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 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 ◽  
Proportional Hazards ◽  
Lung Metastases ◽  
Characteristic Curve ◽  
Staging System ◽  
Cox Proportional Hazards ◽  
Youden Index ◽  
Cell Renal Cell Carcinoma ◽  
Cancer Specific Survival ◽  
Net Reclassification Improvement

Abstract Background: It has limitations in predicting patient cancer-specific 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-7th staging system in adults diagnosed with ccRCC.Methods: We used the SEER database to identify 24477 cases of ccRCC between 2010 and 2015. 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 cancer-specific survival rates of ccRCC patients. In the development and validation cohorts, we compared our cancer-specific survival model with the AJCC-7th prognosis model to evaluate the performance of the nomogram by calculating the concordance index (C-index), Youden 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-7th stage, lymph node metastases, bone metastases, liver metastases, lung metastases, radiotherapy, and no surgery were risk factors for the cancer-specific survival of ccRCC. The C-index, Youden Index, AUC, NRI, IDI, and calibration plots demonstrated the good performance of the nomogram compared to the AJCC-7th 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-7th 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 cancer-specific survival more accurately than the AJCC-7th staging system alone. The prognostic factors were easily obtained.

scholarly journals Nomogram Based on microRNA Signature Contributes to Improve Survival Prediction of Clear Cell Renal Cell Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Enfa Zhao ◽  
Xiaofang Bai
Keyword(s):  
Renal Cell Carcinoma ◽  
Prognostic Factors ◽  
Renal Cell ◽  
Clear Cell ◽  
Staging System ◽  
Survival Prediction ◽  
Mirna Signature ◽  
Cell Renal Cell Carcinoma ◽  
Ajcc Staging System ◽  
Ajcc Staging

Objective. Numerous microRNAs (miRNAs) have been identified in ccRCC and recommended to be used for predicting clear cell renal cell carcinoma (ccRCC) prognosis. However, it is not clear whether a miRNA-based nomogram results in improved survival prediction in patients with ccRCC. Methods. miRNA profiles from tumors and normal tissues were downloaded from The Cancer Genome Atlas (TCGA) database and analyzed using the “limma” package. The association between differentially expressed miRNAs and patient prognosis was identified using univariate, least absolute shrinkage and selection operator (LASSO), and multivariate Cox regression analyses. Next, all patients were randomly divided into development and validation cohorts at a ratio of 1 : 1. A nomogram was established based on independent prognostic factors in the development cohort. The prognostic performance of the nomogram was validated in both cohorts using the concordance index (C-index) and calibration plots. Results. Multivariate Cox analysis identified the 13-miRNA signature, as well as AJCC stage and age, as independent prognostic factors after adjusting for other clinical covariates. The nomogram was built based on the independent variables. In the development cohort, the C-index for the constructed nomogram to predict overall survival (OS) was 0.792, which was higher than the C-index (0.731) of the AJCC staging system and C-index (0.778) of the miRNA signature. The nomogram demonstrated good discriminative ability in the validation cohort in predicting OS, with a C-index of 0.762. The calibration plots indicated an excellent agreement between the nomogram predicted survival probability and the actual observed outcomes. Furthermore, decision curve analysis (DCA) indicated that the nomogram was superior to the AJCC staging system in increasing the net clinical benefit. Conclusions. The novel proposed nomogram based on a miRNA signature is a more reliable and robust tool for predicting the OS of patients with ccRCC compared to AJCC staging system, thus, improving clinical decision-making.

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 Analysis of Prognostic Factors from 9387 Merkel Cell Carcinoma Cases Forms the Basis for the New 8th Edition AJCC Staging System

2016 ◽  
Vol 23 (11) ◽  
pp. 3564-3571 ◽  
Author(s):  
Kelly L. Harms ◽  
Mark A. Healy ◽  
Paul Nghiem ◽  
Arthur J. Sober ◽  
Timothy M. Johnson ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Merkel Cell Carcinoma ◽  
Staging System ◽  
Merkel Cell ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
8Th Edition

scholarly journals A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma

2020 ◽  
Author(s):  
Na Wang ◽  
Jin Yang ◽  
Jun Lyu ◽  
Qingqing Liu ◽  
Hairong He ◽  
...  
Keyword(s):  
Small Intestine ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Survival Rates ◽  
Discrimination Performance ◽  
Staging System ◽  
Tnm Staging ◽  
Superior Performance ◽  
Cancer Specific Survival ◽  
Net Reclassification Improvement

