Dataset Information

A prognostic nomogram based on lymph node ratio for postoperative vulvar squamous cell carcinoma from the Surveillance, Epidemiology, and End Results database: a retrospective cohort study.

ABSTRACT:

Background

Vulvar carcinoma is a rare gynecological malignancy. The most commonly used staging system for vulvar cancer is the 2009 International Federation of Gynecology and Obstetrics (FIGO) staging system. Nevertheless, it does not incorporate many indispensable prognostic parameters, which prominently influence vulvar cancer patient survival. Thus, the development of a prediction model for evaluating survival prognosis in postoperative vulvar squamous cell cancer patients is of vital importance.

Methods

Data from 2,166 patients with pathologically confirmed diagnosis of vulvar squamous cell carcinoma from 2004 to 2015 were acquired from the Surveillance, Epidemiology, and End Results (SEER) database. Thirty percent of the patients were randomly assigned to the validation group, and the remainder were used to develop the nomogram. Parameters that significantly correlated with overall survival (OS) were used to create the nomogram. Concordance index (C-index), calibration curve, and decision curve analysis (DCA) were used to assess the predictive accuracy and discriminability of the nomogram model. Additionally, the C-index and DCA of the nomogram and the FIGO staging system were compared.

Results

Following multivariate analysis of the training cohort, independent factors for OS, including race, age at diagnosis, marital status, FIGO stage, tumor diameter, and lymph node ratio (LNR), were included in the nomogram model. The calibration curve indicated a high correlation between the nomogram-predicted and observed survival probability. The C-index of the nomogram in the training cohort was 0.772 (95% CI: 0.752-0.792), statistically superior to the C-index value of the FIGO staging system (0.676, 95% CI: 0.654-0.698). In DCA, compared to the FIGO staging system, this nomogram showed a greater net benefit and a wider range of threshold probability. Results were verified by an internal validation cohort.

Conclusions

Our nomogram, based on LNR, showed superior prognostic predictive accuracy compared with the FIGO staging system for predicting OS in postoperative vulvar squamous cell carcinoma patients.

SUBMITTER: Lei L

PROVIDER: S-EPMC7723549 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A prognostic nomogram based on lymph node ratio for postoperative vulvar squamous cell carcinoma from the Surveillance, Epidemiology, and End Results database: a retrospective cohort study.

Lei Lei L Tan Liao L Zhao Xingping X Zeng Fei F Xu Dabao D

Annals of translational medicine 20201101 21

<h4>Background</h4>Vulvar carcinoma is a rare gynecological malignancy. The most commonly used staging system for vulvar cancer is the 2009 International Federation of Gynecology and Obstetrics (FIGO) staging system. Nevertheless, it does not incorporate many indispensable prognostic parameters, which prominently influence vulvar cancer patient survival. Thus, the development of a prediction model for evaluating survival prognosis in postoperative vulvar squamous cell cancer patients is of vital ...[more]

