scholarly journals Development and validation of a nomogram to predict overall survival for patients with metastatic renal cell carcinoma

2020 ◽  
Author(s):  
Wenwen Zheng ◽  
Weiwei Zhu ◽  
Shengqiang Yu ◽  
Kangqi Li ◽  
Yuexia Ding ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Staging System ◽  
Survival Prediction ◽  
Seer Database ◽  
Training Set ◽  
Ajcc Staging System ◽  
Validation Set ◽  
Ajcc Staging ◽  
Metastatic Rcc

Abstract Background: The prognosis of metastatic renal cell carcinoma (RCC) patients vary widely because of clinical and pathological heterogeneity. We aimed to develop a novel nomogram to predict overall survival (OS) for this population. Methods: Metastatic RCC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016. These patients were randomly assigned to a training set and a validation set at a ratio of 1:1. Significant prognostic factors of survival were identified through Cox regression models and then integrated to form a nomogram to predict 1-, 3- and 5-year OS. The nomogram was subsequently subjected to validations via the training and the validation sets. The performance of this model was evaluated by using Harrell’s concordance index (C-index), calibration curve, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). Results: Overall, 2315 eligible metastatic RCC patients were enrolled from the SEER database. A nomogram of survival prediction for patients of newly diagnosed with metastatic RCC was established, in which eight clinical factors significantly associated with OS were involved, including Fuhrman grade, lymph node status, sarcomatoid feature, cancer-directed surgery, bone metastasis, brain metastasis, liver metastasis, and lung metastasis. The new model presented better discrimination power than the American Joint Committee on Cancer (AJCC) staging system (7th edition) in the training set (C-indexes, 0.701 vs. 0.612, P <0.001) and the validation set (C-indexes, 0.676 vs. 0.600, P <0.001). The calibration plots of the nomogram exhibited optimal agreement between the predicted values and the observed values. The results of NRI and IDI also indicated the superior predictive capability of the nomogram relative to the AJCC staging system. The DCA plots revealed higher clinical use of our model in survival prediction. Conclusions: We developed and validated an effective nomogram to provide individual OS prediction for metastatic RCC patients, which would be beneficial to clinical trial design, patient counseling, and therapeutic modality selection.

scholarly journals Development and Validation of a Nomogram to Predict Overall Survival for Patients with Metastatic Renal Cell Carcinoma

2020 ◽  
Author(s):  
Wenwen Zheng ◽  
Weiwei Zhu ◽  
Shengqiang Yu ◽  
Kangqi Li ◽  
Yuexia Ding ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Staging System ◽  
Survival Prediction ◽  
Seer Database ◽  
Training Set ◽  
Ajcc Staging System ◽  
Validation Set ◽  
Ajcc Staging ◽  
Metastatic Rcc

Abstract Background: The prognosis of metastatic renal cell carcinoma (RCC) patients vary widely because of clinical and pathological heterogeneity.We aimed to develop a novel nomogram to predict overall survival (OS) for this population.Methods: Metastatic RCC patients were selected from the Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2016. These patients wererandomly assignedto a training set and a validation set at a ratio of 1:1. Significant prognostic factors of survival were identified through Cox regression models and then integrated to form a nomogram to predict 1-, 3- and 5-year OS. The nomogram was subsequently subjected to validationsvia the training and the validation sets. The performance of this model was evaluated by using Harrell’s concordance index (C-index), calibration curve, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA). Results: Overall, 2315 eligible metastatic RCC patients were enrolled from the SEER database. A nomogram of survival prediction for patients of newly diagnosed with metastatic RCC was established, in which eight clinical factors significantly associated with OS were involved, including Fuhrman grade, lymph node status, sarcomatoid feature, cancer-directed surgery, bone metastasis, brain metastasis, liver metastasis, and lung metastasis.The new model presented better discrimination power than the American Joint Committee on Cancer (AJCC) staging system (7th edition) in the training set (C-indexes, 0.701 vs. 0.612, P<0.001) and the validation set (C-indexes, 0.675 vs. 0.600, P<0.001). The calibration plots of the nomogram exhibited optimal agreement between the predicted values and the observed values.The results of NRI and IDI also indicated the superior predictive capability of the nomogram relative to the AJCC staging system. The DCA plots revealed higher clinical use of our model in survival prediction.Conclusions: We developed and validated an effective nomogram to provide individual OS prediction for metastatic RCC patients, which would be beneficial to clinical trial design, patient counseling, and therapeutic modality selection.

