Development of a Patient Decision Aid to Support Shared Decision Making for Patients with Recurrent High-Grade Glioma

Have a vital end-user been overlooked? Developing a shared decision intervention for patients with potential pancreatic cancer regarding the choice of surgery

Objective

To develop a patient decision aid facilitating shared decision making for patients with potential pancreatic cancer deciding about no treatment, surgical or medical treatment.

Methods

Based on a user-centred design by Wittemann et al., we developed a shared decision making intervention in three phases: 1) Understanding decision needs 2) Development of a patient decision aid (PtDA) based on a generic template 3) Assessment of the intervention from interviews with patients (n = 11), relatives (n = 11), nurses (n = 4) and surgeons (n = 2) analysed with thematic analysis, and measuring patients' perceptions of choice of options with the Decisional Conflict Scale.

Results

Results showed varying experiences with the use of the PtDA, with surgeons not finding PtDA useful as it was impractical and constraining with patients' conversations. There was no difference in patients' perceptions in choosing options for those being presented vs those patients not being presented for the PtDA.

Conclusion

The format and structure of the PtDA was not feasible for the surgeons as fundamental users in the present clinic.

Innovation

This study highlights the urgent need to consider clinical context before introducing a predefined tool and shows the importance of a multistakeholder approach. Research should focus on finding means to successful implement shared decision making.

Shared decision making with breast cancer patients - does it work? Results of the cluster-randomized, multicenter DBCG RT SDM trial

BACKGROUND AND PURPOSE

Shared decision making (SDM) is a patient engaging process advocated especially for preference-sensitive decisions, such as adjuvant treatment after breast cancer. An increasing call for patient engagement in decision making highlights the need for a systematic SDM approach. The objective of this trial was to investigate whether the Decision Helper (DH), an in-consultation patient decision aid, increases patient engagement in decisions regarding adjuvant whole breast irradiation.

MATERIAL AND METHODS

Oncologists at four radiotherapy units were randomized to practice SDM using the DH versus usual practice. Patient candidates for adjuvant whole breast irradiation after breast conserving surgery for node-negative breast cancer were eligible. The primary endpoint was patient-reported engagement in the decision process assessed with the Shared Decision Making Questionnaire (SDM-Q-9) (range 0-100, 4 points difference considered clinical relevant). Other endpoints included oncologist-reported patient engagement, decisional conflict, fear of cancer recurrence, and decision regret after 6 months.

RESULTS

Of the 674 included patients, 635 (94.2%) completed the SDM-Q-9. Patients in the intervention group reported higher level of engagement (median 80; IQR 68.9 to 94.4) than the control group (71.1; IQR 55.6 to 82.2; p < 0.0001). Oncologist-reported patient engagement was higher in the invention group (93.3; IQR 82.2 to 100) compared to control group (73.3; IQR 60.0 to 84.4) (p < 0.0001).

CONCLUSION

Patient engagement in medical decision making was significantly improved with the use of an in-consultation patient decision aid compared to standard. The DH on adjuvant whole breast irradiation is now recommended as standard of care in the Danish guideline.

Large language models as decision aids in neuro-oncology: a review of shared decision-making applications

Shared decision-making (SDM) is crucial in neuro-oncology, fostering collaborations between patients and healthcare professionals to navigate treatment options. However, the complexity of neuro-oncological conditions and the cognitive and emotional burdens on patients present significant barriers to achieving effective SDM. This discussion explores the potential of large language models (LLMs) such as OpenAI's ChatGPT and Google's Bard to overcome these barriers, offering a means to enhance patient understanding and engagement in their care. LLMs, by providing accessible, personalized information, could support but not supplant the critical insights of healthcare professionals. The hypothesis suggests that patients, better informed through LLMs, may participate more actively in their treatment choices. Integrating LLMs into neuro-oncology requires navigating ethical considerations, including safeguarding patient data and ensuring informed consent, alongside the judicious use of AI technologies. Future efforts should focus on establishing ethical guidelines, adapting healthcare workflows, promoting patient-oriented research, and developing training programs for clinicians on the use of LLMs. Continuous evaluation of LLM applications will be vital to maintain their effectiveness and alignment with patient needs. Ultimately, this exploration contends that the thoughtful integration of LLMs into SDM processes could significantly enhance patient involvement and strengthen the patient-physician relationship in neuro-oncology care.

Treatment of Adult Gliomas: A Current Update

Gliomas are the most common type of primary brain tumor in adults. Glioma treatment requires a multidisciplinary approach involving surgery, radiotherapy, and chemotherapy. Multiple trials have been conducted to establish the appropriate choice of treatment to achieve long-term survival and better quality of life. This review provides up-to-date evidence regarding treatment strategies for gliomas.