A Novel Nomogram including AJCC Stages Could Better Predict Survival for NSCLC Patients Who Underwent Surgery: A Large Population-Based Study
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In this study, we aimed to establish a novel nomogram model which was better than the current American Joint Committee on Cancer (AJCC) stage to predict survival for non-small-cell lung cancer (NSCLC) patients who underwent surgery. Patients and Methods. 19617 patients with initially diagnosed NSCLC were screened from Surveillance Epidemiology and End Results (SEER) database between 2010 and 2015. These patients were randomly divided into two groups including the training cohort and the validation cohort. The Cox proportional hazard model was used to analyze the influence of different variables on overall survival (OS). Then, using R software version 3.4.3, we constructed a nomogram and a risk classification system combined with some clinical parameters. We visualized the regression equation by nomogram after obtaining the regression coefficient in multivariate analysis. The concordance index (C-index) and calibration curve were used to perform the validation of nomogram. Receiver operating characteristic (ROC) curves were used to evaluate the clinical utility of the nomogram.Univariate and multivariate analyses demonstrated that seven factors including age, sex, stage, histology, surgery, and positive lymph nodes (all, P < 0.001) were independent predictors of OS. Among them, stage (C-index = 0.615), positive lymph nodes (C-index = 0.574), histology (C-index = 0.566), age (C-index = 0.563), and sex (C-index = 0.562) had a relatively strong ability to predict the OS. Based on these factors, we established and validated the predictive model by nomogram. The calibration curves showed good consistency between the actual OS and predicted OS. And the decision curves showed great clinical usefulness of the nomogram. Then, we built a risk classification system and divided NSCLC patients into two groups including high-risk group and low-risk group. The Kaplan-Meier curves revealed that OS in the two groups was accurately differentiated in the training cohort (P < 0.001). And then, we validated this result in the validation cohort which also showed that patients in the high-risk group had worse survival than those in the low-risk group.The results proved that the nomogram model had better performance to predict survival for NSCLC patients who underwent surgery than AJCC stage. These tools may be helpful for clinicians to evaluate prognostic indicators of patients undergoing operation.Keywords:
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The current neck management for early oral squamous cell carcinoma (OSCC) has always been a controversial issue. A comprehensive model is necessary for predicting an individual's metastasis risk and appropriate patient counseling.A nomogram for predicting 2-year LNM in patients with cT1-2N0 OSCC was developed and validated using clinicopathological data from 642 patients from 2000 to 2018 in four hospitals, China.Three variables (pathology grade, depth of invasion, tumor-infiltrating lymphocytes) were included in nomogram. C-indices were 0.826 (95% CI: 0.786-0.866) and 0.726 (95% CI: 0.653-0.780) in the internal and external validation. Kaplan-Meier method found the 2-year LNM rate of high-risk group (35.8%) was much higher than that of the low-risk group (14.5%). The nomogram model has an advantage over the 8th AJCC TNM stage in predicting the individual 2-year LNM probability for early OSCC.Patients with low-risk nomogram score may receive neck observation; those with high-risk score should receive END.
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To develop a nomogram for predicting the prognosis of T1 esophageal squamous cell carcinoma (ESCC) patients with positive lymph node. T1 ESCC patients with lymph node metastasis diagnosed between 2010 and 2015 were selected from the Surveillance, Epidemiology, and Final Results (SEER) database. The entire cohort was randomly divided in the ratio of 7:3 into a training group (n=457) and validation group (n=192), respectively. Prognostic factors were identified by univariate and multivariate Cox regression models. Harrell's concordance index (C-index), receiver operating characteristic (ROC) curve, and calibration curve were used to evaluate the discrimination and calibration of the nomogram. The accuracy and clinical net benefit of the nomogram compared with the 7th AJCC staging system were evaluated using net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). The nomogram consisted of eight factors: insurance, T stage, summary stage, primary site, radiation code, chemotherapy, surgery, and radiation sequence with surgery. In the training and validation cohorts, the AUCs exceeded 0.700, and the C-index scores were 0.749 and 0.751, respectively, indicating that the nomogram had good discrimination. The consistency between the survival probability predicted by the nomogram and the actual observed probability was indicated by the calibration curve in the training and validation cohorts. For NRI>0 and IDI>0, the predictive power of the nomogram was more accurate than that of the 7th AJCC staging system. Furthermore, the DCA curve indicated that the nomogram achieved better clinical utility than the traditional system. Unlike the 7th AJCC staging system, the developed and validated nomogram can help clinical staff to more accurately, personally and comprehensively predict the 1-year and 3-year OS probability of T1 ESCC patients with lymph node metastasis.
