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

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.

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.

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.

Advantage of log odds of positive lymph nodes in prognostic evaluation of patients with early-onset colon cancer

BACKGROUND

Colon cancer (CC) is one of the most common cancers of the digestive tract, the third most common cancer worldwide, and the second most common cause of cancer-related deaths. Previous studies have demonstrated a higher risk of lymph node metastasis (LNM) in young patients with CC. It might be reasonable to treat patients with early-onset locally advanced CC with extended lymph node dissection. However, few studies have focused on early-onset CC (ECC) patients with LNM. At present, the methods of predicting and evaluating the prognosis of ECC patients with LNM are controversial.

AIM

To compare the prognostic values of four lymph node staging indices and establish the best nomogram for patients with ECC.

METHODS

From the data of patients with CC obtained from the Surveillance, Epidemiology, and End Results (SEER) database, data of young patients with ECC (≤ 50 years old) was screened. Patients with unknown data were excluded from the study, while the remaining patients were included. The patients were randomly divided into a training group (train) and a testing group (test) in the ratio of 7:3, while building the model. The model was constructed by the training group and verified by the testing group. Using multiple Cox regression models to compare the prediction efficiency of LNM indicators, nomograms were built based on the best model selected for overall survival (OS) and cause-specific survival (CSS). In the two groups, the performance of the nomogram was evaluated by constructing a calibration plot, time-dependent area under the curve (AUC), and decision curve analysis. Finally, the patients were grouped based on the risk score predicted by the prognosis model, and the survival curve was constructed after comparing the survival status of the high and low-risk groups.

RESULTS

Records of 26922 ECC patients were screened from the SEER database. N classification, positive lymph nodes (PLN), lymph node ratio (LNR) and log odds of PLN (LODDS) were considered to be independent predictors of OS and CSS. In addition, independent risk factors for OS included gender, race, marital status, primary site, histology, grade, T, and M classification, while the independent prognostic factors for CSS included race, marital status, primary site, grade, T, and M classification. The prediction model including LODDS is composed of minimal Akaike information criterion, maximal concordance indexes, and AUCs. Factors including gender, race, marital status, primary site, histology, grade, T, M classification, and LODDS were integrated into the OS nomogram, while race, marital status, primary site, grade, T, M classification, and LODDS were included into the CSS nomogram. The nomogram representing both cohorts had been successfully verified in terms of prediction accuracy and clinical practicability.

CONCLUSION

LODDS is superior to N-stage, PLN, and LNR of ECC. The nomogram containing LODDS might be helpful in tumor evaluation and clinical decision-making, since it provides an appropriate prediction of ECC.

A new lymph node ratio-based staging system for rectosigmoid cancer: a retrospective study with external validation

BACKGROUND

This study evaluated the clinical value of a new American Joint Committee on Cancer (AJCC) tumor node metastasis (TNM) staging prediction model based on lymph node ratio (LNR) in rectosigmoid cancer (RSC).

METHODS

The analysis included 1444 patients with nonmetastatic RSC diagnosed pathologically between 2010 and 2016 who were collected from the National Cancer Institute Surveillance, Epidemiology, and Results database. The AJCC N-stage was redefined according to the LNR cutoff point, and the ability of the new staging system to predict prognosis was compared with that of the AJCC TNM staging system. Data from 739 patients from our hospital were used for external validation.

RESULTS

According to the number of examined lymph nodes and LNR, the N stage was divided into five groups (LNR0-5). The 5-year OS of patients divided according to the new T lymph node ratio M (TLNRM) staging into stage I (T1LNR1, T1LNR2), IIA (T1LNR3, T2LNR1, T2LNR2, T2LNR3, T1LNR4, T3LNR1), IIB (T2LNR4), IIC (T3LNR2, T4a LNR1, T1LNR5), IIIA (T3LNR3, T2LNR5, T4b LNR1, T4a LNR2, T3LNR4), IIIB (T3LNR5, T4a LNR3, T4a LNR4, T4b LNR2), and IIIC (T4b LNR3, T4a LNR5, T4b LNR4, T4b LNR5) was significantly different ( P <0.05). Decision curve analysis showed that the net income of the new TLNRM staging system for different decision thresholds was higher than the prediction line of the traditional eighth TNM staging system. The smaller Akaike information criterion and Bayesian information suggested that the new staging system had a higher sensitivity for predicting prognosis than the traditional staging system. TLNRM II and III patients benefited from adjuvant chemotherapy, while adjuvant chemotherapy did not improve the prognosis of TNM II patients. These findings were confirmed by the external validation data.

