Weidong Shen1, Naoko Sakamoto2, Limin Yang3,4. 1. Institute of Otolaryngology, Department of Otolaryngology - Head and Neck Surgery, Chinese PLA General Hospital, Beijing, 100853, China. 2. Department of Epidemiology Research, Toho University, Tokyo, 143-0015, Japan. 3. Division of Allergy, Department of Medical Subspecialties, National Center for Child Health and Development, Tokyo, 157-8535, Japan. yo-r@ncchd.go.jp. 4. Medical Support Center for Japan Environment and Children's Study (JECS), National Center for Child Health and Development, Tokyo, 157-8535, Japan. yo-r@ncchd.go.jp.
Abstract
PURPOSE: The main objective of this study was to evaluate the cumulative incidence of cause-specific death and other causes of death for patients with head and neck adenoid cystic carcinoma (ACC). The secondary aim was to model the probability of cause-specific death and build a competing risk nomogram to predict cause-specific mortality for this disease. METHODS: Data were extracted from the US National Cancer Institute's Surveillance Epidemiology, and End Results (SEER)-18 dataset. The study cohort included patients with a diagnosis of primary head and neck ACC during the period 2004-2013. We calculated the cumulative incidence function (CIF) for cause-specific death and other causes of death, and constructed the Fine and Gray's proportional subdistribution hazard model, as well as a competing-risk nomogram based on Fine and Gray's model, to predict the probability of cause-specific death for patients with head and neck ACC. RESULTS: After data selection, 1435 cases were included for analysis. Five-year cumulative incidence of cause-specific death was 17.4% (95% confidence interval [CI] 15.1-19.8%) and cumulative incidence of other causes of death was 5.8% (95% CI 4.4-7.4%). Predictors of cause-specific death for head and neck ACC included age, tumor size, advanced T stage, positive lymph node, distant metastasis, and surgery. The nomogram was well-calibrated, and had good discriminative ability. CONCLUSION: The large sample allowed us to construct a reliable predictive model for rare malignancy. The model performance was good, with a concordance index of 0.79, and the nomogram can provide useful individualized predictive information for patients with head and neck ACC.
PURPOSE: The main objective of this study was to evaluate the cumulative incidence of cause-specific death and other causes of death for patients with head and neck adenoid cystic carcinoma (ACC). The secondary aim was to model the probability of cause-specific death and build a competing risk nomogram to predict cause-specific mortality for this disease. METHODS: Data were extracted from the US National Cancer Institute's Surveillance Epidemiology, and End Results (SEER)-18 dataset. The study cohort included patients with a diagnosis of primary head and neck ACC during the period 2004-2013. We calculated the cumulative incidence function (CIF) for cause-specific death and other causes of death, and constructed the Fine and Gray's proportional subdistribution hazard model, as well as a competing-risk nomogram based on Fine and Gray's model, to predict the probability of cause-specific death for patients with head and neck ACC. RESULTS: After data selection, 1435 cases were included for analysis. Five-year cumulative incidence of cause-specific death was 17.4% (95% confidence interval [CI] 15.1-19.8%) and cumulative incidence of other causes of death was 5.8% (95% CI 4.4-7.4%). Predictors of cause-specific death for head and neck ACC included age, tumor size, advanced T stage, positive lymph node, distant metastasis, and surgery. The nomogram was well-calibrated, and had good discriminative ability. CONCLUSION: The large sample allowed us to construct a reliable predictive model for rare malignancy. The model performance was good, with a concordance index of 0.79, and the nomogram can provide useful individualized predictive information for patients with head and neck ACC.
Authors: Ning Su; Yu Fang; Jinni Wang; Xiaopeng Tian; Shuyun Ma; Jun Cai; Yuchen Zhang; Yi Xia; Panpan Liu; Qingqing Cai Journal: Transl Cancer Res Date: 2022-08 Impact factor: 0.496