Background and Objectives
A relation between the size of treatment efficacy and severity of the disease has been postulated and observed as linear for a few therapies. We have called this relation the effect model. Our objectives were to demonstrate that the relation is general and not necessarily linear.
Study Design and Setting
We extend the number of observed effect model. Then we established three numerical models of treatment activity corresponding to the three modes of action we have identified. Using these models, we simulated the relation.
Empirical evidence confirms the effect model and suggests that it may be linear over a short range of event frequency. However, it provides an incomplete understanding of the phenomenon because of the inescapable limitations of data from randomized clinical trials. Numerical modeling and simulation show that the real effect model is likely to be more complicated. It is probably linear only in rare instances. The effect model is general. It depends on factors related to the individual, disease and outcome.
Contrarily to common, assumption, since the effect model is often curvilinear, the relative risk cannot be granted as constant. The effect model should be taken into account when discovering and developing new therapies, when making, health care policy decisions or adjusting clinical decisions to the patient risk profile.
To read this article in full you will need to make a payment
Purchase one-time access:Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
One-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:Subscribe to Journal of Clinical Epidemiology
Already a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
- Meta-analysis in clinical research.Ann Intern Med. 1987; 107: 224-233
- An effect model for the assessment of drug benefit: example of antiarrhythmic drugs in post-myocardial infarction patients.J Cardiovasc Pharmacol. 1993; 22: 356-363
- Does drug treatment improve survival? Reconciling the trials in mild-to-moderate hypertension.J Hypertens. 1995; 13: 805-811
- The relation between treatment benefit and underlying risk in meta-analysis.BMJ. 1996; 313: 735-738
- Baseline risk as predictor of treatment benefit: three clinical meta-re-analyses.Stat Med. 2000; 19: 3497-3518
- Practical methodology of meta-analyses (overviews) using updated individual patient data. Cochrane Working Group.Stat Med. 1995; 14: 2057-2079
- Beta-blockade during and after myocardial infarction: an overview of the randomized trials.Prog Cardiovasc Dis. 1985; 27: 335-371
- Overview of randomized trials of angiotensin-converting enzyme inhibitors on mortality and morbidity in patients with heart failure. Collaborative Group on ACE Inhibitor Trials.JAMA. 1995; 273: 1450-1456
- Beta-Blocker Pooling Project Research Group (Coordinators: Boissel JP, Leizorovicz A). The Beta-blocker Pooling Project (B.B.P.P.): subgroup findings from randomized trials in post infarction patients.Eur Heart J. 1988; 9: 8-16
- The population risk as an explanatory variable in research synthesis of clinical trials.Stat Med. 1996; 15: 1713-1728
- Antihypertensive drugs in very old people: a subgroup meta-analysis of randomised controlled trials.Lancet. 1999; 353: 793-796
- Response to “Inclusion of women and minorities in clinical trials and the NIH revitalization act of 1993. The perspective of NIH clinical trialists”.Control Clin Trials. 1995; 16: 286-288
- Pharmacogenetics and responders to a therapy: theoretical background and practical problems.Clin Chem Lab Med. 2003; 41: 564-572
- Clinical trial simulation using therapeutic effect modelling: application to ivabradine efficacy in patients with angina pectoris.J Pharmacokinet Pharmacodyn. 2002; 29: 339-363
- Revisiting the effect compartment through timing errors in drug administration.TiPS. 1998; 19: 49-54
- Pharmacokinetic and pharmacodynamic data analysis.Swedish Pharmaceutical Society, Stockholm2000 (p. 61)
- A pharmacokinetic simulation model for ivabradine in healthy volunteers.Eur J Pharm Sci. 2000; 10: 285-294
- Development of a sequential linked pharmacokinetic and pharmacodynamic simulation model for ivabradine in healthy volunteers.Eur J Pharm Sci. 2000; 10: 275-284
- An assessment of clinically useful measures of the consequences of treatment.N Engl J Med. 1988; 318: 1728-1733
- An evidence based approach to individualising treatment.BMJ. 1995; 311: 1356-1359
- Individualizing aspirin therapy for prevention of cardiovascular events.JAMA. 1998; 280: 1949-1950
- Individual response to treatment: is it a valid assumption?.BMJ. 2004; 329: 966-968
- Secondary prevention after high-risk acute myocardial infarction with low-dose Acebutolol.Am J Cardiol. 1990; 66: 251-260
Published online: November 29, 2007
Accepted: July 10, 2007
© 2008 Elsevier Inc. Published by Elsevier Inc. All rights reserved.