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      Representativeness of Randomized Clinical Trial Cohorts in End-stage Kidney Disease : A Meta-analysis

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          Abstract

          How similar are dialysis-dependent patients recruited to large, multicenter randomized clinical trials compared with the general dialysis-dependent population? In this meta-analysis of 189 trials including 80 104 participants, trial participants were significantly younger, more likely to be male, and less likely to have diabetes or diabetic nephropathy than patients in the US national registry. Moreover, the mortality rate of dialysis-dependent patients recruited to large, multicenter randomized trials was substantially lower than that of registry patients, both overall and when only studies recruiting participants from the United States were considered. These findings imply that caution should be exercised when generalizing results from clinical trials to the broader dialysis-dependent patient population. Systematic differences between patients included in randomized clinical trials (RCTs) and the general patient population may influence the generalizability of RCT findings. Comprehensive national registries of patients with end-stage kidney disease who are undergoing dialysis provide a unique opportunity to compare trial and real-world patient cohorts. To determine if participants in large, multicenter dialysis trials were similar to the general population undergoing dialysis in terms of age, comorbidities, and mortality rate. MEDLINE, PubMed, and the Cochrane Central Register of Controlled Trials were systematically searched on January 6, 2017, for studies published from January 1, 2007, to December 31, 2016. Data sources were published manuscripts, supplementary material, and trial registration information. Data on the general population undergoing dialysis were derived from the US Renal Data System (USRDS). Data were analyzed from March 17 to July 22, 2018. Randomized clinical trials enrolling only participants undergoing dialysis for end-stage kidney disease with 100 or more adult participants from 2 or more sites. Abstract screening and data extraction were performed independently by 2 researchers. Data were pooled using a random-effects model. The primary outcome was difference in mean age between the RCT and USRDS populations. Secondary outcomes included differences in mortality rate and comorbidities. The search identified 186 RCTs, enrolling 79 104 participants. Compared with the 2011 USRDS population, RCT participants were younger (mean age, 58.9 years; 95% CI, 58.3-59.5 years vs 61.2 years; P  < .001), more likely to be male (58.9%; 95% CI, 57.6%-60.1% vs 55.7%; P  < .001), and have coronary artery disease (26.9%; 95% CI, 22.2%-31.7% vs 17.7%; P  < .001) and less likely to have diabetes (40.2%; 95% CI, 36.7%-43.6% vs 44.2%; P  = .03) or heart failure (19.6%; 95% CI, 15.1%-24.0% vs 29.8%; P  < .001). The mortality rate per 100 patient-years during trial participation was less than half that of the USRDS population (8.9; 95% CI, 7.8-10.0 vs 18.6; P  < .001). The differences in age, mortality, and coronary artery disease remained when studies recruiting only from the United States were considered. Diabetes was more common in RCT participants from the United States than in the registry population. Participants in large, multicenter RCTs of patients with end-stage kidney disease undergoing dialysis are younger, have a different pattern of comorbidities, and have a lower mortality rate than the general population of patients undergoing dialysis. This finding has implications for the generalization of trial results to the broader patient population and for future trial design. This meta-analysis of 189 studies involving 80 104 participants examines whether participants in large, multicenter dialysis trials were similar to the general population undergoing dialysis in terms of age, comorbidities, and mortality rate.

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          Pharmaceutical industry sponsorship and research outcome and quality: systematic review.

          To investigate whether funding of drug studies by the pharmaceutical industry is associated with outcomes that are favourable to the funder and whether the methods of trials funded by pharmaceutical companies differ from the methods in trials with other sources of support. Medline (January 1966 to December 2002) and Embase (January 1980 to December 2002) searches were supplemented with material identified in the references and in the authors' personal files. Data were independently abstracted by three of the authors and disagreements were resolved by consensus. 30 studies were included. Research funded by drug companies was less likely to be published than research funded by other sources. Studies sponsored by pharmaceutical companies were more likely to have outcomes favouring the sponsor than were studies with other sponsors (odds ratio 4.05; 95% confidence interval 2.98 to 5.51; 18 comparisons). None of the 13 studies that analysed methods reported that studies funded by industry was of poorer quality. Systematic bias favours products which are made by the company funding the research. Explanations include the selection of an inappropriate comparator to the product being investigated and publication bias.
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            A literature review on the representativeness of randomized controlled trial samples and implications for the external validity of trial results

