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Hou X, Liang F, Lou Y. Clinical features and prognostic factors for malignant parotid tumors in children and adolescents: A population-based study. JOURNAL OF STOMATOLOGY, ORAL AND MAXILLOFACIAL SURGERY 2024; 125:101741. [PMID: 38104649 DOI: 10.1016/j.jormas.2023.101741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2023] [Revised: 12/11/2023] [Accepted: 12/14/2023] [Indexed: 12/19/2023]
Abstract
PURPOSE We performed a population-based cohort study to investigate the clinical characteristics and survival rates of primary malignant parotid tumors (MPT) in children and adolescents. METHODS The Surveillance, Epidemiology, and End Results (SEER) database was used to identify all pediatric and adolescent patients with MPT who were diagnosed between 2000 and 2018. Based on a number of parameters, survival curves were produced using Kaplane-Meier estimates. The log-rank test was used to compare survival curves. The influence of each component on overall survival (OS) was examined using a multivariate Cox proportional hazards model. RESULTS There were 352 identified pediatric and adolescent patients with MPT. At diagnosis, the age ranged from 1.0 to 19 years, with a median of 15 years. Mucoepidermoid carcinoma (MC) (46.5 %) was the most common histological subtype, followed by acinar cell carcinoma (ACC) (36.4 %) and others (17.1 %) such as adenoid cystic carcinoma and squamous cell carcinoma. All patients had overall survival rates of 98.8 %, 95.6 %, and 94.6 % at 1-year, 3-year and 5-year, respectively. The results of the Cox proportional hazard regression showed that tumor grade, SEER stage, radiotherapy, and treatment regimens were significant independent predictors of overall survival. CONCLUSIONS In pediatric and adolescent MPT, tumor grade, SEER stage, adjuvant radiation, and treatment regimens were found to be important independent predictors of survival. More research is required to validate the role of adjuvant radiation.
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MESH Headings
- Humans
- Adolescent
- Child
- Parotid Neoplasms/epidemiology
- Parotid Neoplasms/diagnosis
- Parotid Neoplasms/pathology
- Parotid Neoplasms/therapy
- Parotid Neoplasms/mortality
- Male
- Female
- SEER Program/statistics & numerical data
- Prognosis
- Child, Preschool
- Infant
- Carcinoma, Mucoepidermoid/epidemiology
- Carcinoma, Mucoepidermoid/diagnosis
- Carcinoma, Mucoepidermoid/pathology
- Carcinoma, Mucoepidermoid/therapy
- Carcinoma, Mucoepidermoid/mortality
- Survival Rate
- Young Adult
- Proportional Hazards Models
- Carcinoma, Acinar Cell/epidemiology
- Carcinoma, Acinar Cell/diagnosis
- Carcinoma, Acinar Cell/pathology
- Carcinoma, Acinar Cell/therapy
- Cohort Studies
- United States/epidemiology
- Carcinoma, Squamous Cell/diagnosis
- Carcinoma, Squamous Cell/epidemiology
- Carcinoma, Squamous Cell/pathology
- Carcinoma, Squamous Cell/therapy
- Carcinoma, Adenoid Cystic/epidemiology
- Carcinoma, Adenoid Cystic/diagnosis
- Carcinoma, Adenoid Cystic/therapy
- Carcinoma, Adenoid Cystic/pathology
- Carcinoma, Adenoid Cystic/mortality
- Neoplasm Staging
- Kaplan-Meier Estimate
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Affiliation(s)
- Xiapei Hou
- Department of Stomatology, Northwest Women's and Children's Hospital, Xi'an, Shaanxi, China
| | - Fuhua Liang
- Department of Pediatric Surgery, Nanning Maternity and Child Health Hospital, Nanning, Guangxi, China
| | - Yi Lou
- Department of Pediatric Surgery, Hangzhou Children's Hospital, Hangzhou, Zhejiang, China.
