Benefits and harms of roflumilast in moderate to severe COPD.

BACKGROUND: Roflumilast, a phosphodiesterase 4 inhibitor, has been approved for the prevention of chronic obstructive pulmonary disease (COPD) exacerbations. It is unclear which patients will have a favourable benefit-harm balance with roflumilast. Our aim was to quantitatively assess the benefits and harms of roflumilast (500 µg/day) compared with placebo. METHODS: We used summary data released by the US Food and Drug Administration to estimate the treatment effects of roflumilast. Data from trials and observational studies were used to estimate the baseline risks for COPD exacerbations and gastrointestinal, neurological and psychiatric harms associated with roflumilast. Using simulation, we calculated the probability that roflumilast provides net benefit. We examined the impacts of different baseline risks for exacerbations and the severity of exacerbations, and varied weights (ie, relative importance) for outcomes and treated death as a competing risk in the analyses. RESULTS: The probability that roflumilast provides net benefit approximates 0% across different age categories of men and women with varying baseline risks for exacerbations. Using different weights for outcomes did not change the probability that roflumilast provides a net benefit. Only in the sensitivity analysis restricted to the prevention of severe exacerbations was there a probability of >50% that roflumilast provides a net benefit if the baseline risk of having at least one severe exacerbation per year exceeds 22%. CONCLUSIONS: Our results suggest that roflumilast only provides a net benefit to patients at a high risk of severe exacerbations. Guideline developers should consider different recommendations for patients with COPD at different baseline risks for exacerbations.

Multimorbidity and evidence generation.

Most people with a chronic disease actually have more than one, a condition known as multimorbidity. Despite this, the evidence base to prevent adverse disease outcomes has taken a disease-specific approach. Drawing on a conference, Improving Guidelines for Multimorbid Patients, the goal of this paper is to identify challenges to the generation of evidence to support the care of people with multimorbidity and to make recommendations for improvement. We identified three broad categories of challenges: 1) challenges to defining and measuring multimorbidity; 2) challenges related to the effects of multimorbidity on study design, implementation and analysis; and 3) challenges inherent in studying heterogeneity of treatment effects in patients with differing comorbid conditions. We propose a set of recommendations for consideration by investigators and others (reviewers, editors, funding agencies, policymaking organizations) involved in the creation of evidence for this common type of person that address each of these challenges. The recommendations reflect a general approach that emphasizes broader inclusion (recruitment and retention) of patients with multimorbidity, coupled with more rigorous efforts to measure comorbidity and comorbidity burden and the influence of multimorbidity on outcomes and the effects of therapy. More rigorous examination of heterogeneity of treatment effects requires careful attention to prioritizing the most important comorbid-related questions, and also requires studies that provide greater statistical power than conventional trials have provided. Relatively modest changes in the orientation of current research along these lines can be helpful in pointing to and partially addressing selected knowledge gaps. However, producing a robust evidence base to support patient-centered decision making in complex individuals with multimorbidity, exposed to many different combinations of potentially interacting factors that can modify the risks and benefits of therapies, is likely to require a clinical research enterprise fundamentally restructured to be more fully integrated with routine clinical practice.

Assessing heterogeneity of treatment effect in a clinical trial with the proportional interactions model.

Understanding how individuals vary in their response to treatment is an important task of clinical research. For standard regression models, a proportional interactions model first described by Follmann and Proschan (1999) offers a powerful approach for identifying effect modification in a randomized clinical trial when multiple variables influence treatment response. In this paper, we present a framework for using the proportional interactions model in the context of a parallel-arm clinical trial with multiple prespecified candidate effect modifiers. To protect against model misspecification, we propose a selection strategy that considers all possible proportional interactions models. We develop a modified Bonferroni correction for multiple testing that accounts for the positive correlation among candidate models. We describe methods for constructing a confidence interval for the proportionality parameter. In simulation studies, we show that our modified Bonferroni adjustment controls familywise error and has greater power to detect proportional interactions compared with multiplcity-corrected subgroup analyses. We demonstrate our methodology by using the Studies of Left Ventricular Dysfunction Treatment trial, a placebo-controlled randomized clinical trial of the efficacy of enalapril to reduce the risk of death or hospitalization in chronic heart failure patients. An R package called anoint is available for implementing the proportional interactions methodology.

