Prognostic value of log odds of positive lymph nodes in node-positive lung squamous cell carcinoma patients after surgery: a SEER population-based study

A novel log odds of positive lymph nodes-based nomogram for predicting overall survival in patients with colorectal signet ring cell carcinoma: a SEER population-based study

PURPOSE

Considering the poor prognosis and high lymph node (LN) involvement rate of colorectal signet ring cell carcinoma (SRCC), this study aimed to construct a prognostic nomogram to predict overall survival (OS) with satisfactory accuracy and utility, based on LN status indicators with superior predictability.

METHODS

Using the Surveillance, Epidemiology, and End Results (SEER) database, we obtained cases of colorectal SRCC patients and employed univariate and multivariate Cox analyses to determine independent prognostic factors. Kaplan-Meier curves were utilized to visualize survival differences among these factors. Receiver operating characteristic curves were generated to assess predictive performances of models incorporating various LN status indicators. A novel nomogram, containing optimal LN status indicators and other prognostic factors, was developed to predict OS, whose discriminatory ability and accuracy were evaluated using calibration curves and decision curve analysis.

RESULTS

A total of 1663 SRCC patients were screened from SEER database. Older patients and those with grades III-IV, tumor sizes > 39 mm, T3/T4 stage, N1/N2 stage, M1 stage, and higher log odds of positive lymph nodes (LODDS) values exhibited poorer prognoses. Age, grade, tumor size, TNM stage, and LODDS were independent prognostic factors. The model containing N stage and LODDS outperformed the one relying solely on N stage as LN status indicator, resulting in a validated nomogram for accurately predicting OS in SRCC patients.

CONCLUSION

The integration of LODDS, N stage, and other risk factors into a nomogram offered precise OS predictions, enhancing therapeutic decision-making and tailored follow-up management for colorectal SRCC patients.

A survival nomogram model for patients with resectable non-small cell lung cancer and lymph node metastasis (N1 or N2) based on the Surveillance, Epidemiology, and End Results Database and single-center data

Background

The 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.

Methods

The 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.

Results

ROC 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.

Conclusions

The 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.

Construction and validation of a nomogram based on the log odds of positive lymph nodes to predict cancer-specific survival in patients with small cell lung cancer after surgery

Background

The lymph node ratio (LNR) is useful for predicting survival in patients with small cell lung cancer (SCLC). The present study compared the effectiveness of the N stage, number of positive LNs (NPLNs), LNR, and log odds of positive LNs (LODDS) to predict cancer-specific survival (CSS) in patients with SCLC.

Materials and methods

674 patients were screened using the Surveillance Epidemiology and End Results database. The Kaplan-Meier survival and receiver operating characteristic (ROC) curves were performed to address optimal estimation of the N stage, NPLNs, LNR, and LODDS to predict CSS. The optimal LN status group was incorporated into a nomogram to estimate CSS in SCLC patients. The ROC curve, decision curve analysis, and calibration plots were utilized to test the discriminatory ability and accuracy of this nomogram.

Results

The LODDS model showed the highest accuracy compared to the N stage, NPLNs, and LNR in predicting CSS for SCLC patients. LODDS, age, sex, tumor size, and radiotherapy status were included in the nomogram. The results of calibration plots provided evidences of nice consistency. The ROC and DCA plots suggested a better discriminatory ability and clinical applicability of this nomogram than the 8th TNM and SEER staging systems.

Conclusions

LODDS demonstrated a better predictive power than other LN schemes in SCLC patients after surgery. A novel LODDS-incorporating nomogram was built to predict CSS in SCLC patients after surgery, proving to be more precise than the 8th TNM and SEER staging.

Comparation between novel online models and the AJCC 8th TNM staging system in predicting cancer-specific and overall survival of small cell lung cancer

Background

Most of previous studies on predictive models for patients with small cell lung cancer (SCLC) were single institutional studies or showed relatively low Harrell concordance index (C-index) values. To build an optimal nomogram, we collected clinicopathological characteristics of SCLC patients from Surveillance, Epidemiology, and End Results (SEER) database.

Methods

24,055 samples with SCLC from 2010 to 2016 in the SEER database were analyzed. The samples were grouped into derivation cohort (n=20,075) and external validation cohort (n=3,980) based on America's different geographic regions. Cox regression analyses were used to construct nomograms predicting cancer-specific survival (CSS) and overall survival (OS) using derivation cohort. The nomograms were internally validated by bootstrapping technique and externally validated by calibration plots. C-index was computed to compare the accuracy and discrimination power of our nomograms with the 8th of version AJCC TNM staging system and nomograms built in previous studies. Decision curve analysis (DCA) was applied to explore whether the nomograms had better clinical efficiency than the 8th version of AJCC TNM staging system.

Results

Age, sex, race, marital status, primary site, differentiation, T classification, N classification, M classification, surgical type, lymph node ratio, radiotherapy, and chemotherapy were chosen as predictors of CSS and OS for SCLC by stepwise multivariable regression and were put into the nomograms. Internal and external validations confirmed the nomograms were accurate in prediction. C-indexes of the nomograms were relatively satisfactory in derivation cohort (CSS: 0.761, OS: 0.761) and external validation cohort (CSS: 0.764, OS: 0.764). The accuracy of the nomograms was superior to that of nomograms built in previous studies. DCA showed the nomograms conferred better clinical efficiency than 8th version of TNM staging system.

