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Gao S, Huang Q, Wei S, Lv Y, Xie Y, Hao Y. Prognostic nomogram based on pre-treatment HALP score for patients with advanced non-small cell lung cancer. Clinics (Sao Paulo) 2024; 79:100371. [PMID: 38735175 PMCID: PMC11101934 DOI: 10.1016/j.clinsp.2024.100371] [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: 08/20/2023] [Revised: 03/27/2024] [Accepted: 04/17/2024] [Indexed: 05/14/2024] Open
Abstract
BACKGROUND To explore the correlation of pre-treatment Hemoglobin-Albumin-Lymphocyte-Platelet (HALP) score with the prognosis of patients with advanced Non-Small Cell Lung Cancer (NSCLC) undergoing first-line conventional platinum-based chemotherapy. METHODS In this retrospective cohort study, 203 patients with advanced NSCLC were recruited from January 2017 to December 2021. The cut-off value for the HALP score was determined by Receiver Operating Characteristic (ROC) curve analysis. The baseline characteristics and blood parameters were recorded, and the Log-rank test and Kaplan-Meier curves were applied for the survival analysis. In the univariate and multivariate analyses, the Cox regression analysis was carried out. The predictive accuracy and discriminative ability of the nomogram were determined by the Concordance index (C-index) and calibration curve and compared with a single HALP score by ROC curve analysis. RESULTS The optimal cut-off value for the HALP score was 28.02. The lower HALP score was closely associated with poorer Progression-Free Survival (PFS) and Overall Survival (OS). The male gender and other pathological types were associated with shorter OS. Disease progression and low HALP were correlated with shorter OS and PFS. In addition, nomograms were established based on HALP scores, gender, pathology type and efficacy rating, and used to predict OS. The C-index for OS prediction was 0.7036 (95% CI 0.643 to 0.7643), which was significantly higher than the C-index of HALP at 6-, 12-, and 24-months. CONCLUSION The HALP score is associated with the prognosis of advanced NSCLC patients receiving conventional platinum-based chemotherapy, and the nomogram established based on the HALP score has a better predictive capability for OS.
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Affiliation(s)
- Shan Gao
- Medical Oncology Division 1, Clinical Oncology Center, People' s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China; The First Clinical Medical College, Jinan University, Guangzhou, Guangdong, China
| | - Qin Huang
- Department of Oncology and Chemotherapy, Yulin Red Cross Hospital, Yulin, Guangxi, China
| | - Suosu Wei
- Department of Scientific Cooperation of Guangxi Academy of Medical Sciences, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Yanru Lv
- Department of Scientific Cooperation of Guangxi Academy of Medical Sciences, People's Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Yanyan Xie
- Medical Oncology Division 1, Clinical Oncology Center, People' s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China
| | - Yanrong Hao
- Medical Oncology Division 1, Clinical Oncology Center, People' s Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi, China.
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Guo XW, Ji L, Xi XX, Zhao WW, Liu YC, Zhou SB, Ji SJ. Predictive potential of preoperative Naples prognostic score-based nomogram model for the prognosis in surgical resected thoracic esophageal squamous cell carcinoma patients: A retrospective cohort study. Medicine (Baltimore) 2024; 103:e38038. [PMID: 38701277 PMCID: PMC11062709 DOI: 10.1097/md.0000000000038038] [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: 10/10/2023] [Accepted: 04/05/2024] [Indexed: 05/05/2024] Open
Abstract
The present study aimed to establish an effective prognostic nomogram model based on the Naples prognostic score (NPS) for resectable thoracic esophageal squamous cell carcinoma (ESCC). A total of 277 patients with ESCC, who underwent standard curative esophagectomy and designated as study cohort, were retrospectively analyzed. The patients were divided into different groups, including NPS 0, NPS 1, NPS 2, and NPS 3 or 4 groups, for further analysis, and the results were validated in an external cohort of 122 ESCC patients, who underwent surgery at another cancer center. In our multivariate analysis of the study cohort showed that the tumor-node-metastasis (TNM) stage, systemic inflammation score, and NPS were the independent prognostic factors for the overall survival (OS) and progression-free survival (PFS) durations. In addition, the differential grade was also an independent prognostic factor for the OS in the patients with ESCC after surgery (all P < .05). The area under the curve of receiver operator characteristics for the PFS and OS prediction with systemic inflammation score and NPS were 0.735 (95% confidence interval [CI] 0.676-0.795, P < .001) and 0.835 (95% CI 0.786-0.884, P < .001), and 0.734 (95% CI 0.675-0.793, P < .001) and 0.851 (95% CI 0.805-0.896, P < .001), respectively. The above independent predictors for OS or PFS were all selected in the nomogram model. The concordance indices (C-indices) of the nomogram models for predicting OS and PFS were 0.718 (95% CI 0.681-0.755) and 0.669 (95% CI 0.633-0.705), respectively, which were higher than that of the 7th edition of American Joint Committee on Cancer TNM staging system [C-index 0.598 (95% CI 0.558-0.638) for OS and 0.586 (95% CI 0.546-0.626) for PFS]. The calibration curves for predicting the 5-year OS or PFS showed a good agreement between the prediction by nomogram and actual observation. In the external validation cohort, the nomogram discrimination for OS was better than that of the 7th edition of TNM staging systems [C-index: 0.697 (95% CI 0.639-0.755) vs 0.644 (95% CI 0.589-0.699)]. The calibration curves showed good consistency in predicting the 5-year survival between the actual observation and nomogram predictions. The decision curve also showed a higher potential of the clinical application of predicting the 5-years OS of the proposed nomogram model as compared to that of the 7th edition of TNM staging systems. The preoperative NPS-based nomogram model had a certain potential role for predicting the prognosis of ESCC patients.
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Affiliation(s)
- Xin-Wei Guo
- Department of Radiation Oncology, Affiliated Taixing People’s Hospital of Nanjing Medical University, Kangda College, Taixing, People’s Republic of China
| | - Lei Ji
- Department of Radiation Oncology, The First Affiliated Hospital of Soochow University, Suzhou, People’s Republic of China
| | - Xiao-Xiang Xi
- Department of Thoracic Surgery, Affiliated Taixing People’s Hospital of Nanjing Medical University, Kangda College, Taixing, People’s Republic of China
| | - Wei-Wei Zhao
- Department of Radiation Oncology, Affiliated Taixing People’s Hospital of Nanjing Medical University, Kangda College, Taixing, People’s Republic of China
| | - Yang-Chen Liu
- Department of Radiation Oncology, Affiliated Taixing People’s Hospital of Nanjing Medical University, Kangda College, Taixing, People’s Republic of China
| | - Shao-Bing Zhou
- Department of Radiation Oncology, Affiliated Taixing People’s Hospital of Nanjing Medical University, Kangda College, Taixing, People’s Republic of China
| | - Sheng-Jun Ji
- Department of Radiotherapy and Oncology, The Affiliated Suzhou Hospital of Nanjing Medical University, Gusu School, Nanjing Medical University, Suzhou, People’s Republic of China
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Deng X, Yang X, Bu M, Tang A, Zhang H, Long L, Zeng Z, Wang Y, Chen P, Jiang M, Chen BT. Nomogram for prediction of hearing rehabilitation outcome in children with congenital sensorineural hearing loss after cochlear implantation. Heliyon 2024; 10:e29529. [PMID: 38699755 PMCID: PMC11063407 DOI: 10.1016/j.heliyon.2024.e29529] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 04/08/2024] [Accepted: 04/09/2024] [Indexed: 05/05/2024] Open
Abstract
Background Reliable predictors for rehabilitation outcomes in patients with congenital sensorineural hearing loss (CSNHL) after cochlear implantation (CI) are lacking. The purchase of this study was to develop a nomogram based on clinical characteristics and neuroimaging features to predict the outcome in children with CSNHL after CI. Methods Children with CSNHL prior to CI surgery and children with normal hearing were enrolled into the study. Clinical data, high resolution computed tomography (HRCT) for ototemporal bone, conventional brain MRI for structural analysis and brain resting-state fMRI (rs-fMRI) for the power spectrum assessment were assessed. A nomogram combining both clinical and imaging data was constructed using multivariate logistic regression analysis. Model performance was evaluated and validated using bootstrap resampling. Results The final cohort consisted of 72 children with CSNHL (41 children with poor outcome and 31 children with good outcome) and 32 healthy controls. The white matter lesion from structural assessment and six power spectrum parameters from rs-fMRI, including Power4, Power13, Power14, Power19, Power23 and Power25 were used to build the nomogram. The area under the receiver operating characteristic (ROC) curve of the nomogram obtained using the bootstrapping method was 0.812 (95 % CI = 0.772-0.836). The calibration curve showed no statistical difference between the predicted value and the actual value, indicating a robust performance of the nomogram. The clinical decision analysis curve showed a high clinical value of this model. Conclusions The nomogram constructed with clinical data, and neuroimaging features encompassing ototemporal bone measurements, white matter lesion values from structural brain MRI and power spectrum data from rs-fMRI showed a robust performance in predicting outcome of hearing rehabilitation in children with CSNHL after CI.
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Affiliation(s)
- Xi Deng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Xueqing Yang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Meiru Bu
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Anzhou Tang
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Huiting Zhang
- MR Research Collaboration, Siemens Healthineers Ltd., 430000, Wuhan, PR China
| | - Liling Long
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Zisan Zeng
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Yifeng Wang
- Institute of Brain and Psychological Sciences, Sichuan Normal University, No. 5, Jing'an Road, Chengdu, 610066, Sichuan, PR China
| | - Ping Chen
- Department of Otorhinolaryngology Head and Neck Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Muliang Jiang
- Department of Radiology, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, 530021, Guangxi, PR China
| | - Bihong T. Chen
- Department of Diagnostic Radiology, City of Hope National Medical Center, 1500 E, Duarte, CA, 91010, USA
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Chen R, Zhu L, Zhang Y, Cui D, Chen R, Guo H, Peng L, Xiao C. Predicting the unpredictable: a robust nomogram for predicting recurrence in patients with ampullary carcinoma. BMC Cancer 2024; 24:212. [PMID: 38360582 PMCID: PMC10870520 DOI: 10.1186/s12885-024-11960-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 02/05/2024] [Indexed: 02/17/2024] Open
Abstract
OBJECTIVE To screen the risk factors affecting the recurrence risk of patients with ampullary carcinoma (AC)after radical resection, and then to construct a model for risk prediction based on Lasso-Cox regression and visualize it. METHODS Clinical data were collected from 162 patients that received pancreaticoduodenectomy treatment in Hebei Provincial Cancer Hospital from January 2011 to January 2022. Lasso regression was used in the training group to screen the risk factors for recurrence. The Lasso-Cox regression and Random Survival Forest (RSF) models were compared using Delong test to determine the optimum model based on the risk factors. Finally, the selected model was validated using clinical data from the validation group. RESULTS The patients were split into two groups, with a 7:3 ratio for training and validation. The variables screened by Lasso regression, such as CA19-9/GGT, AJCC 8th edition TNM staging, Lymph node invasion, Differentiation, Tumor size, CA19-9, Gender, GPR, PLR, Drinking history, and Complications, were used in modeling with the Lasso-Cox regression model (C-index = 0.845) and RSF model (C-index = 0.719) in the training group. According to the Delong test we chose the Lasso-Cox regression model (P = 0.019) and validated its performance with time-dependent receiver operating characteristics curves(tdROC), calibration curves, and decision curve analysis (DCA). The areas under the tdROC curves for 1, 3, and 5 years were 0.855, 0.888, and 0.924 in the training group and 0.841, 0.871, and 0.901 in the validation group, respectively. The calibration curves performed well, as well as the DCA showed higher net returns and a broader range of threshold probabilities using the predictive model. A nomogram visualization is used to display the results of the selected model. CONCLUSION The study established a nomogram based on the Lasso-Cox regression model for predicting recurrence in AC patients. Compared to a nomogram built via other methods, this one is more robust and accurate.
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Affiliation(s)
- Ruiqiu Chen
- Medical School of Chinese PLA, Beijing, China
- Faculty of Hepato-Biliary-Pancreatic Surgery, the First Medical Centre, Chinese People s Liberation Army (PLA) General Hospital, Beijing, China
- The First School of Clinical Medicine, Lanzhou University, No. 1, Donggangxi Rd, Chengguan District, 730000, Lanzhou, Gansu, China
| | - Lin Zhu
- Medical School of Chinese PLA, Beijing, China
- Faculty of Hepato-Biliary-Pancreatic Surgery, the First Medical Centre, Chinese People s Liberation Army (PLA) General Hospital, Beijing, China
- The First School of Clinical Medicine, Lanzhou University, No. 1, Donggangxi Rd, Chengguan District, 730000, Lanzhou, Gansu, China
| | - Yibin Zhang
- Department of Hepatobiliary Surgery, Zhongshan Hospital of Xiamen University, Xiamen, Fujian, China
| | - Dongyu Cui
- The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | | | - Hao Guo
- The Fourth Hospital of Hebei Medical University, Shijiazhuang, China
| | - Li Peng
- The Fourth Hospital of Hebei Medical University, Shijiazhuang, China.
| | - Chaohui Xiao
- Faculty of Hepato-Biliary-Pancreatic Surgery, the First Medical Centre, Chinese People s Liberation Army (PLA) General Hospital, Beijing, China.
- Key Laboratory of Digital Hepatobiliary Surgery PLA, Beijing, China.
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Bai J, Huang M, Zhou J, Song B, Hua J, Ding R. Development of a predictive nomogram for postembolization syndrome after transcatheter arterial chemoembolization of hepatocellular carcinoma. Sci Rep 2024; 14:3303. [PMID: 38332011 PMCID: PMC10853204 DOI: 10.1038/s41598-024-53711-y] [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: 09/04/2023] [Accepted: 02/04/2024] [Indexed: 02/10/2024] Open
Abstract
Post-embolization syndrome (PES) is a frequent complication after receiving transcatheter arterial chemoembolization (TACE) in patients with hepatocellular carcinoma (HCC), but only a few studies have focused on the factors influencing PES in those patients. In this study, the impact factors of PES were explored and a nomogram was constructed to predict the occurrence of PES in HCC patients with TACE. This was a retrospective cohort study of HCC patients who underwent TACE obtained from the third affiliated Hospital of Kunming Medical University between January 1, 2020, and September 1, 2022. T‑test and Chi‑square test were used to search for factors influencing PES occurrence, and then the nomogram was further established based on multivariable logistic regression analysis. Validation of the predictive nomogram was also evaluated by calibration curve, concordance index (C-index), and receiver operating characteristic (ROC) curves. The enrolled patients (n = 258) were randomly assigned to the primary cohort (n = 180) and validation cohort (n = 78) in a 7:3 ratio. Among 180 patients in the primary cohort, 106 (58.89%) experienced PES. TACE types (P = 0.015), embolization degree (P = 0.008), and tumor number (P = 0.026) were identified as predictors by the logistic regression analysis and were used to develop the predictive nomogram. The internally validated and externally validated C-indexes were 0.713 and 0.703, respectively. The calibration curves presented good consistency between actual and predictive survival. Types of embolic agents, embolization degree, and tumor number were found to be the predictors of PES after TACE. The nomogram could reliably predict PES in HCC patients with TACE. This predictive model might be considered for clinical practice.
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Affiliation(s)
- Jinfeng Bai
- Minimally Invasive Intervention Department, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | - Ming Huang
- Minimally Invasive Intervention Department, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | - Jinmei Zhou
- Minimally Invasive Intervention Department, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | - Bohan Song
- Minimally Invasive Intervention Department, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | - Jianjie Hua
- Minimally Invasive Intervention Department, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | - Rong Ding
- Minimally Invasive Intervention Department, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China.
