Learning from data to predict future symptoms of oncology patients.

Effective symptom management is a critical component of cancer treatment. Computational tools that predict the course and severity of these symptoms have the potential to assist oncology clinicians to personalize the patient's treatment regimen more efficiently and provide more aggressive and timely interventions. Three common and inter-related symptoms in cancer patients are depression, anxiety, and sleep disturbance. In this paper, we elaborate on the efficiency of Support Vector Regression (SVR) and Non-linear Canonical Correlation Analysis by Neural Networks (n-CCA) to predict the severity of the aforementioned symptoms between two different time points during a cycle of chemotherapy (CTX). Our results demonstrate that these two methods produced equivalent results for all three symptoms. These types of predictive models can be used to identify high risk patients, educate patients about their symptom experience, and improve the timing of pre-emptive and personalized symptom management interventions.

The eSMART study protocol: a randomised controlled trial to evaluate electronic symptom management using the advanced symptom management system (ASyMS) remote technology for patients with cancer.

INTRODUCTION: While some evidence exists that real-time remote symptom monitoring devices can decrease morbidity and prevent unplanned admissions in oncology patients, overall, these studies have significant methodological weaknesses. The electronic Symptom Management using the Advanced Symptom Management System (ASyMS) Remote Technology (eSMART) study is designed to specifically address these weaknesses with an appropriately powered, repeated-measures, parallel-group stratified randomised controlled trial of oncology patients. METHODS AND ANALYSIS: A total of 1108 patients scheduled to commence first-line chemotherapy (CTX) for breast, colorectal or haematological cancer will be recruited from multiple sites across five European countries.Patients will be randomised (1:1) to the ASyMS intervention (intervention group) or to standard care currently available at each site (control group). Patients in the control and intervention groups will complete a demographic and clinical questionnaire, as well as a set of valid and reliable electronic patient-reported outcome measures at enrolment, after each of their CTX cycles (up to a maximum of six cycles) and at 3, 6, 9 and 12 months after completion of their sixth cycle of CTX. Outcomes that will be assessed include symptom burden (primary outcome), quality of life, supportive care needs, anxiety, self-care self-efficacy, work limitations and cost effectiveness and, from a health professional perspective, changes in clinical practice (secondary outcomes). ETHICS AND DISSEMINATION: Ethical approval will be obtained prior to the implementation of all major study amendments. Applications will be submitted to all of the ethics committees that granted initial approval.eSMART received approval from the relevant ethics committees at all of the clinical sites across the five participating countries. In collaboration with the European Cancer Patient Coalition (ECPC), the trial results will be disseminated through publications in scientific journals, presentations at international conferences, and postings on the eSMART website and other relevant clinician and consumer websites; establishment of an eSMART website (www.esmartproject.eu) with publicly accessible general information; creation of an eSMART Twitter Handle, and production of a toolkit for implementing/utilising the ASyMS technology in a variety of clinical practices and other transferable health care contexts. TRIAL REGISTRATION NUMBER: NCT02356081.