Difficulty assisting with health care tasks among caregivers of multimorbid older adults.

BACKGROUND: Family caregivers provide assistance with health care tasks for many older adults with chronic illnesses. The difficulty they experience in providing this assistance, and related implications for their well-being, have not been well described. OBJECTIVE: The objectives of this study are: (1) to describe caregiver's health care task difficulty (HCTD), (2) determine the characteristics associated with HCTD, and (3) explore the association between HCTD and caregiver well-being. DESIGN: This is a cross-sectional study. PARTICIPANTS: Baseline sample of caregivers to older (aged 65+ years) multimorbid adults enrolled in an ongoing cluster-randomized controlled trial (N = 308). MAIN MEASURES: The HCTD scale (0-16) is comprised of questions measuring self-reported difficulty in assisting older adults with eight health care tasks, including taking medication, visiting health care providers, and managing medical bills. Caregivers were categorized using this scale into no, low, medium, and high HCTD groups. We used ordinal logistic regression and multivariate linear regression analyses to examine the relationships between HCTD, caregiver self-efficacy, caregiver strain (Caregiver Strain Index), and depression (Center for Epidemiological Studies Depression Scale), controlling for patient and caregiver socio-demographic and health factors. KEY RESULTS: Caregiver age and number of health care tasks performed were positively associated with increased HCTD. The quality of the caregiver's relationship with the patient, and self-efficacy were inversely associated with increased HCTD. A one-point increase in self-efficacy was associated with a significant lower odds of reporting high HCTD (OR, 0.64; 95% CI, 0.54, 0.77).Adjusted linear regression models indicated that high HCTD was independently associated with significantly greater caregiver strain (B, 2.7; 95% CI, 1.12, 4.29) and depression (B, 3.01; 95% CI, 1.06, 4.96). CONCLUSIONS: This study demonstrates that greater HCTD is associated with increased strain and depression among caregivers of multimorbid older adults. That caregiver self-efficacy was strongly associated with HCTD suggests health-system-based educational and empowering interventions might improve caregiver well-being.

A framework for organizing and selecting quantitative approaches for benefit-harm assessment.

BACKGROUND: Several quantitative approaches for benefit-harm assessment of health care interventions exist but it is unclear how the approaches differ. Our aim was to review existing quantitative approaches for benefit-harm assessment and to develop an organizing framework that clarifies differences and aids selection of quantitative approaches for a particular benefit-harm assessment. METHODS: We performed a review of the literature to identify quantitative approaches for benefit-harm assessment. Our team, consisting of clinicians, epidemiologists, and statisticians, discussed the approaches and identified their key characteristics. We developed a framework that helps investigators select quantitative approaches for benefit-harm assessment that are appropriate for a particular decisionmaking context. RESULTS: Our framework for selecting quantitative approaches requires a concise definition of the treatment comparison and population of interest, identification of key benefit and harm outcomes, and determination of the need for a measure that puts all outcomes on a single scale (which we call a benefit and harm comparison metric). We identified 16 quantitative approaches for benefit-harm assessment. These approaches can be categorized into those that consider single or multiple key benefit and harm outcomes, and those that use a benefit-harm comparison metric or not. Most approaches use aggregate data and can be used in the context of single studies or systematic reviews. Although the majority of approaches provides a benefit and harm comparison metric, only four approaches provide measures of uncertainty around the benefit and harm comparison metric (such as a 95 percent confidence interval). None of the approaches considers the actual joint distribution of benefit and harm outcomes, but one approach considers competing risks when calculating profile-specific event rates. Nine approaches explicitly allow incorporating patient preferences. CONCLUSION: The choice of quantitative approaches depends on the specific question and goal of the benefit-harm assessment as well as on the nature and availability of data. In some situations, investigators may identify only one appropriate approach. In situations where the question and available data justify more than one approach, investigators may want to use multiple approaches and compare the consistency of results. When more evidence on relative advantages of approaches accumulates from such comparisons, it will be possible to make more specific recommendations on the choice of approaches.