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Luo J, Zhu WC, Chen QX, Yang CF, Huang BJ, Zhang SJ. A prognostic model based on DNA methylation-related gene expression for predicting overall survival in hepatocellular carcinoma. Front Oncol 2024; 13:1171932. [PMID: 38304027 PMCID: PMC10830715 DOI: 10.3389/fonc.2023.1171932] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 12/27/2023] [Indexed: 02/03/2024] Open
Abstract
Background Hepatocellular carcinoma (HCC) continues to increase in morbidity and mortality among all types of cancer. DNA methylation, an important epigenetic modification, is associated with cancer occurrence and progression. The objective of this study was to establish a model based on DNA methylation risk scores for identifying new potential therapeutic targets in HCC and preventing cancer progression. Methods Transcriptomic, clinical, and DNA methylation data on 374 tumor tissues and 50 adjacent normal tissues were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma database. The gene expression profiles of the GSE54236 liver cancer dataset, which contains data on 161 liver tissue samples, were obtained from the Gene Expression Omnibus database. We analyzed the relationship between DNA methylation and gene expression levels after identifying the differentially methylated and expressed genes. Then, we developed and validated a risk score model based on the DNA methylation-driven genes. A tissue array consisting of 30 human hepatocellular carcinoma samples and adjacent normal tissues was used to assess the protein and mRNA expression levels of the marker genes by immunohistochemistry and qRT-PCR, respectively. Results Three methylation-related differential genes were identified in our study: GLS, MEX3B, and GNA14. The results revealed that their DNA methylation levels were negatively correlated with local gene expression regulation. The gene methylation levels correlated strongly with the prognosis of patients with liver cancer. This was confirmed by qRT-PCR and immunohistochemical verification of the expression of these genes or proteins in tumors and adjacent tissues. These results revealed the relationship between the level of relevant gene methylation and the prognosis of patients with liver cancer as well as the underlying cellular and biological mechanisms. This allows our gene signature to provide more accurate and appropriate predictions for clinical applications. Conclusion Through bioinformatics analysis and experimental validation, we obtained three DNA methylation marker: GLS, MEX3B, and GNA14. This helps to predict the prognosis and may be a potential therapeutic target for HCC patients.
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Affiliation(s)
- Jin Luo
- Department of Traditional Chinese Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
- Department of Traditional Chinese Medicine, Shenzhen Children’s Hospital, Shenzhen, Guangdong, China
| | - Wan-Cui Zhu
- State Key Laboratory of Oncology in South China, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Qiu-Xia Chen
- Department of Traditional Chinese Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Chang-Fu Yang
- Department of Oncology, The People’s Hospital of Gaozhou, Gaozhou, China
| | - Bi-Jun Huang
- Department of Experimental Research, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Shi-Jun Zhang
- Department of Traditional Chinese Medicine, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
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Shi J, Fan Y, Long J, Zhang S, Zhang Z, Tang J, Chen W, Liu S. Development and Validation of Nomograms to Predict Risk and Prognosis in Salivary Gland Carcinoma Patient with Distant Metastases. EAR, NOSE & THROAT JOURNAL 2023:1455613231212060. [PMID: 38044557 DOI: 10.1177/01455613231212060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2023] Open
Abstract
Background: Salivary gland carcinoma (SGC) patients with distant metastasis (DM) are rare, and understanding this disease is insufficient. Nomograms can predict the prognostic probability of patients, while few studies have examined diagnostic and prognostic factors in SGC patients with DM. The purpose of this study was to establish and validate the risk and prognostic nomograms of SGC patients with DM. Methods: Based on the SEER database, we analyzed the data of SGC patients between 2004 and 2015. Logistic regression analyses and Cox proportional hazards regression analyses were used to identify risk and prognostic factors for DM in SGC patients. Based on the Akaike information criterion (AIC) value and likelihood ratio test, the best-fitting model was selected to build risk and prognostic nomograms, and the results were evaluated by receiver operating characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and Kaplan-Meier (K-M) survival curves. ROC curves were also used to compare the nomograms with the American Joint Committee on Cancer (AJCC) staging system. Results: 7418 SGC patients were included in the study, and 307 (4.14%) of them were diagnosed with DM. This study identified that there are variables (age ≥ 80, no-parotid gland primary site, histologic type of mucoepidermoid carcinoma and squamous cell carcinoma, T stage ≥ T2, N staged ≥ N1, histologic grade ≥ III, and tumor size ≥ 41 mm) associated with the occurrence of DM in SGC patients. Therefore, we constructed diagnostic and prognostic nomograms after incorporating these variables. ROC curves illustrated the better predictive efficacy of 2 nomograms over the AJCC staging system. DCA curves, calibration curves, and K-M survival curves showed that 2 nomograms can accurately predict the occurrence and prognosis of DM among SGC patients in training and validation sets. Conclusion: It was shown that the nomograms were highly discriminative in predicting the diagnosis and prognosis of SGC patients with DM, and could identify high-risk patients, thereby providing SGC patients with individualized treatment plans.
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Affiliation(s)
- Jiayu Shi
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Yunjian Fan
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jiazhen Long
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Shuqi Zhang
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Zhen Zhang
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Jin Tang
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Wenyue Chen
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
| | - Shuguang Liu
- Department of Oral and Maxillofacial Surgery, Stomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong Province, China
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Zhang D, Li L. Risk factors and prognostic models of lymph node metastatic hypopharyngeal squamous cell carcinoma. Eur Arch Otorhinolaryngol 2023; 280:5019-5029. [PMID: 37351665 DOI: 10.1007/s00405-023-08077-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 06/14/2023] [Indexed: 06/24/2023]
Abstract
PURPOSE To explore the risk factors for lymph node metastasis (LNM) and establish nomograms for predicting survival outcomes and assessing individual risk in patients with LNM and hypopharyngeal squamous carcinoma (HSCC). METHODS Clinical data of patients with HSCC were retrospectively reviewed. The study's primary endpoints were overall survival (OS) and disease-specific survival (DSS). Nomograms were established based on Cox regression analyses. The accuracy and calibration ability of the nomograms were evaluated using the C-index, area under the curve, calibration curves, and decision curve analysis. RESULTS Overall, 2888 patients were enrolled, and the LNM rate was 74.2%. Age ≤ 60 years, male sex, unmarried status, pyriform sinus location, grade III-IV, tumor larger than 4 cm, and advanced T stage increased the risk of LNM. In addition, LNM was a negative prognostic factor for OS and DSS. Ten variables were identified and incorporated into nomograms to estimate OS and DSS. Our nomograms outperformed the traditional staging system in training and validation cohorts. Patients were stratified into risk subgroups based on the OS- and DSS-nomogram scores. Patients in the high-risk subgroup had a higher risk of death and disease-specific mortality than those in the low- and intermediate-risk subgroups. CONCLUSIONS LNM worsens the prognosis of HSCC. This study identified the independent prognostic factors for HSCC with LNM and developed satisfactory OS- and DSS-monogram to provide individual prediction and risk classification for patients with this diagnosis.
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Affiliation(s)
- Di Zhang
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Pan jia yuan nan Road 17, Beijing, 100021, China
| | - Lixi Li
- Department of Medical Oncology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Chaoyang District, Pan jia yuan nan Road 17, Beijing, 100021, China.
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Liu N, Li D, Zhou Y, Zhang X, Liu S, Ma R. Development and validation of a prognostic nomogram for the renal relapse of lupus nephritis. Med Clin (Barc) 2023; 161:277-285. [PMID: 37414598 DOI: 10.1016/j.medcli.2023.03.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2022] [Revised: 03/09/2023] [Accepted: 03/15/2023] [Indexed: 07/08/2023]
Abstract
OBJECTIVES This study aims to assess the risk of relapse after complete remission (CR) and partial remission (PR), and to develop a prognostic nomogram predicting the probability in lupus nephritis (LN) patients. METHODS Data from patients with LN who had been in remission were collected as a training cohort. The prognostic factors were analyzed using the univariable and multivariable Cox model for the training group. A nomogram was then developed using significant predictors in multivariable analysis. Both discrimination and calibration were assessed by bootstrapping with 100 resamples. RESULTS A total of 247 participants were enrolled, including 108 in the relapse group and 139 in the no relapse group. In multivariate Cox analysis, Systemic Lupus Erythematosus Disease Activity Index (SLEDAI), erythrocyte sedimentation rate (ESR), complement 1q (C1q), and antiphospholipid (aPL), anti-Sm antibody were found to be significant for predicting relapse rates. The prognostic nomogram including the aforementioned factors effectively predicted 1- and 3-year probability of flare-free. Moreover, a favorable consistency between the predicted and actual survival probabilities was demonstrated using calibration curves. CONCLUSIONS High SLEDAI, ESR, and positive aPL, anti-Sm antibody are potential risk factors for LN flare, while high C1q can reduce its recurrence. The visualized model we established can help predict the relapse risk of LN and aid clinical decision-making for individual patients.
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Affiliation(s)
- Nanchi Liu
- Department of Nephrology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, PR China
| | - Dongchuan Li
- Department of Nephrology, The Eighth People's Hospital of Qingdao, Qingdao, Shandon 266000, PR China
| | - Yan Zhou
- Department of Nephrology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, PR China
| | - Xingjian Zhang
- Department of Nephrology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, PR China
| | - Shanshan Liu
- Department of Nephrology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, PR China
| | - Ruixia Ma
- Department of Nephrology, Affiliated Hospital of Qingdao University, Qingdao, Shandong 266003, PR China.
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Wang Z, Zhao Z, Li W, Bao X, Liu T, Yang X. A Nomogram for Predicting Progression-free Survival in Patients with Endometrial Cancer. Clin Oncol (R Coll Radiol) 2023; 35:e516-e527. [PMID: 37230875 DOI: 10.1016/j.clon.2023.05.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 02/25/2023] [Accepted: 05/05/2023] [Indexed: 05/27/2023]
Abstract
AIMS Endometrial cancer is one of the most widely known gynaecological malignancies that lacks a prognostic prediction model. This study aimed to develop a nomogram to predict progression-free survival (PFS) in patients with endometrial cancer. MATERIALS AND METHODS Information for endometrial cancer patients diagnosed and treated from 1 January 2005 to 30 June 2018 was collected. The Kaplan-Meier survival analysis and multivariate Cox regression analysis were carried out to determine the independent risk factors and a nomogram was constructed by R based on analytical factors. Internal and external validation were then carried out to predict the probability of 3- and 5-year PFS. RESULTS In total, 1020 patients with endometrial cancer were included in the study and the relationship between 25 factors and prognosis was analysed. Postmenopause (hazard ratio = 2.476, 95% confidence interval 1.023-5.994), lymph node metastasis (hazard ratio = 6.242, 95% confidence interval 2.815-13.843), lymphovascular space invasion (hazard ratio = 4.263, 95% confidence interval 1.802-10.087), histological type (hazard ratio = 2.713, 95% confidence interval 1.374-5.356), histological differentiation (hazard ratio = 2.601, 95% confidence interval 1.141-5.927) and parametrial involvement (hazard ratio = 3.596, 95% confidence interval 1.622-7.973) were found to be independent prognostic risk factors; these factors were selected to establish a nomogram. The consistency index for 3-year PFS were 0.88 (95% confidence interval 0.81-0.95) in the training cohort and 0.93 (95% confidence interval 0.87-0.99) in the verification set. The areas under the receiver operating characteristic curve for the 3- and 5-year PFS predictions are 0.891 and 0.842 in the training set; the same conclusion also appeared in the verification set [0.835 (3-year), 0.803(5-year)]. CONCLUSIONS This study established a prognostic nomogram for endometrial cancer that provides a more individualised and accurate estimation of PFS for patients, which will help physicians make follow-up strategies and risk stratification.
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Affiliation(s)
- Z Wang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China
| | - Z Zhao
- Department of Ultrasound, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan, China
| | - W Li
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China
| | - X Bao
- Department of Obstetrics and Gynecology, Weifang People's Hospital, Weifang, China
| | - T Liu
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China
| | - X Yang
- Department of Obstetrics and Gynecology, Qilu Hospital of Shandong University, Jinan, China.
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11
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Fu J, Du F, Tian T, Huang H, Zhang L, Li D, Liu Y, Zhang D, Gao L, Zheng T, Liu Y, Zhao Y. Development and validation of prognostic nomograms based on De Ritis ratio and clinicopathological features for patients with stage II/III colorectal cancer. BMC Cancer 2023; 23:620. [PMID: 37400788 DOI: 10.1186/s12885-023-11125-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 06/28/2023] [Indexed: 07/05/2023] Open
Abstract
BACKGROUND Metabolic derangements and systemic inflammation are related to the progression of colorectal cancer (CRC) and the prognoses of these patients. The survival of stage II and III CRC patients existed considerable heterogeneity highlighting the urgent need for new prediction models. This study aimed to develop and validate prognostic nomograms based on preoperative serum liver enzyme as well as evaluate the clinical utility. METHODS A total of 4014 stage II/III primary CRC patients pathologically diagnosed from January 2007 to December 2013 were included in this study. These patients were randomly divided into a training set (n = 2409) and a testing set (n = 1605). Univariate and multivariate Cox analyses were used to select the independent factors for predicting overall survival (OS) and disease-free survival (DFS) of stage II/III CRC patients. Next, nomograms were constructed and validated to predict the OS and DFS of individual CRC patients. The clinical utility of nomograms, tumor-node-metastasis (TNM), and the American Joint Committee on Cancer (AJCC) system was evaluated using time-dependent ROC and decision curve analyses. RESULTS Among seven preoperative serum liver enzyme markers, aspartate aminotransferase-to-alanine aminotransferase ratio (De Ritis ratio) was identified as an independent factor for predicting both OS and DFS of stage II/III CRC patients. The nomograms incorporated De Ritis ratio and significant clinicopathological features achieved good accuracy in terms of OS and DFS prediction, with C-index of 0.715 and 0.692, respectively. The calibration curve showed good agreement between prediction by nomogram and actual observation. The results of time-dependent ROC and decision curve analyses suggested that the nomograms had improved discrimination and greater clinical benefits compared with TNM and AJCC staging. CONCLUSIONS De Ritis ratio was an independent predictor in predicting both the OS and DFS of patients with stage II/III CRC. Nomograms based on De Ritis ratio and clinicopathological features showed better clinical utility, which is expected to help clinicians develop appropriate individual treatment strategies for patients with stage II /III CRC.
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Affiliation(s)
- Jinming Fu
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
- Department of Biostatistics, School of Public Health, Xuzhou Medical University, Xuzhou, 221004, China
| | - Fenqi Du
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University, 150 Haping Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Tian Tian
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Hao Huang
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Lei Zhang
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Dapeng Li
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Yupeng Liu
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Ding Zhang
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Lijing Gao
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Ting Zheng
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China
| | - Yanlong Liu
- Department of Colorectal Surgery, Harbin Medical University Cancer Hospital, Harbin Medical University, 150 Haping Road, Harbin, 150081, Heilongjiang Province, People's Republic of China.
| | - Yashuang Zhao
- Department of Epidemiology, College of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, Heilongjiang Province, People's Republic of China.
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Zhang Q, Huang MJ, Wang HY, Wu Y, Chen YZ. A novel prognostic nomogram for adult acute lymphoblastic leukemia: a comprehensive analysis of 321 patients. Ann Hematol 2023:10.1007/s00277-023-05267-6. [PMID: 37173535 DOI: 10.1007/s00277-023-05267-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2022] [Accepted: 05/06/2023] [Indexed: 05/15/2023]
Abstract
The cure rate of acute lymphoblastic leukemia (ALL) in adolescents and adults remains poor. This study aimed to establish a prognostic model for ≥14-year-old patients with ALL to guide treatment decisions. We retrospectively analyzed the data of 321 ALL patients between January 2017 and June 2020. Patients were randomly (2:1 ratio) divided into either the training or validation set. A nomogram was used to construct a prognostic model. Multivariate Cox analysis of the training set showed that age > 50 years, white blood cell count > 28.52×109/L, and MLL rearrangement were independent risk factors for overall survival (OS), while platelet count >37×109/L was an independent protective factor. The nomogram was established according to these independent prognostic factors in the training set, where patients were grouped into two categories: low-risk (≤13.15) and high-risk (>13.15). The survival analysis, for either total patients or sub-group patients, showed that both OS and progression-free survival (PFS) of low-risk patients was significantly better than that of high-risk patients. Moreover, treatment analysis showed that both OS and progression-free survival (PFS) of ALL with stem cell transplantation (SCT) were significantly better than that of ALL without SCT. Further stratified analysis showed that in low-risk patients, the OS and PFS of patients with SCT were significantly better than those of patients without SCT. In contrast, in high-risk patients, compared with non-SCT patients, receiving SCT can only significantly prolong the PFS, but it does not benefit the OS. We established a simple and effective prognostic model for ≥ 14-year-old patients with ALL that can provide accurate risk stratification and determine the clinical strategy.
