scholarly journals A Novel Nomogram for Predicting Cancer-Specific Survival in Women with Uterine Sarcoma: A Large Population-Based Study

2021 ◽  
Author(s):  
Yuan-jie Li ◽  
Jun Lyu ◽  
Chen Li ◽  
Hai-rong He ◽  
Jin-feng Wang ◽  
...  
Keyword(s):  
Cox Regression ◽  
Validation Cohort ◽  
Large Population ◽  
Staging System ◽  
Uterine Sarcoma ◽  
Operating Characteristics ◽  
Cancer Specific Survival ◽  
Cox Regression Analysis ◽  
Ajcc Staging System ◽  
Ajcc Staging

Abstract Background: To develop a comprehensive nomogram for predicting the cancer-specific survival (CSS) for uterine sarcoma (US).Methods: 3861 patients of US between 2010 to 2015 were identified for this study from the Surveillance, Epidemiology, and End Results (SEER) database. They were randomly divided into a training cohort (n = 2702) and a validation cohort (n = 1159) in a 7-to-3 ratio by R software. Multivariate Cox regression analysis was performed to select predictive variables and then to identify independent prognostic factors. The concordance index (C-index), the area under the time-dependent receiver operating characteristics curve (AUC), the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to compare the new survival nomogram with the AJCC 7th edition prognosis model.Results: We have established a nomogram for determining the 1-, 3-, and 5-year CSS probabilities of US patients. In this nomogram, pathology grade has the highest risk on CSS in US, followed by the age at diagnosis, then surgery status. The C-index for the nomogram (0.796, 0.767 for the training and validation cohort, respectively) was higher than those for the AJCC staging system (0.706 and 0.713, respectively). Furthermore, AUC value, NRI, IDI, calibration plotting, and DCA showed that this nomogram exhibited better performance than the AJCC staging system alone.Conclusion: Our study validated the first comprehensive nomogram for US which could provide more accurately and individualized survival predictions for US patients in clinical practice.

A single-institution validation of the AJCC staging system for stage IV melanoma

2007 ◽  
Vol 25 (18_suppl) ◽  
pp. 8517-8517
Author(s):  
H. Neuman ◽  
A. Patel ◽  
C. Hanlon ◽  
M. S. Brady ◽  
A. C. Halpern ◽  
...  
Keyword(s):  
Cox Regression ◽  
Stage Iv ◽  
Staging System ◽  
Single Institution ◽  
Cox Regression Analysis ◽  
Tertiary Center ◽  
Staging Systems ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
Stage Iv Melanoma

8517 Background: We sought to validate the AJCC staging system for stage IV melanoma in a contemporary, prospective, single- institution cohort and explore additional clinical factors that may influence prognosis. Methods: A prospective institutional database identified 1319 patients with stage IV melanoma. To minimize tertiary center referral bias, only patients seen prior to a stage IV diagnosis were included (n=687). Variables were dichotomized: lactate dehydrogenase (LDH) (=200, >200), number of metastases (1, >1), and number of involved organs (1, >1). Kaplan-Meier curves were generated and Cox regression was used to identify factors independently predictive of survival. Results: Demographics are provided in the table . The median age at diagnosis of stage IV was 55 years (range 16–94) and the median disease free interval (DFI) was 12 months (0–181). The overall median survival was 10 months (5–21) with a median follow-up for survivors of 31 months (9–68); 569 deaths were observed. Cox regression analysis ( table ) identified younger age at stage IV diagnosis, a longer DFI, and a normal LDH to be predictive of improved survival. Patients with either distant skin/subcutaneous/nodal or pulmonary disease experienced prolonged survival when compared to patients with metastases to other visceral sites. Survival was improved in patients with a single metastatic site at diagnosis of stage IV. Gender, antecedent stage, and number of involved organs were not associated with outcome. Conclusions: In this single institution cohort of patients with stage IV melanoma, poorer survival in patients with non-pulmonary visceral metastases and/or abnormal LDH levels as described by the AJCC staging system was confirmed. Additionally, the number of metastases at the time of diagnosis of stage IV was the most powerful predictor of poorer survival and may be a variable to consider in future staging systems. No significant financial relationships to disclose. [Table: see text]

scholarly journals Survival analysis of patients with stage T2a and T2b perihilar cholangiocarcinoma treated with radical resection

2020 ◽  
Author(s):  
Jian Zhao ◽  
Wei Zhang ◽  
Jun Zhang ◽  
Yi Zhang ◽  
Wenjie Ma ◽  
...  
Keyword(s):  
Cox Regression ◽  
Staging System ◽  
Tnm Staging ◽  
Perihilar Cholangiocarcinoma ◽  
Curative Intent ◽  
Cox Regression Analysis ◽  
Significant Difference ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
8Th Edition