Abstract Background: The objective of this study was to develop a practical nomogram for predicting the cancer-specific survival (CSS) of patients with small-intestine adenocarcinoma. Methods: Patients diagnosed with small-intestine adenocarcinoma. between 2010 and 2015 were selected for inclusion in this study from the Surveillance, Epidemiology, and End Results (SEER) database. The selected patients were randomly divided intothe training and validation cohorts at a ratio of 7:3.The predictors of CSS were identified by applying both forward and backward stepwise selection methods in a Cox regression model. The performance of the nomogram was measured by the concordance index (C-index), the area under receiver operating characteristic curve (AUC), calibration plots, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI), and decision-curve analysis (DCA). Results: Multivariate Cox regression indicated that factors including age at diagnosis, sex, marital status, insurance status, histology grade, SEER stage, surgery status, T stage, and N stage were independent covariates associated with CSS. These factors were used to construct a predictive model, which was built and virtualized by a nomogram. The C-index of the constructed nomogram was 0.858. The AUC values indicated that the established nomogram displayed better discrimination performance than did the seventh edition of the American Joint Committee on Cancer TNM staging system in predicting CSS. The IDI and NRI also showed that the nomogram exhibited superior performance in both the training and validation cohorts. Furthermore, the calibrated nomogram predicted survival rates that closely corresponded to actual survival rates, while the DCA demonstrated the considerable clinical usefulness of the nomogram. Conclusion: We have constructed a nomogram for predicting the CSS of small-intestine adenocarcinoma patients. This prognostic model may improve the ability of clinicians to predict survival in individual patients and provide them with treatment recommendations.

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.

scholarly journals The prognostic significance of different proportion of signet-ring cells of colorectal carcinoma

2021 ◽  
Author(s):  
Wei Chen ◽  
Huajun Cai ◽  
Kui Chen ◽  
Xing Liu ◽  
Weizhong Jiang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Staging System ◽  
Signet Ring Cell ◽  
Significant Difference ◽  
Signet Ring ◽  
Ajcc Staging System ◽  
Ajcc Staging

While the prognosis of patients with partial SRCC (PSRCC) has been rarely reported, colorectal signet-ring cell carcinoma (SRCC) has been associated with poor prognosis. The aim of this study was to analyze the prognosis of patients with different SRC composition and establish a prediction model. A total of 91 patients with SRC component were included in the study. These patients were divided into two groups: SRCC group (SRC composition > 50%; n=41) and partial SRCC (PSRCC) group (SRC composition ≤ 50%; n=50). COX regression model was used to identify independent prognostic factors for overall survival (OS). A predictive nomogram was established and compared with the 7th AJCC staging system. After a median follow-up of 16 months, no significant difference in OS was observed in either group. Preoperative carcinoembryonic antigen (CEA) level, pN stage, M stage, preoperative ileus, and adjuvant chemotherapy were independent prognostic risk factors for OS (p<0.05). A nomogram for predicting the overall survival of colorectal SRCC was established with a C-index of 0.800, and it showed better performance than that of the 7th AJCC staging system (p<0.001). In summary, the ratio of SRC component was not an independent prognostic factor of the OS. Those patients with less than 50% of SRC component should be given the same clinical attention. A predictive nomogram for survival based on five independent prognostic factors was developed and showed better performance than the 7th AJCC staging system. This resulted to be helpful for individualized prognosis prediction and risk assessment.

scholarly journals Development and Validation of a Prognostic Nomogram for Gastric Signet Ring Cell Carcinoma: A Multicenter Population-Based Study

2021 ◽  
Vol 11 ◽  
Author(s):  
Shuairan Zhang ◽  
Yang Liu ◽  
Zihan Jiao ◽  
Zenan Li ◽  
Jin Wang ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
Staging System ◽  
Signet Ring Cell Carcinoma ◽  
Signet Ring Cell ◽  
Seer Database ◽  
Kaplan Meier ◽  
Signet Ring ◽  
Ajcc Staging System ◽  
Ring Cell ◽  
Ajcc Staging

