Log odds of positive lymph nodes predicts survival in patients treated with neoadjuvant therapy followed by esophagectomy

Prognostic nomogram for predicting the overall survival rate of patients with uterine clear-cell carcinoma: Based on SEER database

OBJECTIVE

To evaluate the risk factors for uterine clear-cell carcinoma (UCCC) and construct nomograms predicting 1-, 3-, and 5-year overall survival rates of patients with UCCC.

METHODS

The demographic and clinical information of 1674 patients diagnosed with UCCC between 2004 and 2015, including age, race, marital status, tumor size, American Joint Committee on Cancer (AJCC) stage, and details of surgery and radiotherapy/chemotherapy, was collected from the Surveillance, Epidemiology, and End Results (SEER) database. After excluding patients with unknown AJCC stage, race, marital status, or lymph node information, 1469 patients remained. Risk factors were determined using univariate and multivariate analyses, and nomograms were developed to predict 1-, 3-, and 5-year overall survival of UCCC. Various indicators were used to evaluate the performance of the nomogram, such as the C-index, net classification improvement (NRI) and decision curve analysis (DCA).

RESULTS

Age, log odds of positive lymph nodes, AJCC stage, surgery status, and chemotherapy status were independent risk factors for UCCC. The C-indexes of the training group and AJCC stage groups were 0.771 and 0.697, respectively. The results for the area under the receiver operating characteristics curve, NRI, and calibration curves indicated that the nomogram had good predictive ability. DCA revealed that the nomogram had greater clinical applicability than AJCC stage alone. Internal validation using the validation cohort also demonstrated that this nomogram had good predictive performance.

CONCLUSION

A new nomogram comprising a combination of demographic and clinical characteristics provided better survival predictions than the AJCC staging system alone, which will facilitate prognostic assessments and clinical decision-making.

Construction and validation of log odds of positive lymph nodes (LODDS)-based nomograms for predicting overall survival and cancer-specific survival in ovarian clear cell carcinoma patients

Background

Ovarian clear cell carcinoma (OCCC) is one of the special histologic subtypes of ovarian cancer. This study aimed to construct and validate log odds of positive lymph nodes (LODDS)-based nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with OCCC.

Methods

Patients who underwent surgical treatment between 2010 and 2016 were extracted from the Surveillance Epidemiology and End Results (SEER) database and the data of OCCC patients from the First Affiliated Hospital of Dalian Medical University were used as the external validation group to test the validity of the prognostic model. The best-fitting models were selected by stepwise Cox regression analysis. Survival probability was calculated by the Kaplan-Meier method, and the differences in survival time between subgroups were compared using the log-rank test. Each nomogram's performance was assessed by the calibration plots, decision curve analysis (DCA), and receiver operating characteristics (ROC) curves.

Results

T stage, distant metastasis, marital status, and LODDS were identified as significant risk factors for OS. A model with four risk factors (age, T stage, stage, and LODDS value) was obtained for CSS. Nomograms were constructed by incorporating the prognostic factors to predict 1-, 3- and 5-year OS and CSS for OCCC patients, respectively. The area under the curve (AUC) range of our nomogram model for OS and CSS prediction ranged from 0.738-0.771 and 0.769-0.794, respectively, in the training cohort. The performance of this model was verified in the internal and external validation cohorts. Calibration plots illustrated nomograms have good prognostic reliability.

Conclusion

Predictive nomograms were constructed and validated to evaluate the OS and CSS of OCCC patients. These nomograms may provide valuable prognostic information and guide postoperative personalized care in OCCC.

Combination of the Ratio Between Negative and Harvested Lymph Nodes and Metastatic Lymph Node Count as a Prognostic Indicator in Stage III Colon Cancer: A Retrospective Cohort Study

BACKGROUND

This study aimed to investigate the relationship between the ratio of negative lymph nodes (NLN) number to the number of metastatic lymph nodes (MLN) and the harvested lymph nodes (HLN) number ratio survival rate and compare its prognostic value.

METHODS

This retrospective cohort study included 207 stage III colon cancer patients between 2010 and 2018 at a single center. NLN/MLN and NLN/HLN cut-off values were determined with the receiver operating characteristic (ROC) curve according to 5-year survival. The patients were divided into high-risk and low-risk groups according to the cut-off value. These 2 groups were evaluated according to the clinicopathological data of the patients.