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Abstract Background Esophageal cancer (EC) is a malignant tumor with high mortality. Nomogram is an important tool used in clinical prognostic assessment. We aimed to establish a novel nomogram to predict the overall survival (OS) of EC patients after radical esophagectomy. Methods Data pertaining to the survival, demography, and clinicopathology of 311 EC patients who underwent radical esophagectomy were retrospectively investigated. The nomogram was established based on Cox hazard regression analysis. The calibration curves and Harrell's concordance index (C‐index) were used to verify the predictive accuracy and ROC curves were used to assess the efficacy of the nomogram. Kaplan–Meier curves showed the prognostic value of the related risk classification system. Pearson correlation test was performed to determine the correlation between the risk classification system and TNM staging. Results The median OS and 5‐year survival rates in the primary and validation cohorts were 44 months and 29.8%, and 52 months and 27.1%, respectively. We used six independent prognostic factors—age, Sex, AGR, PRL, N stage, and PNI—in the nomogram. The C‐index of nomogram was 0.75 and 0.70 in the primary and validation cohorts, respectively. Calibration curves indicated high consistency between actual and predicted OS. ROC curves showed that nomogram has a better efficacy compared with TNM staging in both cohorts. Patients were divided into three risk groups according to the total nomogram score, the median OS in each group was significantly different in both cohorts. Furthermore, the risk classification system was strongly correlated with the T and N staging system and exhibited a better OS prediction capability. Conclusions We established a novel and practical nomogram with a subordinate risk classification system to predict the OS of patients after radical esophagectomy. Compared with AJCC staging, this nomogram had preferable clinical capability in terms of individual prognosis assessment.
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This study was aimed to develop a nomogram for predicting the cancer-specific survival (CSS) of patients with clear-cell renal cell carcinoma (ccRCC).Based on the Surveillance, Epidemiology, and End Results (SEER) database, 24,477 patients diagnosed with ccRCC between 2010 and 2015 were collected.They were randomly divided into a training cohort (n = 17,133) and a validation cohort (n = 7,344).Univariate and multivariate Cox regression analyses were performed in the training cohort to identify independent prognostic factors for construction of nomogram.Then, the nomogram was used to predict the 3-and 5-year CSS.The performance of nomogram was evaluated by using concordance index (C-index), net reclassification improvement (NRI), integrated discrimination improvement (IDI), calibration curve, and decision curve analysis (DCA).Moreover, the nomogram and tumor node metastasis (TNM) staging system (AJCC 7 th edition) were compared.Eleven variables were screened to develop the nomogram.The area under the receiver operating characteristic (ROC) curve (AUC) and the calibration plots indicated satisfactory ability of the nomogram.Compared with the AJCC 7 th edition of TNM stage, C-index, NRI, and IDI showed that the nomogram had improved performance.Furthermore, the 3-and 5-year DCA curves of nomogram yielded more net benefits than the AJCC 7 th edition of TNM stage in both the training and validation sets.We developed and validated a nomogram for predicting the CSS of patients with ccRCC, which was more precise than the AJCC 7 th edition of TNM staging system.
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Abstract Background Gastric neuroendocrine carcinoma (GNEC) is a rare histology of gastric cancer. The retrospective study was designed to construct and validate a nomogram for predicting the cancer-specific survival (CSS) of postoperative GNEC patients. Methods Data for 28 patients from the Hangzhou TCM Hospital were identified as the external validation cohort. A total of 1493 patients were included in the SEER database and randomly assigned to the training group (1045 patients) and internal validation group (448 patients). The nomogram was constructed using the findings of univariate and multivariate Cox regression studies. The model was evaluated by consistency index (C-index), calibration plots, and clinical net benefit. Finally, the effect between the nomogram and AJCC staging system was compared by net reclassification index (NRI) and integrated discrimination improvement (IDI). Results Age, gender, grade, T stage, N stage, metastasis, primary site, tumor size, RNE, and chemotherapy were incorporated in the nomogram. The C-indexes were 0.792 and 0.782 in the training and internal verification sets. The 1-, 3-, and 5-year CSS predicted by the nomogram and actual measurements had good agreement in calibration plots. The 1-, 3-, and 5-year NRI were 0.21, 0.29, and 0.37, respectively. The 1-, 3-, and 5-year IDI values were 0.10, 0.12, and 0.13 (P < 0.001), respectively. In 1-, 3-, and 5-year CSS prediction using DCA curves, the nomogram outperformed the AJCC staging system. The nomogram performed well in both the internal and external validation cohorts. Conclusion We developed and validated a nomogram to predict 1-, 3-, and 5-year CSS for GNEC patients after surgical resection. This well-performing model could help doctors enhance the treatment plan.