Abstract Background: Both the 7th and 8th editions of the American Joint Committee on Cancer (AJCC) staging system for perihilar cholangiocarcinoma (pCCA) had the same definition for T2a and T2b. But the value of this classification as prognostic factor remains unclear. Methods: 178 patients with stage T2a or T2b who underwent curative intent resection for pCCA between Jan 2010 and Dec 2018 were enrolled. Relationships between survival and clinicopathological factors including patient demographics and tumor characteristics were evaluated using univariate and multivariate Cox regression analysis. The overall survival (OS) were calculated by Kaplan-Meier method.Results: There was no significant difference in OS between T2a and T2b groups，and the median OS duration were 37 and 31 months (P=0.354). Both the 7th and 8th edition of the AJCC TNM staging demonstrated a poor prognostic predictive performance. High level of preoperative AST (≥85.0IU/L) and CA19-9 (≥1000 U/mL), vascular resection and lower pathological differentiation of the tumor were the independent predictors for poor survival after resection.Conclusion: The newly released 8th edition of AJCC staging system demonstrated a poor ability to discriminate the prognosis of patients with stage T2a and T2b pCCA after resection.

scholarly journals Development and validation of a nomogram to predict cancer-specific survival of uveal melanoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qiaozhu Zeng ◽  
Yuou Yao ◽  
Mingwei Zhao
Keyword(s):  
Prognostic Factors ◽  
Uveal Melanoma ◽  
Validation Cohort ◽  
Staging System ◽  
Competing Risk ◽  
Cancer Specific Survival ◽  
Training Cohort ◽  
Ajcc Staging System ◽  
Ajcc Staging

Abstract Background Uveal melanoma (UM) is a rare but aggressive cancer, which is the most common primary intraocular malignancy in adults. We aimed to develop and validate a competing risk nomogram to predict cancer-specific survival (CSS) of patients with UM, as well as compare its prognostic value with that of the American Joint Committee on Cancer (AJCC) staging system. Methods Data of patients diagnosed with UM from 2010 to 2015 were identified from the Surveillance, Epidemiology, and End Results (SEER) database. We extracted and integrated significant prognostic factors based on competing risk regression to build a nomogram. The nomogram with an online prediction version was also created. The performance of the nomogram was evaluated using Harrell’s concordance index (C-index) and calibration plots. Receiver operating characteristic (ROC) curve was carried out to estimate clinical applicability of the model. Improvements in the predictive accuracy of our new model compared with AJCC staging system were estimated by calculating the relative integrated discrimination improvement (IDI) and the net reclassification improvement (NRI). Results A total of 839 eligible patients with primary UM were randomly assigned to a training cohort (588, 70%) and a validation cohort (251, 30%). Age, histological type, T stage and M stage were independent prognostic factors to predict CSS of UM and were incorporated in the nomogram. The calibration plots indicated that the 3- and 5-year CSS probabilities were consistent between the nomogram prediction and the actual observation. The C-index for this model was 0.778 (95% CI:0.756–0.800) and 0.786 (95% CI: 0.749–0.816) in the training cohort and validation cohort. Areas under the curve (AUCs) were 0.814, 0.771, and 0.792 in the training cohort, 0.788, 0.781 and 0.804 in the validation cohort, respectively. The NRI value in AJCC staging system was − 0.153 (95% CI -0.29 – − 0.041) for 3 years of follow-up and − 0.276 (95% CI -0.415 – − 0.132) for 5 years of follow-up. The IDI values for 3 and 5 years of follow-up in the AJCC staging system were − 0.021 (P = 0.076) and − 0.045 (P = 0.004), respectively. Conclusions We have developed and validated a competing risk nomogram to reliably predict cancer-specific survival of patients with UM. This convenient tool may be useful for evaluating cancer-specific prognosis.

scholarly journals A Novel Nomogram for Predicting Cancer-specific Survival in Women With Uterine Sarcoma: a Large Population-based Study

2021 ◽  
Author(s):  
Yuan-jie Li ◽  
Jun Lyu ◽  
Chen Li ◽  
Hai-rong He ◽  
Jin-feng Wang ◽  
...  
Keyword(s):  
Validation Cohort ◽  
Large Population ◽  
Area Under The Curve ◽  
Staging System ◽  
Population Based ◽  
Uterine Sarcoma ◽  
Cancer Specific Survival ◽  
Traditional System ◽  
Net Reclassification Improvement ◽  
Cox Analysis