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Cheng H, Xu JH, He JQ, Wu CC, Li JF, Xu XL. Nomogram based on immune-inflammatory indicators and age-adjusted charlson comorbidity index score to predict prognosis of postoperative parotid gland carcinoma patients. BMC Oral Health 2024; 24:718. [PMID: 38909208 PMCID: PMC11193213 DOI: 10.1186/s12903-024-04490-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2024] [Accepted: 06/17/2024] [Indexed: 06/24/2024] Open
Abstract
BACKGROUND Parotid gland carcinoma (PGC) is a rare malignant tumor. The purpose of this study was to investigate the role of immune-inflammatory-nutrition indicators and age-adjusted Charlson comorbidity index score (ACCI) of PGC and develop the nomogram model for predicting prognosis. METHOD All patients diagnosed with PGC in two tertiary hospitals, treated with surgical resection, from March 2012 to June 2018 were obtained. Potential prognostic factors were identified by univariate and multivariate Cox regression analyses. The nomogram models were established based on these identified independent prognostic factors. The performance of the developed prognostic model was estimated by related indexes and plots. RESULT The study population consisted of 344 patients with PGC who underwent surgical resection, 285 patients without smoking (82.8%), and 225 patients (65.4%) with mucoepidermoid carcinoma, with a median age of 50.0 years. American Joint Committee on Cancer (AJCC) stage (p < 0.001), pathology (p = 0.019), tumor location (p < 0.001), extranodal extension (ENE) (p < 0.001), systemic immune-inflammation index (SII) (p = 0.004), prognostic nutrition index (PNI) (p = 0.003), ACCI (p < 0.001), and Glasgow prognostic Score (GPS) (p = 0.001) were independent indicators for disease free survival (DFS). Additionally, the independent prognostic factors for overall survival (OS) including AJCC stage (p = 0.015), pathology (p = 0.004), tumor location (p < 0.001), perineural invasion (p = 0.009), ENE (p < 0.001), systemic immune-inflammation index (SII) (p = 0.001), PNI (p = 0.001), ACCI (p = 0.003), and GPS (p = 0.033). The nomogram models for predicting DFS and OS in PGC patients were generated based on these independent risk factors. All nomogram models show good discriminative capability with area under curves (AUCs) over 0.8 (DFS 0.802, and OS 0.825, respectively). Decision curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification index (NRI) show good clinical net benefit of the two nomograms in both training and validation cohorts. Kaplan-Meier survival analyses showed superior discrimination of DFS and OS in the new risk stratification system compared with the AJCC stage system. Finally, postoperative patients with PGC who underwent adjuvant radiotherapy had a better prognosis in the high-, and medium-risk subgroups (p < 0.05), but not for the low-risk subgroup. CONCLUSION The immune-inflammatory-nutrition indicators and ACCI played an important role in both DFS and OS of PGC patients. Adjuvant radiotherapy had no benefit in the low-risk subgroup for PGC patients who underwent surgical resection. The newly established nomogram models perform well and can provide an individualized prognostic reference, which may be helpful for patients and surgeons in proper follow-up strategies.
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Affiliation(s)
- Hao Cheng
- Department of Radiotherapy Oncology, The First Affiliated Hospital of Xinxiang Medical University, 88 Jiankang Road, Xinxiang, Henan, 453100, Henan, China
| | - Jin-Hong Xu
- Department of Otolaryngology, AnYang District Hospital, Anyang, Henan, 455000, China
| | - Jia-Qi He
- Department of Radiotherapy Oncology, Affiliated Cancer Hospital of Zhengzhou University, Zhengzhou, Henan, 450000, China
| | - Chen-Chen Wu
- Department of Radiotherapy Oncology, The First Affiliated Hospital of Xinxiang Medical University, 88 Jiankang Road, Xinxiang, Henan, 453100, Henan, China
| | - Jia-Fan Li
- Department of Radiotherapy Oncology, The First Affiliated Hospital of Xinxiang Medical University, 88 Jiankang Road, Xinxiang, Henan, 453100, Henan, China
| | - Xue-Lian Xu
- Department of Radiotherapy Oncology, The First Affiliated Hospital of Xinxiang Medical University, 88 Jiankang Road, Xinxiang, Henan, 453100, Henan, China.