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To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with surgically resected intrahepatic cholangiocarcinoma (ICC).The nomograms were developed using a development cohort of 947 ICC patients after surgery selected from Surveillance, Epidemiology, and End Results database, and externally validated using a training cohort of 159 patients admitted at our institution. Nomograms for OS and CSS were established based on the independent prognostic factors identified by COX regression models and Fine and Grey's models, respectively. The performance of the nomograms was validated internally and externally by using the concordance index (c-index), and calibration plot, and compared with that of AJCC 8th edition TNM staging system by using c-index and decision curve analysis.Age, T stage, M stage, lymph node ratio (LNR) level and tumor grade were independent prognostic predictors for OS in ICC patients, while T stage, M stage, LNR level and tumor grade were independent prognostic predictors for CSS. Nomogram predicting OS was with a c-index of 0.751 on internal validation and 0.725 up to external validation, while nomogram for CSS was with a c-index of 0.736 on internal validation and 0.718 up to external validation. Calibration plots exhibited that the nomograms-predicted and actual OS/CSS probabilities were fitted well on both internal and external validation. Additionally, the nomograms exhibited superiority over AJCC 8th edition TNM staging system with higher c-indices and net benefit gains, in predicting OS and CSS in ICC patients after surgery.The constructed nomograms could predict OS and CSS with good performance, which could be served as an effective tool for prognostic evaluation and individual treatment strategies optimization in ICC patients after surgery in clinical practice.
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This study aimed to develop and validate a nomogram for predicting cancer-specific survival (CSS) in patients with non-keratinized large cell squamous cell carcinoma (NKLCSCC) at 3, 5, and 8 years after diagnosis.Data on SCC patients were collected from the Surveillance, Epidemiology, and End Results database. Training (70%) and validation (30%) cohorts were generated using random selection of patients. Independent prognostic factors were selected using the backward stepwise Cox regression model. To predict the CSS rates in patients with NKLCSCC at 3, 5, and 8 years after diagnosis, all of the factors were incorporated into the nomogram. Indicators such as the concordance index (C-index), area under the time-dependent receiver operating characteristic curve (AUC), net reclassification index (NRI), integrated discrimination improvement (IDI), calibration curve, and decision-curve analysis (DCA) were then used to validate the performance of the nomogram.This study included 9,811 patients with NKLCSCC. Twelve prognostic factors were identified by Cox regression analysis in the training cohort, which were age, number of regional nodes examined, number of positive regional nodes, sex, race, marital status, American Joint Committee on Cancer (AJCC) stage, surgery status, chemotherapy status, radiotherapy status, summary stage, and income. The constructed nomogram was validated both internally and externally. The nomogram had good discrimination ability, as indicated by the comparatively high C-indices and AUC values. The nomogram was properly calibrated, as indicated by the calibration curves. Our nomogram was superior to the AJCC model, as illustrated by its superior NRI and IDI values. DCA curves indicated the clinical usability of the nomogram.The first nomogram for prognosis predictions of patients with NKLCSCC has been developed and verified. Its performance and usability demonstrated that the nomogram could be utilized in clinical settings. However, additional external verification is still required.
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Abstract Background Anal squamous cell carcinoma (ASCC) is the main subtype of anal cancer and has great heterogeneity in prognosis. We aimed to construct a nomogram for predicting their 1‐, 3‐, and 5‐year overall survival (OS) rates. Methods Patients with ASCC, enrolled between January 1, 2010 and December 31, 2017, were identified from the SEER database. They were divided into a training group and a validation group in a ratio of 7:3. Univariate and multivariate Cox analyses were used to identify the prognostic factors for OS. Then a prognostic nomogram was established and validated by Harrell consistency index (C‐index), area under the curve (AUC) of the receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Results We identified 761 patients in training group and 326 patients in validation group. Four prognostic factors including age, sex, AJCC stage, and radiotherapy were identified and integrated to construct a prognostic nomogram. The C‐index and AUC values proved the model's effectiveness and calibration plots manifested its excellent discrimination. Furthermore, in comparison to the AJCC stage, the C‐index, AUC, and DCA proved the nomogram to be of good predictive value. Finally, we constructed a risk stratification model for dividing patients into low‐risk, medium‐risk, and high‐risk groups, and there were obvious differences in OS. Conclusions A prognostic nomogram was firstly established for predicting the survival probability of ASCC patients and helping clinicians improve their risk management.
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Abstract Objective: This study aimed to establishand validates a nomogram to predict the overall survival (OS) of patients with intrahepatic cholangiocarcinoma (ICC). Patients and methods: The ICC patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2015. Then, the independent prognosis-related factors were obtained from the training set using the Cox regression model for the establishment of a nomogram. Results : We identified 3675 eligible patients with a median survival time of 9 months (0–153 months). According to multivariate analysis, age, sex, marital status, grade, T stage, N stage, M stage, surgery, chemotherapy and radiotherapy were identified as the factors to independently predictthe prognosis for ICC (all P <0.05). Thereafter, the above factors were incorporated for the construction of a nomogram. In comparison with the AJCC 8th TNM classification system and the SEER summary stage system, our constructed nomogram showed higher ability in discrimination, as revealed by the C-index (all P <0.001).Besides, the internal as well as external calibration curve analysis demonstrated that the predicted results were highly consistent with the actual ones. On the other hand, our nomogram outperformed the AJCC 8th TNM classification system and the SEER summary stage system in predicting the 3- and 5-year OS, as suggested by time-independent area under the curve (tAUC) values. Conclusion : Our constructed nomogram performs well, indicating its potential as an efficient approach to evaluate the prognosis of ICC patients.
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