Abstract Background: To perform a comprehensive nomogram to predict the cancer-specific survival (CSS) for uterine sarcoma (US) based on the Surveillance, Epidemiology, and End Results (SEER) database.Methods: A total of 3861 patients with US between 2010 and 2015 were identified in this study. They were randomly divided into a training cohort (n = 2702) and a validation cohort (n = 1159) in a 7-to-3 ratio by R software. We performed multivariate Cox analysis to select predictive variables and identify independent prognostic factors. Then, the discrimination and calibration of the nomogram were evaluated by concordance index (C-index) and the area under the curve (AUC). Finally, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), calibration plotting, and decision-curve analysis (DCA) were used to evaluate the benefits of the new prediction model.Results: We have established a nomogram to predict 1-, 3-, and 5-year CSS for US patients. In this nomogram, pathology grade has the highest risk on CSS in US, followed by age at diagnosis, then surgery status. Comparing to the AJCC staging system, the nomogram showed better predictive discrimination with higher C-index in both training and validation cohort (0.796 and 0.767 vs0.706 and 0.713, respectively) . Furthermore, AUC value, calibration plotting, NRI, IDI, and DCA also demonstrated better performance than the traditional system.Conclusion: Our study validated the first comprehensive nomogram for US which could provide more accurately and individualized survival predictions for US patients in clinical practice.

scholarly journals Survival analysis of patients with stage T2a and T2b perihilar cholangiocarcinoma treated with radical resection

2020 ◽  
Author(s):  
Jian Zhao ◽  
Wei Zhang ◽  
Jun Zhang ◽  
Yi Zhang ◽  
Wenjie Ma ◽  
...  
Keyword(s):  
Cox Regression ◽  
Staging System ◽  
Tnm Staging ◽  
Perihilar Cholangiocarcinoma ◽  
Curative Intent ◽  
Cox Regression Analysis ◽  
Significant Difference ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
8Th Edition

Abstract Background: Both the 7th and 8th editions of the American Joint Committee on Cancer (AJCC) staging system for perihilar cholangiocarcinoma (pCCA) had the same definition for T2a and T2b. But the value of this classification as prognostic factor remains unclear. Methods: 178 patients with stage T2a or T2b who underwent curative intent resection for pCCA between Jan 2010 and Dec 2018 were enrolled. Relationships between survival and clinicopathological factors including patient demographics and tumor characteristics were evaluated using univariate and multivariate Cox regression analysis. The overall survival (OS) were calculated by Kaplan-Meier method.Results: There was no significant difference in OS between T2a and T2b groups，and the median OS duration were 37 and 31 months (P=0.354). Both the 7th and 8th edition of the AJCC TNM staging demonstrated a poor prognostic predictive performance. High level of preoperative AST (≥85.0IU/L) and CA19-9 (≥1000 U/mL), vascular resection and lower pathological differentiation of the tumor were the independent predictors for poor survival after resection.Conclusion: The newly released 8th edition of AJCC staging system demonstrated a poor ability to discriminate the prognosis of patients with stage T2a and T2b pCCA after resection.

scholarly journals Proposed Modification of the pN2 Classification of the 8th Edition AJCC Staging System for Esophageal Squamous Cell Carcinoma: A Preliminary Study Based on the Chinese Population

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Kexing Xi ◽  
Hui Yu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Regression Analysis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Chinese Population ◽  
Cox Regression ◽  
Staging System ◽  
Cox Regression Analysis ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
8Th Edition

Objective. To evaluate the efficacy of the nodal staging of the 8th edition AJCC staging system for esophageal squamous cell carcinoma (ESCC) and propose a modification of the current pN2 classification. Methods. 1188 patients who underwent esophagectomy for ESCC at Sun Yat-sen University Cancer Center in Guangzhou (Guangdong, China) between January 2005 and June 2010 were reviewed. We used the X-tile software to determine the optimal cutoff points. Kaplan–Meier method and log-rank test were used to compare the differences of survival. Multivariate Cox regression analysis was performed for the factors that were statistically significant in univariate analysis. Result. In multivariate Cox regression analysis, alcohol consumption, pT status, and pN status were independent prognostic factors for overall survival (OS) according to the current pN classifications. And the observed 5-year OS rates for groups pN0, pN1, pN2, pN3 were 66.7%, 45.0%, 31.5%, and 21.5%, respectively (P<0.001). Based on the above results, the current pN2 classification was further subdivided as pN2a [3 metastatic lymph nodes (LNs)] and pN2b (4−6 metastatic LNs) groups. The 5-year OS rates for groups pN0, pN1, pN2a, pN2b, and pN3 were 66.7%, 45.0%, 37.7%, 26.3% and 21.5%, respectively (P<0.001). The rate of 5-year disease-free survival (DFS) was 60.0% for patients with pN0, compared with 36.8%, 29.3%, 20.8%, and 14.3% for those with pN1, pN2a, pN2b, and pN3, respectively (P<0.001).The current pN2 classification should be subdivided as pN2a (3 metastatic LNs) and pN2b (4–6 metastatic LNs) groups. The modified pN2 classification could better discriminate the survival differences between patients with 3–6 metastatic LNs for ESCC in the Chinese population.

