Phase 1 oncology trials involve risk and offer a relatively low prospect of benefit to participants. Some claim that participants constitute a vulnerable population requiring special protections. We undertook this study to determine whether phase 1 oncology trial participants have demographic and health status characteristics of a vulnerable population. We reviewed participant demographic and health status data from phase 1 trials sponsored by the Cancer Therapy Evaluation Program at the National Cancer Institute that began between 1991 and 2002 and from 11 previously published studies. Main outcome measures were median age, sex, race/ethnicity, performance status, previous therapy, educational achievement level, and health insurance coverage. Almost 10 000 participants in trials sponsored by the Cancer Therapy Evaluation Program had a median age of 57 years, 90% self-identified as white, 93% had near-normal performance status, 85% had some form of health insurance, and 92% had been previously treated for cancer; 20 000 individuals from published studies had comparable profiles. The demographic and health status characteristics of phase 1 oncology trial participants are not those of a conventional vulnerable population and suggest little reason to assume that, as a group, they have a compromised ability to understand information or to make informed and voluntary decisions.

Portions of this research were selected for poster presentation at the 2020 Society for Academic Emergency Medicine annual meeting. However, this meeting was canceled due to public health concerns.

The value of understanding and incorporating heterogeneity in decisions based on cost-effectiveness has been matter of growing interest in healthcare. Recent contributions have been proposed to characterize this value. They include the expected value of individualized care (EVIC) and the static and dynamic value of heterogeneity (VoH). While the EVIC represents the expected societal cost of ignoring patient-level heterogeneity, the VoH approach helps to define the optimal specification of a subgroup for cost-effectiveness analysis considering the available information and the related parameter uncertainty. However, the interpretation of such metrics should consider additional elements of the health system. Social value judgments and the fact that individuals do not necessarily make decisions according to social interests should be taken into account when the healthcare system pursues to implement a centered patient model such as individualized care. This paper develops a conceptual framework to explore the impact of alternative approaches to decision-making on population health and the potential trade-offs between those approaches. The main purpose of the study is to make explicit considerations that could help policy makers in their task of evaluating the implementation of a centered patient model in a healthcare system. Four decision making approaches are defined on the basis of two elements: first, the type of values used to construct health outcomes (private or societal values) and second, the level at which a decisions is made (central versus devolved). The model is formalized using classical cost-effectiveness decision rules. The alternative approaches are contrasted in terms of net health benefits which are estimated for different scenarios and illustrated with a stylized numerical example. OBJECTIVES:Cost-effectiveness analysis of health technologies typically involves the calculation of incremental cost-effectiveness ratios (ICERs). In some jurisdictions, decision makers compare these ICERs to an explicit cost-effectiveness "threshold" as part of their deliberations. The use of a threshold remains controversial and there is disagreement over what such a threshold, if adopted, should represent. Furthermore, there are many issues and limitations with the interpretation of ICERs. This paper argues that the needs of decision makers and patients would be better served by abandoning ICERs and thresholds altogether and adopting instead a decision framework based upon a modified notion of "net benefit". METHODS: Using recent Ontario-based cost-effectiveness analyses as examples, we demonstrate that the traditional interpretation of ICERs can be misleading. We also demonstrate why comparing ICERs to an explicit threshold cannot satisfy the needs of decision makers or patients -regardless of the threshold used -except under very specific circumstances. We then show how the traditional "net benefit" approach to decision making may be modified to incorporate concerns for efficiency, equity, societal and ethical valu...

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