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Literature DB >> 15313996

Tips for learners of evidence-based medicine: 1. Relative risk reduction, absolute risk reduction and number needed to treat.

Alexandra Barratt¹, Peter C Wyer, Rose Hatala, Thomas McGinn, Antonio L Dans, Sheri Keitz, Virginia Moyer, Gordon Guyatt For.

Abstract

Mesh：

Year: 2004 PMID： 15313996 PMCID： PMC509050 DOI： 10.1503/cmaj.1021197

Source DB: PubMed Journal: CMAJ ISSN： 0820-3946 Impact factor: 8.262

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14 in total

1. Tips for learning and teaching evidence-based medicine: introduction to the series.

Authors: Peter C Wyer; Sheri Keitz; Rose Hatala; Robert Hayward; Alexandra Barratt; Victor Montori; Eric Wooltorton; Gordon Guyatt
Journal: CMAJ Date: 2004-08-17 Impact factor: 8.262

2. Health outcomes associated with antihypertensive therapies used as first-line agents. A systematic review and meta-analysis.

Authors: B M Psaty; N L Smith; D S Siscovick; T D Koepsell; N S Weiss; S R Heckbert; R N Lemaitre; E H Wagner; C D Furberg
Journal: JAMA Date: 1997-03-05 Impact factor: 56.272

3. Can we individualize the 'number needed to treat'? An empirical study of summary effect measures in meta-analyses.

Authors: Toshiaki A Furukawa; Gordon H Guyatt; Lauren E Griffith
Journal: Int J Epidemiol Date: 2002-02 Impact factor: 7.196

4. Evidence based purchasing: understanding results of clinical trials and systematic reviews.

Authors: T Fahey; S Griffiths; T J Peters
Journal: BMJ Date: 1995-10-21

5. The number needed to treat: a clinically useful nomogram in its proper context.

Authors: G Chatellier; E Zapletal; D Lemaitre; J Menard; P Degoulet
Journal: BMJ Date: 1996-02-17

6. When should an effective treatment be used? Derivation of the threshold number needed to treat and the minimum event rate for treatment.

Authors: J C Sinclair; R J Cook; G H Guyatt; S G Pauker; D J Cook
Journal: J Clin Epidemiol Date: 2001-03 Impact factor: 6.437

7. The framing effect of relative and absolute risk.

Authors: D J Malenka; J A Baron; S Johansen; J W Wahrenberger; J M Ross
Journal: J Gen Intern Med Date: 1993-10 Impact factor: 5.128

Review 8. An empirical study of the effect of the control rate as a predictor of treatment efficacy in meta-analysis of clinical trials.

Authors: C H Schmid; J Lau; M W McIntosh; J C Cappelleri
Journal: Stat Med Date: 1998-09-15 Impact factor: 2.373

9. Measured enthusiasm: does the method of reporting trial results alter perceptions of therapeutic effectiveness?

Authors: C D Naylor; E Chen; B Strauss
Journal: Ann Intern Med Date: 1992-12-01 Impact factor: 25.391

10. A randomized trial of propranolol in patients with acute myocardial infarction. I. Mortality results.

Authors:
Journal: JAMA Date: 1982-03-26 Impact factor: 56.272

50 in total

1. Tips for learning and teaching evidence-based medicine: introduction to the series.

Authors: Peter C Wyer; Sheri Keitz; Rose Hatala; Robert Hayward; Alexandra Barratt; Victor Montori; Eric Wooltorton; Gordon Guyatt
Journal: CMAJ Date: 2004-08-17 Impact factor: 8.262

2. Tips for learners of evidence-based medicine: 2. Measures of precision (confidence intervals).

Authors: Victor M Montori; Jennifer Kleinbart; Thomas B Newman; Sheri Keitz; Peter C Wyer; Virginia Moyer; Gordon Guyatt
Journal: CMAJ Date: 2004-09-14 Impact factor: 8.262

3. Vioxx: lessons for Health Canada and the FDA.

Authors:
Journal: CMAJ Date: 2005-01-04 Impact factor: 8.262

Review 4. Tips for learners of evidence-based medicine: 4. Assessing heterogeneity of primary studies in systematic reviews and whether to combine their results.

Authors: Rose Hatala; Sheri Keitz; Peter Wyer; Gordon Guyatt
Journal: CMAJ Date: 2005-03-01 Impact factor: 8.262

Tips for learners of evidence-based medicine: 1. Relative risk reduction, absolute risk reduction and number needed to treat.

1. Tips for learning and teaching evidence-based medicine: introduction to the series.

2. Health outcomes associated with antihypertensive therapies used as first-line agents. A systematic review and meta-analysis.

3. Can we individualize the 'number needed to treat'? An empirical study of summary effect measures in meta-analyses.

4. Evidence based purchasing: understanding results of clinical trials and systematic reviews.

5. The number needed to treat: a clinically useful nomogram in its proper context.

6. When should an effective treatment be used? Derivation of the threshold number needed to treat and the minimum event rate for treatment.

7. The framing effect of relative and absolute risk.

Review 8. An empirical study of the effect of the control rate as a predictor of treatment efficacy in meta-analysis of clinical trials.

9. Measured enthusiasm: does the method of reporting trial results alter perceptions of therapeutic effectiveness?

10. A randomized trial of propranolol in patients with acute myocardial infarction. I. Mortality results.

1. Tips for learning and teaching evidence-based medicine: introduction to the series.

2. Tips for learners of evidence-based medicine: 2. Measures of precision (confidence intervals).

3. Vioxx: lessons for Health Canada and the FDA.

Review 4. Tips for learners of evidence-based medicine: 4. Assessing heterogeneity of primary studies in systematic reviews and whether to combine their results.

5. NNT for studies with long-term follow-up.

6. What is so odd about odds?

7. Views on recertification.

8. Challenges of teaching EBM.

9. Challenges of teaching EBM.

10. When should I stop anticoagulation for atrial fibrillation?