A tool for assessing adverse events in phase I/II oncology clinical trials Journal Articles uri icon

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abstract

  • 6518 Background: RECIST and NCI's Common Terminology Criteria are accepted systems that have standardized the reporting of oncology clinical trial outcomes. A standard system for attributing causality to Serious Adverse Events (SAEs) is lacking which can impact drug development and patient safety. The objectives of this study were to: 1) understand the clinical reasoning behind causality assessment during phase I/II oncology clinical trials; and, 2) use this information to develop a causality assessment tool for oncology. Methods: In-depth interviews were conducted with oncologists and trial coordinators at 6 Canadian academic cancer centres. Five main conceptual categories were explored: clinical reasoning; information resources; tools; challenges and concerns; and education. Interviews were recorded and transcribed verbatim. Individual interview content analysis was followed by thematic analysis across the interview set. A new causality assessment tool was developed based upon the qualitative findings and an analysis of existing generic tools. Results: Thirty-two interviews were conducted between May and August 2006 (65% participation). Half of participants were female, 66% were oncologists and 42% had more than 10 years of clinical trial experience. Data showed that participants use a common strategy to assess causality: they gather information, eliminate alternative explanations, and consider the study drug as the cause of the SAE. Over half cited the quality of information resources as a major factor contributing to uncertainty when assessing causality. Participants expressed the need for a standardized approach to causality assessment in oncology clinical trials. The tool developed in this study guides users to consider 5 statements related to potential alternative etiologies and 4 related to other factors that support a drug-SAE connection. The user is asked for their overall impression using a continuous probability rating scale. Conclusions: Attributing causality to SAEs is complex and uncertain. Clinicians describe using a logical system of reasoning, but have encountered barriers which must be addressed. We have developed and are validating a new tool to assist cancer clinicians in providing higher quality safety data about new cancer drugs early in development. [Table: see text]

publication date

  • June 20, 2007