scholarly journals Nomogram for predicting cancer-specific survival of patients with buccal squamous cell carcinoma: a population-based study

2020 ◽  
Author(s):  
Wei-Ming Wang ◽  
xiuhong chu ◽  
sisi yang ◽  
ying wang ◽  
chuanyu hu
Keyword(s):  
Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Prognostic Value ◽  
Cox Regression ◽  
Staging System ◽  
Cancer Specific Survival ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
Buccal Squamous Cell Carcinoma

Abstract Background The use of the traditional American Joint Committee on Cancer (AJCC) staging system alone has limitations in predicting the survival of buccal squamous cell carcinoma (BSCC) patients. We aimed to establish a comprehensive prognostic nomogram whose prognostic value compared with AJCC system. Methods Patients were obtained from the SEER (Surveillance, Epidemiology, and End Result) database. The Cox regression model was used to select variables using a backward stepwise selection method. Based on the predictive model for determining prognostic factors, a nomogram was developed to predict the cancer-specific survival rates of BSCC patients at 3, 5 and 8 years. We used several standard model validation methods to evaluate the performance of the survival model: concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), net reclassification improvement (NRI), calibration plots, decision curve analyses (DCAs), and integrated discrimination improvement (IDI). Results Multivariate analysis showed that age, AJCC stage, N stage, M stage, pathological grade, and surgical status were risk factors for survival. The c-index chart, the AUC chart, and the calibration chart show that the performance of the nomogram is better, and the NRI and IDI values show that the performance of the nomogram is better than that of the AJCC staging system. The 3-year, 5-year and 8-year DCA curves of nomogram show that it has more net benefit than traditional AJCC staging system, both in terms of training and validation queues. Conclusion We developed and validated the first BSCC prognosis nomogram, which has a better prognostic value than the separate AJCC staging system. Our BSCC prognosis nomogram is a valuable tool for explaining the risks of the next 3, 5 and 8 years in clinical practice.

scholarly journals A practical nomogram for predicting cancer-specific survival in patients with clear-cell renal cell carcinoma

2020 ◽  
Author(s):  
Qian Wen ◽  
Xinwen Wang ◽  
Xiaoye Wang ◽  
Tiao Bai ◽  
Mei Tao
Keyword(s):  
Prognostic Factors ◽  
Lung Metastases ◽  
Characteristic Curve ◽  
Staging System ◽  
Cox Proportional Hazards ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Specific Survival ◽  
Net Reclassification Improvement ◽  
Ajcc Staging System ◽  
Ajcc Staging

Abstract Background: It has limitations in predicting patient survival to use of the traditional American Joint Committee on Cancer (AJCC) staging system alone.Objectives: We aimed to establish and evaluate a comprehensive prognostic nomogram and compare its prognostic value with the AJCC staging system in adults diagnosed with ccRCC.Patients and Methods: We used the SEER database to identify 24477 cases of ccRCC between 2010 and 2015. The patients were randomly divided into two groups. In the development cohort, we used multivariate Cox proportional-hazards analyses to select significant variables, and used R software to establish a nomogram for predicting the 3-year and 5-year survival rates of ccRCC patients. In the development and validation cohorts, we compared our survival model with the AJCC prognosis model to evaluate the performance of the nomogram by calculating the concordance index (C-index), area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI), and performing calibration plotting and decision curve analyses (DCAs). Results: Eleven identified independent prognostic factors were used to establish the nomogram. Age at diagnosis, being unmarried, higher grades, larger tumor size, higher AJCC stage, lymph node metastases, bone metastases, liver metastases, lung metastases, radiotherapy, and no surgery were risk factors for the survival of ccRCC. The C-index, AUC, NRI, IDI, and calibration plots demonstrated the good performance of the nomogram compared to the AJCC staging system. Moreover, the 3-year and 5-year DCA curves showed that the nomogram yielded net benefits that were greater than the traditional AJCC staging system.Conclusion: This study is the first to indicate that married status is an important prognostic parameter in ccRCC. Our results also demonstrate that the developed nomogram can predict survival more accurately than the AJCC staging system alone. The prognostic factors were easily obtained.