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Li J, Rao Y, Wang X, Yu L, Qiu K, Mao M, Song Y, Pang W, Cheng D, Zhang Y, Feng L, Wang X, Shao X, Luo Y, Zheng Y, Li X, Xu Y, Xu W, Zhao Y, Ren J. Prognostic effects of previous cancer history on patients with major salivary gland cancer. Oral Dis 2024; 30:492-503. [PMID: 36740958 DOI: 10.1111/odi.14530] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 01/23/2023] [Accepted: 02/02/2023] [Indexed: 02/07/2023]
Abstract
OBJECTIVES To explore the prognostic effects of previous cancer history on patients with major salivary gland cancer (SGC). SUBJECTS AND METHODS SGC patients with (sec-SGC) and without (one-SGC) a previous cancer from the SEER database were identified. Cox proportional hazards regression (CoxPH) models were used to compare the prognosis between sec-SGC and one-SGC patients. Subgroup analyses for sec-SGC patients by gender, previous cancer types, previous cancer histology, and cancer diagnosis interval (CDI) were performed. Two CoxPH models were constructed to distinguish sec-SGC patients with different prognostic risks. RESULTS 9098 SGC patients were enrolled. Overall, sec-SGC patients (adjusted HR [aHR] = 1.26, p < 0.001), especially those with a CDI ≤ 5 years (aHR = 1.47, p < 0.001), had worse overall survival (OS) than one-SGC patients. In subgroup analysis, only sec-SGC patients with a previous head and neck cancer who were female (aHR = 2.38, p = 0.005), with a CDI ≤ 5 years (aHR = 1.65, p = 0.007) or with a previous squamous cell carcinoma (aHR = 6.52, p < 0.001) had worse OS. Our models successfully differentiated all sec-SGC patients into high-, intermediate- and low-risk groups with different prognosis. CONCLUSIONS Sec-SGC patients with different previous cancer types, gender, CDI and previous cancer histology had varied prognosis. The models we constructed could help differentiate the prognosis of sec-SGC patients with different risks.
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Affiliation(s)
- Junhong Li
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Yufang Rao
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaoyu Wang
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Libo Yu
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Ke Qiu
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Minzi Mao
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Yao Song
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Wendu Pang
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Danni Cheng
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Yuyang Zhang
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Lan Feng
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Xinyi Wang
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiuli Shao
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | - Yaxin Luo
- Department of Epidemiology and Biostatistics, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Yongbo Zheng
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
| | | | | | - Wei Xu
- Department of Biostatistics, Princess Margaret Cancer Centre and Dalla Lana School of Public Health, Toronto, Ontario, Canada
| | - Yu Zhao
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
| | - Jianjun Ren
- Department of Oto-Rhino-Laryngology, West China Hospital, Sichuan University, Chengdu, China
- West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China
- Department of Oto-Rhino-Laryngology, Langzhong People's Hospital, Langzhong, China
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He Q, Xiong Y, Xia P, Yang X, Yu Y, Chen Z. Predicting cancer-specific mortality in T1/2 hepatocellular carcinoma after radiofrequency ablation by competing risk nomogram: A population-based analysis. Clin Res Hepatol Gastroenterol 2024; 48:102283. [PMID: 38219821 DOI: 10.1016/j.clinre.2024.102283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2023] [Revised: 01/04/2024] [Accepted: 01/10/2024] [Indexed: 01/16/2024]
Abstract
BACKGROUND Radiofrequency ablation (RFA) is one of the primary treatment methods for T1/2 hepatocellular carcinoma (HCC), but the risk factors after RFA remain controversial. This study aims to identify the key factors associated with cancer-specific mortality (CSM) in patients with T1/2 HCC after RFA using competing risk analysis and to establish a prognostic nomogram for improved clinical management. METHODS A total of 2,135 T1/2 HCC patients treated with RFA were obtained from the Surveillance, Epidemiology, and End Results (SEER) database and randomly categorized into training and validation sets. Univariate and multivariable competing risk analyses were performed to identify risk factors associated with CSM and construct a competing risk nomogram. Receiver operating characteristic (ROC) curves, concordance indices (C-indexes), calibration plots, and decision curve analysis (DCA) were conducted to evaluate the predictive efficiency and clinical applicability of the nomogram in the training and validation sets. Patients were stratified according to their nomogram score, and the different risk groups were compared using cumulative incidence function (CIF) curves and Gray's validation . RESULTS The 5-year CSM rate for HCC patients treated with RFA was 30.1 %. Grade, tumor size, tumor number, cirrhosis, and AFP level were identified as independent risk factors for CSM. A prognostic nomogram was developed based on these risk factors. The time-dependent C-indexes (0.65) were greater than those of the AJCC stage model (0.55) during the 12 to 60 months of follow-up. The calibration plots of the competing risk nomograms demonstrated excellent consistency between actual survival and nomogram predictions. ROC analyses showed that the 1-, 3-, and 5-year AUC values in both the training and validation cohorts were all greater than 0.63 and exceeded those of the AJCC stage model. DCA demonstrated the clinical usefulness of the nomogram. Patients were classified into low-, moderate-, and high-risk groups based on the nomogram scores, with the high-risk group showing significantly higher CSM rates after RFA compared to the other two groups. CONCLUSIONS We identified Grade, AFP, cirrhosis, tumor size, and tumor number as independent risk factors associated with CSM. The competing risk nomogram exhibited high performance in predicting the probability of CSM for HCC patients undergoing RFA.