RESULT

The time-dependent ROC curve showed the optimal cut-off values of NLN as 3.86 and .79, respectively. These values show 83 patients in the high-risk group and 124 in the low-risk group. There was no difference between the groups in tumor localization and T stage. According to Kaplan-Meier survival analysis, mean survival was 35.88 months in the high-risk group and 50.18 months in the low-risk group. The risk of death in the high-risk group was 305% compared to the low-risk group (Hazard Ratio: 3.05, 95% 1.91 - 4.88) (P < .001).

CONCLUSION

NLNs are among the critical prognostic factors in colon cancer. Although NLNs have a positive correlation with the survival rate of the patients, there is no statistical difference in tumor T stage and localization.

The Prognostic Significance of Lymph Node Ratio for Esophageal Cancer: A Meta-Analysis

INTRODUCTION

This meta-analysis aimed to investigate the prognostic significance of positive lymph node ratio (LNR) in patients with esophageal cancer.

MATERIALS AND METHODS

The meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. We conducted a systematic search of relevant literature published until April 2022 in PubMed, EMBASE, and the Cochrane Library. The primary and secondary outcomes were overall survival (OS) and disease-free survival (DFS), with corresponding hazard ratios (HR) and 95% confidence intervals (CI). The included studies were subgrouped based on age, study area, adjuvant therapy, sensitivity analysis, and assessment of publication bias. We analyzed and discussed the results.

RESULTS

We included 21 studies with 29 cohorts and 11,849 patients. The Newcastle-Ottawa Scale scores of the included studies were no less than six, indicating high research quality. The combined results of HR and 95% CI showed that patients with esophageal cancer with a lower LNR had better OS (HR, 2.58; 95% CI, 2.15-3.11; P < 0.001) and DFS (HR, 3.07; 95% CI, 1.85-5.10; P < 0.001). The subgroup analysis suggested that geographic region, age, and adjuvant therapy affected OS. When any cohort was excluded, no significant changes were observed in the pooled HR of the OS group, indicating reliable and robust results. Egger's and Begg's tests showed no potential publication bias in the studies that used OS as an outcome measurement index, indicating reliable results. Sensitivity analyses and assessments of publication bias (<10) were not performed because of an insufficient number of DFS studies.

CONCLUSION

Patients with a lower positive LNR had a higher survival rate, suggesting that positive LNR may be a promising predictor of EC prognosis in esophageal cancer. After radical resection of esophageal cancer, the ratio of the number of dissected lymph nodes to the number of positive lymph nodes in patients with esophageal cancer should be considered to accurately evaluate the prognosis.

Log Odds of Positive Lymph Nodes (LODDS) as an Independent Predictor of Overall Survival Following Radical Cystectomy in Urothelial Bladder Cancer: Time to Rethink Conventional Node Staging

BACKGROUND

Radical cystectomy (RC) with lymph node dissection is the mainstay of treatment for patients with muscle-invasive bladder cancer (MIBC) and high risk non-MIBC. The American Joint Committee on Cancer's (AJCC) node staging and lymph node ratio (LNR) systems are used in estimating prognosis; however, they do not directly factor in negative dissected nodes. In this study, we evaluated the log odds of positive lymph nodes (LODDS), a novel measure of nodal involvement, as a predictor of survival.

PATIENTS AND METHODS

Eighty-three patients who underwent RC were retrospectively included and their demographic and clinical data were collected. Kaplan-Meier curve and Cox regression were used for survival analyses.

RESULTS

Median number of dissected lymph nodes was 13 (range 3-45). ROC curve analysis indicated -0.92 as the optimal LODDS cutoff. LODDS > -0.92 was associated with higher T stage, lymphovascular invasion, and significantly worse overall survival (OS) (mean OS 18.6 vs. 45.1 months, P-value < .001). Furthermore, we evaluated AJCC node staging, LNR, and LODDS in three separate multivariable Cox regression models. Among 3 different measures of nodal disease burden, only LODDS was an independent predictor of OS (HR 2.71, 95% CI 1.28-5.73, P = .009).

CONCLUSIONS

Our results show that LODDS is an independent predictor of OS and outperforms AJCC node staging and LNR in forecasting prognosis among patients with urothelial bladder cancer who undergo RC.

