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

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.

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

10.21203/rs.2.21096/v1 ◽

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.

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

10.21203/rs.2.21096/v3 ◽

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.

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

10.21203/rs.2.24343/v1 ◽

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.

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Development and validation of prognostic nomograms for patients with colon neuroendocrine neoplasms

World Journal of Surgical Oncology ◽

10.1186/s12957-021-02338-8 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Ruitong Xu ◽

Bingrong Zhou ◽

Ping Hu ◽

Bingyan Xue ◽

Danyang Gu ◽

...

Keyword(s):

Tnm Classification ◽

Age Groups ◽

Staging System ◽

Tnm Staging ◽

Superior Performance ◽

Neuroendocrine Neoplasms ◽

Cancer Specific Survival ◽

Size Grade ◽

Precise Prediction ◽

Development And Validation

Abstract Background Colon neuroendocrine neoplasms (NENs) have one of the poorest median overall survival (OS) rates among all NENs. The American Joint Committee on Cancer (AJCC) tumor–node–metastasis (TNM) staging system—currently the most commonly used prediction model—has limited prediction accuracy because it does not include parameters such as age, sex, and treatment. The aim of this study was to construct nomograms containing various clinically important parameters to predict the prognosis of patients with colon NENs more accurately. Methods Using the Surveillance, Epidemiology, and End Results (SEER) database, we performed a retrospective analysis of colon NENs diagnosed from 1975 to 2016. Data were collected from 1196 patients; almost half were female (617/1196, 51.6%), and the average age was 61.94 ± 13.05 years. Based on the age triple cut-off values, there were 396 (33.1%), 408 (34.1%), and 392 (32.8%) patients in age groups 0–55 years, 55–67 years, and ≥ 68 years, respectively. Patients were randomized into training and validation cohorts (3:1). Independent prognostic factors were used for construction of nomograms to precisely predict OS and cancer-specific survival (CSS) in patients with colon NENs. Results Multivariate analysis showed that age ≥ 68 years, sex, tumor size, grade, chemotherapy, N stage, and M stage were independent predictors of OS. In the validation cohort, the Concordance index (C-index) values of the OS and CSS nomograms were 0.8345 (95% confidence interval [CI], 0.8044–0.8646) and 0.8209 (95% CI, 0.7808–0.861), respectively. C-index also indicated superior performance of both nomograms (C-index 0.8347 for OS and 0.8668 for CSS) compared with the AJCC TNM classification (C-index 0.7159 for OS and 0.7366 for CSS). Conclusions We established and validated new nomograms for more precise prediction of OS and CSS in patients with colon NENs to facilitate individualized clinical decisions.

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A Constructed and Validated Nomogram for Preoperatively Predicting Cancer-specific Survival Rates in Pediatric Patients with Brainstem Malignant Gliomas: A SEER-based Study

10.21203/rs.3.rs-368683/v1 ◽

2021 ◽

Author(s):

wenqiang Che ◽

Jun Lyu ◽

Chengzhuo Li ◽

Xiangyu Wang

Keyword(s):

Regression Analysis ◽

Pediatric Patients ◽

Cox Regression ◽

Characteristic Curve ◽

Malignant Gliomas ◽

Survival Rates ◽

Cancer Specific Survival ◽

Cox Regression Analysis ◽

Calibration Curves ◽

Practical Tool

Abstract Purpose: Pediatric patients diagnosed with brainstem malignant gliomas (BSMGs) have a poor prognosis. Our study aimed to construct and validate a prognostic nomogram to preoperatively predict the cancer‐specific survival (CSS) rates in these patients.Methods: From 1998 to 2016, we extracted patients' data from Surveillance Epidemiology and End Results (SEER) database. A total of 1160 patients were enrolled and randomly divided into training and validating groups. Subsequently, the Cox regression analysis was used to screen variables. Then, the nomogram was constructed. Lastly, we calculated C-indexes and plotted calibration curves and the utility of decision curve analyses (DCAs) to assess our survival model's benefits.Result: Here, after multivariate cox regression analysis, we established four variables for constructing nomogram for CSS rates. Subsequently, the C-index, the area under the receiver operating characteristic curve, and calibration curves were used to confirm the nomogram's good performance. DCAs of the nomogram indicated that both groups obtained good 1-, 3-, and 5-year net benefits. Conclusion: The nomogram model for preoperatively predicting CSS provided a convenient and practical tool to assess pediatric patients' prognosis with BSMG.

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

10.21203/rs.2.24343/v2 ◽

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.

