of obesity surgery, we were asked to review the literature to estimate the effectiveness of bariatric surgery relative to nonsurgical therapy for weight loss and reduction in preoperative obesity-related comorbid conditions. We were also asked to compare outcomes of surgical techniques. This paper is part of a larger evidence report titled Pharmacological and Surgical Treatment of Obesity, which was prepared for the Agency for Healthcare Research and Quality and is available at www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=hstat1a.chapter.19289. Methods Literature Search and Selection We began with an electronic search of MEDLINE on 16 October 2002, followed by a search of EMBASE and subsequent periodic search updates (on 22 May, 2 June, 12 June, and 3 July 2003). We also assessed existing reviews of surgical therapy for obesity (10, 25, 26). Three reviewers independently reviewed the studies, abstracted data, and resolved disagreements by consensus (2 reviewers per study). The principal investigator settled any unresolved disagreements. We focused on studies that assessed surgery and used a concurrent comparison group. This category includes randomized, controlled trials (RCTs); controlled clinical trials; and cohort studies. A brief scan of the literature showed that these types of studies were rare. Therefore, we also elected to include case series with 10 or more patients, since these studies can be used to assess adverse events and could potentially augment the efficacy data from comparative studies. Publication bias is one potential limitation of analyzing the available literature because poor or negative results are not as likely to be reported as are successes or positive results. Extraction of Study-Level Variables We abstracted data from the articles, including number of patients and comorbid conditions, adverse events, types of outcome measures, and time from intervention until outcome. Detailed data were also collected on characteristics of the study samples, including median age, percentage of women, median baseline weight (in kilograms or body mass index [BMI]), percentage of patients with comorbid conditions at baseline (diabetes, hypertension, dyslipidemia, and sleep apnea), percentage of improvement or resolution of preexisting comorbid conditions, and median follow-up time. We also recorded whether the case series studies reported on consecutive patients. Choice of Outcomes The main outcomes of interest were weight loss, mortality, complication rates, and control of obesity-related comorbid conditions. We used the most commonly reported measurement of weight loss, that is, kilograms, which allowed us to include the greatest number of studies. Among 111 surgical studies reporting weight loss, 43 reported weight loss in kilograms or pounds, 17 reported excess weight loss or some variant, 46 reported both of these outcomes, and 5 reported neither. A total of 89 studies had sufficient data to be included in the weight loss analysis. Because weight loss achieves health benefits primarily by reducing the incidence or severity of weight-related comorbid conditions, we also compared the effects on these outcomes. Quality of life, an important outcome in assessing tradeoffs between benefits and risks, was reported infrequently. Statistical Analyses Because we included both comparative studies and case series, we conducted several types of analyses. The vast number of types of surgical procedures and technical variations required that we aggregate those that were clinically similar and identify the comparisons that were of most interest to the clinical audience. On the basis of discussions with bariatric surgeons, we categorized obesity surgery procedures by procedure type (for example, gastric bypass, vertical banded gastroplasty), laparoscopic or open approach, and specific surgical details such as length of Roux limb (see the larger evidence report for details). Analysis of the Efficacy of Surgical Weight Loss We extracted the mean weight loss and standard deviation at 12 postoperative months and at the maximum follow-up time (36 months). These times were chosen because they are clinically relevant and are most commonly reported. Of the 89 weight loss studies, 71 reported baseline BMI (average, 47.1 kg/m2), 16 reported baseline weight in kilograms or pounds (average, 123.3 kg), and 2 did not report either. The average age of patients was 38 years, and more than three quarters were women. For comparative studies that reported a within-study comparison of 2 procedures, a mean difference was calculated. Mean differences were pooled by using a random-effects model, and 95% CIs were estimated; the same method was used to determine a pooled mean weight loss for each group considering all studies combined. However, mean difference in weight loss was not calculated. Analysis of Surgery Mortality We recorded the number of deaths observed and the total number of patients in each procedure group. If the study self-identified the deaths as early or postoperative or as occurring within 30 days of the surgery, we termed these early deaths. If the