PMID: 33313127

Similar Datasets

Project description:BackgroundLymph node (LN) involvement is an important prognostic indicator for patients with Wilms tumor (WT), and there have been previous reports of utilizing LN density (LND = positive LN/LNs examined) as an advanced metric to risk-stratify patients with WT.ObjectiveThe purpose of this study was to describe patient characteristics that affect LN yield and assess the effect of LND on the overall survival (OS) in patients with WT, with the expectation that patients with LNDs above a critical cut-point would demonstrate lower OS.Study designThe Surveillance, Epidemiology, and End Result (SEER) database was queried for all patients diagnosed with unilateral WT from 2004 to 2015. Patient and disease characteristics were collected, and Poisson regression was used to identify characteristics correlated with LN yield. LND was calculated for LN-positive patients, and multivariable survival analysis was performed, including patient demographics and LND as variables.Results1489 patients with unilateral WT were identified for analysis, 231 (15.51%) of whom were LN-positive. Median patient age at diagnosis was three years (IQR 1-5). On Poisson regression, the year of diagnosis, patient age, tumor size and laterality, and stage were found to impact LN yield. For patients with positive LNs, five-year OS of patients with LNDs above 0.4 was worse than those below 0.4 (76.1% vs 89.6%, p = 0.041). On multivariable analysis, tumor size and LND remained significant predictors of OS.DiscussionAdministrative databases such as SEER provide an excellent resource for studying conditions where large patient numbers for analysis are difficult to obtain. Unfortunately, the SEER database is unable to account for every factor that could affect LN sampling patterns. Additionally, favorable vs unfavorable histology is not available in SEER, and SEER utilizes its own staging system, which makes comparison to Children's Oncology Group staging difficult. Despite these limitations, the findings of this study are similar to those previously published using administrative databases analyzing LN sampling patterns and the effect of LND on OS in WT.ConclusionsAnalysis of the SEER database confirms that there are several patient- and disease-specific factors that affect the number of LNs sampled during nephrectomy for WT, and that LND may be a predictor of OS. These findings highlight the need for standardization of LN sampling patterns for pediatric renal tumors and support the investigation of LND in future studies to further risk-stratify WT patients to tailor therapy intensity.

Project description:BackgroundDue to the lack of large-scale clinical trials, the treatment strategies of small bowel adenocarcinoma (SBA) are controversial, especially for stage II patients. According to the National Comprehensive Cancer Network (NCCN) guideline, few lymph nodes (LNs) examined (<5 for duodenum or <8 for jejunal/ileal primary location) are one of the high-risk features for stage II patients, for whom adjuvant chemotherapy is recommended. This consensus is originally drawn from data in the Surveillance, Epidemiology, and End Results Database (SEER) between 1988 and 2010. However, the surgical modalities and chemotherapy strategies changed a lot after 2004 for SBA patients. The previous data may not represent a true picture of current therapeutics. Thus, we reanalyzed the SEER database and updated the cutoff point of LN numbers resected with respect to cancer-specific survival (CSS) using the latest SEER information.MethodsPatients diagnosed with stage II SBA and who underwent curative surgery between 2004 and 2018 were extracted from the SEER database. CSS was calculated using the Kaplan-Meier method and compared by log-rank test. Maximum survival differences based on total LNs examined for duodenal and jejunoileal tumors were determined separately with the cut-point analysis and maximum log-rank χ2 statistic. A nomogram model was constructed based on the multivariate Cox analysis to predict 5- and 10-year CSS and was then validated with an internal cohort.ResultsA total of 935 stage II SBA patients met the inclusion criteria. The greatest difference in survival was found in patients who had removal of at least 5 LNs for duodenal and 12 LNs for jejunoileal tumors. Multivariate Cox analysis showed that age, T stage, histology grade, primary site, and LN numbers were independent prognostic factors for survival. The C index of nomogram model was 0.701 (95% CI, 0.661-0.741, p < 0.001).ConclusionsThe number of LNs harvested is an important prognostic factor for survival in stage II SBA patients. LN number examined <5 remains a high-risk factor for duodenum, but the cutoff point for jejunal/ileal tumors should rise from 8 to 12. Appropriate radical lymphadenectomy should be performed in stage II SBA surgery.