Development and validation of nodal staging score in pN0 patients with esophageal squamous cell carcinoma: A population study from the SEER database and a single-institution cohort

BACKGROUND

Patients with esophageal squamous cell carcinoma (ESCC) with lymph node metastasis may be misclassified as pN0 due to an insufficient number of lymph nodes examined (LNE). The purpose of this study was to confirm that patients with ESCC are indeed pN0 and to propose an adequate number for the correct nodal stage using the nodal staging score (NSS) developed by the beta-binomial model.

METHODS

A total of 1249 patients from the Surveillance, Epidemiology, and End Results (SEER) database between 2000 and 2017, and 1404 patients diagnosed with ESCC in our database between 2005 and 2018 were included. The NSS was developed to assess the probability of pN0 status based on both databases. The effectiveness of NSS was verified using survival analysis, including Kaplan-Meier curves and Cox models.

RESULTS

Many patients were misclassified as pN0 based on our algorithm due to insufficient LNE. As the number of LNE increased, false-negative findings dropped; accordingly, the NSS increased. In addition, NSS was an independent prognostic indicator for pN0 in patients with ESCC in the SEER database (hazard ratio [HR] 0.182, 95% confidence interval [CI] 0.046-0.730, p = 0.016) and our database (HR 0.215, 95% CI 0.055-0.842, p = 0.027). A certain number of nodes must be examined to achieve 90% of the NSS.

CONCLUSIONS

NSS could determine the probability of true pN0 status for patients, and it was sufficient in predicting survival and obtaining adequate numbers for lymphadenectomy.

Developing and validating a prognostic nomogram for ovarian clear cell carcinoma patients: A retrospective comparison of lymph node staging schemes with competing risk analysis

Purpose

Lymph node (LN) involvement is a key factor in ovarian clear cell carcinoma (OCCC) although, there several indicators can be used to define prognosis. This study examines the prognostic performances of each indicator for OCCC patients by comparing the number of lymph nodes examined (TNLE), the number of positive lymph nodes (PLN), lymph node ratio (LNR), and log odds of metastatic lymph nodes (LODDS).

Methods

1,300 OCCC patients who underwent lymphadenectomy between 2004 and 2015 were extracted from the Surveillance Epidemiology and End Results (SEER) database. Primary outcomes were Overall Survival (OS) and the cumulative incidence of Cancer-Specific Survival (CSS). Kaplan–Meier’s and Fine-Gray’s tests were implemented to assess OS and CSS rates. After conducting multivariate analysis, nomograms using OS and CSS were constructed based upon an improved LN system. Each nomograms’ performance was assessed using Receiver Operating Characteristics (ROC) curves, calibration curves, and the C-index which were compared to traditional cancer staging systems.

Results

Multivariate Cox’s regression analysis was used to assess prognostic factors for OS, including age, T stage, M stage, SEER stage, and LODDS. To account for the CSS endpoint, a proportional subdistribution hazard model was implemented which suggested that the T stage, M stage, SEER stage, and LNR are all significant. This enabled us to develop a LODDS-based nomogram for OS and a LNR-based nomogram for CSS. C-indexes for both the OS and CSS nomograms were higher than the traditional American Joint Committee on Cancer (AJCC), 8th edition, staging system. Area Under the Curve (AUC) values for predicting 3- and 5-year OS and CSS between nomograms also highlighted an improvement upon the AJCC staging system. Calibration curves also performed with consistency, which was verified using a validation cohort.

Conclusions

LODDS and LNR may be better predictors than N stage, TNLE, and PLNs. For OCCC patients, both the LODDS-based and LNR-based nomograms performed better than the AJCC staging system at predicting OS and CSS. However, further large sample, real-world studies are necessary to validate the assertion.

Evaluation of log odds of positive lymph nodes in predicting the survival of patients with non-small cell lung cancer treated with neoadjuvant therapy and surgery: a SEER cohort-based study

Background

Log odds of positive lymph nodes (LODDS) is a novel lymph node (LN) descriptor that demonstrates promising prognostic value in many tumors. However, there is limited information regarding LODDS in patients with non-small cell lung cancer (NSCLC), especially those receiving neoadjuvant therapy followed by lung surgery.

