Patients with head and neck cancer who self-report high levels of pain, loss of appetite, shortness of breath, and tiredness are more likely to visit hospital emergency rooms within 14 days, according to a new study by a multi-disciplinary team of researchers led by Terry Fox New Investigator Dr. Antoine Eskander (Sunnybrook Research Institute).
These findings, published in the Journal of Clinical Oncology (January 2021), provide the first evidence that tools currently used by patients to report their symptoms could be analyzed to pre-emptively identify who is at a higher risk of visiting the hospital, allowing clinicians to create interventions that address these issues early on.
“Patients with head and neck cancer have been shown to experience some of the highest rates of symptom burden relative to other cancer sites, which affects survival and quality of life while also placing a financial burden on healthcare systems that foot the bill for those visits,” says Dr. Eskander. “By finding ways to use self-reporting tools that already exist to determine who is at a higher risk of these adverse events, we can potentially create interventions that address them before they lead to further complications.”
To make this finding, the team analyzed data from 11,761 patients with head and neck cancer. The data came from a survey called the Edmonton Symptom Assessment System (ESAS) which is routinely administered to cancer patients in Ontario during prior to out-patient visits with their physicians. This allowed them to find a strong correlation between high ESAS scores in the categories of pain, appetite, shortness of breath, and tiredness and incidences of hospitalization and emergency department visits, revealing that the ESAS is a stronger predictor of adverse events like emergency department visits and unplanned hospitalizations than any other clinical or sociodemographic factor.
Having learned this, the team is now working to create tools and protocols that will help impact patients dealing with high symptom burdens.
“We are now working on creating automated mechanisms like machine learning algorithms and app-based software that can review ESAS scores to identify patients who are at a high risk of adverse events so their healthcare teams can be alerted and can intervene before an adverse event occurs,” says Dr. Eskander.
Patient-Reported Symptom Burden as a Predictor of Emergency Department Use and Unplanned Hospitalization in Head and Neck Cancer: A Longitudinal Population-Based Study
Christopher W. Noel, Rinku Sutradhar, Haoyu Zhao, Victoria Delibasic, David Forner, Jonathan C. Irish, Jonathan Kim, Zain Husain, Alyson Mahar, Irene Karam, Danny J. Enepekides, Kelvin K. W. Chan, Simron Singh, Julie Hallet, Natalie G. Coburn, and Antoine Eskander
This study was partially funded by a Terry Fox New Investigator Award to Dr. Antoine Eskander for Symptom Burden As a Predictor of Emergency Room Visits and Unplanned Hospitalizations In Patients With Head and Neck Cancer