Background:Vaginal brachytherapy (VBT) in high–intermediate-risk endometrial cancer (EC) provides a significant reduction in the risk of local cancer recurrence, but without survival benefit and with increased mucosal atrophy. Five-year local control is estimated to be similar for VBT and a watchful waiting policy (WWP), in which patients receive VBT combined with external radiation in case of a recurrence. Our aim was to assess treatment preferences of EC patients and clinicians regarding VBT and WWP, and to evaluate their preferred and perceived involvement in treatment decision making.Methods:Interviews were held with 95 treated EC patients. The treatment trade-off method was used to assess the minimally desired benefit from VBT in local control. Patients' preferred and perceived involvement in decision making were assessed using a questionnaire. Seventy-seven clinicians completed a questionnaire assessing their minimally desired benefit and preferred involvement in decision making.Results:Minimally desired benefit of VBT was significantly lower for patients than for clinicians (median=0 vs 8%, P<0.001), for irradiated than for non-irradiated patients (median=0 vs 6.5%, P<0.001), and for radiation oncologists than for gynaecologists (median=4 vs 13%, P<0.001). Substantial variation existed within the groups of patients and clinicians. Participants preferred the patient and clinician to share in the decision about VBT. However, irradiated patients indicated low perceived involvement in actual treatment decision making.Conclusions:We found variations between and within patients and clinicians in minimally desired benefit from VBT. However, the recurrence risk at which patients preferred VBT was low. Our results showed that patients consider active participation in decision making essential.
Patient recruitment is one of the most important barriers to successful completion of clinical trials and thus to obtaining evidence about new methods for prevention, diagnostics and treatment. The reason is that recruitment is effort consuming. It requires the identification of candidate patients for the trial (the population under study), and verifying for each patient whether the eligibility criteria are met. The work we describe in this paper aims to support the comparison of population under study in different trials, and the design of eligibility criteria for new trials. We do this by introducing structured eligibility criteria, that enhance reuse of criteria across trials. We developed a method that allows for automated structuring of criteria from text. Additionally, structured eligibility criteria allow us to propose suggestions for relaxation of criteria to remove potentially unnecessarily restrictive conditions. We thereby increase the recruitment potential and generalizability of a trial. Our method for automated structuring of criteria enables us to identify related conditions and to compare their restrictiveness. The comparison is based on the general meaning of criteria, comprised of commonly occurring contextual patterns, medical concepts and constraining values. These are automatically identified using our pattern detection algorithm, state of the art ontology annotators and semantic taggers. The comparison uses predefined relations between the patterns, concept equivalences defined in medical ontologies, and threshold values. The result is a library of structured eligibility criteria which can be browsed using fine grained queries. Furthermore, we developed visualizations for the library that enable intuitive navigation of relations between trials, criteria and concepts. These visualizations expose interesting co-occurrences and correlations, potentially enhancing meta-research. The method for criteria structuring processes only certain types of criteria, which results in low recall of the method (18%) but a high precision for the relations we identify between the criteria (94%). Analysis of the approach from the medical perspective revealed that the approach can be beneficial for supporting trial design, though more research is needed.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.