scholarly journals Development and validation of a nomogram to predict overall survival for patients with metastatic renal cell carcinoma

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Wenwen Zheng ◽  
Weiwei Zhu ◽  
Shengqiang Yu ◽  
Kangqi Li ◽  
Yuexia Ding ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Staging System ◽  
Seer Database ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
Metastatic Rcc

Abstract Background Heterogeneity of metastatic renal cell carcinoma (RCC) constraints accurate prognosis prediction of the tumor. We therefore aimed at developing a novel nomogram for accurate prediction of overall survival (OS) of patients with metastatic RCC. Methods We extracted 2010 to 2016 data for metastatic RCC patients in the Surveillance, Epidemiology, and End Results (SEER) database, and randomly stratified them equally into training and validation sets. Prognostic factors for OS were analyzed using Cox regression models, and thereafter integrated into a 1, 3 and 5-year OS predictive nomogram. The nomogram was validated using the training and validation sets. The performance of this model was evaluated by the Harrell’s concordance index (C-index), calibration curve, integrated discrimination improvement (IDI), category-free net reclassification improvement (NRI), index of prediction accuracy (IPA), and decision curve analysis (DCA). Results Overall, 2315 metastatic RCC patients in the SEER database who fulfilled our inclusion criteria were utilized in constructing a nomogram for predicting OS of newly diagnosed metastatic RCC patients. The nomogram incorporated eight clinical factors: Fuhrman grade, lymph node status, sarcomatoid feature, cancer-directed surgery and bone, brain, liver, and lung metastases, all significantly associated with OS. The model was superior to the American Joint Committee on Cancer (AJCC) staging system (7th edition) both in training (C-indices, 0.701 vs. 0.612, P < 0.001) and validation sets (C-indices, 0.676 vs. 0.600, P < 0.001). The calibration plots of the nomogram corresponded well between predicted and observed values. NRI, IDI, and IPA further validated the superior predictive capability of the nomogram relative to the AJCC staging system. The DCA plots revealed reliable clinical application of our model in prognosis prediction of metastatic RCC patients. Conclusions We developed and validated an accurate nomogram for individual OS prediction of metastatic RCC patients. This nomogram can be applied in design of clinical trials, patient counseling, and rationalizing therapeutic modalities.

scholarly journals Development and validation of a nomogram to predict overall survival for patients with metastatic renal cell carcinoma

2020 ◽  
Author(s):  
Wenwen Zheng ◽  
Weiwei Zhu ◽  
Shengqiang Yu ◽  
Kangqi Li ◽  
Yuexia Ding ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Overall Survival ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Staging System ◽  
Seer Database ◽  
Ajcc Staging System ◽  
Ajcc Staging ◽  
Metastatic Rcc