Assessing the applicability of trial evidence to a target sample in the presence of heterogeneity of treatment effect.

PURPOSE: To propose methods for the quantitative assessment of the applicability of evidence from a trial to a target sample using individual data. METHODS: Demonstration was with a trial of drug therapy to prevent mortality and an accompanying registry of people with heart failure. Principal components analysis with biplots did not identify measurement discrepancies. Multiple imputation with chained equations addressed missing predictor values. A proportional hazards model with interaction term, including graphical interpretation and a multivariate interaction test, identified heterogeneity of treatment effect. An interval of homogeneity of treatment effect was the interval of the baseline risk of outcome in which no two treatment effects were statistically significantly different. Absolute risk reduction for individuals was estimated for both benefit and harm outcomes and presented in a bivariate treatment effects scatterplot. RESULTS: Overall, the trial evidence applied to most of the registry according to overlapping distributions of estimated benefit and harm. However, 52% of trial and 33% of registry participants were estimated to have net benefit, and 14% of trial and 36% of registry participants were estimated to have strong net harmful treatment effect, that is, the individual estimate of harm was more than twice the estimate of benefit. CONCLUSIONS: The proposed methods provide quantitative assessment of the applicability of trial evidence to a target sample. They combine the strengths of different study designs, namely, unbiased effects estimation from trials and representation in observational studies, while addressing the practical challenges of combining information, namely, measurement discrepancies and missing data.

The prevalence of clinically-relevant comorbid conditions in patients with physician-diagnosed COPD: a cross-sectional study using data from NHANES 1999-2008.

BACKGROUND: Treatment of chronic diseases such as chronic obstructive pulmonary disease (COPD) is complicated by the presence of comorbidities. The objective of this analysis was to estimate the prevalence of comorbidity in COPD using nationally-representative data. METHODS: This study draws from a multi-year analytic sample of 14,828 subjects aged 45+, including 995 with COPD, from the National Health and Nutrition Examination Survey (NHANES), 1999-2008. COPD was defined by self-reported physician diagnosis of chronic bronchitis or emphysema; patients who reported a diagnosis of asthma were excluded. Using population weights, we estimated the age-and-gender-stratified prevalence of 22 comorbid conditions that may influence COPD and its treatment. RESULTS: Subjects 45+ with physician-diagnosed COPD were more likely than subjects without physician-diagnosed COPD to have coexisting arthritis (54.6% vs. 36.9%), depression (20.6% vs. 12.5%), osteoporosis (16.9% vs. 8.5%), cancer (16.5% vs. 9.9%), coronary heart disease (12.7% vs. 6.1%), congestive heart failure (12.1% vs. 3.9%), and stroke (8.9% vs. 4.6%). Subjects with COPD were also more likely to report mobility difficulty (55.6% vs. 32.5%), use of >4 prescription medications (51.8% vs. 32.1), dizziness/balance problems (41.1% vs. 23.8%), urinary incontinence (34.9% vs. 27.3%), memory problems (18.5% vs. 8.8%), low glomerular filtration rate (16.2% vs. 10.5%), and visual impairment (14.0% vs. 9.6%). All reported comparisons have p < 0.05. CONCLUSIONS: Our study indicates that COPD management may need to take into account a complex spectrum of comorbidities. This work identifies which conditions are most common in a nationally-representative set of COPD patients (physician-diagnosed), a necessary step for setting research priorities and developing clinical practice guidelines that address COPD within the context of comorbidity.

Prevalence of diabetes treatment effect modifiers: the external validity of trials to older adults.