Conclusions

We developed practical nomograms for CSS (https://guowei2020.shinyapps.io/DynNom-CSS-SCLC/) and OS (https://drboidedwater.shinyapps.io/DynNom-OS-SCLC/) prediction of SCLC patients which may facilitate clinicians in individualized therapeutics.

Comparisons of different lymph node staging systems for predicting overall survival of node-positive patients with renal cell carcinoma: a retrospective cohort study using the Surveillance, Epidemiology and End Results database

OBJECTIVES

To 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).

DESIGN

A retrospective cohort study using data from the Surveillance, Epidemiology and End Results (SEER) database.

SETTING AND PARTICIPANTS

1904 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 MEASURE

The 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.

RESULTS

Data 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.

CONCLUSIONS

NPLN, 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.

A Novel ypTLM Staging System Based on LODDS for Gastric Cancer After Neoadjuvant Therapy: Multicenter and Large-Sample Retrospective Study

BACKGROUND

The accuracy of the eighth AJCC ypTNM staging system on the prognosis of gastric cancer (GC) patients after neoadjuvant therapy (NAT) is controversial. This study aimed to develop and validate a novel staging system using the log odds of positive lymph nodes scheme (LODDS).

METHODS

A retrospective analysis of 606 GC patients who underwent radical gastrectomy after neoadjuvant therapy was conducted as the development cohort. (Fujian Medical University Affiliated Union Hospital (n = 183), Qinghai University Affiliated Hospital (n = 169), Mayo Clinic (n = 236), Lanzhou University First Hospital (n = 18)). The validation cohort came from the SEER database (n = 1701). A novel ypTLoddsS (ypTLM) staging system was established using the 3-year overall survival. The predictive performance of two systems was compared.

RESULTS

Two-step multivariate Cox regression analysis in both cohorts showed that ypTLM was an independent predictor of overall survival of GC patients after neoadjuvant therapy (HR: 1.57, 95% CI: 1.30-1.88, p < 0.001). In the development cohort, ypTLM had better discrimination ability than ypTNM (C-index: 0.663 vs 0.633, p < 0.001), better prediction homogeneity (LR: 97.7 vs. 70.9), and better prediction accuracy (BIC: 3067.01 vs 3093.82; NRI: 0.36). In the validation cohort, ypTLM had a better prognostic predictive ability (C-index: 0.614 vs 0.588, p < 0.001; LR: 11,909.05 vs. 11,975.75; BIC: 13,263.71 vs 13,328.24; NRI: 0.22). The time-dependent ROC curve shows that the predictive performance of ypTLM is better than ypTNM, and the analysis of the decision curve shows that ypTLM achieved better net benefits.

CONCLUSION

A LODDS-based ypTLM staging system based on multicenter data was established and validated. The predictive performance was superior to the eighth AJCC ypTNM staging system.

Construction and validation of nomograms based on the log odds of positive lymph nodes to predict the prognosis of lung neuroendocrine tumors

Background

This research aimed to investigate the predictive performance of log odds of positive lymph nodes (LODDS) for the long-term prognosis of patients with node-positive lung neuroendocrine tumors (LNETs).

Methods

We collected 506 eligible patients with resected N1/N2 classification LNETs from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The study cohort was split into derivation cohort (n=300) and external validation cohort (n=206) based on different geographic regions. Nomograms were constructed based on the derivation cohort and validated using the external validation cohort to predict the 1-, 3-, and 5-year cancer-specific survival (CSS) and overall survival (OS) of patients with LNETs. The accuracy and clinical practicability of nomograms were tested by Harrell’s concordance index (C-index), integrated discrimination improvement (IDI), net reclassification improvement (NRI), calibration plots, and decision curve analyses.

Results

The Cox proportional-hazards model showed the high LODDS group (-0.79≤LODDS) had significantly higher mortality compared to those in the low LODDS group (LODDS<-0.79) for both CSS and OS. In addition, age at diagnosis, sex, histotype, type of surgery, radiotherapy, and chemotherapy were also chosen as predictors in Cox regression analyses using stepwise Akaike information criterion method and included in the nomograms. The values of C-index, NRI, and IDI proved that the established nomograms were better than the conventional eighth edition of the TNM staging system. The calibration plots for predictions of the 1-, 3-, and 5-year CSS/OS were in excellent agreement. Decision curve analyses showed that the nomograms had value in terms of clinical application.

Conclusions

We created visualized nomograms for CSS and OS of LNET patients, facilitating clinicians to bring individually tailored risk assessment and therapy.

