급성허혈뇌졸중에서 혈전용해치료의 유효성과 안전성에 관한 예후모형 개발
Prognostic Modeling for an Efficacy and a Safety of Thrombolysis in Acute Ischemic Stroke
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Background: The aims of this study were to develop and internally and externally validate a prognostic model that can predict the benefit and harm of thrombolysis in patients with acute ischemic stroke and that may be used promptly in an emergency setting. Methods: The data of a consecutive series of patients who were hospitalized to Seoul National University Bundang Hospital within 12 hours of stroke onset between January 2004 and March 2008 and with relevant ischemic lesions on diffusion-weighted MRI were used to develop and internally validate the prognostic model. The external validation was performed using the data of patients from five participating centers of the Clinical Research Center for Stroke that had been collected between April 2008 and September 2009. The score on the modified Rankin Disability Scale at 3 months was selected to determine the efficacy outcome,and the occurrence of symptomatic hemorrhagic transformation was used to evaluate the safety outcome. Prognostic models were constructed with logistic regression, and both internal and external validations were performed. Results: The discriminative abilities of the efficacy model (C statistic=0.880) and the safety prognostic model (C statistic=0.864)were confirmed. External validation of both models revealed remarkably little degradation in the discrimination power (C statistic=0.835 and 0.822 for the efficacy and safety models, respectively). Conclusions: This study shows that the efficacy and safety prognostic models developed with basic clinical variables were reliably validated with independent data. Both models may be helpful to clinicians in the emergency setting to identify patients who would benefit from thrombolysis.
Abstract
Background: The aims of this study were to develop and internally and externally validate a prognostic model that can predict the benefit and harm of thrombolysis in patients with acute ischemic stroke and that may be used promptly in an emergency setting. Methods: The data of a consecutive series of patients who were hospitalized to Seoul National University Bundang Hospital within 12 hours of stroke onset between January 2004 and March 2008 and with relevant ischemic lesions on diffusion-weighted MRI were used to develop and internally validate the prognostic model. The external validation was performed using the data of patients from five participating centers of the Clinical Research Center for Stroke that had been collected between April 2008 and September 2009. The score on the modified Rankin Disability Scale at 3 months was selected to determine the efficacy outcome,and the occurrence of symptomatic hemorrhagic transformation was used to evaluate the safety outcome. Prognostic models were constructed with logistic regression, and both internal and external validations were performed. Results: The discriminative abilities of the efficacy model (C statistic=0.880) and the safety prognostic model (C statistic=0.864)were confirmed. External validation of both models revealed remarkably little degradation in the discrimination power (C statistic=0.835 and 0.822 for the efficacy and safety models, respectively). Conclusions: This study shows that the efficacy and safety prognostic models developed with basic clinical variables were reliably validated with independent data. Both models may be helpful to clinicians in the emergency setting to identify patients who would benefit from thrombolysis.