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Affiliation(s)
- Qian Zhang
- Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
- Fujian Provincial Key Laboratory on Hematology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Mei-Juan Huang
- Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China
- Fujian Provincial Key Laboratory on Hematology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Han-Yu Wang
- Department of Cardiac Surgery, Union Hospital, Fujian Medical University, Fuzhou, Fujian, China
| | - Yong Wu
- Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China.
- Fujian Provincial Key Laboratory on Hematology, Fujian Medical University Union Hospital, Fuzhou, China.
| | - Yuan-Zhong Chen
- Fujian Institute of Hematology, Fujian Medical University Union Hospital, Fuzhou, China.
- Fujian Provincial Key Laboratory on Hematology, Fujian Medical University Union Hospital, Fuzhou, China.
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13
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Wang L, Peng JL, Wu JZ. Nomogram to predict the prognosis of patients with AFP-negative hepatocellular carcinoma undergoing chemotherapy: A SEER based study. Medicine (Baltimore) 2023; 102:e33319. [PMID: 37000113 PMCID: PMC10063275 DOI: 10.1097/md.0000000000033319] [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: 10/05/2022] [Revised: 01/27/2023] [Accepted: 02/27/2023] [Indexed: 04/01/2023] Open
Abstract
This study aimed to formulate reliable nomograms for predicting the outcomes of α-fetoprotein (AFP)-negative hepatocellular carcinoma (HCC) patients after chemotherapy. HCC patients with normal AFP expression who received chemotherapy were screened and evaluated from the surveillance, epidemiology, and end results database. The prognostic factors for predicting outcomes of HCC patients undergoing chemotherapy were chosen by analyzing the results of Cox analyses. Then, a nomogram integrating the prognostic factors was established. The discrimination ability of the nomogram was evaluated with computation of area under the curve (AUC) and calibration curve. A total of 2424 patients with AFP-negative HCC undergoing chemotherapy were identified. The median overall survival (OS) for HCC patients undergoing chemotherapy was 33 months. Age, race, pathologic grade, N stage, M stage, surgery, and lung metastases were significantly linked to OS. These relevant factors were incorporated into the nomogram. AUC values of the prognostic nomogram for 3- and 5-year OS were 0.696 and 0.706 in the training groups, which were superior to those of the tumor node metastasis (TNM) stage (0.641 and 0.671) in training groups. The calibration curves indicated a high consistency between the predicted probability of nomograms and the actual observation. The validation groups produced AUC values of 0.674 and 0.736 for 3- and 5-year OS, which were superior to those of the TNM stage (0.601 and 0.637) in validation groups. The results revealed significantly unfavorable OS in the high-risk group (P < .001). Nomograms to accurately predict the OS for AFP-negative HCC patients after chemotherapy were established and exhibited a more accurate predication than the conventional TNM staging system.
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Affiliation(s)
- Lei Wang
- Department of Rehabilitation Medicine, Hunan Provincial People’s Hospital, The First Affiliated Hospital of Hunan Normal University, Changsha, People’s Republic of China
| | - Jin-Lin Peng
- Department of Gastroenterology, Tongji Hospital, Tongji Medical College, Huazhong University of Science & Technology, Wuhan, People’s Republic of China
| | - Ji-Zhou Wu
- The First Affiliated Hospital of Guangxi Medical University, Nanning, People’s Republic of China
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Shi H, Li X, Chen Z, Jiang W, Dong S, He R, Zhou W. Nomograms for Predicting the Risk and Prognosis of Liver Metastases in Pancreatic Cancer: A Population-Based Analysis. J Pers Med 2023; 13:jpm13030409. [PMID: 36983591 PMCID: PMC10056156 DOI: 10.3390/jpm13030409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Revised: 02/11/2023] [Accepted: 02/21/2023] [Indexed: 03/03/2023] Open
Abstract
The liver is the most prevalent location of distant metastasis for pancreatic cancer (PC), which is highly aggressive. Pancreatic cancer with liver metastases (PCLM) patients have a poor prognosis. Furthermore, there is a lack of effective predictive tools for anticipating the diagnostic and prognostic techniques that are needed for the PCLM patients in current clinical work. Therefore, we aimed to construct two nomogram predictive models incorporating common clinical indicators to anticipate the risk factors and prognosis for PCLM patients. Clinicopathological information on pancreatic cancer that referred to patients who had been diagnosed between the years of 2004 and 2015 was extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression analyses and a Cox regression analysis were utilized to recognize the independent risk variables and independent predictive factors for the PCLM patients, respectively. Using the independent risk as well as prognostic factors derived from the multivariate regression analysis, we constructed two novel nomogram models for predicting the risk and prognosis of PCLM patients. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve, the consistency index (C-index), and the calibration curve were then utilized to establish the accuracy of the nomograms’ predictions and their discriminability between groups. Using a decision curve analysis (DCA), the clinical values of the two predictors were examined. Finally, we utilized Kaplan–Meier curves to examine the effects of different factors on the prognostic overall survival (OS). As many as 1898 PCLM patients were screened. The patient’s sex, primary site, histopathological type, grade, T stage, N stage, bone metastases, lung metastases, tumor size, surgical resection, radiotherapy, and chemotherapy were all found to be independent risks variables for PCLM in a multivariate logistic regression analysis. Using a multivariate Cox regression analysis, we discovered that age, histopathological type, grade, bone metastasis, lung metastasis, tumor size, and surgery were all independent prognostic variables for PCLM. According to these factors, two nomogram models were developed to anticipate the prognostic OS as well as the risk variables for the progression of PCLM in PCLM patients, and a web-based version of the prediction model was constructed. The diagnostic nomogram model had a C-index of 0.884 (95% CI: 0.876–0.892); the prognostic model had a C-index of 0.686 (95% CI: 0.648–0.722) in the training cohort and a C-index of 0.705 (95% CI: 0.647–0.758) in the validation cohort. Subsequent AUC, calibration curve, and DCA analyses revealed that the risk and predictive model of PCLM had high accuracy as well as efficacy for clinical application. The nomograms constructed can effectively predict risk and prognosis factors in PCLM patients, which facilitates personalized clinical decision-making for patients.
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Affiliation(s)
- Huaqing Shi
- Second College of Clinical Medicine, Lanzhou University, Lanzhou 730000, China
| | - Xin Li
- The First Clinical Medical College, Lanzhou University, Lanzhou 730030, China
| | - Zhou Chen
- The First Clinical Medical College, Lanzhou University, Lanzhou 730030, China
| | - Wenkai Jiang
- Second College of Clinical Medicine, Lanzhou University, Lanzhou 730000, China
| | - Shi Dong
- Second College of Clinical Medicine, Lanzhou University, Lanzhou 730000, China
| | - Ru He
- The First Clinical Medical College, Lanzhou University, Lanzhou 730030, China
| | - Wence Zhou
- Second College of Clinical Medicine, Lanzhou University, Lanzhou 730000, China
- Department of General Surgery, Lanzhou University Second Hospital, Lanzhou 730030, China
- Correspondence:
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Yan X, He Y, Jia M, Yang J, Huang K, Zhang P, Lai J, Chen M, Fan S, Li S, Fan Z, Teng H. Development of a Dynamic Nomogram for Predicting the Probability of Satisfactory Recovery after 6 Months for Cervical Traumatic Spinal Cord Injury. Orthop Surg 2023; 15:1008-1020. [PMID: 36782280 PMCID: PMC10102307 DOI: 10.1111/os.13679] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 01/04/2023] [Accepted: 01/17/2023] [Indexed: 02/15/2023] Open
Abstract
OBJECTIVE Cervical traumatic spinal cord injury (CTSCI) is a seriously disabling disease that severely affects the physical and mental health of patients and imposes a huge economic burden on patients and their families. Accurate identification of the prognosis of CTSCI patients helps clinicians to design individualized treatment plans for patients. For this purpose, a dynamic nomogram was developed to predict the recovery of CTSCI patients after 6 months. METHODS We retrospectively included 475 patients with CTSCI in our institution between March 2013 and January 2022. The outcome variable of the current study was a satisfactory recovery of patients with CTSCI at 6 months. Univariate analyses and univariate logistic regression analyses were used to assess the factors affecting the prognosis of patients with CTSCI. Subsequently, variables (P < 0.05) were included in the multivariate logistic regression analysis to evaluate these factors further. Eventually, a nomogram model was constructed according to these independent risk factors. The concordance index (C-index) and the calibration curve were utilized to assess the model's predictive ability. The discriminating capacity of the prediction model was measured by the receiver operating characteristic (ROC) area under the curve (AUC). One hundred nine patients were randomly selected from 475 patients to serve as the center's internal validation test cohort. RESULTS The multivariate logistic regression model further screened out six independent factors that impact the recovery of patients with CTSCI. Including admission to the American Spinal Injury Association Impairment Scale (AIS) grade, the length of high signal in the spinal cord, maximum spinal cord compression (MSCC), spinal segment fractured, admission time, and hormonal therapy within 8 h after injury. A nomogram prediction model was developed based on the six independent factors above. In the training cohort, the AUC of the nomogram that included these predictors was 0.879, while in the test cohort, it was 0.824. The nomogram C-index incorporating these predictors was 0.872 in the training cohort and 0.813 in the test cohort, while the calibration curves for both cohorts also indicated good consistency. Furthermore, this nomogram was converted into a Web-based calculator, which provided individual probabilities of recovery to be generated for individuals with CTSCI after 6 months and displayed in a graphical format. CONCLUSION The nomogram, including ASIA grade, the length of high signal in the spinal cord, MSCC, spinal segment fractured, admission time, and hormonal therapy within 8 h after injury, is a promising model to predict the probability of content recovery in patients with CTSCI. This nomogram assists clinicians in stratifying patients with CTSCI, enhancing evidence-based decision-making, and individualizing the most appropriate treatment.
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Affiliation(s)
- Xin Yan
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yaozhi He
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Mengxian Jia
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jiali Yang
- Department of Pediatric Allergy and Immunology, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China
| | - Kelun Huang
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Peng Zhang
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Jiaxin Lai
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Minghang Chen
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Shikang Fan
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Sheng Li
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Ziwei Fan
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Honglin Teng
- Department of Spine Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Ruan GT, Song MM, Zhang KP, Xie HL, Zhang Q, Zhang X, Tang M, Zhang XW, Ge YZ, Yang M, Zhu LC, Shi HP. A novel nutrition-related nomogram for the survival prediction of colorectal cancer-results from a multicenter study. Nutr Metab (Lond) 2023; 20:2. [PMID: 36600242 DOI: 10.1186/s12986-022-00719-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2022] [Accepted: 12/18/2022] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Precisely predicting the short- and long-term survival of patients with cancer is important. The tumor-node-metastasis (TNM) stage can accurately predict the long-term, but not short-term, survival of cancer. Nutritional status can affect the individual status and short-term outcomes of patients with cancer. Our hypothesis was that incorporating TNM stage and nutrition-related factors into one nomogram improves the survival prediction for patients with colorectal cancer (CRC). METHOD This multicenter prospective primary cohort included 1373 patients with CRC, and the internal validation cohort enrolled 409 patients with CRC. Least absolute shrinkage and selection operator regression analyses were used to select prognostic indicators and develop a nomogram. The concordance (C)-index, receiver operating characteristic (ROC) curve, and decision curve analysis (DCA) were used to assess the prognostic discriminative ability of the nomogram, TNM stage, Patient-Generated Subjective Global Assessment (PGSGA), and TNM stage + PGSGA models. The overall survival (OS) curve of risk group stratification was calculated based on the nomogram risk score. RESULTS TNM stage, radical resection, reduced food intake, activities and function declined, and albumin were selected to develop the nomogram. The C-index and calibration plots of the nomogram showed good discrimination and consistency for CRC. Additionally, the ROC curves and DCA of the nomogram showed better survival prediction abilities in CRC than the other models. The stratification curves of the different risk groups of the different TNM categories were significantly different. CONCLUSION The novel nomogram showed good short- and long-term outcomes of OS in patients with CRC. This model provides a personalized and convenient prognostic prediction tool for clinical applications.
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Affiliation(s)
- Guo-Tian Ruan
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Meng-Meng Song
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Kang-Ping Zhang
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Hai-Lun Xie
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Qi Zhang
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Xi Zhang
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Meng Tang
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Xiao-Wei Zhang
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Yi-Zhong Ge
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Ming Yang
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China.,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China
| | - Li-Chen Zhu
- Department of Immunology, School of Preclinical Medicine, Guangxi Medical University, Nanning, China
| | - Han-Ping Shi
- Department of Gastrointestinal Surgery/Department of Clinical Nutrition, Beijing Shijitan Hospital, Capital Medical University, 10 Tie Yi Road, Beijing, 100038, China. .,Key Laboratory of Cancer FSMP for State Market Regulation, Beijing, 100038, China.
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Ma X, Xing Y, Li Z, Qiu S, Wu W, Bai J. Construction and validation of a prognostic nomogram in metastatic breast cancer patients of childbearing age: A study based on the SEER database and a Chinese cohort. Front Oncol 2022; 12:999873. [PMID: 36505800 PMCID: PMC9732809 DOI: 10.3389/fonc.2022.999873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2022] [Accepted: 11/04/2022] [Indexed: 11/27/2022] Open
Abstract
Introduction Cancer in patients of childbearing age continues to become increasingly common. The purpose of this study was to explore the impact of metastatic breast cancer (MBC) on overall survival (OS) and cancer-specifific survival (CSS) in patients of childbearing age and to construct prognostic nomograms to predict OS and CSS. Methods Data from MBC patients of childbearing age were obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015, and the patients were randomly assigned into the training and validation cohorts. Univariate and multivariate Cox analyses were used to search for independent prognostic factors impacting OS and CSS, and these data were used to construct nomograms. The concordance index (C-index), area under the curve (AUC), and calibration curves were used to determine the predictive accuracy and discriminative ability of the nomograms. Additional data were obtained from patients at the Yunnan Cancer Hospital to further verify the accuracy of the nomograms. Results A total of 1,700 MBC patients of childbearing age were identifified from the SEER database, and an additional 92 eligible patients were enrolled at the Yunnan Cancer Hospital. Multivariate Cox analyses identifified 10 prognostic factors for OS and CSS that were used to construct the nomograms. The calibration curve for the probabilities of OS and CSS showed good agreement between nomogram prediction and clinical observations. The C-index of the nomogram for OS was 0.735 (95% CI = 0.725-0.744); the AUC at 3 years was 0.806 and 0.794 at 5 years.The nomogram predicted that the C-index of the CSS was 0.740 (95% CI = 0.730- 0.750); the AUC at 3 years was 0.811 and 0.789 at 5 years. The same results were observed in the validation cohort. Kaplan- Meier curves comparing the low-,medium-, and high-risk groups showed strong prediction results for the prognostic nomogram. Conclusion We identifified several independent prognostic factors and constructed nomograms to predict the OS and CSS for MBC patients of childbearing age.These prognostic models should be considered in clinical practice to individualize treatments for this group of patients.
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Song XQ, Liu ZX, Kong QY, He ZH, Zhang S. Nomogram for prediction of peritoneal metastasis risk in colorectal cancer. Front Oncol 2022; 12:928894. [PMID: 36419892 PMCID: PMC9676355 DOI: 10.3389/fonc.2022.928894] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 10/24/2022] [Indexed: 09/09/2023] Open
Abstract
OBJECTIVE Peritoneal metastasis is difficult to diagnose using traditional imaging techniques. The main aim of the current study was to develop and validate a nomogram for effectively predicting the risk of peritoneal metastasis in colorectal cancer (PMCC). METHODS A retrospective case-control study was conducted using clinical data from 1284 patients with colorectal cancer who underwent surgery at the First Affiliated Hospital of Guangxi Medical University from January 2010 to December 2015. Least absolute shrinkage and selection operator (LASSO) regression was applied to optimize feature selection of the PMCC risk prediction model and multivariate logistic regression analysis conducted to determine independent risk factors. Using the combined features selected in the LASSO regression model, we constructed a nomogram model and evaluated its predictive value via receiver operating characteristic (ROC) curve analysis. The bootstrap method was employed for repeated sampling for internal verification and the discrimination ability of the prediction models evaluated based on the C-index. The consistency between the predicted and actual results was assessed with the aid of calibration curves. RESULTS Overall, 96 cases of PMCC were confirmed via postoperative pathological diagnosis. Logistic regression analysis showed that age, tumor location, perimeter ratio, tumor size, pathological type, tumor invasion depth, CEA level, and gross tumor type were independent risk factors for PMCC. A nomogram composed of these eight factors was subsequently constructed. The calibration curve revealed good consistency between the predicted and actual probability, with a C-index of 0.882. The area under the curve (AUC) of the nomogram prediction model was 0.882 and its 95% confidence interval (CI) was 0.845-0.919. Internal validation yielded a C-index of 0.868. CONCLUSION We have successfully constructed a highly sensitive nomogram that should facilitate early diagnosis of PMCC, providing a robust platform for further optimization of clinical management strategies.
