Annie Park1, Amy Alabaster2, Hanjie Shen3, Loren K Mell3,4, Jed A Katzel5. 1. Department of Internal Medicine, Scripps Mercy, San Diego, California. 2. Division of Research, Kaiser Permanente, Oakland, California. 3. Center for Precision Radiation Medicine, La Jolla, California. 4. Department of Radiation Medicine and Applied Sciences, University of California San Diego, San Diego, California. 5. Department of Oncology, Kaiser Permanente, Santa Clara, California.
Abstract
BACKGROUND: It is difficult to predict whether a patient with head and neck cancer (HNC) is more likely to die of the cancer or another comorbidity. Competing event models can help to identify individual patients or groups of patients who may be undertreated or overtreated in clinical practice. METHODS: Patients with HNC (n = 884), aged 18 to 85 years and diagnosed from 2000 to 2015 with stage II to IVB disease according to the seventh edition of the American Joint Committee on Cancer system, were identified. With a generalized competing event (GCE) model that controlled for age, sex, tumor site, surgical treatment, and Charlson Comorbidity Index (CCI), the association between these factors and the relative hazard for cancer mortality was determined. Logistic regression models were used to estimate the odds of receiving platinum-based chemoradiotherapy or a less intensive therapy, with adjustments made for age, sex, tumor site, CCI, stage, smoking, and alcohol abuse history. RESULTS: Compared with men, women had an increased relative hazard ratio for death from HNC versus other causes, which was reported as an adjusted ω+ ratio comparing women with men (ω+ ratio, 1.95; 95% CI, 1.09-3.49), even though they were less likely to receive intensive chemoradiotherapy than men (adjusted odds ratio, 0.69; 95% CI, 0.48-0.99). CONCLUSIONS: These findings indicate that women in this cohort may be undertreated in clinical practice and potentially miss the opportunity for their HNC to be aggressively treated. This study supports the use of GCE models to identify patients who are potentially undertreated and may also help to guide future research in health disparities.
BACKGROUND: It is difficult to predict whether a patient with head and neck cancer (HNC) is more likely to die of the cancer or another comorbidity. Competing event models can help to identify individual patients or groups of patients who may be undertreated or overtreated in clinical practice. METHODS:Patients with HNC (n = 884), aged 18 to 85 years and diagnosed from 2000 to 2015 with stage II to IVB disease according to the seventh edition of the American Joint Committee on Cancer system, were identified. With a generalized competing event (GCE) model that controlled for age, sex, tumor site, surgical treatment, and Charlson Comorbidity Index (CCI), the association between these factors and the relative hazard for cancer mortality was determined. Logistic regression models were used to estimate the odds of receiving platinum-based chemoradiotherapy or a less intensive therapy, with adjustments made for age, sex, tumor site, CCI, stage, smoking, and alcohol abuse history. RESULTS: Compared with men, women had an increased relative hazard ratio for death from HNC versus other causes, which was reported as an adjusted ω+ ratio comparing women with men (ω+ ratio, 1.95; 95% CI, 1.09-3.49), even though they were less likely to receive intensive chemoradiotherapy than men (adjusted odds ratio, 0.69; 95% CI, 0.48-0.99). CONCLUSIONS: These findings indicate that women in this cohort may be undertreated in clinical practice and potentially miss the opportunity for their HNC to be aggressively treated. This study supports the use of GCE models to identify patients who are potentially undertreated and may also help to guide future research in health disparities.
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