BACKGROUND AND AIMS: Potential treatment effect modifiers (TEMs) are specific diseases or conditions with a well-described mechanism for treatment effect modification. The prevalence of TEMs in older adults with type 2 diabetes mellitus (DM) is unknown. Objectives were to 1) determine the prevalence of pre-specified potential TEMs; 2) demonstrate the potential impact of TEMs in the older adult population using a simulated trial; 3) identify TEM combinations associated with number of hospitalizations to test construct validity. METHODS: Data are from the nationally-representative United States National Health and Examination Survey, 1999-2004: 8646 Civilian, non-institutionalized adults aged 45-64 or 65+ years, including 1443 with DM. TEMs were anemia, congestive heart failure, liver inflammation, polypharmacy, renal insufficiency, cognitive impairment, dizziness, frequent mental distress, mobility difficulty, and visual impairment. A trial was simulated to examine prevalence of potential TEM impact. The cross-sectional association between TEM patterns and number of hospitalizations was estimated to assess construct validity. RESULTS: The prevalence of TEMs was substantial such that 19.0% (95% CI 14.8-23.2) of middle-aged adults and 38.0% (95% CI 33.4-42.5) of older adults had any two. A simulated trial with modest levels of interaction suggested the prevalence of TEMs could nullify treatment benefit in 3.9-27.2% of older adults with DM. Compared to having DM alone, hospitalization rate was increased by several combinations of TEMs with substantial prevalence. CONCLUSIONS: We provide national benchmarks that can be used to evaluate TEM prevalence reported by clinical trials of DM, and correspondingly their external validity to older adults.

Evaluating health outcomes in the presence of competing risks: a review of statistical methods and clinical applications.

BACKGROUND: An evaluation of the effect of a healthcare intervention (or an exposure) must consider multiple possible outcomes, including the primary outcome of interest and other outcomes such as adverse events or mortality. The determination of the likelihood of benefit from an intervention, in the presence of other competing outcomes, is a competing risks problem. Although statistical methods exist for quantifying the probability of benefit from an intervention while accounting for competing events, these methods have not been widely adopted by clinical researchers. OBJECTIVES: (1) To demonstrate the importance of considering competing risks in the evaluation of treatment effectiveness, and (2) to review appropriate statistical methods, and recommend how they might be applied. RESEARCH DESIGN AND METHODS: We reviewed 3 statistical approaches for analyzing the competing risks problem: (a) cause-specific hazard (CSH), (b) cumulative incidence function (CIF), and (c) event-free survival (EFS). We compare these methods using a simulation study and a reanalysis of a randomized clinical trial. RESULTS: Simulation studies evaluating the statistical power to detect the effect of intervention under different scenarios showed that: (1) CSH approach is best for detecting the effect of an intervention if the intervention only affects either the primary outcome or the competing event; (2) EFS approach is best only when the intervention affects both primary and competing events in the same manner; and (3) CIF approach is best when the intervention affects both primary and competing events, but in opposite directions. Using data from a randomized controlled trial, we demonstrated that a comprehensive approach using all 3 approaches provided useful insights on the effect of an intervention on the relative and absolute risks of multiple competing outcomes. CONCLUSIONS: CSH is the fundamental measure of outcome in competing risks problems. It is appropriate for evaluating treatment effects in the presence of competing events. Results of CSH analysis for primary and competing outcomes should always be reported even when EFS or CIF approaches are called for. EFS is appropriate for evaluating the composite effect of an intervention, only when combining different endpoints is clinically and biologically meaningful, and the treatment has similar effects on all event types. CIF is useful for evaluating the likelihood of benefit from an intervention over a meaningful period. CIF should be used for absolute risk calculations instead of the widely used complement of the Kaplan-Meier (1 - KM) estimator.

Physician evaluation and management of Medicare home health patients.