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Affiliation(s)
- Xian-qing Song
- General Surgery Department, Ningbo Fourth Hospital, Ningbo, Zhejiang, China
| | - Zhi-xian Liu
- Proctology Department, Beilun People’s Hospital of Ningbo, Ningbo, Zhejiang, China
| | - Qing-yuan Kong
- General Surgery Department, Baoan People’s Hospital of Shenzhen, Shenzhen, Guangdong, China
| | - Zhen-hua He
- General Surgery Department, Hezhou People’s Hospital, Hezhou, Guangxi, China
| | - Sen Zhang
- Department of Colorectal Surgery, First Affiliated Hospital of Guangxi Medical University, Nanning, Guangxi, China
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Zhang W, Zhang Y, Liu Q, Nie Y, Zhu X. Development and validation of a prognostic nomogram for decompensated liver cirrhosis. World J Clin Cases 2022; 10:10467-10477. [PMID: 36312496 PMCID: PMC9602236 DOI: 10.12998/wjcc.v10.i29.10467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Revised: 08/31/2022] [Accepted: 09/09/2022] [Indexed: 02/05/2023] Open
Abstract
BACKGROUND Decompensated liver cirrhosis (DLC) is a stage in the progression of liver cirrhosis and has a high mortality.
AIM To establish and validate a novel and simple-to-use predictive nomogram for evaluating the prognosis of DLC patients.
METHODS A total of 493 patients with confirmed DLC were enrolled from The First Affiliated Hospital of Nanchang University (Nanchang, Jiangxi Province, China) between December 2013 and August 2019. The patients were divided into two groups: a derivation group (n = 329) and a validation group (n = 164). Univariate and multivariate Cox regression analyses were performed to assess prognostic factors. The performance of the nomogram was determined by its calibration, discrimination, and clinical usefulness.
RESULTS Age, mechanical ventilation application, model for end-stage liver disease (MELD) score, mean arterial blood pressure, and arterial oxygen partial pressure/inhaled oxygen concentration were used to construct the model. The C-indexes of the nomogram in the derivation and validation groups were 0.780 (95%CI: 0.670-0.889) and 0.792 (95%CI: 0.698-0.886), respectively. The calibration curve exhibited good consistency with the actual observation curve in both sets. In addition, decision curve analysis indicated that our nomogram was useful in clinical practice.
CONCLUSION A simple-to-use novel nomogram based on a large Asian cohort was established and validated and exhibited improved performance compared with the Child-Turcotte-Pugh and MELD scores. For patients with DLC, the proposed nomogram may be helpful in guiding clinicians in treatment allocation and may assist in prognosis prediction.
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Affiliation(s)
- Wang Zhang
- Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Yue Zhang
- Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Qi Liu
- Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Yuan Nie
- Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Xuan Zhu
- Department of Gastroenterology, Jiangxi Clinical Research Center for Gastroenterology, The First Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
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20
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Ren C, Ma Y, Jin J, Ding J, Jiang Y, Wu Y, Li W, Yang X, Han L, Ma Q, Wu Z, Shi Y, Wang Z. Development and external validation of a dynamic nomogram to predict the survival for adenosquamous carcinoma of the pancreas. Front Oncol 2022; 12:927107. [PMID: 36033500 PMCID: PMC9411813 DOI: 10.3389/fonc.2022.927107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 07/25/2022] [Indexed: 01/27/2023] Open
Abstract
ObjectiveWe aimed to develop a nomogram to predict the survival and prognosis of adenosquamous carcinoma of the pancreas (ASCP).BackgroundAdenosquamous carcinoma of the pancreas (ASCP) is a relatively rare histological subtype of pancreatic exocrine neoplasms. It was reported a worse survival in ASCP than in pancreatic adenocarcinoma (PDAC). Prediction of ASCP prognosis is of great importance.MethodsHistologically confirmed ASCP patients from the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) Program database were finally enrolled and divided into development and internal validation cohorts. Moreover, a multi-center cohort of 70 patients from China was registered as the external validation. A nomogram was developed based on independent predictors of ASCP determined in multivariable analysis.ResultsA total of 233 patients from SEER were finally included. Univariate and Multivariate analysis showed that tumor size, radiotherapy, chemotherapy, and lymph node ratio (LNR) were considered the independent prognostic indicators. We developed a nomogram according to these four parameters. The C index of the nomogram in the development cohort was 0.696. Through analysis of the area under the curve (AUC) of the different cohorts, we observed that the predictive efficacy of the nomogram for 1-, and 2-year overall survival (OS) were better than those of the American Joint Committee on Cancer (AJCC) TNM (8th) staging system both in the development and validation cohort. External validation confirmed that 1-year survival is 67.2% vs. 29.7%, similar to the internal cohort analysis.ConclusionThe nomogram showed good performance in predicting the survival of ASCP. It could help surgeons to make clinical decisions and develop further plans.
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Affiliation(s)
- Chao Ren
- Department of Hepatobiliary and Pancreatic Surgery, The Affiliated Jinhua Hospital of Zhejiang University School of Medicine, Jinhua, China
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yifei Ma
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Jiabin Jin
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Jiachun Ding
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yina Jiang
- Department of Pathology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yinying Wu
- Department of Medical Oncology, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Wei Li
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Xue Yang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Liang Han
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Qingyong Ma
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Zheng Wu
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
| | - Yusheng Shi
- Department of General Surgery, Pancreatic Disease Center, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
- *Correspondence: Yusheng Shi, ; Zheng Wang,
| | - Zheng Wang
- Department of Hepatobiliary Surgery, The First Affiliated Hospital of Xi’an Jiaotong University, Xi’an, China
- *Correspondence: Yusheng Shi, ; Zheng Wang,
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Zhou YW, Wei GX, Tang LS, Hao YT, Wang JL, Qiu M. Clinical characteristics and prognostic factors of anal adenocarcinoma: a nomogram development based on SEER database and validation in the WCH database. Int J Colorectal Dis 2022; 37:1773-1784. [PMID: 35781608 DOI: 10.1007/s00384-022-04211-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/27/2022] [Indexed: 02/08/2023]
Abstract
PURPOSE The purpose of this study was to comprehensively understand anal canal adenocarcinomas (AA) and develop a nomogram for prognostic prediction of AA. METHODS Data were extracted from the Surveillance, Epidemiology, and End Results (SEER) database (the year 2004-2015). An external validation set was collected from West China Hospital (WCH) databases. Propensity-score matching (PSM) was performed to balance the demographic characteristic. A novel nomogram was developed to estimate individual survival probability and its performance was validated using the concordance index (C-index), calibration curves, and decision curve analyses (DCA). RESULTS A total of 7901 patients were enrolled including 749 AA patients and 7152 squamous cell carcinomas of the anal canal (ASCC) patients. Before PSM, patients with AA had shorter cancer-specific survival (CSS) and OS than those with ASCC. However, after PSM, patients with AA were related to a favorable OS (p < 0.001), but a comparable CSS (p = 0.140) to those with ASCC. Age, sex, grade, surgery, and M stage were the independent prognostic factors of CSS for AA and were included in the establishment of a novel nomogram. Patients from the WCH database (n = 112) were used as an external validation cohort. The C-index of the nomogram was 0.78 and 0.735 in internal and external validation, respectively, which suggested the good discrimination power of the model. Furthermore, calibration curves and DCA suggested good agreement between the predicted and actual survival. Lastly, a risk classification system based on a nomogram revealed the reliability of the novel model. CONCLUSION AA and ASCC had distinct clinical features. AA was associated with a better prognosis than ASCC after PSM. The model of nomogram showed an accurate predictive ability for prognostic factors of AA patients.
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Affiliation(s)
- Yu-Wen Zhou
- Department of Biotherapy, West China Hospital of Sichuan University, Cancer Center, Chengdu, China
| | - Gui-Xia Wei
- Department of Colorectal Cancer Center, West China Hospital of Sichuan University, Sichuan Province, 37 Guoxue Xiang Street, Chengdu, 610041, China
| | - Lian-Sha Tang
- Department of Biotherapy, West China Hospital of Sichuan University, Cancer Center, Chengdu, China
| | - Ya-Ting Hao
- School of Clinical Medicine, Ningxia Medical University, Yinchuan, China
| | - Jia-Ling Wang
- Department of Biotherapy, West China Hospital of Sichuan University, Cancer Center, Chengdu, China
| | - Meng Qiu
- Department of Colorectal Cancer Center, West China Hospital of Sichuan University, Sichuan Province, 37 Guoxue Xiang Street, Chengdu, 610041, China.
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22
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Huang YY, Liu X, Liang SH, Wu LL, Ma GW. Nomogram predicts the prognosis of patients with thymic carcinoma: A population-based study using SEER data. TUMORI JOURNAL 2022:3008916221109334. [PMID: 35897150 DOI: 10.1177/03008916221109334] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Thymic carcinoma (TC) is a rare malignant tumor that can have a poor prognosis, and accurate prognostication prediction remains difficult. We aimed to develop a nomogram to predict overall survival (OS) and cancer-specific survival (CSS) based on a large cohort of patients. METHODS The Surveillance Epidemiology and End Results (SEER) database was searched to identify TC patients (1975-2016). Univariate and multivariable Cox regression analyses were used to identify predictors of OS and CSS, which were used to construct nomograms. The nomograms were evaluated using the concordance index (C-index), calibration curve, receiver operating characteristic curve, and decision curve analysis (DCA). Subgroup analysis was performed to identify high-risk patients. RESULTS The analysis identified six predictors of OS (Masaoka stage, surgical method, lymph node metastasis, liver metastasis, bone metastasis, and radiotherapy) and five predictors of CSS (Masaoka stage, surgical method, lymph node metastasis, tumor size, and brain metastasis), which were used to create nomograms for predicting three-year and five-year OS and CSS. The nomograms had reasonable C-index values (OS: 0.687 [training] and 0.674 [validation], CSS: 0.712 [training] and 0.739 [validation]). The DCA curve revealed that the nomograms were better for predicting OS and CSS, relative to the Masaoka staging system. CONCLUSION We developed nomograms using eight clinicopathological factors that predicted OS and CSS among TC patients. The nomograms performed better than the traditional Masaoka staging system and could identify high-risk patients. Based on the nomograms' performance, we believe they will be useful prognostication tools for TC patients.
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Affiliation(s)
- Yang-Yu Huang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Xuan Liu
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Shen-Hua Liang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Lei-Lei Wu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China
| | - Guo-Wei Ma
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
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Hu CG, Hu BE, Zhu JF, Zhu ZM, Huang C. Prognostic significance of the preoperative hemoglobin to albumin ratio for the short-term survival of gastric cancer patients. World J Gastrointest Surg 2022; 14:580-593. [PMID: 35979426 PMCID: PMC9258240 DOI: 10.4240/wjgs.v14.i6.580] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Revised: 03/20/2022] [Accepted: 05/28/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Hemoglobin and albumin are associated with the prognosis of gastric cancer (GC) patients. However, the prognostic value of the hemoglobin to albumin ratio (HAR) for the short-term survival of GC patients with D2 radical resection has not been studied.
AIM To investigate the significance of the HAR in evaluating the short-term survival of GC patients after D2 radical resection and to construct a nomogram to predict the prognosis in GC patients after surgery, thus providing a reference for the development of postoperative individualized treatment and follow-up plans.
METHODS Cox regression and Kaplan-Meier analysis was used for prognostic analysis. Logistic regression was used to analyze the relationships between HAR and the clinicopathological characteristics of the GC patients. A prognostic nomogram model for the short-term survival of GC patients was constructed by R software.
RESULTS HAR was an independent risk factor for the short-term survival of GC patients. GC patients with a low HAR had a poor prognosis (P < 0.001). Low HAR was markedly related to high stage [odds ratio (OR) = 0.45 for II vs I; OR = 0.48 for III vs I], T classification (OR = 0.52 for T4 vs T1) and large tumor size (OR = 0.51 for ≥ 4 cm vs < 4 cm) (all P < 0.05). The nomogram model was based on HAR, age, CA19-9, CA125 and stage, and the C-index was 0.820.
CONCLUSION Preoperative low HAR was associated with short-term survival in GC patients. The prognostic nomogram model can accurately predict the short-term survival of GC patients with D2 radical resection.
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Affiliation(s)
- Ce-Gui Hu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Bai-E Hu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Jin-Feng Zhu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Zheng-Ming Zhu
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
| | - Chao Huang
- Department of Gastrointestinal Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang 330006, Jiangxi Province, China
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Zhang Z, Zhanghuang C, Wang J, Tian X, Wu X, Li M, Mi T, Liu J, Jin L, Li M, He D. Development and Validation of Nomograms to Predict Cancer-Specific Survival and Overall Survival in Elderly Patients With Prostate Cancer: A Population-Based Study. Front Oncol 2022; 12:918780. [PMID: 35814387 PMCID: PMC9259789 DOI: 10.3389/fonc.2022.918780] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 05/23/2022] [Indexed: 12/27/2022] Open
Abstract
ObjectiveProstate cancer (PC) is the most common non-cutaneous malignancy in men worldwide. Accurate predicting the survival of elderly PC patients can help reduce mortality in patients. We aimed to construct nomograms to predict cancer-specific survival (CSS) and overall survival (OS) in elderly PC patients.MethodsInformation on PC patients aged 65 years and older was downloaded from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression models were used to determine independent risk factors for PC patients. Nomograms were developed to predict the CSS and OS of elderly PC patients based on a multivariate Cox regression model. The accuracy and discrimination of the prediction model were tested by the consistency index (C-index), the area under the subject operating characteristic curve (AUC), and the calibration curve. Decision curve analysis (DCA) was used to test the clinical value of the nomograms compared with the TNM staging system and D’Amico risk stratification system.Results135183 elderly PC patients in 2010-2018 were included. All patients were randomly assigned to the training set (N=94764) and the validation set (N=40419). Univariate and multivariate Cox regression model analysis revealed that age, race, marriage, histological grade, TNM stage, surgery, chemotherapy, radiotherapy, biopsy Gleason score (GS), and prostate-specific antigen (PSA) were independent risk factors for predicting CSS and OS in elderly patients with PC. The C-index of the training set and the validation set for predicting CSS was 0.883(95%CI:0.877-0.889) and 0.887(95%CI:0.877-0.897), respectively. The C-index of the training set and the validation set for predicting OS was 0.77(95%CI:0.766-0.774)and 0.767(95%CI:0.759-0.775), respectively. It showed that the proposed model has excellent discriminative ability. The AUC and the calibration curves also showed good accuracy and discriminability. The DCA showed that the nomograms for CSS and OS have good clinical potential value.ConclusionsWe developed new nomograms to predict CSS and OS in elderly PC patients. The models have been internally validated with good accuracy and reliability and can help doctors and patients to make better clinical decisions.
