Cancer Research on Prevention and Treatment    2021, Vol. 48 Issue (09) : 853-858     DOI: 10.3971/j.issn.1000-8578.2021.21.0259
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A Survival Prediction Model of Pulmonary Sarcomatoid Carcinoma Based on SEER Database
LIU Ying1, XIE Bin1, WANG Meng2, LI Yiran1, YAN Wenjin1, XU Xingxiang3, MIN Lingfeng3
1. The First Clinical College of Dalian Medical University, Dalian 116000, China; 2. Clinical Medical College of Yangzhou University, Yangzhou 225001, China; 3. Department of Respiratory and Critical Care Medicine, Northern Jiangsu People’s Hospital, Yangzhou 225001, China
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Abstract Objective To analyze the factors affecting the prognosis of patients with pulmonary sarcomatoid carcinoma (PSC) and construct a nomogram prediction model for the prognosis of PSC patients. Methods Based on the SEER database, 1671 patients diagnosed as PSC from 1988 to 2015 were collected and divided into modeling group and validation group according to the ratio of 7:3. Univariate and multivariate Cox regression analysis were performed in the modeling group to explore independent risk factors affecting the prognosis and construct a nomogram survival prediction model. The consistency index and calibration curve were used for verification in the modeling group and the test module respectively. Results Age, gender, histological type, TNM stage, tumor diameter >50mm, surgery, radiotherapy and chemotherapy were independent factors that affected the prognosis of PSC patients. The nomogram prediction model was constructed and verified based on independent factors. The C indexes of the modeling group and the test model were 0.790 (95%CI: 0.776-0.804) and 0.781 (95%CI: 0.759-0.803), respectively. The calibration curves of the modeling group and the test model indicated that the predicted survival rate was basically the same as the actual survival rate. Conclusion The nomogram prediction model constructed based on the results of multivariate analysis can predict the prognosis of PSC patients, and has high accuracy and consistency.
Keywords Pulmonary sarcomatoid carcinoma      Prognostic factors      Predictive model      SEER database     
ZTFLH:  R734.2  
Issue Date: 14 September 2021
 Cite this article:   
LIU Ying,XIE Bin,WANG Meng, et al. A Survival Prediction Model of Pulmonary Sarcomatoid Carcinoma Based on SEER Database[J]. Cancer Research on Prevention and Treatment, 2021, 48(09): 853-858.
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http://www.zlfzyj.com/EN/10.3971/j.issn.1000-8578.2021.21.0259
http://www.zlfzyj.com/EN/Y2021/V48/I09/853
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LIU Ying
XIE Bin
WANG Meng
LI Yiran
YAN Wenjin
XU Xingxiang
MIN Lingfeng
[1] Li X, Wu D, Liu H, et al. Pulmonary sarcomatoid carcinoma:
progress, treatment and expectations[J]. Ther Adv Med Oncol,
2020, 12: 1758835920950207.
[2] Sim JK, Chung SM, Choi JH, et al. Clinical and molecular
characteristics of pulmonary sarcomatoid carcinoma[J]. Korean J
Intern Med, 2018, 33(4): 737-744.
[3] Franks TJ, Galvin JR. Sarcomatoid carcinoma of the lung:
histologic criteria and common lesions in the differential
diagnosis[J]. Arch Pathol Lab Med, 2010, 134(1): 49-54.
[4] 毛玉焕, 冀瑛瑛, 商映雪, 等. 79例肺肉瘤样癌的临床特征及预后
分析[J]. 肿瘤防治研究, 2018, 45(5): 295-299. [Mao YH, Ji YY,
Shang YX, et al. Clinical Features and Prognosis of 79 Cases of
Pulmonary Sarcomatoid Carcinoma[J]. Zhong Liu Fang Zhi Yan
Jiu, 2018, 45(5): 295-299.]
[5] Beasley MB, Brambilla E, Travis WD. The 2004 World Health
Organization classification of lung tumors[J]. Semin Roentgenol,
2005, 40(2): 90-97.
