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      Low hemoglobin increases risk for cerebrovascular disease, kidney disease, pulmonary vasculopathy, and mortality in sickle cell disease: A systematic literature review and meta-analysis

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          Abstract

          Sickle cell disease (SCD) is characterized by deoxygenation–induced polymerization of hemoglobin in red blood cells, leading to hemolytic anemia, vaso–occlusion, and the development of multiple clinical complications. To characterize the clinical burden associated with differences in hemoglobin concentration and hemolysis measures, a systematic literature review of MEDLINE, EMBASE, and related meta–analyses was undertaken. For quantitative analyses related to hemoglobin concentration, pooled results were analyzed using random effects models to control for within–and between–study variability. To derive risk ratios associated with hemoglobin concentration change, we combined ratios of means from select studies, which reported hazard and odds ratios in meta–analyses for hemoglobin concentration–related outcomes and changes between groups. Forty-one studies were identified for inclusion based on relating hemoglobin concentration to clinical outcomes. Meta–analyses demonstrated that mean hemoglobin concentration was significantly lower in patients with cerebrovascular disease (0.4 g/dL), increased transcranial Doppler velocity in cerebral arteries (0.6 g/dL), albuminuria (0.6 g/dL), elevated estimated pulmonary artery systolic pressure (0.9 g/dL), and in patients that subsequently died (0.6 g/dL). In a risk reduction meta–analysis, modeled increased hemoglobin concentrations of 1 g/dL or greater resulted in decreased risk of negative clinical outcomes of 41% to 64%. In conclusion, chronic anemia is associated with worse clinical outcomes in individuals with SCD and even modest increases in hemoglobin concentration may be beneficial in this patient population. This systematic review has been registered on Prospero (Registration number CRD42018096860; https://www.crd.york.ac.uk/prospero/).

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          A random-effects regression model for meta-analysis.

          Many meta-analyses use a random-effects model to account for heterogeneity among study results, beyond the variation associated with fixed effects. A random-effects regression approach for the synthesis of 2 x 2 tables allows the inclusion of covariates that may explain heterogeneity. A simulation study found that the random-effects regression method performs well in the context of a meta-analysis of the efficacy of a vaccine for the prevention of tuberculosis, where certain factors are thought to modify vaccine efficacy. A smoothed estimator of the within-study variances produced less bias in the estimated regression coefficients. The method provided very good power for detecting a non-zero intercept term (representing overall treatment efficacy) but low power for detecting a weak covariate in a meta-analysis of 10 studies. We illustrate the model by exploring the relationship between vaccine efficacy and one factor thought to modify efficacy. The model also applies to the meta-analysis of continuous outcomes when covariates are present.
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            Pulmonary hypertension as a risk factor for death in patients with sickle cell disease.

            The prevalence of pulmonary hypertension in adults with sickle cell disease, the mechanism of its development, and its prospective prognostic significance are unknown. We performed Doppler echocardiographic assessments of pulmonary-artery systolic pressure in 195 consecutive patients (82 men and 113 women; mean [+/-SD] age, 36+/-12 years). Pulmonary hypertension was prospectively defined as a tricuspid regurgitant jet velocity of at least 2.5 m per second. Patients were followed for a mean of 18 months, and data were censored at the time of death or loss to follow-up. Doppler-defined pulmonary hypertension occurred in 32 percent of patients. Multiple logistic-regression analysis, with the use of the dichotomous variable of a tricuspid regurgitant jet velocity of less than 2.5 m per second or 2.5 m per second or more, identified a self-reported history of cardiovascular or renal complications, increased systolic blood pressure, high lactate dehydrogenase levels (a marker of hemolysis), high levels of alkaline phosphatase, and low transferrin levels as significant independent correlates of pulmonary hypertension. The fetal hemoglobin level, white-cell count, and platelet count and the use of hydroxyurea therapy were unrelated to pulmonary hypertension. A tricuspid regurgitant jet velocity of at least 2.5 m per second, as compared with a velocity of less than 2.5 m per second, was strongly associated with an increased risk of death (rate ratio, 10.1; 95 percent confidence interval, 2.2 to 47.0; P<0.001) and remained so after adjustment for other possible risk factors in a proportional-hazards regression model. Pulmonary hypertension, diagnosed by Doppler echocardiography, is common in adults with sickle cell disease. It appears to be a complication of chronic hemolysis, is resistant to hydroxyurea therapy, and confers a high risk of death. Therapeutic trials targeting this population of patients are indicated. Copyright 2004 Massachusetts Medical Society
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              A checklist for retrospective database studies--report of the ISPOR Task Force on Retrospective Databases.