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Affiliation(s)
- Zhaoxia Zhang
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Chenghao Zhanghuang
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
- Department of Urology, Kunming Children’s Hospital, Yunnan Provincial Key Research Laboratory of Pediatric Major Diseases, Kunming, China
| | - Jinkui Wang
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Xiaomao Tian
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Xin Wu
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Maoxian Li
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Tao Mi
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Jiayan Liu
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Liming Jin
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Mujie Li
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
| | - Dawei He
- Department of Urology, Chongqing Key Laboratory of Children Urogenital Development and Tissue Engineering, Chongqing, China
- Chongqing Key Laboratory of Pediatrics, Ministry of Education Key Laboratory of Child Development and Disorders, Chongqing, China
- National Clinical Research Center for Child Health and Disorders, China International Science and Technology Cooperation base of Child development and Critical Disorders; Children’s Hospital of Chongqing Medical University, Chongqing, China
- *Correspondence: Dawei He,
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Ma X, Guo J, Zhang C, Bai J. Development of a prognostic nomogram for metastatic pancreatic ductal adenocarcinoma integrating marital status. Sci Rep 2022; 12:7124. [PMID: 35504988 PMCID: PMC9065131 DOI: 10.1038/s41598-022-11318-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Accepted: 04/20/2022] [Indexed: 12/20/2022] Open
Abstract
Previous studies have shown that marital status can affect the overall survival (OS) of cancer patients yet its role in metastatic pancreatic ductal adenocarcinoma (mPDAC) remains unclear. This study aimed to explore the impact of marital status on the OS of mPDAC patients and to construct a prognostic nomogram to predict OS outcomes. Data from patients diagnosed with mPDAC were obtained from the Surveillance, Epidemiology, and End Results database between 1973 and 2015. The patients were randomized into primary and validation cohorts. Kaplan-Meier survival analysis was performed to compare differences in survival depending on marital status. Univariate and multivariate analyses were conducted to identify independent prognostic factors and a nomogram was established based using Cox regression analyses. Validation of the prognostic nomogram was evaluated with a calibration curve and concordance index (C-index). Our data showed significant differences in the OS of mPDAC patients with different marital status by Kaplan-Meier analysis (P < 0.05). Univariate and multivariate analyses confirmed that marital status was an independent OS-related factor in mPDAC patients. Based on the multivariate models of the primary cohort, a nomogram was developed that combined marital status, age, grade, tumor size, surgery of primary site, surgery of lymph node and metastatic. The nomogram showed that marital status had a moderate influence on predicting the OS of mPDAC patients. Moreover, the internally and externally validated C-indexes were 0.633 and 0.619, respectively. A calibration curve confirmed favorable consistency between the observed and predicted outcomes. Marital status was identified as an independent prognostic factor for OS of mPDAC patients and is a reliable and valid parameter to predict the survival of patients with mPDAC. This prognostic model has value and may be integrated as a tool to inform decision-making in the clinic.
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Affiliation(s)
- Xiang Ma
- Yunnan Caner Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China
| | | | | | - Jinfeng Bai
- Yunnan Caner Hospital, The Third Affiliated Hospital of Kunming Medical University, Kunming, 650118, China.
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Development and Verification of Prognostic Nomogram for Penile Cancer Based on the SEER Database. BIOMED RESEARCH INTERNATIONAL 2022; 2022:8752388. [PMID: 35419456 PMCID: PMC9001101 DOI: 10.1155/2022/8752388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/28/2022] [Accepted: 03/08/2022] [Indexed: 11/25/2022]
Abstract
Aim We aimed to establish a prognostic nomogram for penile cancer (PC) patients based on the Surveillance, Epidemiology, and End Results Program (SEER) database. Methods Data from 1643 patients between 2010 and 2015 were downloaded and extracted from the SEER database. They were randomly divided into the development group (70%) and the verification group (30%), and then, univariate and multivariate Cox proportional hazards regression, respectively, was used to explore the possible risk factors of PC. The factors significantly related to overall survival (OS) and cancer-specific survival (CSS) were used to establish the nomogram, which was assessed via the concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve. An internal validation was conducted to test the accuracy and effectiveness of the nomogram. Kaplan–Meier calculation was used to predict the further OS and CSS status of these patients. Results On multivariate Cox proportional hazards regression, the independent prognostic risk factors associated with OS were age, race, marital status, N/M stage, surgery, surgery of lymph nodes, and histologic type, with a moderate C-index of 0.737 (95% confidence interval (CI): 0.713–0.760) and 0.766 (95% CI: 0.731–0.801) in the development and verification groups, respectively. The areas under the ROC (AUC) of 3- and 5-year OS were 0.749 and 0.770, respectively. While marital status, N/M stage, surgery, surgery of lymph nodes, and histologic type were significantly linked to PC patients' CSS, which have better C-index of 0.802 (95% confidence interval (CI): 0.771–0.833) and 0.82 (95% CI: 0.775–0.865) in the development and verification groups, and the AUC of 3- and 5-year CSS were 0.766 and 0.787. Both of the survival calibration curves of 3- and 5-year OS and CSS brought out a high consistency. Conclusion Our study produced a satisfactory nomogram revealing the survival of PC patients, which could be helpful for clinicians to assess the situation of PC patients and to implement further treatment.
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Liu Z, Zhang X, Liu H, Wang D. A nomogram for short-term recurrent pain after percutaneous vertebroplasty for osteoporotic vertebral compression fractures. Osteoporos Int 2022; 33:851-860. [PMID: 34762140 DOI: 10.1007/s00198-021-06232-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 11/02/2021] [Indexed: 02/06/2023]
Abstract
UNLABELLED In clinical practice, it was found that some patients experienced short-term recurrent pain (SRP) in the original site after PVP treatment. This study was designed to develop and validate a nomogram for predicting the potential risks of SRP after PVP, which may help to provide a painless postoperative experience and personalized health management for patients with OVCF. INTRODUCTION With the aging of China's population, the incidence of osteoporotic vertebral compression fractures (OVCF) has increased significantly. Percutaneous vertebroplasty (PVP) has been widely accepted due to its minimally invasive, rapid, and effective characteristics. However, it has been found that some patients have short-term recurrent pain (SRP) in the original site after surgery in practical clinical work. METHODS We retrospectively reviewed the clinical data of OVCF patients who were treated with PVP in our center from January 1st, 2019, to December 30th, 2020. A total of 296 patients were enrolled in the study cohort, and patients were randomly divided into the training set (70%) and validation set (30%). Univariate and multivariate logistic regression analyses were used to determine the risk factors of SRP, and a nomogram predictive model was established accordingly. The model was evaluated by calibration curve, receiver operation characteristic (ROC) curve, and decision curve analysis (DCA). RESULTS Among the 296 patients, 83 (27.85%) patients experienced SRP after surgery. The independent risk factors included fracture segments (OR: 14.148, 95%CI: 1.532-130.661; p < 0.019), number of surgical vertebrae (OR: 7.896, 95%CI: 3.007-20.729; p < 0.001; (OR: 12.563, 95%CI: 2.223-70.993; p = 0.004), and smoking (OR: 3.833, 95%CI: 1.219-12.052; p = 0.022). The AUC of the prediction model was 0.819 in the training set and 0.794 in the validation set. The calibration curve and DCA indicated the good performance of this nomogram. CONCLUSION The nomogram prediction model had satisfactory accuracy and clinical utility, which may benefit clinical decision-making for the treatment of OVCF and strengthen patient education.
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Affiliation(s)
- Z Liu
- Department of Orthopedics, Affiliated Hospital of Beihua University, Jilin, 132000, China
| | - X Zhang
- Department of Orthopedics, Affiliated Hospital of Beihua University, Jilin, 132000, China
| | - H Liu
- Department of Orthopedics, Baicheng Central Hospital, Jilin, China
| | - D Wang
- Department of Orthopedics, Affiliated Hospital of Beihua University, Jilin, 132000, China.
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Gong XQ, Zhang Y. Develop a nomogram to predict overall survival of patients with borderline ovarian tumors. World J Clin Cases 2022; 10:2115-2126. [PMID: 35321187 PMCID: PMC8895192 DOI: 10.12998/wjcc.v10.i7.2115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/17/2022] [Accepted: 02/23/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND The prognosis of borderline ovarian tumors (BOTs) has been the concern of clinicians and patients. It is urgent to develop a model to predict the survival of patients with BOTs.
AIM To construct a nomogram to predict the likelihood of overall survival (OS) in patients with BOTs.
METHODS A total of 192 patients with histologically verified BOTs and 374 patients with epithelial ovarian cancer (EOC) were retrospectively investigated for clinical characteristics and survival outcomes. A 1:1 propensity score matching (PSM) analysis was performed to eliminate selection bias. Survival was analyzed by using the log-rank test and the restricted mean survival time (RMST). Next, univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors. In addition, a nomogram model was developed to predict the 1-, 3-, and 5-year overall survival of patients with BOTs. The predictive performance of the model was assessed by using the concordance index (C-index), calibration curves, and decision curve analysis (DCA).
RESULTS For clinical data, there was no significant difference in body mass index, preoperative CA199 concentration, or tumor localization between the BOTs group and EOC group. Women with BOTs were significantly younger than those with EOC. There was a significant difference in menopausal status, parity, preoperative serum CA125 concentration, Federation International of gynecology and obstetrics (FIGO) stage, and whether patients accepted postoperative adjuvant therapy between the BOT and EOC group. After PSM, patients with BOTs had better overall survival than patients with EOC (P value = 0.0067); more importantly, the 5-year RMST of BOTs was longer than that of EOC (P value = 0.0002, 95%CI -1.137 to -0.263). Multivariate Cox regression analysis showed that diagnosed age and surgical type were independent risk factors for BOT patient OS (P value < 0.05). A nomogram was developed based on diagnosed age, preoperative serum CA125 and CA199 Levels, surgical type, FIGO stage, and tumor size. Moreover, the c-index (0.959, 95% confidence interval 0.8708–1.0472), calibration plot of 1-, 3-, and 5-year OS, and decision curve analysis indicated the accurate predictive ability of this model.
CONCLUSION Patients with BOTs had a better prognosis than patients with EOC. The nomogram we constructed might be helpful for clinicians in personalized treatment planning and patient counseling.
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Affiliation(s)
- Xiao-Qin Gong
- Department of Obstetrics and Gynecology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
| | - Yan Zhang
- Department of Gynecology and Obstetrics, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, Hubei Province, China
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Liu K, Jiao YL, Shen LQ, Chen P, Zhao Y, Li MX, Gu BL, Lan ZJ, Ruan HJ, Liu QW, Xu FB, Yuan X, Qi YJ, Gao SG. A Prognostic Model Based on mRNA Expression Analysis of Esophageal Squamous Cell Carcinoma. Front Bioeng Biotechnol 2022; 10:823619. [PMID: 35299644 PMCID: PMC8921680 DOI: 10.3389/fbioe.2022.823619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Background: The aim of this study was to identify prognostic markers for esophageal squamous cell carcinoma (ESCC) and build an effective prognostic nomogram for ESCC.Methods: A total of 365 patients with ESCC from three medical centers were divided into four cohorts. In the discovery phase of the study, we analyzed transcriptional data from 179 cancer tissue samples and identified nine marker genes using edgeR and rbsurv packages. In the training phase, penalized Cox regression was used to select the best marker genes and clinical characteristics in the 179 samples. In the verification phase, these marker genes and clinical characteristics were verified by internal validation cohort (n = 58) and two external cohorts (n = 81, n = 105).Results: We constructed and verified a nomogram model based on multiple clinicopathologic characteristics and gene expression of a patient cohort undergoing esophagectomy and adjuvant radiochemotherapy. The predictive accuracy for 4-year overall survival (OS) indicated by the C-index was 0.75 (95% CI, 0.72–0.78), which was statistically significantly higher than that of the American Joint Committee on Cancer (AJCC) seventh edition (0.65). Furthermore, we found two marker genes (TM9SF1, PDZK1IP) directly related to the OS of esophageal cancer.Conclusion: The nomogram presented in this study can accurately and impersonally predict the prognosis of ESCC patients after partial resection of the esophagus. More research is required to determine whether it can be applied to other patient populations. Moreover, we found two marker genes directly related to the prognosis of ESCC, which will provide a basis for future research.
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Affiliation(s)
- Ke Liu
- School of Information Engineering, Henan University of Science and Technology, Luoyang, China
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Ye-Lin Jiao
- Department of Pathology, Luo Yang First Peoples’s Hospital, Luoyang, China
| | - Liu-Qing Shen
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Pan Chen
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Ying Zhao
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Meng-Xiang Li
- School of Information Engineering, Henan University of Science and Technology, Luoyang, China
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Bian-Li Gu
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Zi-Jun Lan
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Hao-Jie Ruan
- School of Information Engineering, Henan University of Science and Technology, Luoyang, China
| | - Qi-Wei Liu
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Feng-Bo Xu
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Xiang Yuan
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
| | - Yi-Jun Qi
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
- *Correspondence: She-Gan Gao, ; Yi-Jun Qi,
| | - She-Gan Gao
- School of Information Engineering, Henan University of Science and Technology, Luoyang, China
- Henan Key Laboratory of Microbiome and Esophageal Cancer Prevention and Treatment, Henan Key Laboratory of Cancer Epigenetics, Cancer Hospital, The First Affiliated Hospital (College of Clinical Medicine) of Henan University of Science and Technology, Luoyang, China
- *Correspondence: She-Gan Gao, ; Yi-Jun Qi,
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Zhang TT, Zeng J, Yang Y, Wang JJ, Kang YJ, Zhang DH, Liu XZ, Chen K, Wang X, Fang Y. A visualized dynamic prediction model for survival of patients with geriatric thyroid cancer: A population-based study. Front Endocrinol (Lausanne) 2022; 13:1038041. [PMID: 36568078 PMCID: PMC9780441 DOI: 10.3389/fendo.2022.1038041] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 11/28/2022] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVE Thyroid cancer (TC) is a common malignancy with a poor prognosis with aging. However, no accurate predictive survival model exists for patients with geriatric TC.We aimed to establish prediction models of prognosis in elderly TC. METHODS We retrospectively reviewed the clinicopathology characteristics of patients with geriatric TC in the Surveillance, Epidemiology, and End Results database (SEER) from 2004 to 2018. The risk predictors used to build the nomograms were derived from the Cox proportional risk regression. These nomograms were used to predict 1-, 3-, and 5-year overall survival and cancer-specific survival in elderly patients with TC. The accuracy and discriminability of the new model were evaluated by the consistency index (C-index) and calibration curve. The clinical applicability value of the model was assessed using the decision curve analysis. RESULTS We used the SEER database to include 16475 patients with geriatric TC diagnosed from 2004 to 2018. The patients from 2004 to 2015 were randomly sorted out on a scale of 7:3. They were classified into a training group (n = 8623) and a validation group (n = 3669). Patients with TC diagnosed in 2016-2018 were classified into external validation groups (n = 4183). The overall survival nomogram consisted of 10 variables (age, gender, marital status, histologic type, grade, TNM stage, surgery status, and tumor size). A cancer-specific survival nomogram consisted of eight factors (age, tumor size, grade, histologic type, surgery, and TNM stage). The C-index values for the training, validation, and external validation groups were 0.775 (95% confidence interval [CI] 0.785-0.765), 0.776 (95% CI 0.792-0.760), and 0.895(95% CI 0.873-0.917), respectively. The overall survival was consistent with a nomogram based on the calibration curve. Besides, the decision curve analysis showed excellent clinical application value of the nomogram. Additionally, we found that surgery could improve the prognosis of patients with geriatric at high-risk (P < 0.001) but not those at low-risk (P = 0.069). CONCLUSION This was the first study to construct predictive survival nomograms for patients with geriatric TC. The well-established nomograms and the actual results could guide follow-up management strategies.
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Affiliation(s)
- Ting-ting Zhang
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jing Zeng
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yan Yang
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Jin-jing Wang
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Yao-jie Kang
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
| | - Dong-he Zhang
- Department of Day Clinic, The Fifth Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
| | - Xiao-zhu Liu
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Kang Chen
- Department of Endocrinology, The First Medical Center of Chinese People's Liberation Army (PLA) General Hospital, Beijing, China
- *Correspondence: Kang Chen, ; Xuan Wang, ; Yi Fang,
| | - Xuan Wang
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Kang Chen, ; Xuan Wang, ; Yi Fang,
| | - Yi Fang
- Department of Endocrinology, The Fifth Medical Center of Chinese PLA General Hospital, Beijing, China
- *Correspondence: Kang Chen, ; Xuan Wang, ; Yi Fang,
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Zhou S, Sheng N, Ren J, He Q, Zhang Y, Gong J, Wang Z. Clinical Significance of and Predictive Risk Factors for the Postoperative Elevation of Carcinoembryonic Antigen in Patients With Non-Metastatic Colorectal Cancer. Front Oncol 2021; 11:741309. [PMID: 34692522 PMCID: PMC8529031 DOI: 10.3389/fonc.2021.741309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2021] [Accepted: 09/16/2021] [Indexed: 12/24/2022] Open
Abstract
Background Recently, a few researches focus on the correlation between postoperative carcinoembryonic antigen (post-CEA) and the outcome of colorectal cancer (CRC), but none investigates the predictive value of post-CEA in a prognostic model. Besides, current recommendations on the frequency of post-CEA surveillance are not individualized and well followed. There is an absence of identification of patients who are more likely to have abnormal post-CEA levels and need more frequent CEA measurements. Methods Consecutive CRC patients who underwent curative surgery were enrolled and randomly divided into the discovery (n=352) and testing cohort (n=233). Impacts of preoperative CEA (pre-CEA) and post-CEA on prognosis were assessed. Cox regression model was applied to develop prognostic nomograms, which were validated by the concordance index (C-index), calibration curve, and receiver operating characteristic curve (ROC) analysis. And prediction improvement of the nomograms was assessed with net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Logistic regression was used to identify predictive risk factors and construct the prediction model for post-CEA elevation. Results Post-CEA independently predicted overall survival (OS) and disease-free survival (DFS), while pre-CEA did not. Post-CEA elevation represented higher risks in patients with normal pre-CEA, compared to those with persistent elevated CEA. The nomograms for OS and DFS were established with body mass index, tumor differentiation, N stage, lymphocyte-to-monocyte ratio, and post-CEA. The nomograms showed good calibration and superior discrimination than pTNM stage, with the C-index of 0.783 and 0.759 in the discovery set and 0.712 and 0.774 in the testing set for OS and DFS, respectively. Comparisons between models using IDI and NRI implied that the nomograms performed better than pTNM stage and the predictive power could be improved with the addition of post-CEA. The prediction model for post-CEA elevation was established with age, platelet-to-lymphocyte ratio, preoperative CA19-9, and pre-CEA. The AUC of the model in the two cohorts was 0.802 and 0.764, respectively. Conclusions Elevated post-CEA was a strong indicator of poor prognosis. The addition of post-CEA significantly enhanced the performance of prognostic nomograms. And the prediction model for post-CEA elevation may help identify patients who ought to reasonably receive more intensive postoperative surveillance of CEA levels.