BackgroundGastric signet ring cell carcinoma (GSRCC) is a rare disease associated with poor prognosis. A prognostic nomogram was developed and validated in this study to assess GSRCC patients’ overall survival (OS).MethodsPatients diagnosed with GSRCC from the Surveillance, Epidemiology, and End Results (SEER) database (2004–2016) and the First Hospital of China Medical University (CMU1h) were enrolled in this retrospective cohort study. Univariate and multivariate COX analysis was used to determine independent prognostic factors to construct the prognostic nomogram. Predictions were evaluated by the C-index and calibration curve. In addition, the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and Kaplan-Meier analysis were employed to assess the clinical utility of the survival prediction model.ResultsPatients were classified into two cohorts. We randomly divided patients in the SEER database and CMU1h cohort into a training group (n=3068, 80%) and a validation group (n=764, 20%). Age, race, T stage, N stage, M stage, therapy, and tumor size were significantly associated with the prognosis of GSRCC patients. On this basis, a nomogram was constructed, with a C-index in the training and the validation cohorts at 0.772 (95% CI: 0.762–0.782) and 0.774 (95% CI: 0.752–0.796), respectively. The accuracy of the generated nomogram was verified through calibration plots. Similarly, compared with the traditional AJCC staging system, the results of the area under curve (AUC) calculated by ROC, DCA, and Kaplan-Meier curves, demonstrated a good predictive value of the constructed nomogram, compared to the traditional AJCC staging system.ConclusionIn the present study, seven independent prognostic factors of GSRCC were screened out. The established nomogram models based on seven variables provided a visualization of each prognostic factor’s risk and assisted clinicians in predicting the 1-, 3-, and 5-year OS of GSRCC.

scholarly journals A convenient clinical nomogram for predicting the cancer-specific survival of individual patients with small-intestine adenocarcinoma

2020 ◽  
Author(s):  
Na Wang ◽  
Jin Yang ◽  
Jun Lyu ◽  
Qingqing Liu ◽  
Hairong He ◽  
...  
Keyword(s):  
Small Intestine ◽  
Cox Regression ◽  
Characteristic Curve ◽  
Survival Rates ◽  
Discrimination Performance ◽  
Staging System ◽  
Tnm Staging ◽  
Superior Performance ◽  
Cancer Specific Survival ◽  
Net Reclassification Improvement

Abstract Background: The objective of this study was to develop a practical nomogram for predicting the cancer-specific survival (CSS) of patients with small-intestine adenocarcinoma . Methods: Patients diagnosed with small-intestine adenocarcinoma between 2010 and 2015 were selected for inclusion in this study from the Surveillance, Epidemiology, and End Results (SEER) database. The selected patients were randomly divided into the training and validation cohorts at a ratio of 7:3. The predictors of CSS were identified by applying both forward and backward stepwise selection methods in a Cox regression model . The performance of the nomogram was measured by the concordance index (C-index), the area under receiver operating characteristic curve (AUC) , calibration plots, the net reclassification improvement (NRI), the integrated discrimination improvement (IDI) , and decision-curve analysis (DCA). Results: Multivariate Cox regression indicated that factors including age at diagnosis, sex, marital status, insurance status, histology grade, SEER stage, surgery status, T stage, and N stage were independent covariates associated with CSS. These factors were used to construct a predictive model, which was built and virtualized by a nomogram. The C-index of the constructed nomogram was 0.850. The AUC values indicated that the established nomogram displayed better discrimination performance than did the seventh edition of the American Joint Committee on Cancer TNM staging system in predicting CSS. The IDI and NRI also showed that the nomogram exhibited superior performance in both the training and validation cohorts. Furthermore, the calibrated nomogram predicted survival rates that closely corresponded to actual survival rates, while the DCA demonstrated the considerable clinical usefulness of the nomogram. Conclusion: We have constructed a nomogram for predicting the CSS of small-intestine adenocarcinoma patients . This prognostic model may improve the ability of clinicians to predict survival in individual patients and provide them with treatment recommendations.

Prognostic nomogram based on log odds of positive lymph nodes for gastric carcinoma patients after surgical resection

2019 ◽  
Vol 15 (36) ◽  
pp. 4207-4222
Author(s):  
Enfa Zhao ◽  
Changli Zhou ◽  
Shimin Chen
Keyword(s):  
Gastric Carcinoma ◽  
Lymph Nodes ◽  
Staging System ◽  
Predictive Performance ◽  
Cancer Specific Survival ◽  
Node Ratio ◽  
Log Odds ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
Positive Lymph Nodes

Aim: To build a prognostic nomogram based on log odds of positive lymph nodes for patients with gastric carcinoma (GC) after resection, and to compare the predictive performance with the American Joint Committee on Cancer (AJCC) staging system and lymph node ratio (LNR). Methods: Multivariate analyses were performed to identify the independent variables for cancer-specific survival (CSS). A nomogram was constructed based on independent clinicopathological factors. Results: The C-indices for predicting CSS were 0.674 in development cohort and 0.647 in validation cohort, which were higher than that of the AJCC staging system and LNR. Conclusion: The nomogram was more accurate than the AJCC staging system and LNR for predicting CSS in patients undergoing resection for GC.

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