Project description:BackgroundThe ability to predict survival in patients with lymph node metastasis has long been elusive. After surgery, the basis for decision-making on the combination treatment of patients is not clear. The purpose of this study was thus to build a survival nomogram model to effectively predict the overall survival (OS) of patients with non-small cell lung cancer (NSCLC) and lymph node metastasis. The number of dissected lymph nodes (NDLN), number of positive lymph nodes (NPLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) were included in this study to determine the risk factors in patients with advanced NSCLC.MethodsThe data of 5,132 patients with NSCLC and lymph node metastasis (N1 or N2) were extracted from the Surveillance, Epidemiology, and End Results (SEER) database according to inclusion and exclusion criteria and used as the training cohort. We enrolled 117 patients from the First Affiliated Hospital, Zhejiang University School of Medicine as the external validation cohort. Receiver operating characteristic (ROC) analyses were performed to determine the best cutoff values for predicting the prognosis of patients with NSCLC. Based on the risk factors affecting prognosis, a nomogram was constructed using univariate and multivariate Cox proportional hazard regression models. The discrimination ability of the nomogram was evaluated with the concordance index (C-index) and calibration curves. For the independent risk factors, survival curves were drawn using Kaplan-Meier analysis.ResultsROC curve analysis showed that the optimal NPLN cut-off value was 4, LNR was 0.26, and LODDS was -0.25, respectively. However, LNR was nonsignificant in multivariate analysis, with a P value of 0.274. The novel survival nomogram model included seven independent risk factors, among which were NPLN, LODDS, and chemotherapy. Model 4, which included N stage, NPLN, and LODDS, had a higher likelihood ratio (LR) and C-index than did the other models. The C-index was 0.648 [95% confidence interval (CI): 0.636-0.659] in the training cohort and 0.807 (95% CI: 0.751-0.863) in the external validation cohort, showing good prognostic accuracy and discrimination ability. According to the median risk score, the patients in the training cohort and external validation cohort were divided into high-risk and low-risk groups, between which significant differences in OS were found. In the training cohort, age, sex, T stage, N stage, NPLN, LODDS, and chemotherapy were significantly associated with OS (P<0.001). In the external validation cohort, T stage, NPLN, LODDS, and chemotherapy were found to be correlated with OS.ConclusionsThe NPLN and LODDS nomogram is an accurate survival prediction tool for patients with N1 or N2 NSCLC. Patients with lymph node metastasis can benefit from chemotherapy, but no evidence shows that radiotherapy is necessary for patients with resectable NSCLC.

Project description:BackgroundCurrently, there is no reliable method for predicting the prognosis of patients with large cell lung cancer (LCLC). The aim of this study was to develop and validate a nomogram model for accurately predicting the prognosis of patients with LCLC.MethodsLCLC patients, diagnosed from 2007 to 2009, were identified from the Surveillance, Epidemiology and End Results (SEER) database and used as the training dataset. Significant clinicopathologic variables (P<0.05) in a multivariate Cox regression were selected to build the nomogram. The performance of the nomogram model was evaluated by the concordance index (C-index), the area under the curve (AUC), and internal calibration. LCLC patients diagnosed from 2010 to 2016 in the SEER database were selected as a testing dataset for external validation. The nomogram model was also compared with the currently used American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system (8th edition) by using C-index and a decision curve analysis.ResultsEight variables-age, sex, race, marital status, T stage, N stage, M stage, and treatment strategy-were statistically significant in the multivariate Cox model and were selected to develop the nomogram model. This model exhibited excellent predictive performance. The C-index and AUC value were 0.761 [95% confidence interval (CI), 0.754 to 0.768] and 0.886 for the training dataset and 0.773 (95% CI, 0.765 to 0.781) and 0.876 for the testing dataset, respectively. This model also predicted three-year and five-year lung cancer-specific survival (LCSS) in both datasets with good fidelity. This nomogram model performs significantly better than the 8th edition AJCC TNM staging system, with a higher C-index (P<0.001) and better net benefits in predicting LCSS in LCLC patients.ConclusionsWe developed and validated a prognostic nomogram model for predicting 3- and 5-year LCSS in LCLC patients with good discrimination and calibration abilities. The nomogram may be useful in assisting clinicians to make individualized decisions for appropriate treatment in LCLC.