Abstract Background: Heterogeneity of metastatic renal cell carcinoma (RCC) constraints accurate prognosis prediction of the tumor. We therefore aimed at developing a novel nomogram for accurate prediction of overall survival (OS) of patients with metastatic RCC.Methods: We extracted 2010 to 2016 data for metastatic RCC patients in the Surveillance, Epidemiology, and End Results (SEER) database, and randomly stratified them equally into training and validation sets. Prognostic factors for OS were analyzed using Cox regression models, and thereafter integrated into a 1, 3 and 5-year OS predictive nomogram. The nomogram was validated using the training and validation sets. The performance of this model was evaluated by the Harrell’s concordance index (C-index), calibration curve, integrated discrimination improvement (IDI), category-free net reclassification improvement (NRI), index of prediction accuracy (IPA), and decision curve analysis (DCA).Results: Overall, 2315 metastatic RCC patients in the SEER database who fulfilled our inclusion criteria were utilized in constructing a nomogram for predicting OS of newly diagnosed metastatic RCC patients. The nomogram incorporated eight clinical factors: Fuhrman grade, lymph node status, sarcomatoid feature, cancer-directed surgery and bone, brain, liver, and lung metastases, all significantly associated with OS. The model was superior to the American Joint Committee on Cancer (AJCC) staging system (7th edition) both in training (C-indices, 0.701 vs. 0.612, P<0.001) and validation sets (C-indices, 0.676 vs. 0.600, P<0.001). The calibration plots of the nomogram corresponded well between predicted and observed values. NRI, IDI, and IPA further validated the superior predictive capability of the nomogram relative to the AJCC staging system. The DCA plots revealed reliable clinical application of our model in prognosis prediction of metastatic RCC patients.Conclusions: We developed and validated an accurate nomogram for individual OS prediction of metastatic RCC patients. This nomogram can be applied in design of clinical trials, patient counseling, and rationalizing therapeutic modalities.

scholarly journals Development and validation of a Nomogram for predicting the Overall Survival of Patients With Pancreatic Ductal Adenocarcinoma of the Head of the Pancreas

2021 ◽  
Author(s):  
Zhilong Liu ◽  
Haohui Yu ◽  
Mingrong Cao ◽  
Jiexing Li ◽  
Yulin Huang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Staging System ◽  
The United States ◽  
Ductal Adenocarcinoma ◽  
Seer Database ◽  
Training Set ◽  
Head Of The Pancreas ◽  
Ajcc Staging System ◽  
Ajcc Staging

Abstract Background: The purpose of this study is to develop and validate a nomogram to predict the overall survival (OS) of patients with Pancreatic Ductal Adenocarcinoma of the Head of the Pancreas (PDAC-HP).Methods: Using the Surveillance, Epidemiology, and End Results (SEER) database, we collected patients with PDAC-HP in the United States between 2004 and 2015. Patients were randomly divided into training set and validating set at a ratio of 7:3. The training set is used to develop a nomogram for predicting OS. These indicators such as the C index, the area under curve (AUC) of the receiver operating characteristic (ROC), calibration plots and the net reclassification improvement (NRI) and the integrated discrimination improvement (IDI) were used to evaluate the prediction accuracy of the nomogram.Results: A total of 33,893 patients with PDAC-HP over 20 years old were diagnosed between 2004 and 2015 were collected from the SEER database. Using multivariable Cox regression analysis, we identified eight risk factors that were associated with OS, such as age at diagnosis, sex, marital status at diagnosis, race, AJCC staging, surgery, radiotherapy and chemotherapy. A nomogram was constructed based on these variables. Compared with the AJCC staging system, the nomogram has a better C index and AUC in the training set and validatiing set. The calibration plots indicated that the nomogram was able to accurately predict the OS of patients with PDAC-HP at 1, 3, and 5 years.Conclusions: We developed and validated a nomogram, and predicted the OS of patients with PDAC-HP at 1, 3, and 5 years. Compared with the AJCC staging system, the nomogram we constructed has better performance. It shows that our nomogram could be served as an effective tool for prognostic evaluation of patients with PDAC-HP.

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 Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Chao-Yang Wang ◽  
Jin Yang ◽  
Hao Zi ◽  
Zhong-Li Zheng ◽  
Bing-Hui Li ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Gastric Adenocarcinoma ◽  
Clinical Decision Making ◽  
External Validation ◽  
Staging System ◽  
Training Set ◽  
Regional Lymph Nodes ◽  
Ajcc Staging System ◽  
Validation Set ◽  
Ajcc Staging