            Randomized controlled trials (RCTs) are conducted under idealized and rigorously controlled conditions that may compromise their external validity. A literature review was conducted of published English language articles that reported the findings of studies assessing external validity by a comparison of the patient sample included in RCTs reporting on pharmaceutical interventions with patients from everyday clinical practice. The review focused on publications in the fields of cardiology, mental health, and oncology. A range of databases were interrogated (MEDLINE; EMBASE; Science Citation Index; Cochrane Methodology Register). Double-abstract review and data extraction were performed as per protocol specifications. Out of 5,456 de-duplicated abstracts, 52 studies met the inclusion criteria (cardiology, n = 20; mental health, n = 17; oncology, n = 15). Studies either performed an analysis of the baseline characteristics (demographic, socioeconomic, and clinical parameters) of RCT-enrolled patients compared with a real-world population, or assessed the proportion of real-world patients who would have been eligible for RCT inclusion following the application of RCT inclusion/exclusion criteria. Many of the included studies concluded that RCT samples are highly selected and have a lower risk profile than real-world populations, with the frequent exclusion of elderly patients and patients with co-morbidities. Calculation of ineligibility rates in individual studies showed that a high proportion of the general disease population was often excluded from trials. The majority of studies (n = 37 [71.2 %]) explicitly concluded that RCT samples were not broadly representative of real-world patients and that this may limit the external validity of the RCT. Authors made a number of recommendations to improve external validity. Findings from this review indicate that there is a need to improve the external validity of RCTs such that physicians treating patients in real-world settings have the appropriate evidence on which to base their clinical decisions. This goal could be achieved by trial design modification to include a more representative patient sample and by supplementing RCT evidence with data generated from observational studies. In general, a thoughtful approach to clinical evidence generation is required in which the trade-offs between internal and external validity are considered in a holistic and balanced manner. Electronic supplementary material The online version of this article (doi:10.1186/s13063-015-1023-4) contains supplementary material, which is available to authorized users.
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              Sex-Specific Differences in Hemodialysis Prevalence and Practices and the Male-to-Female Mortality Rate: The Dialysis Outcomes and Practice Patterns Study (DOPPS)