A Prognostic Nomogram Based on Log Odds of Positive Lymph Nodes to Predict Overall Survival for Non-Metastatic Bladder Cancer Patients after Radical Cystectomy

(1) Purpose: The purpose of this study was to evaluate the prognostic capacity of the pathological N status (pN), lymph node ratio (LNR), and the log odds of positive lymph nodes (LODDS), and to build a prognostic nomogram to predict overall survival (OS) for bladder cancer patients treated by radical cystectomy. (2) Methods: The clinical and pathological characteristics of 10,938 patients with bladder cancer were identified from the Surveillance, Epidemiology, and End Results (SEER) database from 2004 to 2017. The predictive capacity was assessed by univariate and multivariate Cox regression analyses, the area under the receiver operating characteristic curve (AUC), and C-index. Calibration curves, decision curve analysis (DCA), and risk-grouping were utilized to evaluate the predictive accuracy and discriminative ability of the nomogram. (3) Results: LODDS was an independent risk factor for bladder cancer (all p < 0.001) and demonstrated the highest values of C-index and AUC. The values of AUCs in the training cohort were 0.747, 0.743, and 0.735 for predicting 1-, 3-, and 5-year OS, respectively. Calibration curves and DCA curves suggested the excellent clinical application value of our nomogram. (4) Conclusions: LODDS is a better predictive indicator for bladder cancer patients compared to pN and LNR. The LODDS-incorporated nomogram has excellent accuracy and promising clinical application value for non-metastatic bladder cancer after radical cystectomy.

A Comprehensive Comparison of Different Nodal Subclassification Methods in Surgically Resected Non-Small-Cell Lung Cancer Patients

INTRODUCTION

The revision of the N descriptor in non-small-cell lung cancer has been widely discussed in the past few years. Many different subclassification methods based on number or location of lymph nodes have been proposed for better distinguishing different N patients. This study aimed to systematically collect them and provide a comprehensive comparison among different subclassification methods in a large cohort.

METHOD

Pathological N1 or N2 non-small-cell lung cancer patients undergoing surgical resection between 2005 and 2016 in the Western China Lung Cancer Database were retrospectively reviewed. A literature review was conducted to collect previous subclassification methods. Kaplan-Meier and multivariable Cox analyses were used to examine the prognostic performance of subclassification methods. Decision curve analysis, Akaike's information criterion, and area under the receiver operating curve concordance were also performed to evaluate the standardized net benefit of the subclassification methods.

RESULTS

A total of 1625 patients were identified in our cohort. Eight subclassification methods were collected from previous articles and further grouped into subclassification based on number categories (node number or station number), location categories (lymph node zone or chain) or combination of number and location categories. Subclassification based on combination of lymph node location and number tended to have better discrimination ability in multivariable Cox analysis. No significant superiority among the different subclassification methods was observed in the three statistical models.

CONCLUSION

Subclassification based on the combination of location and number could be used to provide a more accurate prognostic stratification in surgically resected NSCLC and is worth further validation.

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.

Role of Pneumonectomy in T1–4N2M0 Non-Small Cell Lung Cancer: A Propensity Score Matching Analysis

Background

N2 stage disease constitutes approximately 20%–30% of all non-small cell lung cancer (NSCLC). Concurrently, surgery remains the first-choice treatment for patients with N2 NSCLC if feasible. However, the role of pneumonectomy in N2 NSCLC has rarely been investigated and remains controversial.

Methods

We enrolled 26,798 patients with T1–4N2M0 NSCLC (stage IIIA/IIIB) from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. We compared the overall survival (OS) and cancer-specific survival (CSS) between patients who received pneumonectomy and those who did not receive surgery. The Kaplan–Meier method, Cox regression analyses, and propensity score matching (PSM) were applied to demonstrate the effect of pneumonectomy.

Results

Patients receiving pneumonectomy had a significantly better OS and CSS than those without pneumonectomy both before [adjusted-HR (95% CI): 0.461 (0.425–0.501) for OS, 0.444 (0.406–0.485) for CSS] and after PSM [adjusted-HR (95% CI): 0.499 (0.445–0.560) for OS, 0.457 (0.405–0.517) for CSS] with all p-values <0.001. Subgroup analysis demonstrated concordant results stratified by demographic or clinicopathological variables. In sensitivity analysis, no significant difference was observed between patients receiving single pneumonectomy and chemoradiotherapy without surgery in OS and CSS both before [unadjusted-HR (95% CI): 1.016 (0.878–1.176) for OS, 0.934 (0.794–1.099) for CSS, p = 0.832] and after PSM [unadjusted-HR (95% CI): 0.988 (0.799–1.222) for OS, 0.938 (0.744–1.182) for CSS] with all p-values >0.4.

Conclusion

For patients with T1–4N2M0 NSCLC (stage IIIA/IIIB), pneumonectomy is an independent protective factor of OS and should be considered when applicable.

Comparison of 4 lymph node staging systems for the prognostic prediction of esophagogastric junction adenocarcinoma with ≤15 retrieved lymph nodes

BACKGROUND

Directly applying the 8th American Joint Committee on Cancer (AJCC) Tumor Node Metastasis (TNM) staging system to evaluate the prognosis of patients with esophagogastric junction adenocarcinoma (AEG) might lead to under-staging, when insufficient lymph nodes were retrieved during surgery. The prognostic value of 4 lymph nodes staging systems, 8th AJCC TNM N stage, lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), and negative lymph nodes (NLN), in AEG patients having ≤15 retrieved lymph nodes were compared.

