PURPOSE: Comorbidity is an independent predictor of mortality and treatment tolerance in head and neck cancer and should be considered with regard to treatment intensification. Multiple previously validated models can be used to evaluate comorbidity and propensity to benefit from intensive treatment, but they have not been directly compared. MATERIALS AND METHODS: An online tool was developed and used to calculate the Charlson Comorbidity Index (CCI), Adult Comorbidity Evaluation-27 (ACE-27), Cumulative Illness Rating Scale for Geriatrics (CIRS-G), Geriatric 8 (G8), Cancer and Aging Research Group (CARG), and Generalized Competing Event (GCE) scores. To assess interrater variability, five evaluators independently calculated scores on a retrospective cohort of 20 patients. Correlation between models as well as age and performance status were calculated from a cohort of 40 patients. RESULTS: The GCE and G8 models had an excellent (intraclass correlation coefficient and Fleiss' kappa ≥ 0.75) degree of interrater agreement. The CCI, ACE-27, CIRS-G, and CARG had a good (intraclass correlation coefficient and Fleiss' kappa 0.6-0.74) degree of interrater agreement. There was statistically significant correlation between models, especially with the CCI, ACE-27, and CIRS-G indices. Increased age was correlated with an increased CCI score and having moderate to severe comorbidity was correlated with the ACE-27 model. Except for the G8 model, the comorbidity indices were not associated with Eastern Cooperative Oncology Group performance status. CONCLUSION: We developed an online tool to calculate indices of comorbidity in patients with head and neck cancer with a high degree of reproducibility. Comorbidity is not strongly correlated with performance status and should be independently evaluated in patients.
PURPOSE: Comorbidity is an independent predictor of mortality and treatment tolerance in head and neck cancer and should be considered with regard to treatment intensification. Multiple previously validated models can be used to evaluate comorbidity and propensity to benefit from intensive treatment, but they have not been directly compared. MATERIALS AND METHODS: An online tool was developed and used to calculate the Charlson Comorbidity Index (CCI), Adult Comorbidity Evaluation-27 (ACE-27), Cumulative Illness Rating Scale for Geriatrics (CIRS-G), Geriatric 8 (G8), Cancer and Aging Research Group (CARG), and Generalized Competing Event (GCE) scores. To assess interrater variability, five evaluators independently calculated scores on a retrospective cohort of 20 patients. Correlation between models as well as age and performance status were calculated from a cohort of 40 patients. RESULTS: The GCE and G8 models had an excellent (intraclass correlation coefficient and Fleiss' kappa ≥ 0.75) degree of interrater agreement. The CCI, ACE-27, CIRS-G, and CARG had a good (intraclass correlation coefficient and Fleiss' kappa 0.6-0.74) degree of interrater agreement. There was statistically significant correlation between models, especially with the CCI, ACE-27, and CIRS-G indices. Increased age was correlated with an increased CCI score and having moderate to severe comorbidity was correlated with the ACE-27 model. Except for the G8 model, the comorbidity indices were not associated with Eastern Cooperative Oncology Group performance status. CONCLUSION: We developed an online tool to calculate indices of comorbidity in patients with head and neck cancer with a high degree of reproducibility. Comorbidity is not strongly correlated with performance status and should be independently evaluated in patients.
Authors: Daniel R Dickstein; Eric J Lehrer; Kristin Hsieh; Alexandra Hotca; Brianna M Jones; Ann Powers; Sonam Sharma; Jerry Liu; Vishal Gupta; Loren Mell; Zain Husain; Diana Kirke; Krzysztof Misiukiewicz; Marshall Posner; Eric Genden; Richard L Bakst Journal: Cancers (Basel) Date: 2022-06-05 Impact factor: 6.575