              Introduction Because differences in men's and women's physiology have widely been recognized [1], researchers are encouraged to evaluate clinical study data by sex [2],[3]. Important sex-specific distinctions have been recognized in several of the most prevalent medical conditions, such as obesity [4], type 2 diabetes mellitus [5],[6], cardiovascular disease [7],[8], and depression [9]. Many of these conditions coexist with, or may have contributed to, chronic kidney disease [10]. Chronic kidney disease in itself raises numerous gender questions, for example, regarding sex-dependent prevalence [11] and disease awareness [12]. Sex-specific differences in the characteristics, treatment, and outcomes for individuals on renal replacement therapy have, however, only once previously been the primary theme in an international study, and with focus on mortality patterns at the start of dialysis [13]. Here we present a large adult male-to-female comparison of patient and treatment characteristics as well as mortality risk, using evidence from participants in the international Dialysis Outcomes and Practice Patterns Study (DOPPS). We also compare the adult male-to-female mortality risk with that of the general population, as deduced from the Human Mortality Database life tables. We aimed to describe current hemodialysis practice patterns, and identify patient variables or hemodialysis practices that can be modified in order to improve the care of women and men with end-stage renal disease by assessing (1) hemodialysis prevalence among study participants, overall and by country, (2) national differences in sex-dependent hemodialysis patient mortality, (3) sex-dependent differences in hemodialysis characteristics, and (4) the presence of a sex interaction in the associations between hemodialysis characteristics and mortality. Methods Patients and Data Collection DOPPS data The DOPPS is an international prospective cohort study of adult patients (ages ≥18 y) undergoing hemodialysis treated in representative facilities of each participating country (Australia, Belgium, Canada, France, Germany, Italy, Japan, New Zealand, Spain, Sweden, the United Kingdom, and the United States). Phase 1 of the DOPPS collected data from June 1996 to October 2001, Phase 2 from February 2002 to February 2005, Phase 3 from June 2005 to January 2009, and Phase 4 from March 2009 to March 2012. Data collection in Australia, Belgium, Canada, New Zealand, and Sweden did not begin until Phase 2. Due to the small number of DOPPS facilities recruited in New Zealand (n = 2), patients in this country were combined with those in Australia (n = 18 facilities) in subsequent analyses. DOPPS facilities were enrolled randomly from a list of all hemodialysis facilities within each nation at the beginning of each phase of data collection between 1996 and 2012, as described previously [14],[15]. In the current study, we analyzed the following patient populations: (1) 206,374 DOPPS census patients from the initial cross-section of patients in each study phase, i.e., all patients dialyzing in the DOPPS facilities at study start, having data on demographics and mortality; (2) 35,964 prevalent patients (subset of patient population #1 above, based on a random selection of 20–40 hemodialysis patients per participating facility); and (3) 14,941 incident patients from patient population #1 above who were enrolled in the DOPPS within 90 d after initiation of hemodialysis therapy between March 2009 and March 2012. Study approval was received annually from a central institutional review board. Additional national and local ethics committee approvals and written patient consents were obtained as required. Demographic data (including race), comorbid conditions, laboratory values, and medications for sampled patients were abstracted from patient records. Mortality events were collected during study follow-up. Estimated glomerular filtration rate (eGFR) at dialysis initiation was calculated among a subset of population #3 (described above) using the Modification of Diet in Renal Disease Study (MDRD) formula [16]. The Human Mortality Database To compare mortality rates for the general population with those of the DOPPS population, data from the Human Mortality Database was used [17]. Country- and age-group-specific mortality rates were calculated using data from January 2000–December 2009. Individuals aged 90 d dialyzing 3× weekly. bCoronary artery disease, cerebrovascular disease, congestive heart failure, hypertension, peripheral vascular disease, other cardiovascular disease. cCancer, gastrointestinal bleed, lung disease, neurologic disorder, psychologic disorder, recurrent cellulitis. dEuropean countries = Belgium, France, Germany, Italy, Spain, Sweden, UK. eEducation, employment, marital status, smoking status, predialysis systolic blood pressure, blood flow rate, serum potassium, medication prescriptions (erythopoiesis-stimulating agent, phosphate binder, vitamin D, antihypertensive, antibiotic), prior parathyroidectomy, and prior transplant. A/NZ, Australia/New Zealand; BMI, body mass index; CV, cardiovascular; HD, hemodialysis; IDWG, interdialytic weight gain; N. America, North America; PTH, parathyroid hormone. 10.1371/journal.pmed.1001750.g004 Figure 4 Analysis of sex interaction in the associations between hemodialysis patient characteristics and mortality. p-Value is for interaction with sex, shown for variables with p 90 d. Bold indicates p 90 d. Bold indicates p 90 d differ from those of the CHOICE study, which used as-treated analyses for incident patients and showed that catheter use was associated with mortality risk among men but not among women [58]. Thus, hemodialysis vascular access by sex deserves more study to also consider whether our sex-specific findings on vascular access and mortality are partly explained by selection. The present study on hemodialysis patients is shedding light on several sex-dependent issues that have also been addressed in the general population [59]–[61]. Among these issues, smoking and marriage prevalence differed by sex in hemodialysis patients, and may have an effect on outcomes. Our finding of higher rates of clinician-diagnosed depression in women agrees with a previous DOPPS analysis showing that women have a significantly higher prevalence