[6] Avila MR, Marrón FC, Hermoso AF, et al. Primary pulmonary
sarcomatoid carcinomas[J]. Arch Bronconeumol, 2013, 49(9):
405-407.
[7] Lantuéjoul S, Brambilla E. Quoi de neuf dans la classification des
tumeurs pulmonaires selon l’OMS 2004?[J]. Rev Pneumol Clini,
2008, 64(4): 187-194.
[8] Liang X, Cheng Y, Yuan Z, et al. Clinical, pathological and
treatment factors associated with the survival of patients with
pulmonary sarcomatoid carcinoma[J]. Oncol Lett, 2020, 19(6):
4031-4039.
[9] Rahouma M, Kamel M, Narula N, et al. Pulmonary sarcomatoid
carcinoma: an analysis of a rare cancer from the Surveillance,
Epidemiology, and End Results database[J]. Eur J Cardiothorac
Surg, 2018, 53(4): 828-834.
[10] Pelosi G, Sonzogni A, De Pas T, et al. Review article: pulmonary
sarcomatoid carcinomas: a practical overview[J]. Int J Surg
Pathol, 2010, 18(2): 103-120.
[11] 周秀秀, 王良哲, 望云, 等. 原发性肺肉瘤样癌的影像诊断[J].
医学影像学杂志, 2020, 30(7): 1311-1314. [Zhou XX, Wang
LZ, Wang Y, et al. Imaging diagnosis of pulmonary sarcomatoid
carcinoma[J]. Yi Xue Ying Xiang Xue Za Zhi, 30(7): 1311-1314.]
[12] Shum E, Stuart M, Borczuk A, et al. Recent advances in the
management of pulmonary sarcomatoid carcinoma[J]. Expert Rev
Respir Med, 2016, 10(4): 407-416.
[13] Zeng Q, Li J, Sun N, et al. Preoperative systemic immuneinflammation
index predicts survival and recurrence in patients
with resected primary pulmonary sarcomatoid carcinoma[J].
Transl Lung Cancer Res, 2021, 10(1): 18-31.
[14] Hou J, Xing L, Yuan Y. A clinical analysis of 114 cases of
sarcomatoid carcinoma of the lung[J]. Clin Exp Med, 2018, 18(4):
555-562.
[15] 李巧珍, 林炳棋, 张才金. 21例肺肉瘤样癌临床分析和靶向治
疗探讨[J]. 临床肺科杂志, 2019, 24(8): 1474-1479. [Li QZ, Lin
BQ, Zhang CJ. Molecular targeted therapy and clinical analysis of
pulmonary sarcomatoid carcinoma in 21 cases[J]. Lin Chuang Fei
Ke Za Zhi, 2019, 24(8): 1474-1479.]
[16] Maneenil K, Xue Z, Liu M, et al. Sarcomatoid Carcinoma of the
Lung: The Mayo Clinic Experience in 127 Patients[J]. Clin Lung
Cancer, 2018, 19(3): e323-e333.
[17] Lin Y, Yang H, Cai Q, et al. Characteristics and Prognostic
Analysis of 69 Patients With Pulmonary Sarcomatoid
Carcinoma[J]. Am J Clin Oncol, 2016, 39(3): 215-222.
[18] Chaft JE, Sima CS, Ginsberg MS, et al. Clinical outcomes with
perioperative chemotherapy in sarcomatoid carcinomas of the
lung[J]. J Thorac Oncol, 2012, 7(9): 1400-1405.
[19] Diao JD, Wu CJ, Cui HX, et al. Nomogram predicting overall
survival of rectal squamous cell carcinomas patients based on the
SEER database: A population-based STROBE cohort study[J].
Medicine (Baltimore), 2019, 98(46): e17916.
[20] Zhang J, Gong Z, Gong Y, et al. Development and validation of
nomograms for prediction of overall survival and cancer-specific
survival of patients with Stage Ⅳ colorectal cancer[J]. Jpn J Clin
Oncol, 2019, 49(5): 438-446.
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