              Health-related retrospective databases, in particular claims databases, continue to be an important data source for outcomes research. However, retrospective databases pose a series of methodological challenges, some of which are unique to this data source. In an effort to assist decision makers in evaluating the quality of published studies that use health-related retrospective databases, a checklist was developed that focuses on issues that are unique to database studies or are particularly problematic in database research. This checklist was developed primarily for the commonly used medical claims or encounter-based databases but could potentially be used to assess retrospective studies that employ other types of databases, such as disease registries and national survey data. Written in the form of 27 questions, the checklist can be used to guide decision makers as they consider the database, the study methodology, and the study conclusions. Checklist questions cover a wide range of issues, including relevance, reliability and validity, data linkages, eligibility determination, research design, treatment effects, sample selection, censoring, variable definitions, resource valuation, statistical analysis, generalizability, and data interpretation. For many of the questions, key references are provided as a resource for those who want to further examine a particular issue.
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                Author and article information

                Contributors
                Role: InvestigationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: MethodologyRole: VisualizationRole: Writing – original draft
                Role: Formal analysisRole: MethodologyRole: VisualizationRole: Writing – original draftRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                3 April 2020
                2020
                : 15
                : 4
                : e0229959
                Affiliations
                [1 ] University of Tennessee Health Science Center, Memphis, TN, United States of America
                [2 ] University of Illinois at Chicago College of Medicine, Chicago, IL, United States of America
                [3 ] GBT, South San Francisco, CA, United States of America
                [4 ] Xcenda LLC, Palm Harbor, FL, United States of America
                [5 ] School of Medicine, University of California, San Francisco, San Francisco, CA, United States of America
                Université Claude Bernard Lyon 1, FRANCE
                Author notes

                Competing Interests: K.I.A. is an advisory board member for GBT, Novartis, and Bioverativ and has served as a consultant for Modus Therapeutics. V.R.G. has served as a consultant for GBT and CSL Behring. I.A. is a current employee and stockholder of GBT. J.A.C. and K.G. are current employees of Xcenda, LLC, an AmerisourceBergen company. I.E.A. is a current employee of University of California, San Francisco and has served as a consultant for GBT. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

                [¤a]

                Current address: University of Tennessee Health Science Center, Memphis, TN, United States of America

                [¤b]

                Current address: University of Illinois at Chicago College of Medicine, Chicago, IL, United States of America

                [¤c]

                Current address: GBT, South San Francisco, CA, United States of America

                [¤d]

                Current address: Xcenda, LLC, Palm Harbor, FL, United States of America

                [¤e]

                Current address: Department of Epidemiology and Biostatistics, School of Medicine, University of California, San Francisco, San Francisco, CA, United States of America

                Author information
                http://orcid.org/0000-0002-4501-9982
                Article
                PONE-D-19-28851
                10.1371/journal.pone.0229959
                7122773
                32243480
                1f5102ec-766c-44ea-a45a-9d0a2929c556
                © 2020 Ataga et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 15 October 2019
                : 17 February 2020
                Page count
                Figures: 7, Tables: 1, Pages: 17
                Funding
                This study was funded by GBT and Xcenda LLC conducted the study. One author is a GBT employee and holds equity in GBT and two authors are employed by Xcenda LLC; the specific roles of these authors are articulated in the ‘author contributions’ section. All authors were involved in the preparation and editing of the manuscript, as well as the decision to publish.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Proteins
                Hemoglobin
                Research and Analysis Methods
                Mathematical and Statistical Techniques
                Statistical Methods
                Metaanalysis
                Physical Sciences
                Mathematics
                Statistics
                Statistical Methods
                Metaanalysis
                Medicine and Health Sciences
                Clinical Genetics
                Genetic Diseases
                Autosomal Recessive Diseases
                Sickle Cell Disease
                Medicine and Health Sciences
                Hematology
                Hemoglobinopathies
                Sickle Cell Disease
                Medicine and Health Sciences
                Neurology
                Cerebrovascular Diseases
                Stroke
                Medicine and Health Sciences
                Vascular Medicine
                Stroke
                Medicine and Health Sciences
                Hematology
                Anemia
                Medicine and Health Sciences
                Pediatrics
                Medicine and Health Sciences
                Nephrology
                Microalbuminuria
                Research and Analysis Methods
                Database and Informatics Methods
                Database Searching
                Custom metadata
                This analysis has been registered on Prospero (Registration number CRD42018096860; https://www.crd.york.ac.uk/prospero/).

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                Uncategorized

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