METHODS

869 AEG patients diagnosed between 2004 and 2012 with ≤15 retrieved lymph nodes were identified from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox regression analyses were conducted to assess the association of cancer-specific survival (CSS) and overall survival (OS) with 8th AJCC TNM N stage, LNR, LODDS, and NLN respectively. Predictive survival ability was assessed and compared using linear trend χ2 score, likelihood ratio (LR) test, Akaike information criterion (AIC), Harrell concordance index (C-index), and Receiver Operative Curve (ROC).

RESULTS

The N stage, LNR, LODDS, and NLN were all independent prognostic predictors for CSS and OS in multivariate Cox models. Comparatively, LODDS demonstrated higher linear trend χ2 score, LR test score, C-index and integrated area under the curve (iAUC) value, and lower AIC in CSS compared to the other three systems. Moreover, for patients without regional lymph node metastasis, NLN showed higher C-index and lower AIC.

CONCLUSIONS

LODDS showed better predictive performance than N, LNR, and NLN among patients with node-positive patients while NLN performed better in node-negative patients. A combination of LODDS and NLN has the potential to provide more prognostic information than the current AJCC TNM classification.

Log odds of positive lymph nodes as a novel prognostic predictor for colorectal cancer: a systematic review and meta-analysis

BACKGROUND

Colorectal cancer (CRC) is the third most prevalent cancer in the world, which remains one of the leading causes of cancer-related deaths. Accurate prognosis prediction of CRC is pivotal to reduce the mortality and disease burden. Lymph node (LN) metastasis is one of the most commonly used criteria to predict prognosis in CRC patients. However, inaccurate surgical dissection and pathological evaluation may lead to inaccurate nodal staging, affecting the effectiveness of pathological N (pN) classification in survival prediction among patients with CRC. In this meta-analysis, we aimed to estimate the prognostic value of the log odds of positive lymph nodes (LODDS) in patients with CRC.

METHODS

PubMed, Medline, Embase, Web of Science and the Cochrane Library were systematically searched for relevant studies from inception to July 3, 2021. Statistical analyses were performed on Stata statistical software Version 16.0 software. To statistically assess the prognostic effects of LODDS, we extracted the hazard ratio (HR) and 95% confidence interval (CI) of overall survival (OS) and disease-free survival (DFS) from the included studies.

RESULTS

Ten eligible articles published in English involving 3523 cases were analyzed in this study. The results showed that LODDS1 and LODDS2 in CRC patients was correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.77, 95% CI (1.38, 2.28); LODDS2 vs. LODDS0: HR = 3.49, 95% CI (2.88, 4.23)). Meanwhile, LODDS1 and LODDS2 in CRC patients was correlated with poor DFS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.82, 95% CI (1.23, 2.68); LODDS2 vs. LODDS0: HR =3.30, 95% CI (1.74, 6.27)).

CONCLUSIONS

The results demonstrated that the LODDS stage was associated with prognosis of CRC patients and could accurately predict the prognosis of patients with CRC.

Development and Validation of Novel Nomograms to Predict the Overall Survival and Cancer-Specific Survival of Cervical Cancer Patients With Lymph Node Metastasis

Objective

The objective of this study was to establish and validate novel individualized nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in cervical cancer patients with lymph node metastasis.

Methods

A total of 2,956 cervical cancer patients diagnosed with lymph node metastasis (American Joint Committee on Cancer, AJCC N stage=N1) between 2000 and 2018 were included in this study. Univariate and multivariate Cox regression models were applied to identify independent prognostic predictors, and the nomograms were established to predict the OS and CSS. The concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) curves were applied to estimate the precision and discriminability of the nomograms. Decision-curve analysis (DCA) was used to assess the clinical utility of the nomograms.

Results

Tumor size, log odds of positive lymph nodes (LODDS), radiotherapy, surgery, T stage, histology, and grade resulted as significant independent predictors both for OS and CSS. The C-index value of the prognostic nomogram for predicting OS was 0.788 (95% CI, 0.762–0.814) and 0.777 (95% CI, 0.758–0.796) in the training and validation cohorts, respectively. Meanwhile, the C-index value of the prognostic nomogram for predicting CSS was 0.792 (95% CI, 0.767–0.817) and 0.781 (95% CI, 0.764–0.798) in the training and validation cohorts, respectively. The calibration curves for the nomograms revealed gratifying consistency between predictions and actual observations for both 3- and 5-year OS and CSS. The 3- and 5-year area under the curves (AUCs) for the nomogram of OS and CSS ranged from 0.781 to 0.828. Finally, the DCA curves emerged as robust positive net benefits across a wide scale of threshold probabilities.

Conclusion

We have successfully constructed nomograms that could predict 3- and 5-year OS and CSS of cervical cancer patients with lymph node metastasis and may assist clinicians in decision-making and personalized treatment planning.

