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      Risk score to predict serious bleeding in stable outpatients with or at risk of atherothrombosis

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          Abstract

          Aims

          To develop a risk score to quantify bleeding risk in outpatients with or at risk of atherothrombosis.

          Methods and results

          We studied patients in the REACH Registry, a cohort of 68 236 patients with/at risk of atherothrombosis. The outcome of interest was serious bleeding (non-fatal haemorrhagic stroke or bleeding leading to hospitalization and transfusion) over 2 years. Risk factors for bleeding were assessed using modified regression analysis. Multiple potential scoring systems based on the least complex models were constructed. Competing scores were compared on their discriminative ability via logistic regression. The score was validated externally using the CHARISMA population. From a final cohort of 56 616 patients, 804 (1.42%, 95% confidence interval 1.32–1.52) experienced serious bleeding between baseline and 2 years. A nine-item bleeding risk score (0–23 points) was constructed (age, peripheral arterial disease, congestive heart failure, diabetes, hypertension, smoking, antiplatelets, oral anticoagulants, hypercholesterolaemia). Observed incidence of bleeding at 2 years was: 0.46% (score ≤6); 0.95% (7–8); 1.25% (9–10); 2.76% (≥11). The score's discriminative performance was consistent in CHARISMA and REACH (c-statistics 0.64 and 0.68, respectively); calibration in the CHARISMA population was very good (modified Hosmer-Lemeshow c 2 = 4.74; P = 0.69).

          Conclusion

          Bleeding risk increased substantially with a score >10. This score can assist clinicians in predicting the risk of serious bleeding and making decisions on antithrombotic therapy in outpatients.

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          Most cited references16

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          Internal validation of predictive models: efficiency of some procedures for logistic regression analysis.

          The performance of a predictive model is overestimated when simply determined on the sample of subjects that was used to construct the model. Several internal validation methods are available that aim to provide a more accurate estimate of model performance in new subjects. We evaluated several variants of split-sample, cross-validation and bootstrapping methods with a logistic regression model that included eight predictors for 30-day mortality after an acute myocardial infarction. Random samples with a size between n = 572 and n = 9165 were drawn from a large data set (GUSTO-I; n = 40,830; 2851 deaths) to reflect modeling in data sets with between 5 and 80 events per variable. Independent performance was determined on the remaining subjects. Performance measures included discriminative ability, calibration and overall accuracy. We found that split-sample analyses gave overly pessimistic estimates of performance, with large variability. Cross-validation on 10% of the sample had low bias and low variability, but was not suitable for all performance measures. Internal validity could best be estimated with bootstrapping, which provided stable estimates with low bias. We conclude that split-sample validation is inefficient, and recommend bootstrapping for estimation of internal validity of a predictive logistic regression model.
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            Use and misuse of the receiver operating characteristic curve in risk prediction.

            The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients. The c statistic, however, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories. In this setting, calibration is as important to the accurate assessment of risk. For example, a biomarker with an odds ratio of 3 may have little effect on the c statistic, yet an increased level could shift estimated 10-year cardiovascular risk for an individual patient from 8% to 24%, which would lead to different treatment recommendations under current Adult Treatment Panel III guidelines. Accepted risk factors such as lipids, hypertension, and smoking have only marginal impact on the c statistic individually yet lead to more accurate reclassification of large proportions of patients into higher-risk or lower-risk categories. Perfectly calibrated models for complex disease can, in fact, only achieve values for the c statistic well below the theoretical maximum of 1. Use of the c statistic for model selection could thus naively eliminate established risk factors from cardiovascular risk prediction scores. As novel risk factors are discovered, sole reliance on the c statistic to evaluate their utility as risk predictors thus seems ill-advised.
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              Adverse impact of bleeding on prognosis in patients with acute coronary syndromes.