Methods

A total of 2059 patients with NSCLC who received neoadjuvant therapy and surgery were identified from the Surveillance, Epidemiology, and End Results (SEER) database. We used the X-tile software to calculate the LODDS cutoff value. Kaplan–Meier survival analysis and receiver operating characteristic (ROC) curve analysis were performed to compare predictive values of the American Joint Committee on Cancer (AJCC) N staging descriptor and LODDS. Univariate and multivariate Cox regression and inverse probability of treatment weighting (IPTW) analyses were conducted to construct a model for predicting prognosis.

Results

According to the survival analysis, LODDS had better differentiating ability than the N staging descriptor (log-rank test, P < 0.0001 vs. P = 0.031). The ROC curve demonstrated that the AUC of LODDS was significantly higher than that of the N staging descriptor in the 1-, 3-, and 5-year survival analyses (all P < 0.05). Univariate and multivariate Cox regression analyses showed that LODDS was an independent risk factor for patients with NSCLC receiving neoadjuvant therapy followed by surgery both before and after IPTW (all P < 0.001). A clinicopathological model with LODDS, age, sex, T stage, and radiotherapy could better predict prognosis.

Conclusions

Compared with the AJCC N staging descriptor, LODDS exhibited better predictive ability for patients with NSCLC receiving neoadjuvant therapy followed by surgery. A multivariate clinicopathological model with LODDS demonstrated a sound performance in predicting prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09908-3.

The Evaluation of a SEER-Based Nomogram in Predicting the Survival of Patients Treated with Neoadjuvant Therapy Followed by Esophagectomy

Background

A novel nomogram based on the Surveillance, Epidemiology, and End Results (SEER) database has been developed to predict the survival of patients with esophageal carcinoma who received neoadjuvant therapy followed by surgery. We aimed to evaluate the accuracy and value of the nomogram with an external validation cohort.

Methods

A total of 2,224 patients in SEER database were divided into the training cohort (n = 1556) and the internal validation cohort (n = 668), while 77 patients in our institute were enrolled in the external validation cohort. A Cox proportional hazards regression model was used to develop a nomogram based on the training cohort, while the C-indexes, the calibration curves, receiver operating characteristics curve (ROC), and Kaplan-Meier survival curve were applied in the internal and external validation cohort.

Results

Five independent risk factors were identified and integrated into the nomogram (C-index = 0.645, 95%CI 0.627–0.663). The nomogram exhibited good prognostic value in the internal validation cohort (C-index = 0.648 95%CI 0.622–0.674). However, the C-index, calibration plot, receiver operating characteristics curve (ROC) analysis, Kaplan-Meier survival curve of the nomogram in the external validation cohort were not as good as the training and internal validation cohort (C-index = 0.584 95%CI 0.445–0.723). Further analysis demonstrated that the resection margin involvement (R0, R1, or R2 resection) was an independent risk factor for the patients, which was not included in the SEER cohort.

Conclusions

the nomogram based on the SEER database fails to accurately predict the prognosis of the patients in the external validation cohort, which can be caused by the absence of essential information from the SEER database.

Lymph node status and its impact on the prognosis of left-sided and right-sided colon cancer: A SEER population-based study

Background

Some significant differences exist between the outcomes of left‐ and right‐sided colon cancer patients. The presence of nodal metastases is a critical prognostic factor, especially in the absence of distant metastasis. Our research studied the lymph nodes status of left‐ and right‐sided colon cancer patients to determine the influence of this factor on prognosis.

Methods

Our data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. We used the chi‐square test to analyze the clinicopathological characteristics. The X‐tile program was adopted to acquire optimal cutoff points of lymph node index. Kaplan–Meier curves were used to analyze prognosis and multivariate Cox regression models were performed to identify the independent factors associated with survival. Nomograms were built to predict the overall survival of patients, Harrell's C‐index and calibration plots were used to validate the nomograms.

Results

The study included 189,941 patients with colon cancer without metastasis (left 69,885, right 120,056) between 2004 and 2015. There are more patients with adequate examined lymph nodes in right‐sided. Lymph node status in patients with right colon cancer has a more significant impact on the risk of death. LODDS (C‐index: 0.583; AIC: 6875.4) was used to assess lymph node status. The nomograms showed that lymph node status was the main factor to predict the outcome in right‐sided colon patients.

Conclusions

The influence of lymph node status on predicting prognosis is significantly different between patients with left and right colon cancer without metastasis. The tumor site needs to be considered when lymph node status is used to assess the outcome of patients.