Lobectomy Versus Sublobectomy in Stage IIIA/N2 Non-Small Cell Lung Cancer: A Population-Based Study

Background

The role lobectomy plays in stage IIIA/N2 non-small cell lung cancer (NSCLC) is controversial for a long time. What’s more, no previous study concentrates on whether sublobectomy can improve survival outcome for these patients, so we performed this population-based study to investigate whether stage IIIA/N2 NSCLC can benefit from these two surgery types and compare survival outcomes after lobectomy and sublobectomy.

Methods

A total of 21,638 patients diagnosed with stage IIIA/N2 NSCLC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database matched our selection criteria. The study cohort included patients who received no surgery (n = 15,951), sublobectomy (n = 628) and lobectomy (n = 5,059). Kaplan–Meier method, Cox regression analyses, and inverse probability of treatment weighting (IPTW)-adjusted Cox regression were used to illustrate the influence of sublobectomy and lobectomy on overall survival (OS) rates in the study cohort and compare these two surgery types.

Results

Multivariable Cox regression analysis showed sublobectomy [HR: 0.584 (95%CI: 0.531–0.644), P-value <0.001; IPTW-adjusted HR: 0.619 (95%CI: 0.605–0.633), P-value <0.001] and lobectomy [HR: 0.439 (95%CI: 0.420–0.459), P-value <0.001; IPTW-adjusted HR: 0.441 (95%CI: 0.431–0.451), P-value <0.001] were both related to better OS rates compared with no surgery, and lobectomy exhibited better survival than sublobectomy [HR: 0.751 (95%CI: 0.680–0.830), P-value <0.001; IPTW-adjusted HR: 0.713 (95%CI: 0.696–0.731), P-value <0.001]. Moreover, the results in subgroup analyses based on age, tumor size and radiotherapy and chemotherapy strategy in all study cohort were consistent.

Conclusion

Stage IIIA/N2 NSCLC patients could benefit from sublobectomy or lobectomy, and lobectomy provided better OS rates than sublobectomy.

Construction and validation of a prognostic model for stage IIIC endometrial cancer patients after surgery

BACKGROUND

To explore the most predictive lymph node (LN) scheme for stage IIIC endometrial cancer (EC) patients after hysterectomy and develop a scheme-based nomogram.

METHODS

Data from 2626 stage IIIC EC patients, diagnosed between 2010 and 2014, were extracted from the Surveillance, Epidemiology, and End Results (SEER) registry. The predictive ability of four LN schemes was assessed using C-index and Akaike information criterion (AIC). A nomogram based on the most predictive LN scheme was constructed and validated. The comparison of the predictive ability between nomogram and FIGO stage was conducted using the area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA).

RESULTS

FIGO stage (stage IIIC1/stage IIIC2) was not an independent risk factor for OS in stage IIIC EC patients (P = 0.672) and log odds of positive lymph nodes (LODDS) had the best predictive ability (C-index: 0.742; AIC: 8228.95). A nomogram based on LODDS was constructed and validated, which had a decent C-index of 0.742 (0.723-0.762). The nomogram showed a better predictive ability than that of the FIGO staging system.

CONCLUSION

FIGO IIIC1/FIGO IIIC2 could not differentiate the prognosis for stage IIIC EC patients. We developed and validated a nomogram based on LODDS to predict OS for post-operative patients with stage IIIC EC.

Value of the log odds of positive lymph nodes for prognostic assessment of colon mucinous adenocarcinoma: Analysis and external validation

Purpose

To evaluate the impact of the log odds of positive lymph nodes (LODDS) on cancer‐specific survival (CSS) in colon mucinous adenocarcinoma (MAC) patients, compared with pN stage and the lymph nodes ratio (LNR).

Methods

A total of 10,182 colon MAC patients from the Surveillance, Epidemiology, and End Results database were divided into the training group. The external validation group included 153 patients from Fujian Medical University Union Hospital. The Cox regression method was used to identify prognostic risk factors. Nomograms were evaluated by Harrell's concordance index (C‐index) and calibration curves. Recursive partitioning analysis (RPA) was used to develop a novel staging system.

Results

Time‐dependent receiver operating characteristic curves (ROC) to predict CSS showed the areas under the ROC curve of LODDS were always higher than pN stage and LNR. LNR and LODDS classifications can well distinguish the prognosis of patients with the same pN stage. Cox analyses indicated that age, tumor size, pT stage, pN stage, LNR, and LODDS were independent predictors of CSS (p < 0.05). Based on three lymph nodes classifications, we constructed three prognostic nomograms models for CSS. The C‐index of the pN, LNR, and LODDS classification nomograms were 0.746 (95% confidence interval [95% CI]: 0.736–0.756), 0.750 (95% CI: 0.740–0.760), and 0.758 (95% CI: 0.748–0.768), respectively. In external validation, we observed the C‐index of LODDS classification nomograms was 0.787 (95% CI: 0.648–0.926). RPA stage, including four stages, was constructed successfully based on pT stage and LNR or LODDS, respectively. The 3‐, 5‐, and 8‐year areas under the ROC curve of LNR‐RPA stage and LODDS‐RPA stage were superior to tumor‐node‐metastasis stage.