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Affiliation(s)
- Siyu Zhou
- Department of Gastrointestinal Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Nengquan Sheng
- Department of Gastrointestinal Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Jiazi Ren
- Department of Gastrointestinal Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Qian He
- College of Clinical Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yaya Zhang
- College of Clinical Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianfeng Gong
- Department of Gastrointestinal Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Zhigang Wang
- Department of Gastrointestinal Surgery, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
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Huang Z, Lan T, Wang J, Chen Z, Zhang X. Identification and validation of seven RNA binding protein genes as a prognostic signature in oral cavity squamous cell carcinoma. Bioengineered 2021; 12:7248-7262. [PMID: 34585646 PMCID: PMC8806873 DOI: 10.1080/21655979.2021.1974328] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
RNA binding proteins (RBPs) play a pivotal role in various biological processes, and aberrant expression of RBPs is closely associated with tumorigenesis and progression. However, the role of RBPs in oral cavity squamous cell carcinoma (OCSCC) is yet unveiled. In this study, RNA sequences and clinical information of OCSCC samples were acquired from The Cancer Genome Atlas (TCGA) database. A total of 650 RBPs, with significantly different expression between healthy and OCSCC samples, were identified using the limma package. A prognostic model was constructed by Lasso-Cox analysis, resulting in the determination of 7 prognosis-related RBPs: ERMP1, RNASE3, ARL4D, CSRP2, ULK1, ZC3H12D, and RPS28. Based on the prognostic model, the risk scores of the OCSCC samples were calculated. The capability of the prognostic model was further evaluated using the receiver operating characteristic curve (ROC). The areas under ROC were 0.764, 0.771, and 0.809 at 1, 3 and 5-year respectively in the TCGA dataset. Internal and external validation showed satisfactory predictive capability for prognosis in OCSCC. In addition, a nomogram was created to graphically present the model. To further validate the analytical data, qRT-PCR was performed on normal and OCSCC cell lines. The mRNA expression of the 7 prognostic genes was in accordance with the analytical results. Functional analysis and gene connection networks were used to describe the biological functions and underlying interactions among the 7 prognostic genes Overall, 7 prognosis-related RBPs were identified, which could be used to predict clinical prognosis and to identify potential therapeutic targets for OCSCC.
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Affiliation(s)
- Zijing Huang
- Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Province Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, Guangdong, China
| | - Tianjun Lan
- Department of Oral and Maxillofacial Surgery, Sun Yat-sen Memorial Hospital of Sun Yat-Sen University, Guangzhou China
| | - Junjie Wang
- Department of Stomatology, The First Affiliated Hospital of Jinan University, School of Stomatology, Jinan University, Guangzhou China
| | - Zhifeng Chen
- Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou China.,Department of Stomatology, Linzhi People's Hospital, Tibet China
| | - Xiaolei Zhang
- Hospital of Stomatology, Guanghua School of Stomatology, Guangdong Province Key Laboratory of Stomatology, Sun Yat-sen University, Guangzhou, Guangdong, China
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Liu X, Yue S, Huang H, Duan M, Zhao B, Liu J, Xiang T. Risk Stratification Model for Predicting the Overall Survival of Elderly Triple-Negative Breast Cancer Patients: A Population-Based Study. Front Med (Lausanne) 2021; 8:705515. [PMID: 34621757 PMCID: PMC8490672 DOI: 10.3389/fmed.2021.705515] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Accepted: 08/18/2021] [Indexed: 12/27/2022] Open
Abstract
Background: The objective of this study was to evaluate the prognostic value of clinical characteristics in elderly patients with triple-negative breast cancer (TNBC). Methods: The cohort was selected from the Surveillance, Epidemiology, and End Results (SEER) program dating from 2010 to 2015. Univariate and multivariate analyses were performed using a Cox proportional risk regression model, and a nomogram was constructed to predict the 1-, 3-, and 5-year prognoses of elderly patients with TNBC. A concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to verify the nomogram. Results: The results of the study identified a total of 5,677 patients who were randomly divided 6:4 into a training set (n = 3,422) and a validation set (n = 2,255). The multivariate analysis showed that age, race, grade, TN stage, chemotherapy status, radiotherapy status, and tumor size at diagnosis were independent factors affecting the prognosis of elderly patients with TNBC. Together, the 1 -, 3 -, and 5-year nomograms were made up of 8 variables. For the verification of these results, the C-index of the training set and validation set were 0.757 (95% CI 0.743-0.772) and 0.750 (95% CI 0.742-0.768), respectively. The calibration curve also showed that the actual observation of overall survival (OS) was in good agreement with the prediction of the nomograms. Additionally, the DCA showed that the nomogram had good clinical application value. According to the score of each patient, the risk stratification system of elderly patients with TNBC was further established by perfectly dividing these patients into three groups, namely, low risk, medium risk, and high risk, in all queues. In addition, the results showed that radiotherapy could improve prognosis in the low-risk group (P = 0.00056), but had no significant effect in the medium-risk (P < 0.4) and high-risk groups (P < 0.71). An online web app was built based on the proposed nomogram for convenient clinical use. Conclusion: This study was the first to construct a nomogram and risk stratification system for elderly patients with TNBC. The well-established nomogram and the important findings from our study could guide follow-up management strategies for elderly patients with TNBC and help clinicians improve individual treatment.
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Affiliation(s)
- Xiaozhu Liu
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Song Yue
- Department of Gynecology and Obstetrics, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Haodong Huang
- College of Medical Informatics, The Chongqing Medical University, Chongqing, China
| | - Minjie Duan
- College of Medical Informatics, The Chongqing Medical University, Chongqing, China
| | - Binyi Zhao
- Department of Cardiology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jin Liu
- Department of Personnel, Science and Education, The Third Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Tianyu Xiang
- Information Center, The University-Town Hospital of Chongqing Medical University, Chongqing, China
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Huang YY, Wu LL, Liu X, Liang SH, Ma GW. Nomogram predict relapse-free survival of patients with thymic epithelial tumors after surgery. BMC Cancer 2021; 21:847. [PMID: 34294070 PMCID: PMC8299634 DOI: 10.1186/s12885-021-08585-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 07/12/2021] [Indexed: 12/20/2022] Open
Abstract
Background Hematological indicators and clinical characteristics play an important role in the evaluation of the progression and prognosis of thymic epithelial tumors. Therefore, we aimed to combine these potential indicators to establish a prognostic nomogram to determine the relapse-free survival (RFS) of patients with thymic epithelial tumors undergoing thymectomy. Methods This retrospective study was conducted on 156 patients who underwent thymectomy between May 2004 and August 2015. Cox regression analysis were performed to determine the potential indicators related to prognosis and combine these indicators to create a nomogram for visual prediction. The prognostic predictive ability of the nomogram was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, and risk stratification. Decision curve analysis was used to evaluate the net benefits of the model. Results Preoperative albumin levels, neutrophil-to-lymphocyte ratio (NLR), T stage, and WHO histologic types were included in the nomogram. In the training cohort, the nomogram showed well prognostic ability (C index: 0.902). Calibration curves for the relapse-free survival (RFS) were in good agreement with the standard lines in training and validation cohorts. Conclusions Combining clinical and hematologic factors, the nomogram performed well in predicting the prognosis and the relapse-free survival of this patient population. And it has potential to identify high-risk patients at an early stage. This is a relatively novel approach for the prediction of RFS in this patient population. Supplementary Information The online version contains supplementary material available at 10.1186/s12885-021-08585-y.
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Affiliation(s)
- Yang-Yu Huang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Lei-Lei Wu
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of Medicine, Tongji University, Shanghai, P. R. China
| | - Xuan Liu
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Shen-Hua Liang
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Guo-Wei Ma
- State Key Laboratory of Oncology in South China, Sun Yat-sen University Cancer Center, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
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Zhang HR, Xu MY, Yang XG, Wang F, Zhang H, Yang L, Qiao RQ, Li JK, Zhao YL, Zhang JY, Hu YC. Nomogram for Predicting the Postoperative Venous Thromboembolism in Spinal Metastasis Tumor: A Multicenter Retrospective Study. Front Oncol 2021; 11:629823. [PMID: 34249679 PMCID: PMC8264656 DOI: 10.3389/fonc.2021.629823] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 06/14/2021] [Indexed: 12/21/2022] Open
Abstract
Introduction Venous thromboembolism can be divided into deep vein thrombosis and pulmonary embolism. These diseases are a major factor affecting the clinical prognosis of patients and can lead to the death of these patients. Unfortunately, the literature on the risk factors of venous thromboembolism after surgery for spine metastatic bone lesions are rare, and no predictive model has been established. Methods We retrospectively analyzed 411 cancer patients who underwent metastatic spinal tumor surgery at our institution between 2009 and 2019. The outcome variable of the current study is venous thromboembolism that occurred within 90 days of surgery. In order to identify the risk factors for venous thromboembolism, a univariate logistic regression analysis was performed first, and then variables significant at the P value less than 0.2 were included in a multivariate logistic regression analysis. Finally, a nomogram model was established using the independent risk factors. Results In the multivariate logistic regression model, four independent risk factors for venous thromboembolism were further screened out, including preoperative Frankel score (OR=2.68, 95% CI 1.78-4.04, P=0.001), blood transfusion (OR=3.11, 95% CI 1.61-6.02, P=0.041), Charlson comorbidity index (OR=2.01, 95% CI 1.27-3.17, P=0.013; OR=2.29, 95% CI 1.25-4.20, P=0.017), and operative time (OR=1.36, 95% CI 1.14-1.63, P=0.001). On the basis of the four independent influencing factors screened out by multivariate logistic regression model, a nomogram prediction model was established. Both training sample and validation sample showed that the predicted probability of the nomogram had a strong correlation with the actual situation. Conclusion The prediction model for postoperative VTE developed by our team provides clinicians with a simple method that can be used to calculate the VTE risk of patients at the bedside, and can help clinicians make evidence-based judgments on when to use intervention measures. In clinical practice, the simplicity of this predictive model has great practical value.
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Affiliation(s)
- Hao-Ran Zhang
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Ming-You Xu
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Xiong-Gang Yang
- Department of Orthopedics, Huashan Hospital, Fudan University, Shanghai, China
| | - Feng Wang
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Hao Zhang
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Li Yang
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Rui-Qi Qiao
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Ji-Kai Li
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Yun-Long Zhao
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Jing-Yu Zhang
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
| | - Yong-Cheng Hu
- Department of Bone Tumor, Tianjin Hospital, Tianjin, China
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Chen Z, Yang F, Liu H, Fan F, Lin Y, Zhou J, Cai Y, Zhang X, Wu Y, Mao R, Zhang T. Identification of a nomogram based on an 8-lncRNA signature as a novel diagnostic biomarker for childhood acute lymphoblastic leukemia. Aging (Albany NY) 2021; 13:15548-15568. [PMID: 34106877 PMCID: PMC8221355 DOI: 10.18632/aging.203116] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2021] [Accepted: 05/21/2021] [Indexed: 12/27/2022]
Abstract
Childhood acute lymphoblastic leukemia (cALL) still represents a major cause of disease-related death in children. This study aimed to explore the prognostic value of long non-coding RNAs (lncRNAs) in cALL. We downloaded lncRNA expression profiles from the TARGET and GEO databases. Univariate, least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analyses were applied to identify lncRNA-based signatures. We identified an eight-lncRNA signature (LINC00630, HDAC2-AS2, LINC01278, AL356599.1, AC114490.1, AL132639.3, FUT8.AS1, and TTC28.AS1), which separated the patients into two groups with significantly different overall survival rates. A nomogram based on the signature, BCR ABL1 status and white blood cell count at diagnosis was developed and showed good accuracy for predicting the 3-, 5- and 7-year survival probability of cALL patients. The C-index values of the nomogram in the training and internal validation set reached 0.8 (95% CI, 0.757 to 0.843) and 0.806 (95% CI, 0.728 to 0.884), respectively. The nomogram proposed in this study objectively and accurately predicted the prognosis of cALL. In vitro experiments suggested that LINC01278 promoted the proliferation of leukemic cells and inhibited leukemic cell apoptosis by targeting the inhibition of miR-500b-3p in cALL, and LINC01278 may be a biological target for the treatment of cALL in the future.
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Affiliation(s)
- Zhang Chen
- Affiliated Hospital of Southwest Jiaotong University, Chengdu 610036, China
| | - Fan Yang
- Emergency Department, Peking University Third Hospital, Peking University School of Medicine, Beijing 100083, China
| | - Hui Liu
- Department of Neurology, General Hospital of Western Theater Command, Chengdu 610500, China
| | - Fan Fan
- Department of Neurology, General Hospital of Western Theater Command, Chengdu 610500, China
| | - Yanggang Lin
- Affiliated Hospital of Southwest Jiaotong University, Chengdu 610036, China
| | - Jinhua Zhou
- Affiliated Hospital of Southwest Jiaotong University, Chengdu 610036, China
| | - Yun Cai
- Department of Orthopedics, General Hospital of Western Theater Command, Chengdu 610083, China
| | - Xiaoxiao Zhang
- West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu 610041, China
| | - Yingxin Wu
- Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University and The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu 610031, China
| | - Rui Mao
- Affiliated Hospital of Southwest Jiaotong University, Chengdu 610036, China.,Center of Gastrointestinal and Minimally Invasive Surgery, Department of General Surgery, The Third People's Hospital of Chengdu, Affiliated Hospital of Southwest Jiaotong University and The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Chengdu 610031, China
| | - Tongtong Zhang
- Medical Research Center, The Third People's Hospital of Chengdu, The Second Chengdu Hospital Affiliated to Chongqing Medical University, Chengdu 610031, China
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Li L, Zeng Q, Xue N, Wu M, Liang Y, Xu Q, Feng L, Xing S, Chen S. A Nomogram Based on Aspartate Aminotransferase/Alanine Aminotransferase (AST/ALT) Ratio to Predict Prognosis After Surgery in Gastric Cancer Patients. Cancer Control 2021; 27:1073274820954458. [PMID: 32959672 PMCID: PMC7513419 DOI: 10.1177/1073274820954458] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
INTRODUCTION Using the TMN classification alone to predict survival in patients with gastric cancer has certain limitations, we conducted this study was to develop an effective nomogram based on aspartate aminotransferase/alanine aminotransferase (AST/ALT) ratio to predict overall survival (OS) in surgically treated gastric cancer. METHODS we retrospectively analyzed 190 cases of gastric cancer and used Cox regression analysis to identify the significant prognostic factors for OS in patients with resectable gastric cancer. The predictive accuracy of nomogram was assessed using a calibration plot, concordance index (C-index) and decision curve. This was then compared with a traditional TNM staging system. Based on the total points (TPS) by nomogram, we further divided patients into different risk groups. RESULTS multivariate analysis of the entire cohort revealed that independent risk factors for survival were age, clinical stage and AST/ALT ratio, which were entered then into the nomogram. The calibration curve for the probability of OS showed that the nomogram-based predictions were in good agreement with actual observations. Additionally, the C-index of the established nomogram for predicting OS had a superior discrimination power compared to the TNM staging system [0.794 (95% CI: 0.749-0.839) vs 0.730 (95% CI: 0.688-0.772), p < 0.05]. Decision curve also demonstrated that the nomogram was better than the TNM staging system. Based on TPS of the nomogram, we further subdivided the study cohort into 3 groups including low risk (TPS ≤ 158), middle risk (158 < TPS ≤ 188) and high risk (TPS > 188) categories. The differences in OS rate were significant among the groups. CONCLUSION the established nomogram is associated with a more accurate prognostic prediction for individual patients with resectable gastric cancer.