Project description:BackgroundPatients with T1 stage early colorectal cancer (CRC) can be treated with radical surgery or endoscopic surgery. Endoscopic surgery has a number of advantages, including minimal trauma and a rapid recovery. However, it cannot remove regional lymph nodes to assess whether there is lymph node metastasis. Thus, the analysis of the risk factors of lymph node metastasis in patients with T1 stage CRC is of great significance in the selection of appropriate treatment methods. Although previous studies have explored the risk factors for lymph node metastasis in T1 stage CRC patients, the number of cases were relatively insufficient, and further exploration is necessary.MethodsA total of 2,085 patients who had been pathologically diagnosed with CRC from 2015 to 2017 from the Surveillance, Epidemiology, and End Results (SEER) database. Among the patients, 324 had lymph node metastasis. A multivariate logistic regression analysis was conducted to analyze the risk factors of lymph node metastasis in patients with T1 stage CRC. Next, we established a prediction model to predict lymph node metastasis in patients with T1 stage CRC.ResultsThe results of the multivariate logistic regression analysis showed that age at diagnosis, rectosigmoid cancer, poorly differentiated or undifferentiated tumor cells, and distant metastasis were independent factors of lymph node metastasis in patients with T1 stage CRC (P<0.05). This study used the R4.0.3 statistical software for the statistical analysis. The data set was randomly divided into a training set and verification set. The training set comprised 1,460 patients, and the verification set comprised 625 patients. The area under the receiver operating characteristic curve (AUC) of the training set was 0.675 [95% confidence interval (CI): 0.635-0.714], and the AUC of the verification set was 0.682 (95% CI: 0.617-0.747). In the validation set, the model was tested by the Hosmer-Lemeshow Goodness-of-Fit Test (χ2=4.018, P=0.855), and the results showed that the model was reliable at predicting lymph node metastasis in patients with T1 stage CRC.ConclusionsFor CRC patients with high risk factors of lymph node metastasis, endoscopic physicians should carefully evaluate the advantages and disadvantages of the endoscopic surgery before deciding whether to perform this surgery.

Project description:ObjectivesTo compare the prognostic values of three lymph node staging systems in renal cell carcinoma (RCC), including the number of positive lymph nodes (NPLN), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS).DesignA retrospective cohort study using data from the Surveillance, Epidemiology and End Results (SEER) database.Setting and participants1904 patients with pathological N1 RCC, diagnosed from 2004 to 2015 and underwent nephrectomy combined with lymph node dissection, were identified from the SEER database.Primary outcome measureThe primary outcome of this study was overall survival (OS). Restricted cubic spline functions and multivariable Cox regression analyses were employed to characterise the associations of OS with NPLN, LNR and LODDS, respectively.ResultsData of 1904 eligible RCC patients were extracted from the SEER database. The mortality risks of RCC patients increased with the increasing of NPLN, LNR and LODDS. NPLN (NPLN3 vs NPLN1, HR 1.22, 95% CI 1.05 to 1.43, p=0.001), LNR (LNR3 vs LNR1, HR 1.46, 95% CI 1.28 to 1.67, p<0.001; LNR2 vs LNR1, HR 1.28, 95% CI 1.09 to 1.50, p=0.002) and LODDS (LODDS3 vs LODDS1, HR 1.48, 95% CI 1.28 to 1.72, p<0.001; LODDS2 vs LODDS1, HR 1.34, 95% CI 1.17 to 1.53, p<0.001) were all independent prognostic factors of OS. The predictive abilities of LNR (Akaike information criterion, AIC: 19576.3, optimism-corrected C-index: 0.677) and LODDS (AIC: 19579.2, optimism-corrected C-index: 0.676) were comparable, superior to NPLN (AIC: 19603.7, optimism-corrected C-index: 0.673). In subgroup analyses, the LODDS classification could better stratify survival of RCC patients, in particular for those with the number of dissected lymph nodes <13 or NPLN≤2.ConclusionsNPLN, LNR and LODDS were all independent predictors of OS in RCC. When compared with NPLN and LNR, LODDS had a better performance in survival prediction and risk stratification. The three metrics all had the potential to be integrated into future versions of the American Joint Committee on Cancer staging manual.

Dataset Information

A prognostic nomogram based on lymph node ratio for postoperative vulvar squamous cell carcinoma from the Surveillance, Epidemiology, and End Results database: a retrospective cohort study.

Background

Methods

Results

Conclusions

Publications

A prognostic nomogram based on lymph node ratio for postoperative vulvar squamous cell carcinoma from the Surveillance, Epidemiology, and End Results database: a retrospective cohort study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets