The impact of the lymph node density on overall survival in patients with Wilms' tumor: a SEER analysis

Prediction values of different lymph nodes staging systems for survival of children with Wilms tumor

Background

Wilms tumor is one of the most common pediatric kidney cancers with poor prognosis. This study aims to explore the predictive values of lymph nodes (LNs), positive lymph node density (LND) and log odds of positive lymph nodes (LODDS) for the 5-year mortality of children with Wilms tumor.

Methods

The cohort study collected the data of 874 participants with Wilms tumor in the Surveillance, Epidemiology, and End Results (SEER) database. The univariate COX proportional risk model was used to explore the possible covariates. The univariate and multivariable COX proportional risk model were employed for exploring the correlations of LNs, LND, and LODDS with the 5-year mortality of Wilms tumor patients. The predictive values of LNs, LND, and LODDS for the 5-year mortality of children with Wilms tumor were evaluated via concordance and 95% confidence interval (CI).

Results

The follow-up time was 5 years, and 804 participants survived in the end. The results delineated that LND >0 [hazard ratio (HR) =1.92, 95% CI: 1.01-3.67] as well as LND ≥0.93 (HR =4.87, 95% CI: 2.42-9.81) were correlated with increased risk of 5-year mortality while LODDS ≥-0.34 (HR =4.09, 95% CI: 2.18-7.65) was linked with elevated risk of 5-year mortality. The concordance of LNs for predicting the 5-year mortality of Wilms tumor patients was 0.623 (95% CI: 0.566-0.681). The concordances of LND, and LODDS for predicting the 5-year mortality of Wilms tumor patients were 0.623 (95% CI: 0.566-0.681) and 0.616 (95% CI: 0.562-0.669).

Conclusions

The predictive value of LODDS for the 5-year mortality of children with Wilms tumor was similar with LNs and LND. The findings might provide a new tool for helping the clinicians identify those with poor prognosis, and timely treatments should be offered to these patients.

Identifying risk and prognostic factors for synchronous liver metastasis in small bowel adenocarcinoma: a predictive analysis using the SEER database

Background

Small bowel adenocarcinoma (SBA) is a rare gastrointestinal malignancy with an increasing incidence and a high propensity for liver metastasis (LM). This study aimed to investigate the risk factors for synchronous LM and prognostic factors in patients with LM.

Methods

Utilizing the Surveillance, Epidemiology, and End Results (SEER) database, this study analyzed data from 2,064 patients diagnosed with SBA between 2010 and 2020. Logistic regression was used to determine risk factors for synchronous LM. A nomogram was developed to predict the risk of LM in SBA patients, and its predictive performance was assessed through receiver operating characteristic (ROC) curves and calibration curves. Kaplan-Meier and Cox regression analyses were conducted to evaluate survival outcomes for SBA patients with LM.

Results

Synchronous LM was present in 13.4% of SBA patients (n = 276). Six independent predictive factors for LM were identified, including tumor location, T stage, N stage, surgical intervention, retrieval of regional lymph nodes (RORLN), and chemotherapy. The nomogram demonstrated good discriminative ability, with an area under the curve (AUC) of 83.8%. Patients with LM had significantly lower survival rates than those without LM (P < 0.001). Survival analysis revealed that advanced age, tumor location in the duodenum, surgery, RORLN and chemotherapy were associated with cancer-specific survival (CSS) in patients with LM originating from SBA.

Conclusions

This study highlights the significant impact of LM on the survival of SBA patients and identifies key risk factors for its occurrence. The developed nomogram aids in targeted screening and personalized treatment planning.

Insights into Personalized Care Strategies for Wilms Tumor: A Narrative Literature Review

Wilms tumor (WT), or nephroblastoma, is the predominant renal malignancy in the pediatric population. This narrative review explores the evolution of personalized care strategies for WT, synthesizing critical developments in molecular diagnostics and treatment approaches to enhance patient-specific outcomes. We surveyed recent literature from the last five years, focusing on high-impact research across major databases such as PubMed, Scopus, and Web of Science. Diagnostic advancements, including liquid biopsies and diffusion-weighted MRI, have improved early detection precision. The prognostic significance of genetic markers, particularly WT1 mutations and miRNA profiles, is discussed. Novel predictive tools integrating genetic and clinical data to anticipate disease trajectory and therapy response are explored. Progressive treatment strategies, particularly immunotherapy and targeted agents such as HIF-2α inhibitors and GD2-targeted immunotherapy, are highlighted for their role in personalized treatment protocols, especially for refractory or recurrent WT. This review underscores the necessity for personalized management supported by genetic insights, with improved survival rates for localized disease exceeding 90%. However, knowledge gaps persist in therapies for high-risk patients and strategies to reduce long-term treatment-related morbidity. In conclusion, this narrative review highlights the need for ongoing research, particularly on the long-term outcomes of emerging therapies and integrating multi-omic data to inform clinical decision-making, paving the way for more individualized treatment pathways.

Development and validation of a nomogram for predicting cancer-specific survival in small-bowel adenocarcinoma patients using the SEER database

BACKGROUND

Small bowel adenocarcinoma (SBA) is a rare gastrointestinal malignancy forwhich survival is hampered by late diagnosis, complex responses to treatment, and poor prognosis. Accurate prognostic tools are crucial for optimizing treatment strategies and improving patient outcomes. This study aimed to develop and validate a nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database to predict cancer-specific survival (CSS) in patients with SBA and compare it to traditional American Joint Committee on Cancer (AJCC) staging.

METHODS

We analyzed data from 2,064 patients diagnosed with SBA between 2010 and 2020 from the SEER database. Patients were randomly assigned to training and validation cohorts (7:3 ratio). Kaplan‒Meier survival analysis, Cox multivariate regression, and nomograms were constructed for analysis of 3-year and 5-year CSS. The performance of the nomograms was evaluated using Harrell's concordance index (C-index), the area under the receiver operating characteristic (ROC) curve, calibration curves, decision curve analysis (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI).

RESULTS

Multivariate Cox regression identified sex, age at diagnosis, marital status, tumor site, pathological grade, T stage, N stage, M stage, surgery, retrieval of regional lymph nodes (RORLN), and chemotherapy as independent covariates associated with CSS. In both the training and validation cohorts, the developed nomograms demonstrated superior performance to that of the AJCC staging system, with C-indices of 0.764 and 0.759, respectively. The area under the curve (AUC) values obtained by ROC analysis for 3-year and 5-year CSS prediction significantly surpassed those of the AJCC model. The nomograms were validated using calibration and decision curves, confirming their clinical utility and superior predictive accuracy. The NRI and IDI indicated the enhanced predictive capability of the nomogram model.

CONCLUSION

The SEER-based nomogram offers a significantly superior ability to predict CSS in SBA patients, supporting its potential application in clinical decision-making and personalized approaches to managing SBA to improve survival outcomes.

A Nomogram for Predicting Cancer-Specific Survival in Children With Wilms Tumor: A Study Based on SEER Database and External Validation in China

Background

Wilms tumor (WT) is the most common tumor in children. We aim to construct a nomogram to predict the cancer-specific survival (CSS) of WT in children and externally validate in China.

Methods

We downloaded the clinicopathological data of children with WT from 2004 to 2018 in the SEER database. At the same time, we used the clinicopathological data collected previously for all children with WT between 2013 and 2018 at Children's Hospital of Chongqing Medical University (Chongqing, China). We analyzed the difference in survival between the patients in the SEER database and our hospital. Cox regression analysis was used to screen for significant risk factors. Based on these factors, a nomogram was constructed to predict the CSS of children with WT. Calibration curve, concordance index (C-index), the area under the receiver operating curve (AUC) and decision curve analysis (DCA) was used to evaluate the accuracy and reliability of the model.

Results

We included 1,045 children with WT in the SEER database. At the same time, we collected 112 children with WT in our hospital. The Kaplan-Meier curve suggested that children in China with WT had a higher mortality rate than those in the United States. Cox regression analysis revealed that age, lymph node density (LND), and tumor stage were significant prognostic factors for the patients in the SEER database. However, the patients in our hospital only confirmed that the tumor stage and the number of positive regional lymph nodes were significant factors. The prediction model established by the SEER database had been validated internally and externally to prove that it had good accuracy and reliability.

Conclusion

We have constructed a survival prognosis prediction model for children with WT, which has been validated internally and externally to prove accuracy and reliability.

Standardizing lymph nodal sampling for Wilms tumor: A feasibility study with outcomes

BACKGROUND

Despite being mandated by cooperative groups, omission of nodal sampling is the most frequent protocol deviation in surgery for Wilms tumor. The stations as well as the number of nodes that should be sampled are not clearly defined resulting in a marked variation in practices among surgeons. We propose a systematic method for nodal sampling intending to reduce interoperator variation. In this study, we have assessed the feasibility and yield of systematic lymph node sampling and also evaluated the factors influencing nodal metastasis.

METHODS

Prospective evaluation of 113 Wilms tumor patients operated at a single tertiary cancer center between 2015 and 2019. All these patients underwent a systematic 5-station nodal sampling.

RESULTS

Median lymph node yield was 8 and 13.2% (15/113) patients harbored a histologically positive nodal disease. Of the patients with positive nodal disease, interaortocaval nodes had metastasis in 46.7% (n = 7). They represented isolated sites of nodal disease (skip metastases) in 28.6% (n = 4) of patients. Right-sided tumors had more frequent involvement of interaortocaval nodes and skip disease. Tumors with high-risk histology had 12.5 times more odds of harboring nodal disease as compared to low and intermediate-risk histology Wilms tumor.

CONCLUSIONS

The proposed method of systematic station wise sampling provides a template to guide surgeons in performing lymph node harvesting. Interaortocaval nodes sampling should be performed routinely as the incidence of disease at this station is sufficiently high and metastasis may skip hilar nodes.

STUDY OF DIAGNOSTIC TEST

Level III evidence.

Insurance status is related to overall survival in patients with small intestine adenocarcinoma: A population-based study

BACKGROUND

Our goal was to investigate the effect of insurance status on the overall survival (OS) in cases of small intestine adenocarcinoma.

METHODS

The SEER (Surveillance, Epidemiology, and End Results) database was used to identify 3822 patients who were diagnosed with small intestine adenocarcinoma between 2007 and 2015. The proportional hazard ASSUMPTION was evaluated by proportional-hazards assumption test and Schoenfeld residual test. The Kaplan-Meier method and Cox proportional-hazards regression analysis were performed to evaluate the association between insurance status and OS.

RESULTS

We found that the insurance status at the time of diagnosis affected OS at the population level, both in those aged <65 and ≥65 years. Cox multivariate analysis of patients aged <65 years revealed that the hazard of death was greater in the Medicaid group (hazard ratio [HR] = 1.641, 95% confidence interval [CI] = 1.299-2.073, P < 0.001] and uninsured group (HR = 1.472, 95% CI = 1.095-1.979, P = 0.010) compared with the insured group, while the OS did not differ significantly between the Medicaid and uninsured groups. Similarly, the hazard of death among patients aged ≥65 years was higher in the Medicaid than the insured group (HR = 1.403, 95% CI = 1.136-1.733, P = 0.002).

CONCLUSION

Our results suggest that patients with small intestine adenocarcinoma with insurance coverage have a significantly better OS than patients who have Medicaid or are uninsured, while the OS does not differ between Medicaid and uninsured patients.

Factors affecting lymph node sampling patterns and the impact on survival of lymph node density in patients with Wilms tumor: a Surveillance, Epidemiology, and End Result (SEER) database review

BACKGROUND

Lymph 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.

OBJECTIVE

The 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 DESIGN

The 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.

RESULTS

1489 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.

DISCUSSION

Administrative 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.

CONCLUSIONS

Analysis 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.

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

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.

Nomogram for predicting the survival of patients with malignant melanoma: A population analysis

The aim of the current study was to develop and validate a nomogram based on a large population to estimate the 3- and 5-year survival rates of patients with malignant melanoma (MM). Patients were selected from the Surveillance, Epidemiology and End Results database and randomly divided into the training and validation cohorts. A nomogram was developed, and was used to assess the accuracy of the model. Independent prognostic factors associated with overall survival (OS) rate were identified through multivariate analysis, and were included in the internal validation of the nomogram. The nomogram provided high C-indexes for the training cohort [area under the time-dependent receiver operating characteristic curve (AUC) of 0.877 for 3-year OS rate and 0.872 for 5-year OS rate] and the validation cohort (AUC of 0.880 for 3-year OS rate and 0.874 for 5-year OS rate), indicating that the model had good discrimination ability. Calibration plots showed that the predicted 3- and 5-year OS rates probabilities for the training and validation groups were almost identical to the actual observations. The 3- and 5-year decision curves indicated net benefits for both the training and validation cohorts. The nomogram may aid clinicians to provide more accurate prognosis prediction in patient consultations and more personalized postoperative management plans.

Nomograms for predicting the survival rate for cervical cancer patients who undergo radiation therapy: a SEER analysis

Aim: To integrate multiple independent risk factors to establish prognostic nomograms for better predicting overall survival and disease-specific survival in patients with cervical cancer receiving radiation therapy. Materials & methods: Cox analysis used to construct nomograms. The C-index, time-dependent receiver operating characteristic and calibration plots were used to evaluate the performance. The discrimination abilities were compared using the decision curve analysis, net reclassification improvement and integrated discrimination improvement. Results: After randomization, 2869 and 1230 cervical cancer patients were included in the training and validation sets, respectively. Nomograms that incorporated all of the significant independent factors for predicting the 3- and 5-year overall survival and disease-specific survival in the training cohort were established. Conclusion: Compared with the International Federation of Gynecology and Obstetrics staging system, the proposed nomograms exhibit superior prognostic discrimination and survival prediction.

Development and validation of a nomogram for predicting cancer-specific survival in patients with Wilms' tumor

Purpose: The objective of this study was to develop and validate a nomogram for predicting the cancer-specific survival (CSS) in patients with Wilms' tumor (WT). Methods: Patients with WT diagnosed between 2002 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were divided randomly into training and validation cohorts in this study. Multivariate Cox regression analysis was used to screen variables. A Cox proportional-hazards regression model and a nomogram were constructed based on variables that significantly affected the CSS in the training cohort. The nomogram for distinguishing and predicting the CSS was evaluated using the concordance index (C-index), the area under the time-dependent receiver operating characteristic curve (AUC), and calibration plots. Results: In total, 1631 patients from the SEER database were enrolled, with 1141 categorized into the training cohort and 490 into the validation cohort. All significant variables associated with CSS-age, the number of examined lymph nodes, SEER stage, and tumor size-were included in the nomogram. The C-index values of the nomogram in the training and validation cohorts were 0.746 and 0.703, respectively. The 3-, 5-, and 10-year AUCs were 0.755, 0.749, and 0.724, respectively, in the training cohort, and 0.718, 0.707, and 0.718 in the validation cohort. The calibration plots indicated the nomogram could accurately predict the 3-, 5-, and 10-year CSS. Conclusions: We have developed and validated the first nomogram for predicting the survival of WT patients. The nomogram is a reliable tool for distinguishing and predicting the CSS in patients with WT. Information provided by the nomogram may help to improve the clinical practices related to WT.

Determining the optimal cutoff point for lymph node density and its impact on overall survival in children with Wilms' tumor

OBJECTIVE

Previous studies showed that the lymph node density (LND) was a predictor of survival in Wilms' tumor (WT). However, the optimal LND cutoff point is controversial due to methodological shortcomings of previous studies, and no studies have shown the effect of LND on survival in children with WT. The purpose of this study was to remedy this situation.

METHODS

We identified 376 children with WT. LND cutoff point was determined using the median value, the X-tile program, the survival-tree algorithm, and the time-dependent ROC curve analysis. Survival functions were estimated by the Kaplan-Meier method. We used Cox regression analysis to determine the impact of LND on survival. Smooth curve fitting between relative mortality risk and LND was performed.

RESULTS

The LND cutoff point was 0.44, 0.65, 0.65, and 0.64 according to the median value, the X-tile program, the survival-tree algorithm, and the time-dependent ROC curve analysis, respectively. The 5-, 10-, and 20-year overall survival rates were 86.9%, 86.9%, and 84.7%, respectively, in the <0.44 group and 81.3%, 80.3%, and 80.3%, respectively, in the ≥0.44 group. Survival did not differ significantly between the two groups (P=0.185). The 5-, 10-, and 20-year overall survival rates were 87.8%, 87.8%, and 86.0%, respectively, in the < 0.65 or < 0.64 group and 76.5%, 75.1%, and 75.1%, respectively, in the ≥ 0.65 or ≥ 0.64 group. Children with the high LND had a significantly worse survival (P=0.011) if 0.64 or 0.65 was used for the stratification. LND was a significant predictor for overall survival in the multivariate Cox regression analysis (HR =1.797; 95% CI, 1.043-3.097; P=0.035). Smooth curve fitting suggested that the risk of mortality tended to be ascending with the increase in LND in general.

CONCLUSION

The three methods including the X-tile program, the survival-tree algorithm, and the time-dependent receiver operating characteristic (ROC) curve analysis are equivalent in their ability to stratify patients and clearly better than the median method. The results showed that the optimal LND cutoff point was around 0.65 and the LND was a reliable predictor of overall survival in children with WT.

Predictors of nodal metastasis and prognostic significance of lymph node ratio and total lymph node count in tracheobronchial adenoid cystic carcinoma

Purpose

To identify potential risk factors of lymph node metastasis and to verify the prognostic significance of the lymph node ratio (LNR) and the total number of lymph nodes examined (NNE) in tracheobronchial adenoid cystic carcinoma (ACC) patients, using a large population-based database.

Patients and methods

From Surveillance, Epidemiology, and End Results database, we identified 263 patients with tracheobronchial ACC in whom complete lymph node data could be obtained. Logistic regression analysis was performed to determine predictive factors of nodal metastasis. X-tile software determined the optimal cut-off points for LNR and NNE. Kaplan- Meier analyses and Cox regression models were adopted for survival analysis.

Results

Of 263 patients, 75 (28.5%) had lymph node involvement. Tumors of bronchial origin (P<0.001) and tumors larger than 30 mm (P<0.001) were associated with a higher likelihood of nodal involvement. Examination of more than ten lymph nodes could avoid understaging and resulted in improved survival; meanwhile, patients with a LNR of 0.07 or less had favorable prognosis.

Conclusion

Patients with tracheobronchial ACC have significant risk of lymph node metastasis. Bronchial ACC and larger tumor size are both risk factors of lymph node metastasis. LNR and NNE may provide a more precise prediction of survival and could be taken into account in future clinical work.