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Development and Validation of Prognostic Nomograms for Patients with Colon Neuroendocrine NeoplasmsPrognostic Nomograms for Colon Nens’ Patients

10.21203/rs.3.rs-498244/v1 ◽

2021 ◽

Author(s):

Ruitong Xu ◽

Bingrong Zhou ◽

Ping Hu ◽

Bingyan Xue ◽

Danyang Gu ◽

...

Keyword(s):

Tnm Classification ◽

Staging System ◽

Tnm Staging ◽

Superior Performance ◽

Neuroendocrine Neoplasms ◽

Cancer Specific Survival ◽

Size Grade ◽

Precise Prediction ◽

N Stage ◽

Development And Validation

Abstract Background Colon neuroendocrine neoplasms (NENs) have one of the poorest median overall survival (OS) rates among all NENs. The American Joint Committee on Cancer (AJCC) tumor–node–metastasis (TNM) staging system—currently the most commonly used prediction model—has limited prediction accuracy because it does not include parameters such as age, sex, and treatment. The aim of this study was to construct nomograms containing various clinically important parameters to predict the prognosis of patients with colon NENs more accurately. Methods Using the Surveillance, Epidemiology and End Results (SEER) database, we performed a retrospective analysis of colon NENs diagnosed from 1975 to 2016. Data were collected from 1196 patients, most of which were female (617/1196, 51.6%), and the average age was 61.94 ± 13.05 years old. Based on the optimal cutoff value in age (age 0–55 y, 55–67 y, age ≥ 68 y), 396 (33.1%) patients were between 0–55 y, 408 (34.1%) were between 56–67 y and 392 (32.8%) were ≥ 68 y. Patients were randomized into training and validation cohorts (3:1). Independent prognostic factors were used for construction of nomograms to precisely predict OS and cancer-specific survival (CSS) in patients with colon NENs. Results Multivariate analysis showed that age ≥ 68 years, sex, tumor size, grade, chemotherapy, N stage, and M stage were independent predictors of OS. In the validation cohort, the Concordance index (C-index) values of the OS and CSS nomograms were 0.8345 (95% confidence interval [CI], 0.8044–0.8646) and 0.8209 (95% CI, 0.7808–0.861), respectively. C-index also indicated superior performance of both nomograms (C-index 0.8347 for OS and 0.8668 for CSS) compared with the AJCC TNM classification (C-index 0.7159 for OS and 0.7366 for CSS). Conclusions We established and validated new nomograms for more precise prediction of OS and CSS in patients with colon NENs to facilitate individualized clinical decisions.

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Trends of incidence and prognosis of primary adenocarcinoma of the bladder

Therapeutic Advances in Urology ◽

10.1177/17562872211018006 ◽

2021 ◽

Vol 13 ◽

pp. 175628722110180

Author(s):

Haowen Lu ◽

Weidong Zhu ◽

Weipu Mao ◽

Feng Zu ◽

Yali Wang ◽

...

Keyword(s):

Prediction Model ◽

Marital Status ◽

Cox Regression ◽

Tnm Staging ◽

Primary Site ◽

Primary Adenocarcinoma ◽

Cancer Specific Survival ◽

Training Cohort ◽

Cox Regression Analysis ◽

Ajcc Stage

Background: Primary adenocarcinoma of the bladder (ACB) is a rare malignant tumor of the bladder with limited understanding of its incidence and prognosis. Methods: Patients diagnosed with ACB between 2004 and 2015 were obtained from the SEER database. The incidence changes of ACB patients between 1975 and 2016 were detected by Joinpoint software. Nomograms were constructed based on the results of multivariate Cox regression analysis to predict overall survival (OS) and cancer-specific survival (CSS) in patients with ACB, and the constructed nomograms were validated. Results: The incidence of ACB was trending down from 1991 to 2016. A total of 1039 patients were included in the study and randomly assigned to the training cohort (727) and validation cohort (312). In the training cohort, multivariate Cox regression showed that age, marital status, primary site, histology type, grade, AJCC stage, T stage, SEER stage, surgery, radiotherapy, and chemotherapy were independent prognostic factors for OS, whereas these were age, marital status, primary site, histology type, grade, AJCC stage, T/N stage, SEER stage, surgery, and radiotherapy for CSS. Based on the above Cox regression results, we constructed prognostic nomograms for OS and CSS in ACB patients. The C-index of the nomogram OS was 0.773 and the C-index of CSS was 0.785, which was significantly better than the C-index of the TNM staging prediction model. The area under the curve (AUC) and net benefit of the prediction model were higher than those of the TNM staging system. In addition, the calibration curves were very close to the ideal curve, suggesting appreciable reliability of the nomograms. Conclusion: The incidence of ACB patients showed a decreasing trend in the past 25 years. We constructed a clinically useful prognostic nomogram for calculating OS and CSS of ACB patients, which can provide a personalized risk assessment for ACB patient survival.

