Title |
Assessing risk/benefit for trials using preclinical evidence: a proposal
|
---|---|
Published in |
Journal of Medical Ethics, October 2015
|
DOI | 10.1136/medethics-2015-102882 |
Pubmed ID | |
Authors |
Jonathan Kimmelman, Valerie Henderson |
Abstract |
Moral evaluation of risk/benefit in early phase studies requires assessing the clinical promise of a candidate intervention using preclinical evidence. Yet, there is little to guide ethics committees, investigators, sponsors or other stakeholders morally charged with making these assessments ('evaluators'). In what follows, we draw on published guidelines for preclinical study design to develop a structured process for assessing the clinical promise of new interventions. In the first step, evaluators gather all relevant preclinical studies, assess the magnitude of treatment effects and determine clinical promise in light of various threats to valid clinical inference. In the second step, evaluators adjust the assessments of clinical promise from preclinical studies by examining how other agents in the same reference class-and supported by similar evidence-have fared in clinical development. Assessments of clinical promise can then be fed into the moral evaluation of risk and benefit in early phase trials. Though our approach has limitations, it offers a systematic and transparent method for assessing risk/benefit in early phase trials of novel interventions. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
Canada | 3 | 23% |
United States | 2 | 15% |
United Kingdom | 2 | 15% |
Germany | 1 | 8% |
Japan | 1 | 8% |
Unknown | 4 | 31% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 6 | 46% |
Scientists | 4 | 31% |
Practitioners (doctors, other healthcare professionals) | 2 | 15% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 36 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 7 | 19% |
Student > Master | 6 | 17% |
Student > Bachelor | 4 | 11% |
Student > Ph. D. Student | 3 | 8% |
Lecturer | 1 | 3% |
Other | 3 | 8% |
Unknown | 12 | 33% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 4 | 11% |
Medicine and Dentistry | 4 | 11% |
Agricultural and Biological Sciences | 3 | 8% |
Arts and Humanities | 2 | 6% |
Engineering | 2 | 6% |
Other | 8 | 22% |
Unknown | 13 | 36% |