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Affiliation(s)
- Qifan He
- Department of Radiology, Haining People's Hospital, Jiaxing, Zhejiang, China
| | - Yue Xiong
- Department of Radiology, Haining People's Hospital, Jiaxing, Zhejiang, China
| | - Pengcheng Xia
- Department of Radiology, Haining People's Hospital, Jiaxing, Zhejiang, China
| | - Xiaoyu Yang
- Department of Radiology, Haining People's Hospital, Jiaxing, Zhejiang, China
| | - Yihui Yu
- Department of Radiology, Haining People's Hospital, Jiaxing, Zhejiang, China
| | - Zhonghua Chen
- Department of Radiology, Haining People's Hospital, Jiaxing, Zhejiang, China.
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Zhu R, Gong Z, Dai Y, Shen W, Zhu H. A novel postoperative nomogram and risk classification system for individualized estimation of survival among patients with parotid gland carcinoma after surgery. J Cancer Res Clin Oncol 2023; 149:15127-15141. [PMID: 37633867 DOI: 10.1007/s00432-023-05303-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 08/15/2023] [Indexed: 08/28/2023]
Abstract
BACKGROUND Parotid gland carcinoma (PGC) is a rare but aggressive head and neck cancer, and the prognostic model associated with survival after surgical resection has not yet been established. This study aimed to construct a novel postoperative nomogram and risk classification system for the individualized prediction of overall survival (OS) among patients with resected PGC. METHODS Patients with PGC who underwent surgery between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were randomized into training and validation cohorts (7:3). A nomogram developed using independent prognostic factors based on the results of the multivariate Cox regression analysis. Harrell's concordance index (C-index), time-dependent area under the curve (AUC), and calibration plots were used to validate the performance of the nomogram. Moreover, decision curve analysis (DCA) was performed to compare the clinical use of the nomogram with that of traditional TNM staging. RESULTS In this study, 5077 patients who underwent surgery for PGC were included. Age, sex, marital status, tumor grade, histology, TNM stage, surgery type, radiotherapy, and chemotherapy were independent prognostic factors. Based on these independent factors, a postoperative nomogram was developed. The C-index of the proposed nomogram was 0.807 (95% confidence interval 0.797-0.817). Meanwhile, the time-dependent AUC (> 0.8) indicated that the nomogram had a satisfactory discriminative ability. The calibration curves showed good concordance between the predicted and actual probabilities of OS, and DCA curves indicated that the nomogram had a better clinical application value than the traditional TNM staging. Moreover, a risk classification system was built that could perfectly classify patients with PGC into three risk groups. CONCLUSIONS This study constructed a novel postoperative nomogram and corresponding risk classification system to predict the OS of patients with PGC after surgery. These tools can be used to stratify patients with high or low risk of mortality and provide high-risk patients with more directed therapies and closer follow-up.
