(A525) Comorbidities as Part of Clinical Decision-Making in Head and Neck Cancer Patients

Introduction: Assessment of comorbidities has been included in the evaluation of clinical decision making and to predict response to treatment, prognosis, survival, postoperative complications, and quality of life. Understanding how comorbidity has been used and validated in the literature is important to the appropriate and reliable application of comorbidity tools to provide clinically useful information. We aim to summarize the inclusion of comorbidity measured by Adult Comorbidity Evaluation-27 (ACE-27) in research work evaluating treatment decision making and prognostication for Head and Neck cancer patients.

Methods: A medical librarian conducted a search of Embase, Ovid Medline, Scopus, Cochrane, and Clinicaltrials.gov from 2005 to June 12, 2024. Keywords included comorbidity, adult comorbidity evaluation-27, ACE-27, prognosis, treatment decision making, and clinical decision making. Articles were selected that included ACE-27 for the assessment of treatment choice or prognostication in patients with Head and Neck Cancer. Data on the year of publication, sample size, study population, and effect sizes for treatment choice and prognosis will be collected and summarized. A scoping review utilizing this information was conducted.

Results: This search produced 394 articles, 98 of which discussed the role of ACE-27 and either treatment decision making (N=8) or prognostication (N=90) in Head and Neck Cancer. Higher grades of comorbidity were found to produce large effect sizes and reduction in the likelihood of completing guideline-concordant therapies (e.g. severe ACE-27 vs none: OR 0.23, 95% CI 0.08-0.57). ACE-27 was consistently found (70/90, 78%) to be an independent predictor of survival, postoperative complications, and treatment prognosis.

Conclusions: The inclusion of comorbidities in patient decision making related to treatment and outcomes of treatment on Head and Neck cancer patients has widely occurred in the literature. While the focus has been predominantly on predicting survival and rates of complications, large effects are also found on treatment decision making.