Abstract Background Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A significant prognostic nomogram for predicting the respective disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established. Objective We were planning to establish a survival nomogram model for GAC patients who receive surgery and chemotherapy. Methods We identified 5764 GAC patients who had received surgery and chemotherapy from the record of Surveillance, Epidemiology, and End Results (SEER) database. About 70% (n = 4034) of the chosen GAC patients were randomly assigned to the training set, and the rest of the included ones (n = 1729) were assigned to the external validation set. A prognostic nomogram was constructed by the training set and the predictive accuracy of it was validated by the validation set. Results Based on the outcome of a multivariate analysis of candidate factors, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined after surgery, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell’s concordance index) of the nomogram model was some larger than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the constructed nomogram displayed that the probability of DSS commendably accord with the survival rate. Integrated discrimination improvement (IDI) revealed obvious increase and categorical net reclassification improvement (NRI) showed visible enhancement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively (P > 0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI = 0.316–0.470), 0.407 (95% CI = 0.350–0.505), and 0.413 (95% CI = 0.336–0.519), respectively. Decision curve analysis (DCA) proved that the constructed nomogram was preferable to the AJCC staging system. Conclusion The constructed nomogram supplies more credible DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

scholarly journals Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

2019 ◽  
Author(s):  
Chao-Yang Wang ◽  
Jin Yang ◽  
Hao Zi ◽  
Zhong-Li Zheng ◽  
Bing-Hui Li ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Gastric Adenocarcinoma ◽  
Clinical Decision Making ◽  
External Validation ◽  
Staging System ◽  
Training Set ◽  
Regional Lymph Nodes ◽  
Ajcc Staging System ◽  
Validation Set ◽  
Ajcc Staging

Abstract Background: Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A prognostic model for predicting the individual disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established. Objective: We aimed to establish a survival nomogram for GAC patients who receive surgery and chemotherapy. Methods: We identified 5764 GAC patients who had received surgery and chemotherapy from the SEER (Surveillance, Epidemiology, and End Results) database. Approximately 80% (n=4034) of the included patients were randomly assigned to the training set, and the remaining patients (n=1729) were assigned to the external validation set. Nomogram was established by the training set and validated by the validation set. Results: Based on the results of a multivariate analysis, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell’s concordance index) of the model was higher than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the nomogram showed that the probability of DSS optimally corresponded to the survival rate. Integrated discrimination improvement (IDI) and categorical net reclassification improvement (NRI) showed visible improvement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively (P>0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI=0.316–0.470), 0.407 (95% CI=0.350–0.505), and 0.413 (95% CI=0.336–0.519), respectively. Decision curve analysis supported that the constructed nomogram was superior to the AJCC staging system. Conclusion: The proposed nomogram provides more-reliable DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

scholarly journals Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

2019 ◽  
Author(s):  
Chaoyang Wang ◽  
Jin Yang ◽  
Zhongli Zheng ◽  
Binghui Li ◽  
Yang Wang ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Gastric Adenocarcinoma ◽  
Clinical Decision Making ◽  
External Validation ◽  
Staging System ◽  
Training Set ◽  
Regional Lymph Nodes ◽  
Ajcc Staging System ◽  
Validation Set ◽  
Ajcc Staging

Abstract Background: Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A prognostic model for predicting the individual disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established. Objective: We aimed to establish a survival nomogram for GAC patients who receive surgery and chemotherapy. Methods: We identified 5764 GAC patients who had received surgery and chemotherapy from the SEER (Surveillance, Epidemiology, and End Results) database. Approximately 80% (n=4034) of the included patients were randomly assigned to the training set, and the remaining patients (n=1729) were assigned to the external validation set. Nomogram was established by the training set and validated by the validation set. Results: Based on the results of a multivariate analysis, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell’s concordance index) of the model was higher than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the nomogram showed that the probability of DSS optimally corresponded to the survival rate. Integrated discrimination improvement (IDI) and categorical net reclassification improvement (NRI) showed visible improvement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively (P>0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI=0.316–0.470), 0.407 (95% CI=0.350–0.505), and 0.413 (95% CI=0.336–0.519), respectively. Decision curve analysis supported that the constructed nomogram was superior to the AJCC staging system. Conclusion: The proposed nomogram provides more-reliable DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