              The use of multiple antithrombotic drugs and aggressive invasive strategies has increased the risk of major bleeding in acute coronary syndrome (ACS) patients. It is not known to what extent bleeding determines clinical outcome. Using Cox proportional-hazards modeling, we examined the association between bleeding and death or ischemic events in 34,146 patients with ACS enrolled in the Organization to Assess Ischemic Syndromes and the Clopidogrel in Unstable Angina to Prevent Recurrent Events studies. Patients with major bleeding were older, more often had diabetes or a history of stroke, had a lower blood pressure and higher serum creatinine, more often had ST-segment changes on the presenting ECG, and had a 5-fold-higher incidence of death during the first 30 days (12.8% versus 2.5%; P < 0.0001) and a 1.5-fold-higher incidence of death between 30 days and 6 months (4.6% versus 2.9%; P = 0.002). Major bleeding was independently associated with an increased hazard of death during the first 30 days (hazard ratio, 5.37; 95% CI, 3.97 to 7.26; P < 0.0001), but the hazard was much weaker after 30 days (hazard ratio, 1.54; 95% CI, 1.01 to 2.36; P = 0.047). The association was consistent across subgroups according to cointerventions during hospitalization, and there was an increasing risk of death with increasing severity of bleeding (minor less than major less than life-threatening; P for trend = 0.0009). A similar association was evident between major bleeding and ischemic events, including myocardial infarction and stroke. In ACS patients without persistent ST-segment elevation, there is a strong, consistent, temporal, and dose-related association between bleeding and death. These data should lead to greater awareness of the prognostic importance of bleeding in ACS and should prompt evaluation of strategies to reduce bleeding and thereby improve clinical outcomes.
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                Author and article information

                Contributors
                On behalf of : on behalf of the REACH Investigators
                Journal
                Eur Heart J
                eurheartj
                ehj
                European Heart Journal
                Oxford University Press
                0195-668X
                1522-9645
                May 2010
                24 February 2010
                24 February 2010
                : 31
                : 10
                : 1257-1265
                Affiliations
                [1 ]INSERM U-698 ‘Recherche Clinique en Athérothrombose’, Department of Cardiology, simpleCentre Hospitalier Universitaire Bichat-Claude Bernard , 46 rue Henri Huchard, 75877 Paris Cedex 18, France
                [2 ]AP-HP, Hôpital Bichat, Département d'Epidémiologie, simpleBiostatistique et Recherche Clinique , Paris, France
                [3 ]INSERM, U738, Paris, France
                [4 ]simpleUniversité Paris 7 Denis Diderot, UFR de Médecine , Paris, France
                [5 ]simpleNorthwestern University Feinberg School of Medicine , Chicago, IL, USA
                [6 ]Emory School of Medicine, Atlanta, GA, USA
                [7 ]simpleDuke University , Durham, NC, USA
                [8 ]simpleCleveland Clinic , Cleveland, OH, USA
                [9 ]simpleBoston University , Boston, MA, USA
                [10 ]simpleVA Boston Healthcare System and Brigham and Women's Hospital , Boston, MA, USA
                Author notes
                [* ]Corresponding author. Tel: +33 140256644, Fax: +33 140258865, Email: gregory.ducrocq@ 123456bch.aphp.fr
                [†]

                A Complete List of the REACH Registry Investigators appears in J Am Med Assoc 2006; 295:180–189.

                Article
                ehq021
                10.1093/eurheartj/ehq021
                2869443
                20181681
                0f72ca1c-f54c-4edd-bf35-0fee3d8a0f30
                Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2010. For permissions please email: journals.permissions@oxfordjournals.org

                The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that the original authorship is properly and fully attributed; the Journal, Learned Society and Oxford University Press are attributed as the original place of publication with correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org

                History
                : 11 September 2009
                : 30 November 2009
                : 29 December 2009
                Categories
                Clinical Research
                Prevention

                Cardiovascular Medicine
                antithrombotic therapy,bleeding risk,atherothrombosis
                Cardiovascular Medicine
                antithrombotic therapy, bleeding risk, atherothrombosis

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