Conclusion

LODDS to be a better prognostic factor of CSS for colon MAC patients than pN stage and LNR. A nomogram and RPA stage base on LODDS can provide accurate information for personalized cancer treatment.

ACY1 regulating PTEN/PI3K/AKT signaling in the promotion of non-small cell lung cancer progression

Background

Non-small cell lung cancer (NSCLC) has a poor prognosis and is the most common cause of cancer-related deaths worldwide. Aminoacylase 1 (ACY1) plays a promoting role in some cancers, but its role in NSCLC is still unclear.

Methods

Immunohistochemistry, Reverse transcription-polymerase chain reaction (RT-PCR) and western blotting assays were used to determine ACY1 expression patterns in NSCLC tissues and cell lines. The clinical significance of ACY1 in NSCLC was evaluated by χ² test and Kaplan-Meier analysis. MTT, flow cytometry, wound healing, and Transwell assays were performed to assess cell growth, apoptosis, migration, invasion, and tumorigenesis under different treatments. Male athymic BALB/C nude mice were used for xenotransplantation experiments.

Results

The results showed that ACY1 expression was elevated in NSCLC tissue samples and cells, and high ACY1 expression predicted an advanced clinical process and shorter overall survival in patients with NSCLC. Overexpression of ACY1 significantly increased cell growth, migration, invasion, and tumorigenesis, and reduced cell apoptosis, indicating that ACY1 functions as an oncogene in NSCLC. Moreover, ACY1 decreased phosphatase and tensin homolog (PTEN) expression, increased its ubiquitination, and activated PI3K/AKT signaling. Overexpression of PTEN diminished the effects of ACY1 upregulation on cell tumorigenesis promotion.

Conclusions

This study reveals that ACY1 may promote the progression of NSCLC via activating PI3K/AKT signaling in a PTEN-dependent manner. Our study may provide a better understanding of the pathogenesis and development of NSCLC.

Nomogram to predict overall survival based on the log odds of positive lymph nodes for patients with endometrial carcinosarcoma after surgery

PURPOSE

Aims to compare the prognostic performance of the number of positive lymph nodes (PLNN), lymph node ratio (LNR) and log odds of metastatic lymph nodes (LODDS) and establish a prognostic nomogram to predict overall survival (OS) rate for patients with endometrial carcinosarcoma (ECS).

METHODS

Patients were retrospectively obtained from Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. The prognostic value of PLNN, LNR and LODDS were assessed. A prediction model for OS was established based on univariate and multivariate analysis of clinical and demographic characteristics of ECS patients. The clinical practical usefulness of the prediction model was valued by decision curve analysis (DCA) through quantifying its net benefits.

RESULTS

The OS prediction accuracy of LODDS for ECS is better than that of PLNN and LNR. Five factors, age, tumor size, 2009 FIGO, LODDS and peritoneal cytology, were independent prognostic factors of OS. The C-index of the nomogram was 0.743 in the training cohort. The AUCs were 0.740, 0.682 and 0.660 for predicting 1-, 3- and 5-year OS, respectively. The calibration plots and DCA showed good clinical applicability of the nomogram, which is better than 2009 FIGO staging system. These results were verified in the validation cohort. A risk classification system was built that could classify ECS patients into three risk groups. The Kaplan-Meier curves showed that OS in the different groups was accurately differentiated by the risk classification system and performed much better than FIGO 2009.

CONCLUSION

Our results indicated that LODDS was an independent prognostic indicator for ECS patients, with better predictive efficiency than PLNN and LNR. A novel prognostic nomogram for predicting the OS rate of ECS patients was established based on the population in the SEER database. Our nomogram based on LODDS has a more accurate and convenient value for predicting the OS of ECS patients than the FIGO staging system alone.

Prognostic value of different lymph node staging methods for node-positive cardia gastric cancer: a register-based retrospective cohort study

OBJECTIVE

To investigate the prognostic efficacy of lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) in node-positive cardia gastric adenocarcinoma (CGA).

DESIGN

A registry-based retrospective cohort study.

SETTING

Patients diagnosed with node-positive CGA in the Surveillance, Epidemiology, and End Results database from 2010 to 2015.

PARTICIPANTS

A total of 1038 patients were enrolled and randomly assigned (7:3) to the training set (n=723) or validating set (n=315).

PRIMARY OUTCOME MEASURE

Cancer-specific survival (CSS).

RESULTS

The baseline characteristics of the training and validation sets were similar. Based on the optimal cut-off values, LNR was classified into low (<0.09), medium (0.09~0.33) and high (>0.33) groups; LODDS was also classified into low (<-2.09), medium (-2.09~-0.65) and high (>-0.65) groups. CSS was significantly different across LNR and LODDS subgroups. The Harrell concordance index of the N stage was lower than that of the LNR or LODDS. The Akaike information criterion of the N stage was higher than that of the LNR or LODDS. Independent predictors included race, T stage, M stage and LNR (or LODDS), and they were incorporated into nomograms for 1-year, 2-year and 5-year CSS prediction. Calibration plots showed satisfactory results for internal and external validity of the nomogram.