Meta-analysis : Pharmacologic treatment of obesity

Context The effectiveness of pharmacologic therapy in the treatment of obesity is unclear. Contribution This review of 79 clinical trials involving diet plus the obesity drugs sibutramine, orlistat, fluoxetine, sertraline, bupropion, topiramate, or zonisamide shows that these medications can lead to modest weight reductions of approximately 5 kg or less at 1 year. Available evidence is lacking on the effect of these drugs on long-term weight loss, health outcomes such as cardiovascular events and diabetes, and adverse effects. Implications Those considering pharmacologic treatment for obesity should understand that these drugs can lead to modest weight loss at 1 year, but data on long-term effectiveness and safety are lacking. The Editors Obesity has been defined as excess body fat relative to lean body mass (1) and, in humans, is the result of interactions of the environment with multiple genes. The age-adjusted prevalence of obesity was 30.5% in 19992000 (2). Although it is difficult to precisely estimate the change in prevalence of obesity over time because of changing definitions, nearly all clinical authorities agree that obesity is reaching epidemic proportions (2-13). Obesity is currently defined as a body mass index (BMI) of 30 kg/m2 or greater. Individuals whose BMI falls between 25 kg/m2 and 29.9 kg/m2 are considered overweight. Attempts to meet the body weight goal of the Healthy People 2000 initiative (7)to reduce the prevalence of overweight among adults to less than 20% of the populationdid not succeed. Still, many Americans are trying. According to a national survey (14), about 40% of women and 25% of men reported that they were currently trying to lose weight. However, most weight loss attempts consist of 6 months of loss followed by gradual regain to baseline (15). The health consequences of obesity include some of the most common chronic diseases in our society. Obesity is an independent risk factor for heart disease (16). Type 2 diabetes mellitus, hypertension and stroke, hyperlipidemia, osteoarthritis, and sleep apnea are all more common in obese individuals (17-19). A recent prospective study involving 900000 U.S. adults reported that increased body weight was associated with increased death rates for all cancer combined and for cancer at multiple specific sites (20). Adult weight gain is associated with increased risk for breast cancer in postmenopausal women (21). Weight loss of 5% to 10% can be associated with marked reductions in the risk for these chronic diseases (22). In the Diabetes Prevention Program, weight loss of about 5% to 6% among persons with a BMI of 34 kg/m2, along with increased physical activity, resulted in a 58% reduction in the incidence of diabetes (23). In response to the increase in obesity, pharmaceutical treatments for obesity have become both more numerous and more commonly used. Drugs prescribed for weight loss can be divided into 2 categoriesappetite suppressants and lipase inhibitorson the basis of their putative mechanisms of action. Appetite suppressants can be further subdivided on the basis of the neurotransmitters they are believed to affect. This article, which reviews the available evidence on medications used as obesity treatment in adults (Table 1), is part of a larger evidence report prepared for the Agency for Healthcare Research and Quality titled Pharmacological and Surgical Treatment of Obesity. The larger report is available at www.ncbi.nlm.nih.gov/books/bv.fcgi?rid=hstat1a.chapter.19289. Table 1. Prescription Medications Used for Weight Loss Methods Literature Search and Selection Our search for controlled human studies of pharmacologic treatments of obesity began with an electronic search of MEDLINE on 16 October 2002. Subsequently, our librarian conducted current awareness search updates on 22 May, 2 June, 12 June, and 3 July 2003. We also searched the Cochrane Controlled Clinical Trials Register Database and existing systematic reviews. Full details of the search strategy are available in the larger evidence report. To be accepted for analysis, a study of drug therapy had to be a controlled clinical trial that assessed the effect of one of the pharmaceutical agents in humans and reported at least 6-month weight loss outcomes in pounds or kilograms. We made an exception for topiramate, for which most trials reported only percentage of weight loss. Patients in included studies needed to have a BMI of 27 kg/m2 or greater (Appendix Table). The technical expert panel for our evidence report determined which pharmaceutical agents would be included. The panel chose sibutramine, orlistat, phentermine, and diethylpropion, all of which have been approved by the U.S. Food and Drug Administration, as well as other medications being used for weight loss, including fluoxetine, bupropion, sertraline, topiramate, and zonisamide. Extraction of Study-Level Variables and Results Three reviewers, working in groups of 2, extracted data from the same articles and resolved disagreements by consensus. A senior physician resolved any remaining disagreements. We used the Jadad score to evaluate the quality of the studies, using information on study design, method of random assignment, blinding, and withdrawal (34). Jadad scores range from 0 (lowest quality) to 5 (highest quality). We also collected information on withdrawal and dropout rates and calculated the percentage of attrition by dividing the number of patients providing follow-up data by the number of patients initially enrolled. Of the medications we assessed, 3 had up-to-date existing meta-analyses (sibutramine, phentermine, and diethylpropion) and 4 others had a sufficient number of new studies to justify a new meta-analysis (orlistat, fluoxetine, bupropion, and topiramate). However, because heterogeneity was too great for the fluoxetine studies, they are summarized narratively. Selection of Trials for Meta-Analysis The outcome of interest was weight loss between baseline and follow-up. To make our analyses comparable, we stratified them in the same manner as did the recent meta-analysis on sibutramine (35). We defined data collected at 6 months to be data collected at any point between 16 and 24 weeks; likewise, 1-year follow-up data were those collected at any point between 44 and 54 weeks. If a study presented data for 2 or more time points in an interval, for example, 16 and 18 weeks, we chose the longest follow-up measurement for our analysis. Mean Difference For each trial, we extracted the follow-up mean weight loss for the control group, the follow-up mean weight loss for the medication group, and the standard deviation for each group. We then calculated a mean difference for each study, which was the difference between follow-up mean weight loss in the control group versus the medication group. Sensitivity Analyses We conducted sensitivity analyses on 4 study dimensions: Jadad quality score (2 vs. 3), year of publication (1998 or earlier vs. 1999 or later), completion rate (<80% vs. 80% and <70% vs. 70%), and dosage. We tested for differences between subgroups (for example, high-quality vs. lower-quality studies) by conducting a meta-regression analysis using a single dichotomous variable to indicate subgroup membership. We conducted sensitivity analyses to determine the possible impact of dropouts. In these analyses, we assumed that all patients who dropped out had a weight loss of zero. The mean weight loss for a particular study was then recalculated on the basis of the complete sample of both responders and dropouts. We assumed that the standard deviation of weight loss for a study did not change and recalculated the standard error on the basis of the complete sample size. We then conducted a pooled analysis for each medication and follow-up time as performed in the original approach. Meta-Analysis of Weight Loss For the 6-month and 12-month analyses, we estimated a pooled DerSimonianLaird random-effects estimate (36) of the overall mean difference. The mean differences in the individual trials are weighted by both within-study variation and between-study variation in this synthesis. We also report P values derived from the chi-square test of heterogeneity based on the Cochran Q-test (37), and the I2 statistic (38). This latter statistic represents the percentage of study variability that is due to heterogeneity rather than chance and is independent of the number of studies and the effect size metric. Publication Bias We assessed the possibility of publication bias by evaluating a funnel plot. We also conducted an adjusted rank correlation test (39) as a formal statistical test for publication bias. Extraction of Data on Adverse Events We assessed evidence of adverse events from randomized, controlled trials (RCTs) only. We did not include observational studies or case series data. Each trial included in the weight loss analysis was examined to determine whether it reported data on adverse events. Adverse events were recorded as the number of events or the number of people, depending on how the trial chose to report events. Most trials recorded the number of events rather than the number of unique people who experienced the event. Each event was counted as if it represented a unique individual. Because a single individual might have experienced more than 1 event, this assumption may have overestimated the number of people who had an adverse event. Meta-Analysis of Adverse Events For subgroups of events that occurred in 2 or more trials, at least once in the medication group and at least once in the control group, we performed a meta-analysis to estimate the pooled odds ratio and its associated 95% CI. Given that many of the events were rare, we used exact conditional inference to perform the pooling rather than applying the usual asymptotic methods that assume normality. For interpretability, for any significant pooled odds ratio greater than 1 (which indicates that the odds of the adverse