OBJECTIVE: The Medicare home health benefit is predicated on physician referral and involvement. In this study, we investigated (1) the frequency and (2) implications of home health patients' evaluation and management by community physicians. METHODS: The 2005 and 2006 Medicare 5% Standard Analytic Files were linked to the Outcome and Assessment Information Set to examine physician visits among 74,462 fee-for service Medicare beneficiaries with a home health episode of care between July 1, 2005 and December 1, 2006. We examined whether receipt of community physician evaluation and management visits by home health patients was associated with subsequent discharge disposition, comparing discharge from the agency as opposed to inpatient facility transfer. RESULTS: More than one-third (34.6%) of patients did not receive physician evaluation and management visits during their home health episode. Home health patients most commonly incurred physician office visits exclusively (51.5%) or in combination with consultations (6.8%) or house call visits (2.2%), as well as house call visits exclusively (3.3%). Patients who incurred physician evaluation and management visits during their episode of care were more likely to be discharged from home health agencies than their counterparts who did not (77.9% vs. 70.6%, respectively). The association between physician visits and home health discharge was statistically significant in both simple regression models (odds ratio = 1.47; 95% confidence interval [CI], 1.42-1.52) and in multivariate analyses accounting for socio-demographic factors, health, and functioning (odds ratio = 1.45; 95% CI, 1.40-1.51). CONCLUSIONS: More systematic integration of physicians in home care processes may reduce subsequent hospital and other inpatient facility use among home health patients.

Medicare home health patients' transitions through acute and post-acute care settings.

OBJECTIVES: To describe Medicare beneficiaries' transitions through home health care within the context of other acute and post-acute services, and to examine agreement between administrative claims and Outcome and Assessment Information Set (OASIS) measures of health services use. DATA SOURCES: The 2004 Chronic Condition Data Warehouse, including the Medicare 5% standard analytic file and OASIS. Study participants were 66,510 Medicare beneficiaries with a home health start of care assessment between January 15, 2004 and July 15, 2004 who were discharged before December 1, 2004. RESULTS: Home health patients frequently incurred acute and post-acute services during the 14 days preceding admission and the 30 days after discharge, predominantly in acute hospitals. Substantial differences were observed in beneficiaries' health and functioning across living arrangements; patients living alone were less medically complex, less disabled, and received less assistance than those living with others. Agreement between OASIS and administrative claims was uniformly low with regard to inpatient hospital, inpatient rehabilitation, and skilled nursing facility use in the 14 days preceding the home health start of care. Agreement between OASIS and administrative claims was uneven for the period after discharge from home health care; it was determined to be near perfect for inpatient hospital (kappa = 0.85), but was lower for inpatient rehabilitation and hospice (kappa = 0.22 and 0.10, respectively). CONCLUSIONS: Findings reinforce the potential merit of patient-specific rather than setting-specific measures of quality, but underscore practical challenges to constructing measures that span data sources and episodes of care.

Self-selected walking speed was consistent when recorded while using a cane.

OBJECTIVE: To assess whether loss of consistency or systematic measurement error is introduced by allowing older individuals to use a cane during measurement of self-selected walking speed (SSWS). STUDY DESIGN AND SETTING: Observational study of women aged 65+ (Women's Health and Aging Study I, n=1,002). RESULTS: Of individuals who use a cane in daily life, 201 (50.76%) did not use an aid during testing. The Coefficient of Variation was low in individuals who reported cane use in daily life but did not use one in testing (10.72%), and did not vary substantially if a cane was used (12.04%). The Intra-Class Correlation Coefficient was high: 0.958 for those who reported cane use in daily life but did not use one during testing and 0.962 for those who used a cane. In both groups, Bland-Altman plots revealed a small systematic difference between the first and second trials. There was no evidence of effect modification of the association between SSWS and mobility disability by cane use during testing. CONCLUSION: This observational study found neither evidence of poorer consistency nor increased measurement bias in SSWS recorded while using a cane compared to using no assistive device.

Exploring the hierarchy of mobility performance in high-functioning older women.