CONCLUSIONS

LNR and LODDS staging methods have better prognostic efficacy than the traditional N staging method in CGA with node metastasis. Moreover, the two values are promising substitutes for N staging in nomogram development when other independent prognostic factors are incorporated.

Prognostic implications of ENE and LODDS in relation to lymph node-positive colorectal cancer location

•

This is the first study on LODDS and ENE together. The current study showed that LODDS and ENE are liable prognostic parameters of CRC or CC.

•

ENE is an independent influencing factor on the prognosis of both CRC and CC, and the prognostic impact of ENE was observed in both CRC and CC.

•

The frequency of ENE increases from the proximal (right) to the distal (left) colon as well as the rectum.

Background

Extranodal extension (ENE) and log odds of positive lymph nodes (LODDS) are associated with the aggressiveness of both colon and rectal cancers. The current study evaluated the clinicopathological significance and the prognostic impact of ENE and LODDS in the colon and rectal patients independently.

Methods

The clinical and histological records of 389 colorectal cancer (CRC) patients who underwent curative surgery were reviewed.

Results

For the ENE system, 244 patients were in the ENE1 group and 145 in the ENE2 system. Compared with the ENE1 system, the patients included in the ENE2 system were prone to nerve invasion (P < 0.001) and vessel invasion (P < 0.001) with higher TNM (P = 0.009), higher T category (P = 0.003), higher N category (P < 0.001), advanced differentiation (P = 0.013), more number of positive lymph nodes (NPLN) (P < 0.001), more lymph node ratio (LNR) (P < 0.001), and a higher value of LODDS (P < 0.001). ENE was more frequent in patients with left and rectal than right cancer. For the LODDS system, 280 patients were in the LODDS1 group, and 109 in the LODDS2 group. Compared to the LODDS1 group, the patients included in the LODDS2 group were more prone to nerve invasion (P = 0.0351) and vessel invasion (P < 0.001) with a higher rate of N2 stage, less NDLN (P < 0.001), more NPLN (P < 0.001), more LNR (P < 0.001), and a higher value of ENE (P < 0.001). Based on the results in the univariable analysis, the N, NPLN, LNR, LODDS, and ENE were separately incorporated into five different Cox regression models combined with the same confounders. The multivariable Cox regression analysis demonstrated that all the five staging systems were independent prognostic factors for overall survival.

Conclusion

The current study confirmed that the LODDS stage is an independent influence on the prognosis of both CRC and CC patients. ENE is an independent influencing factor on the prognosis of both CRC and CC patients, and the prognostic impact of extracapsular lymph node was observed in both CRC and CC. The frequency of ENE increases from the proximal (right) to the distal (left) colon as well as the rectum. Therefore, combining ENE and LODDS into the current TNM system to compensate for the inadequacy of pN staging needs further investigation.

Dynamic nomograms combining N classification with ratio-based nodal classifications to predict long-term survival for patients with lung adenocarcinoma after surgery: a SEER population-based study

Background

The prognostic roles of three lymph node classifications, number of positive lymph nodes (NPLN), log odds of positive lymph nodes (LODDS), and lymph node ratio (LNR) in lung adenocarcinoma are unclear. We aim to find the classification with the strongest predictive power and combine it with the American Joint Committee on Cancer (AJCC) 8th TNM stage to establish an optimal prognostic nomogram.

Methods

25,005 patients with T1-4N0–2M0 lung adenocarcinoma after surgery between 2004 to 2016 from the Surveillance, Epidemiology, and End Results database were included. The study cohort was divided into training cohort (13,551 patients) and external validation cohort (11,454 patients) according to different geographic region. Univariate and multivariate Cox regression analyses were performed on the training cohort to evaluate the predictive performance of NPLN (Model 1), LODDS (Model 2), LNR (Model 3) or LODDS+LNR (Model 4) respectively for cancer-specific survival and overall survival. Likelihood-ratio χ² test, Akaike Information Criterion, Harrell concordance index, integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to evaluate the predictive performance of the models. Nomograms were established according to the optimal models. They’re put into internal validation using bootstrapping technique and external validation using calibration curves. Nomograms were compared with AJCC 8th TNM stage using decision curve analysis.

Results

NPLN, LODDS and LNR were independent prognostic factors for cancer-specific survival and overall survival. LODDS+LNR (Model 4) demonstrated the highest Likelihood-ratio χ² test, highest Harrell concordance index, and lowest Akaike Information Criterion, and IDI and NRI values suggested Model 4 had better prediction accuracy than other models. Internal and external validations showed that the nomograms combining TNM stage with LODDS+LNR were convincingly precise. Decision curve analysis suggested the nomograms performed better than AJCC 8th TNM stage in clinical practicability.

Conclusions

We constructed online nomograms for cancer-specific survival and overall survival of lung adenocarcinoma patients after surgery, which may facilitate doctors to provide highly individualized therapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08410-6.