Identifying Older People at Risk of Abuse During Routine Screening Practices

OBJECTIVES: To examine the association between various characteristics of community‐based older people and a constructed measure of potential elder abuse.

Race and Sex Differences in the Receipt of Timely and Appropriate Lung Cancer Treatment

Background:Previous research suggests that disparities in non–small-cell lung cancer (NSCLC) survival can be explained in part by disparities in the receipt of cancer treatment. Few studies, however, have considered race and sex disparities in the timing and appropriateness of treatment across stages of diagnosis. Objective:To evaluate the relationship of sex and race with the receipt of timely and clinically appropriate NSCLC treatment for each stage of diagnosis. Method:Surveillance Epidemiology and End Result data linked to Medicare claims for beneficiaries diagnosed with NSCLC between 1995 and 1999 were used to evaluate the relationship between race and sex with timely and appropriate NSCLC treatment while controlling for other demographic characteristics, comorbidities, socioeconomic status, and provider supply (N = 22,145). Results:Overall adjusted rates of timely and appropriate treatment are 37.2%, 58.1%, and 29.2% for Medicare beneficiaries diagnosed with stage I or II, III, and IV NSCLC, respectively. Among stage I or II patients, women were 25% less likely to receive timely surgical resection relative to men, and blacks were 66% less likely to receive timely and appropriate treatment than whites. Black men were least likely to receive resection (22.2% compared with 43.7% for white men). Blacks were 34% less likely to receive timely surgery, chemotherapy, or radiation for stage III disease and were 51% less likely to receive chemotherapy in a timely fashion for stage IV disease relative to whites. Conclusion:Significant variations in appropriate timely treatment were found within and across stages of diagnosis, confirming that sex and race differences in NSCLC treatment exist.