scholarly journals Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

2019 ◽  
Author(s):  
Chao-Yang Wang ◽  
Jin Yang ◽  
Hao Zi ◽  
Zhong-Li Zheng ◽  
Bing-Hui Li ◽  
...  
Keyword(s):  
Lymph Nodes ◽  
Gastric Adenocarcinoma ◽  
Clinical Decision Making ◽  
External Validation ◽  
Staging System ◽  
Training Set ◽  
Regional Lymph Nodes ◽  
Ajcc Staging System ◽  
Validation Set ◽  
Ajcc Staging

Abstract Background: Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A significant prognostic nomogram for predicting the respective disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established.Objective: We were planning to establish a survival nomogram model for GAC patients who receive surgery and chemotherapy. Methods: We identified 5764 GAC patients who had received surgery and chemotherapy from the record of Surveillance, Epidemiology, and End Results (SEER ) database. About 70% ( n =4034) of the chosen GAC patients were randomly assigned to the training set, and the rest of the included ones ( n =1729) were assigned to the external validation set. A prognostic nomogram was constructed by the training set and the predictive accuracy of it was validated by the validation set. Results: Based on the outcome of a multivariate analysis of candidate factors, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined after surgery, number of positive regional lymph nodes , sex , race, grade, derived AJCC stage, summary stage , and radiotherapy status. The C-index (Harrell’s concordance index) of the nomogram model was some larger than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the constructed nomogram displayed that the probability of DSS commendably accord with the survival rate. Integrated discrimination improvement (IDI) revealed obvious increase and categorical net reclassification improvement (NRI) showed visible enhancement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively ( P >0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI=0.316–0.470), 0.407 (95% CI=0.350–0.505), and 0.413 (95% CI=0.336–0.519), respectively. Decision curve analysis (DCA) proved that the constructed nomogram was preferable to the AJCC staging system. Conclusion: The constructed nomogram supplies more credible DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

Estimating survival probability in stage III melanoma: A multivariable individualized patient risk assessment nomogram

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 8020-8020
Author(s):  
D. G. Coit ◽  
C. Qin Zhou ◽  
A. Patel ◽  
K. Panageas
Keyword(s):  
Risk Assessment ◽  
Overall Survival ◽  
Patient Care ◽  
Staging System ◽  
Stage Iii ◽  
Patient Risk ◽  
Ajcc Staging System ◽  
Predicting Outcome ◽  
Stage Iii Melanoma ◽  
Ajcc Staging

8020 Background: Recent revisions in the AJCC staging system have increased its complexity without comparable improvement in prognostic accuracy for patients with Stage III melanoma. Furthermore, there remains significant prognostic heterogeneity, even within Stages IIIA, IIIB, and IIIC. The current study was undertaken to develop a model for individual patient risk assessment, both to facilitate patient care, and to help define prognostically homogeneous patient populations for entry into clinical trials. Methods: Patients with AJCC Stage III melanoma were identified from a prospective single institution database. Overall survival was calculated from the date of Stage III to last followup. A multivariate Cox model of independent prognostic factors was developed, and a multivariable individualized patient risk assessment nomogram was built from that model. Results: Among 1,064 patients with Stage III melanoma, 535 have died, at a median followup of 44 months. Independent predictors of overall survival are shown in the table. Individual patient three and five year survival was predicted by incorporating all eight variables into a prognostic nomogram. The nomogram was superior to the AJCC Staging system in predicting outcome in Stage III melanoma patients. Conclusions: Individual patient risk assessment is more accurate than traditional AJCC staging in predicting outcome in Stage III melanoma. This approach, which can be easily incorporated into a handheld computing environment, offers potential advantages for both patient care and clinical research, and should be explored in the next iteration of the AJCC staging system. [Table: see text] No significant financial relationships to disclose.

Sign in / Sign up

Export Citation Format

Share Document