Literature DB >> 9200390

Selection of thrombolytic therapy for individual patients: development of a clinical model. GUSTO-I Investigators.

R M Califf1, L H Woodlief, F E Harrell, K L Lee, H D White, A Guerci, G I Barbash, R J Simes, W D Weaver, M L Simoons, E J Topol.   

Abstract

We developed a logistic regression model with data from the GUSTO-I trial to predict mortality rate differences in individual patients who received accelerated tissue plasminogen activator (TPA) versus streptokinase treatment for acute myocardial infarction. A nomogram was developed from a reduced version of this model that approximated the underlying risk of patients treated with streptokinase, and thus the benefit of TPA. The 30-day mortality rate with accelerated TPA was 0.063 versus 0.073 with streptokinase and subcutaneously administered heparin and 0.074 with streptokinase and intravenously administered heparin. No baseline patient characteristics were significantly associated with a different relative effect of TPA. Older patients and those with anterior infarction, higher Killip classification (except Killip class IV), lower blood pressure, and increased heart rate had the greatest absolute benefit with accelerated TPA. Patients with acute myocardial infarction who had more high-risk characteristics derived a greater absolute benefit from treatment with accelerated TPA versus streptokinase.

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Year:  1997        PMID: 9200390     DOI: 10.1016/s0002-8703(97)70164-9

Source DB:  PubMed          Journal:  Am Heart J        ISSN: 0002-8703            Impact factor:   4.749


  15 in total

1.  Fibrinolytic treatment for elderly patients with acute myocardial infarction.

Authors:  J M Estess; E J Topol
Journal:  Heart       Date:  2002-04       Impact factor: 5.994

Review 2.  Personalized evidence based medicine: predictive approaches to heterogeneous treatment effects.

Authors:  David M Kent; Ewout Steyerberg; David van Klaveren
Journal:  BMJ       Date:  2018-12-10

3.  A CTSA agenda to advance methods for comparative effectiveness research.

Authors:  Mark Helfand; Sean Tunis; Evelyn P Whitlock; Stephen G Pauker; Anirban Basu; Jon Chilingerian; Frank E Harrell; David O Meltzer; Victor M Montori; Donald S Shepard; David M Kent
Journal:  Clin Transl Sci       Date:  2011-06       Impact factor: 4.689

Review 4.  A plea for a more epidemiological and patient-oriented pharmacovigilance.

Authors:  Veronica Scurti; Marilena Romero; Gianni Tognoni
Journal:  Eur J Clin Pharmacol       Date:  2011-07-20       Impact factor: 2.953

5.  Biases in Individualized Cost-effectiveness Analysis: Influence of Choices in Modeling Short-Term, Trial-Based, Mortality Risk Reduction and Post-Trial Life Expectancy.

Authors:  David van Klaveren; John B Wong; David M Kent; Ewout W Steyerberg
Journal:  Med Decis Making       Date:  2017-03-20       Impact factor: 2.583

6.  Risk and treatment effect heterogeneity: re-analysis of individual participant data from 32 large clinical trials.

Authors:  David M Kent; Jason Nelson; Issa J Dahabreh; Peter M Rothwell; Douglas G Altman; Rodney A Hayward
Journal:  Int J Epidemiol       Date:  2016-12-01       Impact factor: 7.196

Review 7.  Reperfusion therapy for acute myocardial infarction. Which strategy for which patient?

Authors:  E Boersma; E W Steyerberg; M J Van der Vlugt; M L Simoons
Journal:  Drugs       Date:  1998-07       Impact factor: 9.546

8.  Assessing and reporting heterogeneity in treatment effects in clinical trials: a proposal.

Authors:  David M Kent; Peter M Rothwell; John P A Ioannidis; Doug G Altman; Rodney A Hayward
Journal:  Trials       Date:  2010-08-12       Impact factor: 2.279

9.  The Predictive Approaches to Treatment effect Heterogeneity (PATH) Statement.

Authors:  David M Kent; Jessica K Paulus; David van Klaveren; Ralph D'Agostino; Steve Goodman; Rodney Hayward; John P A Ioannidis; Bray Patrick-Lake; Sally Morton; Michael Pencina; Gowri Raman; Joseph S Ross; Harry P Selker; Ravi Varadhan; Andrew Vickers; John B Wong; Ewout W Steyerberg
Journal:  Ann Intern Med       Date:  2019-11-12       Impact factor: 25.391

10.  Covariate adjustment had similar benefits in small and large randomized controlled trials.

Authors:  Douglas D Thompson; Hester F Lingsma; William N Whiteley; Gordon D Murray; Ewout W Steyerberg
Journal:  J Clin Epidemiol       Date:  2014-11-13       Impact factor: 6.437

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