Evaluating the ability of an artificial-intelligence cloud-based platform designed to provide information prior to locoregional therapy for breast cancer in improving patient's satisfaction with therapy: The CINDERELLA trial.

BACKGROUND: Breast cancer therapy improved significantly, allowing for different surgical approaches for the same disease stage, therefore offering patients different aesthetic outcomes with similar locoregional control. The purpose of the CINDERELLA trial is to evaluate an artificial-intelligence (AI) cloud-based platform (CINDERELLA platform) vs the standard approach for patient education prior to therapy. METHODS: A prospective randomized international multicentre trial comparing two methods for patient education prior to therapy. After institutional ethics approval and a written informed consent, patients planned for locoregional treatment will be randomized to the intervention (CINDERELLA platform) or controls. The patients in the intervention arm will use the newly designed web-application (CINDERELLA platform, CINDERELLA APProach) to access the information related to surgery and/or radiotherapy. Using an AI system, the platform will provide the patient with a picture of her own aesthetic outcome resulting from the surgical procedure she chooses, and an objective evaluation of this aesthetic outcome (e.g., good/fair). The control group will have access to the standard approach. The primary objectives of the trial will be i) to examine the differences between the treatment arms with regards to patients' pre-treatment expectations and the final aesthetic outcomes and ii) in the experimental arm only, the agreement of the pre-treatment AI-evaluation (output) and patient's post-therapy self-evaluation. DISCUSSION: The project aims to develop an easy-to-use cost-effective AI-powered tool that improves shared decision-making processes. We assume that the CINDERELLA APProach will lead to higher satisfaction, better psychosocial status, and wellbeing of breast cancer patients, and reduce the need for additional surgeries to improve aesthetic outcome.

Relationship of non-melancholic and melancholic depressive symptoms with all-cause mortality: A prospective study in a primary care population.

OBJECTIVE: To assess relationship of non-melancholic and melancholic subtypes of depressive symptoms with all-cause mortality among cardiovascular risk persons. METHODS: A population-based prospective study of 2522 Finnish middle-aged persons with elevated cardiovascular risk was conducted. Depressive symptoms were assessed by the Beck's Depression Inventory. Data on mortality were obtained from The Official Statistics of Finland after 11-year follow-up. RESULTS: At baseline, the prevalence of non-melancholic and melancholic depressive symptoms was 14.9% and 5.2%, respectively. During the mean follow-up time of 11 years, 8.1% (n = 164) of those without, 13.9% (n = 52) of those with non-melancholic, and 10.7% (n = 14) of those with melancholic depressive symptoms died. Compared to non-depressive subjects, the hazard ratio for time to all-cause mortality was 1.67 (95% CI: 1.21-2.32, p = .002) in non-melancholically depressive and 1.01 (95% CI: 0.56-1.83, p = .97) in melancholically depressive subjects, when adjusted for age, gender, education, smoking, alcohol use, BMI, hypertension, dyslipidaemia, and glucose disorders. In comparison to the mortality rate in the general population throughout Finland over the same period, non-depressiveness was associated with a decreased standardized mortality rate. CONCLUSION: Non-melancholic depressive symptoms seem to be associated with excess all-cause mortality. In clinical settings, recognition of non-melancholic depressive symptoms should be emphasised.