Clinical trials : journal of the Society for Clinical Trials
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In oncology, new combined treatments make it difficult to order dose levels according to monotonically increasing toxicity. New flexible dose-finding designs that take into account uncertainty in dose levels ordering were compared with classical designs through simulations in the setting of the monotonicity assumption violation. We give recommendations for the choice of dose-finding design. ⋯ Innovative oncology treatments may no longer follow monotonic dose levels ordering which makes standard phase I methods fail. In such a setting, appropriate designs, as the No Monotonicity Assumption or Partial Ordering Continual Reassessment Method designs, should be used to safely determine recommended for phase II dose.
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Electronic health record data can be used in multiple ways to facilitate real-world pragmatic studies. Electronic health record data can provide detailed information about utilization of treatment options to help identify appropriate comparison groups, access historical clinical characteristics of participants, and facilitate measuring longitudinal outcomes for the treatments being studied. An additional novel use of electronic health record data is to assess and understand referral pathways and other business practices that encourage or discourage patients from using different types of care. ⋯ While real-time monitoring of business practices from electronic health records provides insights into the validity of key independence assumptions associated with the instrumental variable approaches, we note that there may be some residual confounding by indication or selection bias and describe how alternative sources of electronic health record data can be used to assess the robustness of instrumental variable assumptions to address these challenges. Finally, we also highlight that while some clinical outcomes can be obtained directly from the electronic health record, such as longitudinal opioid utilization and pain intensity levels for the study of the value of complementary and integrative health, it is often critical to supplement clinical electronic health record-based measures with patient-reported outcomes. The experience of this example in evaluating complementary and integrative health demonstrates the use of electronic health record data in several novel ways that may be of use for designing future pragmatic trials.