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Affiliation(s)
- Linfang Li
- Department of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China
| | - Qiuyao Zeng
- Department of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China
| | - Ning Xue
- Department of Clinical Laboratory, Affiliated Tumor Hospital of Zhengzhou University, 377327Henan Tumor Hospital, Zhengzhou, China
| | - Miantao Wu
- Department of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China
| | - Yaqing Liang
- Department of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China
| | - Qingxia Xu
- Department of Clinical Laboratory, Affiliated Tumor Hospital of Zhengzhou University, 377327Henan Tumor Hospital, Zhengzhou, China
| | - Lingmin Feng
- Jia Yuan Medical Reagent Co Ltd, Guangzhou, China
| | - Shan Xing
- Department of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China
| | - Shulin Chen
- Department of Clinical Laboratory Medicine, 71067Sun Yat-sen University Cancer Center; State Key Laboratory of Oncology in South China; Collaborative Innovation Center for Cancer Medicine, Guangzhou, People's Republic of China
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Chang YR, Huang WK, Wang SY, Wu CE, Chen JS, Yeh CN. A Nomogram Predicting Progression Free Survival in Patients with Gastrointestinal Stromal Tumor Receiving Sunitinib: Incorporating Pre-Treatment and Post-Treatment Parameters. Cancers (Basel) 2021; 13:cancers13112587. [PMID: 34070456 PMCID: PMC8197516 DOI: 10.3390/cancers13112587] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/12/2021] [Accepted: 05/20/2021] [Indexed: 12/25/2022] Open
Abstract
Simple Summary Sunitinib has been approved as the second-line targeted treatment for gastrointestinal stromal tumor (GIST) after imatinib failure. It is thus necessary to effectively assess prognosis after sunitinib use. However, the current assessment remains insufficient for the contemporary period. We examined prognostic factors influencing progression-free survival. Furthermore, we constructed a prognostic nomogram model using these significant pre-treatment and post-treatment variables. Abstract The present study aimed to construct a prognostic nomogram incorporating pre-treatment and post-treatment factors to predict progression-free survival (PFS) after use of sunitinib in patients with metastatic gastrointestinal stromal tumors (GISTs) following imatinib intolerance or failure. From 2007 to 2018, 109 metastatic GIST patients receiving sunitinib at Chang Gung Memorial Hospital, Taiwan, were enrolled. A prognostic nomogram to predict PFS was developed. Sixty-three male and forty-six female metastatic GIST patients, with a median age of 61 years (range: 15–91 years), received sunitinib. The median PFS for 109 patients is 9.93 months. For pre-treatment factors, male gender, body mass index more than 18.5 kg/m2, no sarcopenia status, higher lymphocyte count, lower platelet/lymphocyte ratio, good performance status, higher sunitinib dose, and non-liver metastasis were significantly associated with favorable PFS. For post-treatment factors, adverse events with hypertension, hand–foot skin reaction, and diarrhea were significantly associated with favorable PFS. However, only eight clinicopathological independent factors for PFS prediction were selected for prognostic nomogram establishment. The calibration curve for probability of PFS revealed good agreement between the nomogram prediction and actual observation. High risk patients will experience the lowest PFS. A prognostic nomogram integrating eight clinicopathological factors was constructed to assist prognostic prediction for individual patients with advanced GIST after sunitinib use.
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Affiliation(s)
- Yau-Ren Chang
- Department of Surgery and GIST Team, Chang Gung Memorial Hospital at Linkou, ChangGung University College of Medicine, Taoyuan 33305, Taiwan; (Y.-R.C.); (S.-Y.W.)
| | - Wen-Kuan Huang
- Division of Hematology-Oncology, Department of Internal Medicine and GIST Team, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan 33305, Taiwan; (W.-K.H.); (C.-E.W.); (J.-S.C.)
| | - Shang-Yu Wang
- Department of Surgery and GIST Team, Chang Gung Memorial Hospital at Linkou, ChangGung University College of Medicine, Taoyuan 33305, Taiwan; (Y.-R.C.); (S.-Y.W.)
| | - Chiao-En Wu
- Division of Hematology-Oncology, Department of Internal Medicine and GIST Team, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan 33305, Taiwan; (W.-K.H.); (C.-E.W.); (J.-S.C.)
| | - Jen-Shi Chen
- Division of Hematology-Oncology, Department of Internal Medicine and GIST Team, Chang Gung Memorial Hospital at Linkou, Chang Gung University College of Medicine, Taoyuan 33305, Taiwan; (W.-K.H.); (C.-E.W.); (J.-S.C.)
| | - Chun-Nan Yeh
- Department of Surgery and GIST Team, Chang Gung Memorial Hospital at Linkou, ChangGung University College of Medicine, Taoyuan 33305, Taiwan; (Y.-R.C.); (S.-Y.W.)
- Correspondence: ; Tel.: +886-3281200
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Li X, Xu H, Yan L, Gao J, Zhu L. A Novel Clinical Nomogram for Predicting Cancer-Specific Survival in Adult Patients After Primary Surgery for Epithelial Ovarian Cancer: A Real-World Analysis Based on the Surveillance, Epidemiology, and End Results Database and External Validation in a Tertiary Center. Front Oncol 2021; 11:670644. [PMID: 33959514 PMCID: PMC8093627 DOI: 10.3389/fonc.2021.670644] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Accepted: 03/30/2021] [Indexed: 12/18/2022] Open
Abstract
Background The present study aimed to construct and validate a nomogram that can be used to predict cancer-specific survival (CSS) in patients with epithelial ovarian cancer (EOC). Methods A total of 7,129 adult patients with EOC were extracted from the Surveillance, Epidemiology, and End Results database between 2010 and 2015. Patients were randomly divided into the training and validation cohorts (7:3). Cox regression was conducted to evaluate prognostic factors of CSS. The internal validation of the nomogram was performed using concordance index (C-index), AUC, calibration curves, and decision curve analyses (DCAs). Data from 53 adult EOC patients at Shengjing Hospital of China Medical University from 2008 to 2012 were collected for external verification. Kaplan-Meier curves were plotted to compare survival outcomes among risk subgroups. Results Age, grade, histological types, stage, residual lesion size, number of regional lymph nodes resected, number of positive lymph nodes, and chemotherapy were independent risk factors for CSS. Based on the above factors, we constructed a nomogram. The C-indices of the training cohort, internal validation cohort, and external verification group were 0.763, 0.750, and 0.920, respectively. The calibration curve indicated good agreement between the nomogram prediction and actual survival. AUC and DCA results indicated great clinical usefulness of the nomogram. The differences in the Kaplan-Meier curves among different risk subgroups were statistically significant. Conclusions We constructed a nomogram to predict CSS in adult patients with EOC after primary surgery, which can assist in counseling and guiding treatment decision making.
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Affiliation(s)
- Xianli Li
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Haoya Xu
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Limei Yan
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Jian Gao
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Liancheng Zhu
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
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Prognostic Exploration of All-Cause Death in Gingival Squamous Cell Carcinoma: A Retrospective Analysis of 2076 Patients. JOURNAL OF ONCOLOGY 2021; 2021:6676587. [PMID: 33854548 PMCID: PMC8019369 DOI: 10.1155/2021/6676587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/30/2020] [Accepted: 03/12/2021] [Indexed: 12/27/2022]
Abstract
Background We aimed to establish a prognostic model for gingival squamous cell carcinoma (GSCC) that was superior to traditional AJCC staging and to perform a comprehensive comparison of the newly established nomogram with the AJCC staging system. Methods We extracted 2,076 patients with gingival squamous cell carcinoma who had been entered into the SEER (Surveillance, Epidemiology, and End Results) database between 2004 and 2015, and randomly divided 70% of them into the training cohort and the other 30% into the validation cohort. Cox regression analysis was performed in combination with clinical experience and age, race, sex, marital status, tumor location, histological subtype, tumor grade, AJCC stage, chemotherapy status, radiotherapy status, and surgery status as possible prognostic factors. We evaluated and compared the two cohorts using the consistency index (C-index), area under the receiver operating characteristic curves, calibration curves, discriminant improvement index, and decision-curve analysis. Results The Cox retrospective analysis showed that age, AJCC stage, tumor grade, histological subtype, radiotherapy status, and surgery status were significant factors to include in the new model of gingival squamous cell carcinoma. The other indicators were also better for the new model than for the AJCC staging system. Conclusion We have developed and validated a nomogram for performing reliable gingival squamous cell carcinoma prognoses. The prognostic value of the nomogram is higher than that of the AJCC staging system. We expect that the inclusion of more-comprehensive and authoritative data (i.e., not just limited to residents of the United States) would also allow the construction of reliable nomograms for other populations.
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Prognostic Nomogram for pancreatic cancer with lung metastasis: a SEER database-based study. JOURNAL OF PANCREATOLOGY 2021. [DOI: 10.1097/jp9.0000000000000059] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
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Dong W, Yan K, Yu H, Huo L, Xian Z, Zhao Y, Li J, Zhang Y, Cao Z, Fu Y, Cong W, Dong H. Prognostic Nomogram for Sorafenib Benefit in Hepatitis B Virus-Related Hepatocellular Carcinoma After Partial Hepatectomy. Front Oncol 2021; 10:605057. [PMID: 33643907 PMCID: PMC7906076 DOI: 10.3389/fonc.2020.605057] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 12/14/2020] [Indexed: 12/24/2022] Open
Abstract
Background Predicting the long-term prognosis of individuals who experienced sorafenib treatment following partial hepatectomy due to hepatitis B virus (HBV) related hepatocellular carcinoma (HCC) is difficult. This work aims to create an effective prognostic nomogram for HBV related HCC patients who are receiving sorafenib treatment as adjuvant therapy after surgery. Methods A total of 233 HBV-related HCC patients treated with or without sorafenib following partial hepatectomy at the Eastern Hepatobiliary Surgery Hospital from 2008 to 2013 were matched with propensity score matching analysis. The optimal cut-off point of the overall survival (OS) factor level was determined by x-tile. The selection of indicators was based on clinical findings. The Cox regression model with an interaction term was employed for evaluating the predictive value. Using a multivariate Cox proportional hazards model, a nomogram was subsequently formulated to analyze 111 patients treated with sorafenib. The nomogram's discriminative ability and predictive accuracy were determined using the concordance index (C-index), calibration, and ROC curve. Results The matched sorafenib cohort of 111 patients and control cohort of 118 patients were analyzed. Subgroup analysis revealed that low GPC3, pERK, pAKT, serum AFP levels, without MVI, under 50 years old, male, TNM stage I/II and BCLC stage 0/A were significantly associated with a better OS in patients subjected to sorafenib treatment compared to those without sorafenib treatment after surgery. Multivariate analysis of the sorafenib cohort revealed GPC3, pERK, pAKT, serum AST, and BCLC stage as independent factors for OS, and all were included in the nomogram. The survival probability based on the calibration curve showed that the prediction of the nomogram was in good agreement with the actual observation. The C-index of the nomogram for predicting survival was 0.73(95% CI, 0.67-0.78). The area under the ROC curve (AUC) for the nomogram to predict the survival for 1, 3, and 5-year was 0.726, 0.816, and 0.823, respectively. Conclusion This proposed nomogram shows the potential to make a precise prediction regarding the prognosis of HBV-related HCC patients and may help to stratify patients for personalized therapy following partial hepatectomy.
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Affiliation(s)
- Wei Dong
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Kai Yan
- The Fifth Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China
| | - Hua Yu
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Lei Huo
- Department of Radiology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China
| | - Zhihong Xian
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Yanqing Zhao
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Jutang Li
- Department of Gynaecology and Obstetrics, Tong Ren Hospital, Shanghai Jiao Tong University of Medicine, Shanghai, China
| | - Yuchan Zhang
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Zhenying Cao
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Yong Fu
- The Fifth Department of Hepatic Surgery, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China
| | - Wenming Cong
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
| | - Hui Dong
- Department of Pathology, Eastern Hepatobiliary Surgery Hospital, the Second Military Medical University, Shanghai, China.,Key Laboratory of Signaling Regulation and Targeting Therapy of Liver Cancer, the Second Military Medical University, Shanghai, China
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Xie N, Xu Y, Zhong Y, Li J, Yao H, Qin T. Clinicopathological Characteristics and Treatment Strategies of Triple-Negative Breast Cancer Patients With a Survival Longer than 5 Years. Front Oncol 2021; 10:617593. [PMID: 33598434 PMCID: PMC7882729 DOI: 10.3389/fonc.2020.617593] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 12/17/2020] [Indexed: 12/27/2022] Open
Abstract
Purpose Triple-negative breast cancer (TNBC) is characterized by high malignancy and a poor prognosis. Patients with TNBC who survive longer than 5 years represent a unique portion of the population. This study aimed to analyze the clinicopathological features, explore prognostic factors, and evaluate treatment options for these patients. Methods A total of 24,943 TNBC patients were enrolled from the national Surveillance, Epidemiology, and End Results (SEER) database between January 2010 and December 2016. The patients were divided into three groups: group 1, survival time <3 years; group 2, 3–5 years; and group 3, survival time ≥5 years. The overall survival (OS) and breast cancer cause-specific survival (BCSS) were primarily assessed in this study. A propensity score analysis was used to avoid bias caused by the data selection criteria. We used a Cox hazard ratio analysis to determine prognostic factors, which were selected as nomogram parameters to develop a model for predicting patient survival. Results Patients who survived longer than 5 years were more likely to be younger than 55 years, Caucasian, and exhibit a lower AJCC stage, N stage, distant metastasis, lymph node (LN) involvement, and tumor size than those with a shorter survival time (p < 0.05). The multivariable Cox regression analysis showed that age, race, tumor size, LN status, and chemotherapy were independent prognostic factors. Subgroup analyses for patients with tumors ≤20 mm displayed a superior OS and BCSS for breast-conserving surgery (BCS) not treated with a mastectomy. BCS provided at least an equivalent prognosis to a mastectomy in patients with tumors larger than 20 mm. A nomogram with a C-index of 0.776 (95% confidence interval: 0.767–0.785) was developed to predict the 3- and 5-year survival probability for the patients with TNBC. Conclusion A localized surgical approach may represent a superior choice for TNBC patients with a survival time longer than 5 years. Our study indicated that age, race, tumor size, LN status, and chemotherapy were independent prognostic factors. A prognostic nomogram directly quantified patient risk and was better able to predict long-term survival in TNBC patients.
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Affiliation(s)
- Ning Xie
- Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Xu
- Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Ying Zhong
- Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Junwei Li
- Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Herui Yao
- Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Guangdong Provincial Key Laboratory of Malignant Tumor Epigenetics and Gene Regulation, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China.,Breast Tumor Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Tao Qin
- Department of Medical Oncology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
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Jin L, Zou Y, Ruan S, Han H, Zhang Y, Chen Z, Jin H, Shi N. Score for predicting overall survival in pancreatic adenocarcinoma patients with positive lymph nodes after surgery: a novel nomogram-based risk assessment. Gland Surg 2021; 10:529-540. [PMID: 33708536 DOI: 10.21037/gs-20-597] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background Pancreatic adenocarcinoma (PaC) patients with positive lymph nodes (PLNs) have a dismal prognosis and lack a specific prognostic stage. This study aimed to construct a nomogram for the prediction of overall survival (OS) in these patients. Methods A total of 1,340 patients screened from the Surveillance, Epidemiology, and End Results database were included and randomly divided at a ratio of 7:3 into a training set (n=940) and an internal validation set (n=400). Cox regression analyses were conducted to select independent predictors in the training set, and a nomogram was constructed. The model was verified in the internal validation set and in an external validation set, which comprised 64 patients from a Chinese institute. Results Six independent prognostic factors (age at diagnosis, tumor grade, lymph node ratio, T stage, radiotherapy, and chemotherapy) were identified in PaC patients with PLNs and were entered into the nomogram. The final model had a higher C-index for predicting OS than the American Joint Committee on Cancer-8th edition staging system (training set: 0.658 vs. 0.546; internal validation set: 0.661 vs. 0.546; external validation set: 0.691 vs. 0.581). The 1-, 2-, and 3-year area under the receiver operating characteristic curve values indicated better discrimination power for the established nomogram with respect to the prediction of OS in the training, internal validation, and external validation sets than for the American Joint Committee on Cancer-8th edition staging system. Furthermore, the nomogram performed well in both calibration and decision curve analyses (DCA) of clinical applicability. OS in PaC patients with PLNs was significantly distinguished among the three risk groups stratified according to the nomogram score (P<0.001). Conclusions The well-calibrated nomogram was determined to be extremely efficient in predicting survival, and defining a high-risk population based on the nomogram score among PaC patients with PLNs after surgery.