Comparison of Different Lymph Node Staging Schemes for Predicting Survival Outcomes in Node-Positive Endometrioid Endometrial Cancer Patients

Objective: To compare the prognostic predictive performance of six lymph node (LN) staging schemes: American Joint Committee on Cancer (AJCC) N stage, number of retrieved lymph nodes (NRLN), number of positive lymph nodes (NPLN), number of negative lymph nodes (NNLN), lymph node ratio (LNR), and log odds of positive lymph nodes (LODDS) among node-positive endometrioid endometrial cancer (EEC) patients. Methods: A total of 3,533 patients diagnosed with node-positive EEC between 2010 and 2016 from the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively analyzed. We applied X-tile software to identify the optimal cutoff value for different staging schemes. Univariate and multivariate Cox regression models were used to assess the relationships between different LN schemes and survival outcomes [disease-specific survival (DSS) and overall survival (OS)]. Moreover, Akaike information criterion (AIC) and Harrell concordance index (C-index) were used to evaluate the predictive performance of each scheme in both continuous and categorical patterns. Results: N stage (N1/N2) was not an independent prognostic factor for node-positive EEC patients based on multivariate analysis (DSS: p = 0.235; OS: p = 0.145). Multivariate model incorporating LNR demonstrated the most superior goodness of fit regardless of continuous or categorical pattern. Regarding discrimination power of the models, LNR outperformed other models in categorical pattern (OS: C-index = 0.735; DSS: C-index = 0.737); however, LODDS obtained the highest C-index in continuous pattern (OS: 0.736; DSS: 0.739). Conclusions: N stage (N1/N2) was unable to differentiate the prognosis for node-positive EEC patients in our study. However, LNR and LODDS schemes seemed to have a better predictive performance for these patients than other number-based LN schemes whether in DSS or OS, which revealed that LNR and LODDS should be more helpful in prognosis assessment for node-positive EEC patients than AJCC N stage.

Prognostic Nomograms Based on Three Lymph Node Classification Systems for Resected Gastric Adenocarcinoma: A Large Population-Based Cohort Study and External Validation

BACKGROUNDS

The optimal lymph node classification system for prognostic assessment in gastric adenocarcinoma (GAC) patients who undergo lymph node dissection remains unclear. Therefore, this study aimed to compare prognostic nomograms based on AJCC N stage, lymph node ratio (LNR), and log odds of metastatic lymph nodes (LODDS) to evaluate the prognosis and differentiate risk subgroups of patients with resected GAC.

PATIENTS AND METHODS

We collected 4633 patients with resected stage I-III GAC receiving chemotherapy from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. Independent prognostic factors were selected by Cox regression analyses, based on which nomograms were constructed. External validation was performed in 228 cases from Nanjing Drum Tower Hospital. Kaplan-Meier survival analysis was used to evaluate the effect of postoperative radiotherapy (PORT) for different lymph node classifications.

RESULTS

Multivariate analysis indicated that age, grade, primary site, T stage, N stage, LNR, LODDS, and radiotherapy were independent predictors. Good discrimination power and high consistency of calibration plots were obtained from the LODDS system nomogram. The LODDS classification could more precisely differentiate risk subgroups and improve the discrimination of the resected GAC prognosis. A user-friendly webserver of LODDS system was built based on the nomogram for convenient clinical application.

CONCLUSIONS

The LODDS seems to be the most reliable lymph node classification in predicting the prognosis of patients with resected GAC and should be recommended in clinical prognostic assessment. Incorporating LODDS into the staging system will enable clinicians to more accurately predict prognosis and guide radiotherapy regimen decisions.

The prognostic performance of the log odds of positive lymph nodes in patients with esophageal squamous cell carcinoma: A population study of the US SEER database and a Chinese single-institution cohort

Background

The purpose of this study was to assess the prognostic performance of the log odds of positive lymph nodes (LODDS) value compared with the pathological N stage and lymph node ratio (LNR) in patients with esophageal squamous cell carcinoma (ESCC).

Method

In total 1144 patients diagnosed with ESCC from the Surveillance, Epidemiology, and End Results (SEER) database and 930 patients from our validation cohort were eligible. Kaplan–Meier plotter and multivariate Cox proportional hazards models were conducted to investigate the prognostic value of the N stage, LNR stage, and LODDS stage. The homogeneity, discriminatory ability, and monotonicity of these variables were evaluated using the linear trend χ² test, likelihood ratio χ² test, Akaike information criterion (AIC), and consistency index (C‐index) to determine the potential superiorities.

Results

The prognostic LODDS cutoff values were determined to be −1.49 and −0.55 (p < 0.001). Univariate analyses showed significant association among the N, LNR, and LODDS stages and overall survival of the patients (all p < 0.001). Multivariate analyses confirmed that the LODDS stage remained an independent prognostic indicator in both the SEER database and our validation cohort. Subgroup analyses identified the ability of LODDS stage to distinguish heterogeneous patients within various groups in both independent databases. Furthermore, the model with the highest C‐index and smallest AIC value was the one incorporating the LODDS stage among the three investigated nodal classifications of both cohorts.

Conclusion

The novel LODDS stage demonstrated better prognostic performance than the traditional N or LNR stages in ESCC patients. It can serve as an auxiliary factor to improve prognostic performance and can be applied to evaluate the lymph node status to increase the precision of staging and evaluation of survival.