How Reliable is Pain as the Fifth Vital Sign

Background: Although many health care organizations require routine pain screening (eg, “5th vital sign”) with the 0 to 10 numeric rating scale (NRS), its accuracy has been questioned; here we evaluated its accuracy and potential causes for error. Methods: We randomly surveyed veterans and reviewed their charts after outpatient encounters at 2 hospitals and 6 affiliated community sites. Using correlation and receiver operating characteristic analysis, we compared the routinely measured “5th vital sign” (nurse-recorded NRS) with a research-administered NRS (research-recorded NRS) and the Brief Pain Inventory (BPI). Results: During 528 encounters, nurse-recorded NRS and research-recorded NRS correlated moderately (r = 0.627), as did nurse-recorded NRS and BPI severity scales (r = 0.613 for pain during the last 24 hours and r = 0.588 for pain during the past week). Correlation with BPI interference was lower (r = 0.409). However, the research-recorded NRS correlated substantially with the BPI severity during the past 24 hours (r = 0.870) and BPI severity during the last week (r = 0.840). Receiver operating characteristic analysis showed similar results. Of the 98% of cases where a numeric score was recorded, 51% of patients reported their pain was rated qualitatively, rather than with a 0 to 10 scale, a practice associated with pain underestimation (χ2 = 64.04, P < .001). Conclusion: Though moderately accurate, the outpatient “5th vital sign” is less accurate than under ideal circumstances. Personalizing assessment is a common clinical practice but may affect the performance of research tools such as the NRS adopted for routine use.

Age and Gender Differences in Health Care Utilization and Spending for Medicare Beneficiaries in Their Last Years of Life

Mens and womens health care experiences differ as they age. While increasing attention has been focused on gender differences in health status, prevalence of illnesses, and access to quality care among older adults, little is known about differences in their health care in the last years of their lives. This paper uses claims data for a 0.1% random sample of Medicare beneficiaries who died between January 1, 1994 and December 31, 1998 to assess age and gender differences among Medicare-eligible adults in their utilization of health care services in the last year of life. Overall, age is much more important than gender in explaining most of the variation in end-of-life care. The combination of being a Medicare beneficiary and being sick enough to die appears to attenuate gender disparities in health care services utilization.

Differences in Medicare expenditures during the last 3 years of life.

AbstractOBJECTIVE: To examine age, gender, race, and area income differences in Medicare expenditures in the 3 years before death. DESIGN: Cross-sectional study. PARTICIPANTS: A random sample of aged Medicare beneficiaries who died 1996 to 1999, N=241,047. MEASURES: We estimate differences in mean Medicare expenditures by year before death and by age, gender, race, and area income, adjusting for comorbidities and Medicaid enrollment. RESULTS: Expenditures for blacks are lower in the second and third years before death and are not significantly different from whites in the last year of life (LYOL) (y3=70%, P<.0001; y2=82%, P<.0001; LYOL=119%, P=.098). Differences in expenditures between decedents with area incomes over

Developing quality indicators for cancer end-of-life care: Proceedings from a national symposium

35,000 compared to under

Heart Failure: The Hidden Problem of Pain

20,000 attenuate by the LYOL (y3=116%, P<.0001; y2=107%, P<.0001; LYOL=96%, P<.0001). Expenditure patterns for women versus men vary by age. Among the younger cohorts (68 to 74 and 75 to 79), expenditures are higher for women in all 3 years before death. This difference attenuates among older cohorts; in the oldest cohort (90+), expenditures for men exceed those for women by 11% in the LYOL (P<.0001). Older beneficiaries have higher expenditures in the second and third years before death but lower expenditures in the LYOL. On average, the youngest cohort expended

A Framework for Assessing Quality Indicators for Cancer Care at the End of Life

8,017 more in the LYOL relative to the oldest cohort, whereas in the third years before death, the oldest cohort’s expenditures were