scholarly journals Development and Validation of a Preoperative Nomogram for Predicting Survival of Patients with Locally Advanced Prostate Cancer after Radical Prostatectomy

2020 ◽  
Author(s):  
Xianghong Zhou ◽  
Qingyang Ning ◽  
Kun Jin ◽  
Tao Zhang ◽  
Xuelei Ma
Keyword(s):  
Prostate Cancer ◽  
Advanced Prostate Cancer ◽  
Validation Cohort ◽  
Locally Advanced ◽  
Staging System ◽  
Locally Advanced Prostate Cancer ◽  
Training Cohort ◽  
Ajcc Staging System ◽  
N Stage ◽  
Ajcc Staging

Abstract Background: For selected locally advanced prostate cancer (PCa) patients, radical prostatectomy (RP) is one of the first-line treatments. We aimed to develop a preoperative nomogram to identify what kinds of patients can get the most survival benefits after RP. Methods: We conducted analyses with data from the Surveillance, Epidemiology, and End Results (SEER) database. Covariates used for analyses included age at diagnosis, marital status, race, American Joint Committee on Cancer (AJCC) 7th TNM stage, Prostate specific antigen, Gleason biopsy score (GS), percent of positive cores. We estimated the cumulative incidence function for cause-specific death. The Fine and Gray’s proportional subdistribution hazard approach was used to perform multivariable competing risk analyses and reveal prognostic factors. A nomogram was built by these factors (including GS, percent of positive cores and N stage) and validated by concordance index and calibration curves . Risk stratification was established based on the nomogram. Results: We studied 14185 patients. N stage, GS, and percent of positive cores were the independent prognostic factors used to construct the nomogram. For validating, in the training cohort, the C-index was 0.779 (95% CI 0.736–0.822), and in the validation cohort, the C-index was 0.773 (95% CI 0.710–0.836). Calibration curves showed that the predicted survival and actual survival were very close. The nomogram performed better over the AJCC staging system (C-index 0.779 versus 0.764 for training cohort, and 0.773 versus 0.744 for validation cohort). The new stratification of risk groups based on the nomogram also showed better discrimination than the AJCC staging system. Conclusions: The preoperative nomogram can provide favorable prognosis stratification ability to help clinicians identify patients who are suitable for surgery.

scholarly journals Nomogram-Based New Recurrence Predicting System in Early-Stage Papillary Thyroid Cancer

2019 ◽  
Vol 2019 ◽  
pp. 1-7
Author(s):  
Yongfeng Ding ◽  
Zhuochao Mao ◽  
Jiaying Ruan ◽  
Xingyun Su ◽  
Linrong Li ◽  
...  
Keyword(s):  
Risk Factors ◽  
Thyroid Cancer ◽  
Papillary Thyroid Cancer ◽  
Cox Regression ◽  
Early Stage ◽  
Cox Model ◽  
Staging System ◽  
Papillary Thyroid ◽  
Cox Regression Analysis ◽  
Ajcc Staging

Background and Objectives. The clinicopathological risk factors to predict recurrence of papillary thyroid cancer (PTC) patients remain controversial. Methods. PTC patients treated with thyroidectomy between January 1997 and December 2011 at the First Affiliated Hospital of Zhejiang University (Zhejiang cohort) were included. Multivariate Cox regression analysis was conducted to identify independent recurrence predictors. Then, the nomogram model for predicting probability of recurrence was built. Results. According to Zhejiang cohort (N = 1,697), we found that the 10-year event-free survival (EFS) rates of PTC patients with early-stage (TNM stages I, II, and III) were not well discriminated (91.6%, 89.0%, and 90.7%; P=0.768). The multivariate Cox model identified age, bilaterality, tumor size, and nodal status as independent risk factors for tumor recurrence in PTC patients with TNM stages I–III. We then developed a nomogram with the C-index 0.70 (95% CI, 0.64 to 0.76), which was significantly higher (P<0.0001) than the AJCC staging system (0.52). In the validation group, the C-index remained at a similar level. Conclusions. In this study, we build up a new recurrence predicting system and establish a nomogram for early-stage PTC patients. This prognostic model may better predict individualized outcomes and conduct personalized treatments.

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