BACKGROUND: Preventing mobility disability depends on matching interventions to individual needs. The purpose of this study is to improve targeting by determining whether mobility performance is associated with, and predicts, mobility disability hierarchically. The hypothesis is that poorer performance tested by more demanding tasks is more strongly associated with current and future mobility "limitation" (self-reported task modification or difficulty) than is that tested by less demanding tasks, in a graded manner. METHODS: Data come from the Women's Health and Aging Study II (n = 436) at baseline and at 36-month follow-up. Logistic and multinomial regression models examined associations between performance on mobility tests and reported limitation in walking one-half mile, adjusting for risk factors for disability. RESULTS: We found that 76.6% of prevalent and 88.4% of new-onset self-reported limitation fit within the hypothesized hierarchical pattern. The estimated strength of association between a decrement in lower extremity performance and reported limitation increased with task demand for the primary outcome, reported limitation in walking one-half mile. For example, the odds ratios for prevalent report of walking limitation, versus no limitation, for 10% lower performance walking, dressing, repeating chair stands, and climbing, respectively, were 1.05 (95% confidence interval, 0.97-1.17), 1.08 (1.00-1.16), 1.15 (1.06-1.25), and 1.22 (1.12-1.33). CONCLUSIONS: This study partially supports the hypothesis that mobility performance tends to follow a hierarchical pattern. For studying mild mobility disability, walking speed may not be as useful as more demanding tests. Identifying declines in performance through more demanding tests such as climbing should improve the ability to target preventive interventions to individuals at risk of mild mobility decline within a high-functioning population.

Framework for evaluating disease severity measures in older adults with comorbidity.

BACKGROUND: Accounting for the influence of concurrent conditions on health and functional status for both research and clinical decision-making purposes is especially important in older adults. Although approaches to classifying severity of individual diseases and conditions have been developed, the utility of these classification systems has not been evaluated in the presence of multiple conditions. METHODS: We present a framework for evaluating severity classification systems for common chronic diseases. The framework evaluates the: (a) goal or purpose of the classification system; (b) physiological and/or functional criteria for severity graduation; and (c) potential reliability and validity of the system balanced against burden and costs associated with classification. RESULTS: Approaches to severity classification of individual diseases were not originally conceived for the study of comorbidity. Therefore, they vary greatly in terms of objectives, physiological systems covered, level of severity characterization, reliability and validity, and costs and burdens. Using different severity classification systems to account for differing levels of disease severity in a patient with multiple diseases, or, assessing global disease burden may be challenging. CONCLUSIONS: Most approaches to severity classification are not adequate to address comorbidity. Nevertheless, thoughtful use of some existing approaches and refinement of others may advance the study of comorbidity and diagnostic and therapeutic approaches to patients with multimorbidity.

Differences in amount of informal care received by non-Hispanic whites and latinos in a nationally representative sample of older Americans.

The objective of this study was to evaluate informal (unpaid) care and its broad determinants for Latinos in a nationally representative sample. A cross-sectional analysis of the 1993 Asset and Health Dynamics Study, a national probability sample of 7,443 older adults aged 70 and older, was performed to determine the independent effect of Latino ethnicity on the receipt of informal care by disabled older individuals. Self-reported race/ethnicity was used to predict the mean daily hours of informal care received for activity of daily living (ADL) or instrumental activity of daily living (IADL) assistance after adjustment for predisposing, need, and enabling variables. There was a significant association between informal home care and ethnic group, with 44.3% of Latinos receiving informal care, compared with 33.9% of African Americans and 24.6% of non-Hispanic whites (P<.001). After adjustment, Latinos received 11.0 weekly hours of informal care, compared with 7.5 hours for non-Hispanic whites and 6.3 hours for African Americans (P<.001). The results from this nationally representative sample indicate that Latinos receive significantly more hours of informal care on average than African Americans or non-Hispanic whites for ADL and IADL disability. Clinicians should be alert to the significant amount of informal care and possible associated strain in caregivers of older Latinos.