Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis

Lingxiao Qiu; Pan Song; Pingmei Chen; Huaqi Wang; Fangfang Li; Mengxuan Shu; Gen-Cheng Gong; Xiangjin Song; Chun Huang; Hongxia Jia; Nana Li; Guojun Zhang

doi:10.3389/fonc.2021.601185

Clinical Characteristics and Prognosis of Patients With Pulmonary Mucoepidermoid Carcinoma: A SEER-Based Analysis

Front Oncol. 2021 Mar 5:11:601185. doi: 10.3389/fonc.2021.601185. eCollection 2021.

Authors

Lingxiao Qiu^{1

2}, Pan Song³, Pingmei Chen⁴, Huaqi Wang^{1

5

6}, Fangfang Li¹, Mengxuan Shu⁷, Gen-Cheng Gong⁸, Xiangjin Song¹, Chun Huang¹, Hongxia Jia¹, Nana Li¹, Guojun Zhang^{1

5

6}

Affiliations

¹ Department of Respiratory Medicine, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.
² Academy of Medical Sciences, Zhengzhou University, Zhengzhou, China.
³ Department of Urology, West China Hospital of Sichuan University, Chengdu, China.
⁴ Department of Neonatology, West China Guang'an Hospital, Sichuan University, Guang'an, China.
⁵ Zhengzhou Key Laboratory for Chronic Respiratory Disease, Zhengzhou, China.
⁶ Henan Provincial Respiratory Medicine Center, Zhengzhou, China.
⁷ The First Clinical Medical College of Lanzhou University, Lanzhou, China.
⁸ State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.

Abstract

Background: Primary pulmonary mucoepidermoid carcinoma (PMEC) is an extremely rare malignancy. Its clinical characteristics and prognosis are not fully understood. This study evaluated clinical characteristics and prognostic factors of PMEC and established a nomogram to predict its 1-, 3-, 5- and 10-year cancer-specific survival (CSS) rates.

Methods: In the Surveillance, Epidemiology, and End Results database from January 1, 2016 to December 31, 2016, patients pathologically diagnosed with PMEC were identified. Kaplan-Meier analysis and Cox regression were performed to evaluate the CSS stratified by different covariates. A predictive nomogram model was built and validated by the concordance index (C-index) and calibration curves.

Results: A total of 585 PMEC patients were identified. A total of 408 (70%) of patients were placed into the training cohort, and 177 (30%) patients were placed into the validation cohort. The 5- and 10-year CSS rates of stage I-II PMEC patients were 91.4 and 88.9, respectively. The 1-, 3- and 5-year CSS rates of stage III-IV PMEC were 56.5, 39.45, and 32.1%, respectively. Survival curves showed that older age, large tumor size, poor differentiation, and high TNM stage were associated with a significantly worse prognosis. CSS outcomes were significantly better in patients who received surgical treatments (surgical alone, surgery plus radiation and/or chemotherapy). Patients who received radiation and/or chemotherapy had the worst prognosis. Multivariate Cox results revealed that covariates, including age, tumor laterality, tumor sizes, pathological differentiation, lymph node metastasis, distant metastasis, TNM stage and therapy, were independent prognostic factors for PMEC. These factors were used to construct a nomogram. The C-index of the nomogram was 0.921. The calibration curve presented favorable consistency between the predicted CSS and actual observations. This nomogram was validated by the validation cohort. The C-index of the validation cohort was 0.968.

Conclusion: Age, bilateral tumors, tumor size, pathological differentiation grade, lymph node metastasis, distant metastasis, TNM stage and therapy were independent prognostic factors of PMEC patients. The first nomogram for predicting the CSS of PMEC was built and validated, showing its potential value in practice.

Keywords: Surveillance, Epidemiology, and End Results (SEER); clinical characteristics; nomogram; prognosis; pulmonary mucinous epidermoid carcinoma.