참고문헌 (30)
- Harrell FE Jr, "Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors", Stat Med, 15, pp.361~387 (1996)
- Krijnen P, "A clinical prediction rule for renal artery stenosis", Ann Intern Med, 129, pp.705~711 (1998)
- Albers GW, "Intravenous tissue-type plasminogen activator for treatment of acute stroke: the Standard Treatment with Alteplase to Reverse Stroke (STARS) study", JAMA, 283, pp.1145~1150 (2000)
- Clark WM, "The rtPA (alteplase)0- to 6-hour acute stroke trial, part A (A0276g): results of adouble-blind, placebo-controlled, multicenter study. Thromblytictherapy in acute ischemic stroke study investigators", Stroke, 31, pp.811~816 (2000)
- Lewandowski CA, "Combined intravenous and intra-arterial r-TPA versus intra-arterial therapy of acute ischemic stroke: Emergency Management of Stroke (EMS) Bridging Trial", Stroke, 30, pp.2598~2605 (1999)
- 손성일, "급성기 뇌졸중의 혈전용해치료", 대한의사협회지, 52(4), pp.340~355 (2009), 대한의사협회
- Counsell C, "Systematic review of prognostic models in patients with acute stroke", Cerebrovasc Dis, 12, pp.159~170 (2001)
- Reid JM, "Predicting functional outcome after stroke by modelling baseline clinical and CT variables", Age Ageing, 39, pp.360~366 (2010)
- Steyerberg EW, "Clinical Prediction Models, In A Practical Approach to Development, Validation, and Updating" (2009), Springer
- van Swieten JC, "Interobserver agreement for the assessment of handicap in stroke patients", Stroke, 19, pp.604~607 (1988)
- Concato J, "The risk of determining risk with multivariable models", Ann Intern Med, 118, pp.201~210 (1993)
- Laupacis A, "Clinical prediction rules. A review and suggested modifications of methodological standards", JAMA, 277, pp.488~494 (1997)
- Concato J, "Importance of events per independent variable in proportional hazards analysis. I. Background, goals, and general strategy", J Clin Epidemiol, 48, pp.1495~1501 (1995)
- Peduzzi P, "Importance of events per independent variable in proportional hazards regression analysis. II. Accuracy and precision of regression estimates", Clin Epidemiol, 48, pp.1503~1510 (1995)
- Peduzzi P, "A simulation study of the number of events per variable in logistic regression analysis", J Clin Epidemiol, 49, pp.1373~1379 (1996)
- Copas J., "Regression, prediction and shrinkage", J R Stat Soc Ser B, 45, pp.311~354 (1983)
- Van Houwelingen JC, "Predictive value of statistical models", Stat Med, 9, pp.1303~1325 (1990)
- Hanley JA, "The meaning and use of the area under a receiver operating characteristic (ROC) curve", Radiology, 143, pp.29~36 (1982)
- Adams HP J, "Classification of subtype of acute ischemic stroke. Definitions for use in a multicenter clinical trial. TOAST. Trial of Org 10172 in Acute Stroke Treatment", Stroke, 24, pp.35~41 (1993)
- Johnston KC, "A predictive risk model for outcomes of ischemic stroke", Stroke, 31, pp.448~455 (2000)
- Weimar C, "Predicting functional outcome and survival after acute ischemic stroke", J Neurol, 249, pp.888~895 (2002)
- Pozen MW, "A predictive instrument to improve coronary-care-unit admission practices in acute ischemic heart disease. A prospective multicenter clinical trial", N Engl J Med, 310, pp.1273~1278 (1984)
- Savitz SI, "Outcome analysis in clinical trial design for acute stroke: physicians' attitudes and choices", Cerebrovasc Dis, 26, pp.156~162 (2008)
- Ovbiagele B, "Disability status at 1 month is a reliable proxy for final ischemic stroke outcome", Neurology, 75, pp.688~692 (2010)
- Duncan PW, "Outcome measures in acute stroke trials: a systematic review and some recommendations to improve practice", Stroke, 31, pp.1429~1438 (2000)
- Kent DM, "The stroke-thrombolytic predictive instrument: a predictive instrument for intravenous thrombolysis in acute ischemic stroke", Stroke, 37, pp.957~2962 (2006)
- Grau AJ, "Risk factors, outcome, and treatment in subtypes of ischemic stroke: the German stroke data bank", Stroke, 32, pp.2559~2566 (2001)
- Rohl L, "Correlation between diffusion- and perfusionweighted MRI and neurological deficit measured by the Scandinavian Stroke Scale and Barthel Index in hyperacute subcortical stroke", Cerebrovasc Dis, 12, pp.203~213 (2001)
- Saunders DE, "Measurement of infarct size using MRI predicts prognosis in middle cerebral artery infarction", Stroke, 26, pp.2272~2276 (1995)
- Stone SP, "Predicting outcome in acute stroke", Br Med Bull, 56, pp.486~494 (2000)