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Affiliation(s)
- Liang Jin
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yiping Zou
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Shiye Ruan
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Hongwei Han
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yuanpeng Zhang
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhihong Chen
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Haosheng Jin
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Ning Shi
- Department of General Surgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
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Wang J, Fan Y, Xia L. Nomograms to predict lung metastasis probability and lung metastasis subgroup survival in malignant bone tumors. Future Oncol 2021; 17:649-661. [PMID: 33464127 DOI: 10.2217/fon-2020-0553] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
The aim of this study was to construct and validate nomograms for predicting lung metastasis and lung metastasis subgroup overall survival in malignant primary osseous neoplasms. Least absolute shrinkage and selection operator, logistic and Cox analyses were used to identify risk factors for lung metastasis in malignant primary osseous neoplasms and prognostic factors for overall survival in the lung metastasis subgroup. Further, nomograms were established and validated. A total of 3184 patients were collected. Variables including age, histology type, American Joint Committee on Cancer T and N stage, other site metastasis, tumor extension and surgery were extracted for the nomograms. The authors found that nomograms could provide an effective approach for clinicians to identify patients with a high risk of lung metastasis in malignant primary osseous neoplasms and perform a personalized overall survival evaluation for the lung metastasis subgroup.
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Affiliation(s)
- Jie Wang
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, PR China
| | - Yonggang Fan
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, PR China
| | - Lei Xia
- Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, PR China
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46
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Meng X, Ma H, Yin H, Yin H, Yu L, Liu L, Li T, Wang S, Xu Q. Nomogram Predicting the Risk of Locoregional Recurrence After Mastectomy for Invasive Micropapillary Carcinoma of the Breast. Clin Breast Cancer 2021; 21:e368-e376. [PMID: 33414079 DOI: 10.1016/j.clbc.2020.12.003] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Revised: 12/04/2020] [Accepted: 12/09/2020] [Indexed: 11/17/2022]
Abstract
BACKGROUND The risk of locoregional recurrence (LRR) after mastectomy for breast invasive micropapillary carcinoma (IMPC) remains poorly defined. We aimed to construct an effective prognostic nomogram to estimate the individualized risk of LRR for providing accurate information for long-term follow-up. PATIENTS AND METHODS A total of 388 patients with breast IMPC were included in the current study. Based on the Cox regression and clinical significance, a nomogram with an online prediction version was created. This model was evaluated and internally validated by concordance index and calibration plot. Receiver operating characteristic curve and decision curve analysis were used to assess the discrimination and clinical utility, and Kaplan-Meier curves estimated the probability of LRR. RESULTS The variables (age, lymph node metastasis, hormone receptor status, lymphovascular invasion, histologic grade, and adjuvant radiotherapy) were included in the nomogram. This model was well-calibrated to predict the possibility of LRR and displayed favorable clinical utility; the concordance index was 0.86 (95% confidence interval, 0.81-0.91), which was higher than any single predictor. The area under the curve of the nomogram was 0.89, whereas that of the conventional staging system was 0.72. An online prognostic nomogram was built for convenient use. Kaplan-Meier curves showed that the nomogram had a better risk stratification than the conventional staging system. CONCLUSIONS The nomogram could accurately predict the individualized risk of LRR after mastectomy for breast IMPC. By identifying the risk stratification, this model is expected to assist clinicians and patients in improving long-term follow-up strategies.
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Affiliation(s)
- Xiangdi Meng
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Hongyu Ma
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Hang Yin
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Huizi Yin
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Lili Yu
- Department of Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Li Liu
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Tingting Li
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Siqi Wang
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China
| | - Qingyong Xu
- Department of Breast Radiotherapy, Harbin Medical University Cancer Hospital, Harbin, Heilongjiang, China.
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Mao R, Guo P, Lin Z, Yang H, Jayachandran M, Xu C, Zhang T, Qu S, Liu Y. Nomograms for Predicting Non-remission in Patients Who Underwent Bariatric Surgery: A Multicenter Retrospective Study in China. Obes Surg 2021; 31:1967-1978. [PMID: 33415611 DOI: 10.1007/s11695-020-05206-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Revised: 12/23/2020] [Accepted: 12/29/2020] [Indexed: 12/12/2022]
Abstract
BACKGROUND As a reflection of the increasing global incidence of obesity, there is a corresponding increase in the proportion of obese patients undergoing bariatric surgery. This study reviewed the factors and outcomes of patients who underwent bariatric surgical procedures and determined the relationships and developed a nomogram to calculate individualized patient risk. METHODS The nomogram was based on a retrospective study on 259 patients who underwent bariatric surgery at the Chengdu Third People's Hospital from June 2017 to June 2019. The predictive accuracy and discriminative ability of the nomogram were determined by the ROC curve and C-index, respectively. The results were validated using bootstrap resampling and a retrospective study on 121 patients operated on from May 2015 to May 2019 at the Tenth People's Hospital of Shanghai. RESULTS The predictors contained in the prediction nomogram included age, sex, surgical approach, hyperlipidemia, blood pressure (BP), hyperuricemia, body mass index (BMI), and waist circumference (WC). The 6-month model displayed good discrimination with a C-index of 0.765 (95% CI: 0.756 to 0.774) and good calibration. The 1-year model reached a C-index of 0.768 (95% CI, 0.759 to 0.777) in the training cohort. CONCLUSIONS The proposed nomogram resulted in more accurate non-remission prediction for patients with obesity after bariatric surgery and may provide a reference for the preoperative choice of surgical methods.
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Affiliation(s)
- Rui Mao
- Affiliated Hospital of Southwest Jiaotong University, Chengdu, 610036, China
| | - Pengsen Guo
- Affiliated Hospital of Southwest Jiaotong University, Chengdu, 610036, China
| | - Ziwei Lin
- Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, No. 301 Middle Yanchang Road, Shanghai, 200072, China
| | - Huawu Yang
- The Center of Gastrointestinal and Minimally Invasive Surgery, The Third People's Hospital of Chengdu; Affiliated Hospital of Southwest Jiaotong University, Qinglong Road, Chengdu, 610031, China
| | - Muthukumaran Jayachandran
- Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, No. 301 Middle Yanchang Road, Shanghai, 200072, China
| | - Chenxin Xu
- Affiliated Hospital of Southwest Jiaotong University, Chengdu, 610036, China
| | - Tongtong Zhang
- Medical Research Center, The Third People's Hospital of Chengdu, The Second Affiliated Hospital of Chengdu, Chongqing Medical University, Sichuan Province, Chengdu, 610031, China. .,Medical Research Center, The Third People's Hospital of Chengdu, 82 Qinglong street, Qingyang District, Chengdu, 610031, Sichuan Province, China.
| | - Shen Qu
- Department of Endocrinology and Metabolism, Shanghai Tenth People's Hospital, No. 301 Middle Yanchang Road, Shanghai, 200072, China.
| | - Yanjun Liu
- Affiliated Hospital of Southwest Jiaotong University, Chengdu, 610036, China. .,The Center of Gastrointestinal and Minimally Invasive Surgery, The Third People's Hospital of Chengdu; Affiliated Hospital of Southwest Jiaotong University, Qinglong Road, Chengdu, 610031, China.
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Zhang W, Ji L, Wang X, Zhu S, Luo J, Zhang Y, Tong Y, Feng F, Kang Y, Bi Q. Nomogram Predicts Risk and Prognostic Factors for Bone Metastasis of Pancreatic Cancer: A Population-Based Analysis. Front Endocrinol (Lausanne) 2021; 12:752176. [PMID: 35356148 PMCID: PMC8959409 DOI: 10.3389/fendo.2021.752176] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 12/30/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The overall survival (OS) of pancreatic cancer (PC) patients with bone metastasis (BM) is extremely low, and it is pretty hard to treat bone metastasis. However, there are currently no effective nomograms to predict the diagnosis and prognosis of pancreatic cancer with bone metastasis (PCBM). Therefore, it is of great significance to establish effective predictive models to guide clinical practice. METHODS We screened patients from Surveillance Epidemiology and End Results (SEER) database between 2010 and 2016. The independent risk factors of PCBM were identified from univariable and multivariable logistic regression analyses, and univariate and multivariate Cox proportional hazards regression analyses were used to determine independent prognostic factors affecting the prognosis of PCBM. In addition, two nomograms were constructed to predict the risk and prognosis of PCBM. We used the area under the curve (AUC), C-index and calibration curve to determine the predictive accuracy and discriminability of nomograms. The decision curve analysis (DCA) and Kaplan-Meier(K-M) survival curves were employed to further confirm the clinical effectiveness of the nomogram. RESULTS Multivariable logistic regression analyses revealed that risk factors of PCBM included age, primary site, histological subtype, N stage, radiotherapy, surgery, brain metastasis, lung metastasis, and liver metastasis. Using Cox regression analyses, we found that independent prognostic factors of PCBM were age, race, grade, histological subtype, surgery, chemotherapy, and lung metastasis. We utilized nomograms to visually express data analysis results. The C-index of training cohort was 0.795 (95%CI: 0.758-0.832), whereas that of internal validation cohort was 0.800 (95%CI: 0.739-0.862), and the external validation cohort was 0.787 (95%CI: 0.746-0.828). Based on AUC of receiver operating characteristic (ROC) analysis, calibration plots, and decision curve analysis (DCA), we concluded that the risk and prognosis model of PCBM exhibits excellent performance. CONCLUSION Nomogram is sufficiently accurate to predict the risk and prognostic factors of PCBM, allowing for individualized clinical decisions for future clinical work.
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Affiliation(s)
- Wei Zhang
- Department of Orthopedics, Zhejiang Provincial People's Hospital, Qingdao University, Qingdao, China
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
| | - Lichen Ji
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Xijun Wang
- Department of Head and Neck Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China
- State Key Laboratory of Oncology in South China, Sun Yat-sen University, Guangzhou, China
- Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University, Guangzhou, China
| | - Senbo Zhu
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Junchao Luo
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Yin Zhang
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Graduate Department, Bengbu Medical College, Bengbu, China
| | - Yu Tong
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, The Second Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Fabo Feng
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, Hangzhou Medical College People's Hospital, Hangzhou, China
| | - Yao Kang
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, Hangzhou Medical College People's Hospital, Hangzhou, China
- *Correspondence: Yao Kang, ; Qing Bi,
| | - Qing Bi
- Department of Orthopedics, Zhejiang Provincial People’s Hospital, Hangzhou, China
- Department of Orthopedics, Hangzhou Medical College People's Hospital, Hangzhou, China
- *Correspondence: Yao Kang, ; Qing Bi,
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Gao ZY, Zhang T, Zhang H, Pang CG, Jiang WX. Establishment and validation of nomogram model for survival predicting in patients with spinal metastases secondary to lung cancer. Neurol Res 2020; 43:327-335. [PMID: 33377432 DOI: 10.1080/01616412.2020.1866244] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVES To evaluate the prognostic effect of pre-treatment factors in patients with spinal metastases secondary to lung cancer, and establish a novel predicting nomogram for predicting the survival probability. METHODS A total of 209 patients operated for spinal metastases from lung cancer were consecutively enrolled, and divided into the training and validation samples with a ratio of 7:3, for model establishing and validating, respectively. Basing on the training sample, univariate and multivariate COX proportional hazard models were used for identifying the prognostic effect of pre-treatment factors, following which significant prognostic factors would be listed as items in nomogram to calculate the survival probabilities at 3, 6, 12 and 18 months. Then, the C-indexes and the calibration curves would be figured out to evaluate the discrimination ability and accuracy of the model both for the training and validation samples. RESULTS In the multivariate COX analysis, the gender, smoking history, location of spinal metastasis, visceral metastasis, Karnofsky performance status (KPS), adjuvant therapy, lymphocyte percentage and globulin were found to be significantly associated with the overall survival, and a novel nomogram was generated basing on these independent predictors. The C-indexes for the training and validation samples were 0.761 and 0.732, respectively. Favorable consistencies between the predicted and actual survival rates were demonstrated both in the internal and external validations. DISCUSSION Pre-treatment characteristics, including gender, smoking history, location of spinal metastasis, visceral metastasis, KPS, adjuvant therapy, percentage of lymphocyte, and serum globulin level, were identified to be significantly associated with overall survival of patients living with spinal metastases derived from lung cancer, and a user-friendly nomogram was established using these independent predictors.
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Affiliation(s)
- Zhong-Yu Gao
- Department of Orthopedic Surgery, Tianjin First Central Hospital, Tianjin, China
| | - Tao Zhang
- Department of Orthopedic Surgery, Tianjin First Central Hospital, Tianjin, China
| | - Hui Zhang
- Department of Orthopedic Surgery, Tianjin First Central Hospital, Tianjin, China
| | | | - Wen-Xue Jiang
- Department of Orthopedic Surgery, Tianjin First Central Hospital, Tianjin, China
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Prognostic Inflammatory Index Based on Preoperative Peripheral Blood for Predicting the Prognosis of Colorectal Cancer Patients. Cancers (Basel) 2020; 13:cancers13010003. [PMID: 33374924 PMCID: PMC7792597 DOI: 10.3390/cancers13010003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/08/2020] [Accepted: 12/19/2020] [Indexed: 12/24/2022] Open
Abstract
Simple Summary Inflammation plays a critical role in the progression of colorectal cancer (CRC). Peripheral blood cell counts could reflect the extent of systemic inflammation and are readily available in clinical practice. The aim of our study was to construct a novel prognostic inflammatory index (PII) by integrating the blood cell counts associated with prognosis and to evaluate and validate the prognostic value of PII in two independent CRC cohorts. Multivariate Cox analyses in the training cohort of 4154 CRC patients indicated that high OS-PII (>4.27) and high DFS-PII (>4.47) were significantly associated with worse OS (HR: 1.330, p < 0.001) and worse DFS (HR: 1.366, p < 0.001), which has been validated in the external validation cohort of 5161 patients. Both OS-PII and DFS-PII have a stable prognostic performance at various follow-up times, and the nomograms based on OS-PII and DFS-PII achieved good accuracy in personalized survival prediction of patients with CRC. Abstract Host inflammation is a critical component of tumor progression and its status can be indicated by peripheral blood cell counts. We aimed to construct a comprehensively prognostic inflammatory index (PII) based on preoperative peripheral blood cell counts and further evaluate its prognostic value for patients with colorectal cancer (CRC). A total of 9315 patients with stage II and III CRC from training and external validation cohorts were included. The PII was constructed by integrating all the peripheral blood cell counts associated with prognosis in the training cohort. Cox analyses were performed to evaluate the association between PII and overall survival (OS) and disease-free survival (DFS). In the training cohort, multivariate Cox analyses indicated that high OS-PII (>4.27) was significantly associated with worse OS (HR: 1.330, 95% CI: 1.189–1.489, p < 0.001); and high DFS-PII (>4.47) was significantly associated with worse DFS (HR: 1.366, 95% CI: 1.206–1.548, p < 0.001). The prognostic values of both OS-PII and DFS-PII were validated in the external validation cohort. The nomograms achieved good accuracy in predicting both OS and DFS. Time-dependent ROC analyses showed that both OS-PII and DFS-PII have a stable prognostic performance at various follow-up times. The prognostic value of tumor-node-metastasis staging could be enhanced by combining it with either OS-PII or DFS-PII. We demonstrated that PIIs are independent prognostic predictors for CRC patients, and the nomograms based on PIIs can be recommended for personalized survival prediction of patients with CRC.
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