of depressive symptoms according to the Center for Epidemiologic Studies Depression Scale [62]. Access to transplantation has also been previously shown to be lower in women [63], as reinforced by the data presented in Tables 2 and 3. Several limitations need to be acknowledged. The presented analyses of adjusted mortality risk can show only associations, not causation, and can thus merely hint at the mechanisms that render mortality rates similar in men and women on hemodialysis. Likewise, our descriptive findings of hemodialysis prevalence by sex cannot answer why the prevalence of hemodialysis treatment is higher for men than women. However, the large national differences we identified strongly suggest that the reasons go beyond biological ones. After careful review of the present data and the literature, we believe the data suggest that women with end-stage renal disease are less likely than men to receive hemodialysis treatment, perhaps because of psychosocioeconomic factors. It also is possible that women are less likely than men to receive hemodialysis because the severity of their disease is not recognized by their caregivers, they are less aware of their disease and the degree of its severity [12], or they are more reluctant to undergo treatment. The present large study followed a suggestion made many years ago that hemodialysis mortality for women should be analyzed internationally [64]. Despite limitations, it may now open a window of subsequent research opportunities and possibilities to improve patient care. In conclusion, we showed among patients treated with hemodialysis for end-stage renal disease that women differ from men in a vast number of variables, some of which appear related to biology, some to patient care or to society. The finding that the general survival advantage for women is virtually lost for all adult age groups of individuals on dialysis is striking. Variation among the DOPPS regions in the very small survival advantage for women on hemodialysis might be partly explained by similar variations in the general population. The impact of different levels of adjustments on adult male-to-female mortality as well as other sex-related factors (in our statistical interaction studies) points to higher catheter-related mortality risk for women than observed for men, and suggests an opportunity to improve hemodialysis practices. Whether men and women differ by dialysis initiation and chronic kidney disease care is perhaps the most important question raised by the present study. This question is not novel, as national data have been available for decades, but may not previously have been asked as clearly as by the present analysis with a large sample size and international perspective. Future international studies should concentrate on considering sex differences as a factor for treating patients with end-stage renal disease, not only for improving outcomes, but also for equalizing women's access to renal replacement therapy. Supporting Information Figure S1 Adjusted hazard ratios for the adult male-to-female mortality risk in hemodialysis patients, by region (order of case mix and “modifiable” adjustments reversed from Figure 3 ). aStratified by country (including US black race and US non-black race) and phase; n = 36,216 patients (n = 8,258 deaths) among patients with time on dialysis >90 d dialyzing 3× weekly. bCoronary artery disease, cerebrovascular disease, congestive heart failure, hypertension, peripheral vascular disease, other cardiovascular disease. cCancer, gastrointestinal bleed, lung disease, neurologic disorder, psychologic disorder, recurrent cellulitis. dEuropean countries = Belgium, France, Germany, Italy, Spain, Sweden, UK. eEducation, employment, marital status, smoking status, predialysis systolic blood pressure, blood flow rate, serum potassium, medication prescriptions (erythropoiesis-stimulating agent, phosphate binder, vitamin D, antihypertensive, antibiotic), prior parathyroidectomy, and prior transplant. A/NZ, Australia/New Zealand; BMI, body mass index; CV, cardiovascular; HD, hemodialysis; IDWG, interdialytic weight gain; N. America, North America; PTH, parathyroid hormone. (TIF) Click here for additional data file. Table S1 Percentage of patients that are women in the hemodialysis population from national registry data compared to DOPPS. (DOCX) Click here for additional data file. Table S2 Patient characteristics, by sex and country. (DOCX) Click here for additional data file. Table S3 Analysis of sex interaction in the associations between hemodialysis patient characteristics and mortality, by region. (DOCX) Click here for additional data file. Checklist S1 STROBE Statement checklist of items that should be included in reports of observational studies. Responses to the STROBE Statement recommendations are provided in bold italic. (DOCX) Click here for additional data file.
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                Author and article information

                Journal
                JAMA Internal Medicine
                JAMA Intern Med
                American Medical Association (AMA)
                2168-6106
                July 08 2019
                Affiliations
                [1 ]The George Institute for Global Health and University of New South Wales, Sydney, Australia
                [2 ]Sydney School of Public Health, University of Sydney, Sydney, Australia
                [3 ]Chelsea and Westminster Hospital, London, United Kingdom
                [4 ]Faculty of Medicine Vajira Hospital, Navamindradhiraj University, Bangkok, Thailand
                [5 ]Department of Nephrology, Princess Alexandra Hospital, Brisbane, Australia
                [6 ]Faculty of Medicine, University of Queensland, Brisbane, Australia
                [7 ]The George Institute for Global Health, University of Oxford, Oxford, United Kingdom
                [8 ]Department of Epidemiology, Johns Hopkins University, Baltimore, Maryland
                [9 ]Renal Unit, Concord Repatriation General Hospital, Sydney, Australia
                Article
                10.1001/jamainternmed.2019.1501
                6618769
                31282924
                a6daac24-0326-4e94-9638-3e73287debce
                © 2019
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