Improving providers' survival estimates and selection of prognosis- and guidelines-appropriate treatment for patients with symptomatic bone metastases: Development of the Bone Metastases Ensemble Trees for Survival Decision Support Platform

Codesign Use in Palliative Care Intervention Development: A Systematic Review

CONTEXT

Codesign is a methodology that includes active collaboration between stakeholders in designing solutions and has been used in the development and implementation of palliative care (PC) interventions.

OBJECTIVES

To synthesize the state of evidence for codesign in the development of PC interventions.

METHODS

We searched PubMed, EMBASE, and CINAHL for peer-reviewed studies published after 1995 that reported evidence of codesigned interventions and outcomes in patients receiving palliative, hospice, or end-of-life care. We screened studies through independent and blinded dual review within Covidence and assessed study quality with the 2018 Mixed Methods Appraisal Tool. We narratively synthesized codesign duration, engagement approach, stakeholders involved, intervention designs, follow-ups, and outcomes, comparing among codesigns reporting meaningful improvement in outcomes. We created a best practice checklist which we used to evaluate codesign use in each study.

RESULTS

About 1,036 abstracts and 54 full text articles were screened. Twenty-eight studies met inclusion criteria and were abstracted. Feedback collection modalities ranged from iterative drafting, pilot testing, advisory panels, workshops, focus groups, and interviews. Thirteen studies applied pretesting/prototyping through pretest post-test, focus groups, prototypes, alpha and beta testing, and mock-ups. Eleven studies reported improved outcomes, eight of which utilized iterative codesign. All the studies reporting improved outcomes mentioned meeting with stakeholders at least twice. Two studies met all criteria in our codesign best practice checklist.

CONCLUSION

Codesigned PC interventions demonstrate high variance in the modality of acquiring feedback and application of codesign. Successful codesign leading to improvement in outcomes is achieved by involving patients, caregivers, and providers in iterating intervention design.

Prognostication for Patients Receiving Palliative Radiation Therapy

Estimation of patient prognosis plays a central role in guiding decision making for the palliative management of metastatic disease, and a number of statistical models have been developed to provide survival estimates for patients in this context. In this review, we discuss several well-validated survival prediction models for patients receiving palliative radiotherapy to sites outside of the brain. Key considerations include the type of statistical model, model performance measures and validation procedures, studies' source populations, time points used for prognostication, and details of model output. We then briefly discuss underutilization of these models, the role of decision support aids, and the need to incorporate patient preference in shared decision making for patients with metastatic disease who are candidates for palliative radiotherapy.

Evaluation of the Clinical Utility of the Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP): A Case-Based Pilot Assessment

PURPOSE

The Bone Metastases Ensemble Trees for Survival Decision Support Platform (BMETS-DSP) provides patient-specific survival predictions and evidence-based recommendations to guide multidisciplinary management for symptomatic bone metastases. We assessed the clinical utility of the BMETS-DSP through a pilot prepost design in a simulated clinical environment.

METHODS

Ten Radiation Oncology physicians reviewed 55 patient cases at two time points: without and then with the use of BMETS-DSP. Assessment included 12-month survival estimate, confidence in and likelihood of sharing estimates with patients, and recommendations for open surgery, systemic therapy, hospice referral, and radiotherapy (RT) regimen. Paired statistics compared pre- versus post-DSP outcomes. Reported statistical significance is P < .05.

RESULTS

Pre- versus post-DSP, overestimation of true minus estimated survival time was significantly reduced (mean difference -2.1 [standard deviation 4.1] v -1 month [standard deviation 3.5]). Prediction accuracy was significantly improved at cut points of < 3 (72 v 79%), ≤ 6 (64 v 71%), and ≥ 12 months (70 v 81%). Median ratings of confidence in and likelihood of sharing prognosis significantly increased. Significantly greater concordance was seen in matching use of 1-fraction RT with the true survival < 3 months (70 v 76%) and < 10-fraction RT with the true survival < 12 months (55 v 62%) and appropriate use of open surgery (47% v 53%), without significant changes in selection of hospice referral or systemic therapy.

CONCLUSION

This pilot study demonstrates that BMETS-DSP significantly improved physician survival estimation accuracy, prognostic confidence, likelihood of sharing prognosis, and use of prognosis-appropriate RT regimens in the care of symptomatic bone metastases, supporting future multi-institutional validation of the platform.