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Residual Volume of Lymph Nodes During Chemoradiotherapy Based Nomogram to Predict Survival of Nasopharyngeal Carcinoma Patient Receiving Induction Chemotherapy

Frontiers in Oncology ◽

10.3389/fonc.2021.739103 ◽

2021 ◽

Vol 11 ◽

Author(s):

Yan Li ◽

Jian Zang ◽

Jingyi Liu ◽

Shanquan Luo ◽

Jianhua Wang ◽

...

Keyword(s):

Regression Analysis ◽

Nasopharyngeal Carcinoma ◽

Lymph Nodes ◽

Induction Chemotherapy ◽

Cox Regression ◽

Staging System ◽

Tnm Staging ◽

Residual Volume ◽

Discriminative Ability ◽

Cox Regression Analysis

PurposeTo accurately stratify nasopharyngeal carcinoma (NPC) patients who were benefit from induction chemotherapy (IC) followed by chemoradiotherapy (CCRT), we established residual volume of lymph nodes during chemoradiotherapy based nomogram to predict survival for NPC patients.MethodsCox regression analysis were used to evaluate predictive effects of tumor volume parameters. Multivariate Cox regression analysis was used to identify the prognostic factors, and nomogram models were developed to predict survival of NPC patients receiving IC followed by CCRT.ResultsCompared with other tumor volumetric parameters, midRT GTVnd was the best predictive factor for OS (HR: 1.043, 95%CI: 1.031-1.055), PFS (HR: 1.040, 95%CI: 1.030- 1.051), and DMFS (HR: 1.046, 95%CI: 1.034 – 1.059) according to the HR of Cox regression analysis. Based on multivariate analysis, three nomograms included midRT GTVnd were constructed to predict 4-year survival. The C-index of nomograms for each survival endpoints were as follow (training cohort vs. validation cohort): 0.746 vs. 0.731 for OS; 0.747 vs. 0.735 for PFS; 0.768 vs. 0.729 for DMFS, respectively. AUC showed a good discriminative ability. Calibration curves demonstrated a consistence between actual results and predictions. Decision curve analysis (DCA) showed that the nomograms had better clinical predictive effects than current TNM staging system.ConclusionWe identified the best volumetric indicator associated with prognosis was the residual volume of lymph nodes at the fourth week of chemoradiotherapy for patients receiving IC followed by CCRT. We developed and validated three nomograms to predict specific probability of 4-year OS, PFS and DMFS for NPC patient receiving IC followed by CCRT.

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A nomogram based on Aspartate Aminotransferase/Alanine Aminotransferase (AST/ALT) ratio after surgery to predict the prognostic value in patients with gastric cancer

10.21203/rs.3.rs-18794/v1 ◽

2020 ◽

Author(s):

Linfang Li ◽

Shan Xing ◽

Ning Xue ◽

Miantao Wu ◽

Yaqing Liang ◽

...

Keyword(s):

Gastric Cancer ◽

Aspartate Aminotransferase ◽

Alanine Aminotransferase ◽

Cox Regression ◽

Staging System ◽

Tnm Staging ◽

Calibration Plot ◽

Study Cohort ◽

Tnm Staging System ◽

Resectable Gastric Cancer

Abstract Background This study aimed to develop an effective nomogram for predicting overall survival (OS) in surgically treated gastric cancer. Methods We retrospectively evaluated 190 gastric cancer in this study. Cox regression analyses were performed to identify significant prognostic factors for OS in patients with resectable gastric cancer. The predictive accuracy of nomogram was assessed by calibration plot, concordance index (C-index) and decision curve, and then were compared with the traditional TNM staging system. Based on the total points (TPS) by nomogram, we further divided patients into different risk groups. Results On multivariate analysis of the 190 cohort, independent factors for survival were age, clinical stage and Aspartate Aminotransferase/Alanine Aminotransferase (SLR), which were entered into the nomogram. The calibration curve for the probability of OS showed that the nomogram-based predictions were in good agreement with actual observations. And the C-index of the established nomogram for predicting OS had a superior discrimination power compared with the TNM staging system [0.768 (95% CI: 0.725-0.810) vs 0.730 (95% CI: 0.688-0.772), p < 0.05]. Decision curve also demonstrated that the nomogram was better than TNM staging system. Based on the TPS of the nomogram, we further subdivided the study cohort into 3 groups: low risk (TPS ≤ 158), middle risk (158 < TPS ≤ 188), high risk (TPS > 188), the differences of OS rate were significant in the groups. Conclusions The established nomogram resulted in more accurate prognostic prediction for individual patient with resectable gastric cancer.

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