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Affiliation(s)
- Runqiu Zhu
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79# Qingchun Road, Hangzhou, 310003, Zhejiang Province, People's Republic of China
- Zhejiang University School of Medicine, Hangzhou, 310058, People's Republic of China
| | - Zhiyuan Gong
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79# Qingchun Road, Hangzhou, 310003, Zhejiang Province, People's Republic of China
- Zhejiang University School of Medicine, Hangzhou, 310058, People's Republic of China
| | - Yuwei Dai
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79# Qingchun Road, Hangzhou, 310003, Zhejiang Province, People's Republic of China
- Zhejiang University School of Medicine, Hangzhou, 310058, People's Republic of China
| | - Wenyi Shen
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79# Qingchun Road, Hangzhou, 310003, Zhejiang Province, People's Republic of China
- Zhejiang University School of Medicine, Hangzhou, 310058, People's Republic of China
| | - Huiyong Zhu
- Department of Oral and Maxillofacial Surgery, The First Affiliated Hospital, Zhejiang University School of Medicine, 79# Qingchun Road, Hangzhou, 310003, Zhejiang Province, People's Republic of China.
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Fang Q, Cai G, Chen G, Xu X, Zeng H, He Y, Cai S, Wu H. A competing risk-based nomogram to predict cancer-specific survival in patients with retroperitoneal leiomyosarcoma. Heliyon 2023; 9:e16867. [PMID: 37313148 PMCID: PMC10258490 DOI: 10.1016/j.heliyon.2023.e16867] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2023] [Revised: 05/31/2023] [Accepted: 05/31/2023] [Indexed: 06/15/2023] Open
Abstract
Considering the rarity and aggressive nature of retroperitoneal leiomyosarcoma (RLMS), several prognostic factors might contribute to the cancer-specific mortality of these patients. This study aimed to construct a competing risk-based nomogram to predict cancer-specific survival (CSS) for patients with RLMS. In total, 788 cases from the Surveillance, Epidemiology, and End Results (SEER) database (2000-2015) were included. Based on the Fine & Gray's method, independent predictors were screened to develop a nomogram for predicting 1-, 3-, and 5-year CSS. After multivariate analysis, CSS was found significantly associated with tumor characteristics (tumor grade, size, range), as well as surgery status. The nomogram showed solid prediction power and was well calibrated. Through decision curve analysis (DCA), a favorable clinical utility of the nomogram was demonstrated. Additionally, a risk stratification system was developed and distinctive survival between risk groups was observed. In summary, this nomogram showed a better performance than the AJCC 8th staging system and can assist in the clinical management of RLMS.
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Tang L, Zhang L, Zeng Y, Li Y. Competing risk nomogram for predicting cancer-specific mortality in patients with non-melanoma skin cancer. J Cancer Res Clin Oncol 2023:10.1007/s00432-023-04826-8. [PMID: 37142808 DOI: 10.1007/s00432-023-04826-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 04/28/2023] [Indexed: 05/06/2023]
Abstract
PURPOSE This study aimed to assess the cumulative incidences of Non-melanoma skin cancer (NMSC)-specific mortality (NMSC-SM) and develop a competing risk nomogram for NMSC-SM. METHODS Data on patients diagnosed with NMSC between 2010 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. To identify the independent prognostic factors, univariate and multivariate competing risk models were used, and a competing risk model was constructed. Based on the model, we developed a competing risk nomogram to predict the 1-, 3-, 5-, and 8-year cumulative probabilities of NMSC-SM. The precision and ability to discriminate of the nomogram were evaluated through the utilization of metrics, such as receiver-operating characteristic (ROC) area under the curve (AUC), concordance index (C-index), and a calibration curve. Decision curve analysis (DCA) was employed to assess the clinical usefulness of the nomogram. RESULTS Race, age, the primary site of the tumor, tumor grade, size, histological type, summary stage, stage group, order of radiation and surgery, and bone metastases were identified as independent risk factors. The prediction nomogram was constructed using the variables mentioned above. The ROC curves implied the good discrimination ability of the predictive model. The nomogram's C-index was 0.840 and 0.843 in the training and validation sets, respectively, and the calibration plots were well fitted. In addition, the competing risk nomogram demonstrated good clinical usefulness. CONCLUSION The competing risk nomogram displayed excellent discrimination and calibration for predicting NMSC-SM, which can be used in clinical contexts to help guide treatment decisions.
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Affiliation(s)
- Lei Tang
- Outpatient Office, The Fourth Hospital of Changsha, Changsha, Hunan, China
| | - Le Zhang
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Yi Zeng
- Department of Geriatrics, Second Xiangya Hospital, Central South University, Changsha, Hunan, China
| | - Ye Li
- National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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