CONCLUSION

The new TLNRM staging system was superior to the eighth edition AJCC staging system for staging and predicting the prognosis of patients with RSC and may become an effective tool in clinical practice.

Proposal for a new N-stage classification system for intrahepatic cholangiocarcinoma

Background

The number of metastatic lymph nodes (MLNs) is not considered in the nodal status (N classification) of intrahepatic cholangiocarcinoma (ICC) in the current 8thEdition of the American Joint Committee on Cancer (AJCC) staging system. The aim of this study was to find out the optimal cut-off point based on the number of MLNs and establish a modified AJCC staging system for ICC according to the new N category.

Methods

A total of 675 ICC patients diagnosed between 2004 and 2015 were retrieved from the Surveillance, Epidemiology and End Results (SEER) database. The optimal cut-off value of MLNs affecting survival was determined by X-tile software. The relative discriminative power was assessed by Harrell's concordance index (C-index) and Akaike information criterion (AIC).

Results

The proposed new nodal category subdivided patients into three groups (N0, no MLN; N1, 1-3 MLNs; and N2, ≥ 4 MLNs) with significantly different overall survival (P < 0.001). Multivariable analysis revealed that the new nodal category was an independent prognostic factor (P < 0.001). Both the C-index and AIC for our modified staging system were better than those for the 8th AJCC edition (0.574 [95% confidence interval 0.533-0.615] versus 0.570 [95% confidence interval 0.527-0.613], and 853.30 versus 854.21, respectively).

Conclusion

The modified AJCC staging system based on the number of MLNs may prove to be a useful alternative for predicting survival of ICC patients in clinical practice.

Number of positive lymph nodes combined with the logarithmic ratio of positive lymph nodes predicts long-term survival for patients with node-positive parotid gland carcinoma after surgery: a SEER population-based study

PURPOSE

To evaluate the prognostic value of the number of positive lymph nodes (NPLN), the ratio of positive lymph nodes (pLNR), and the logarithmic ratio of positive lymph nodes (LODDS) in patients with parotid gland carcinoma. On this basis, establishing and validating an optimal nomogram.

METHODS

A total of 895 patients with T1-4N1-3M0 parotid gland carcinoma were included in our study from the Surveillance, Epidemiology, and End Results (SEER) database. Patients' data were randomly assigned to the training cohort and the validation cohort by a ratio of 7:3. Univariate and multivariate COX regression analysis were used to explore the relationship between the study factors and the prognosis of parotid gland carcinoma, including overall survival (OS) and cause-specific survival (CSS). The Akaike Information Criterion (AIC) was used to evaluate model fit. Harrell's concordance index (C-index), integrated discrimination improvement (IDI), and net reclassification index (NRI) were used to evaluate the predictive ability of these models. The decision curve analysis was used to evaluate the clinical benefit of the nomograms compared with the TNM stage.

RESULTS

NPLN, pLNR, and LODDS are independent risk factors for the prognostic of PGC. According to the AIC, C index, IDI, and NRI, the models combined with NPLN and LODDS were the best. The decision curves suggested that our nomograms had good predictive abilities for the prognosis of parotid gland carcinoma.

CONCLUSION

The two nomograms which contained NPLN and LODDS had the potential to predict OS and CSS in patients with parotid gland carcinoma.

New Personal Model for Forecasting the Outcome of Patients with Histological Grade III-IV Colorectal Cancer Based on Regional Lymph Nodes

Background

Metastases at regional lymph nodes could easily occur in patients with high-histological-grade colorectal cancer (CRC). However, few models were built on the basis of lymph nodes to predict the outcome of patients with histological grades III-IV CRC.

Methods

Data in the Surveillance, Epidemiology, and End Results databases were used. Univariate and multivariate analyses were performed. A personalized prediction model was built in accordance with the results of the analyses. A nomogram was tested in two datasets and assessed using a calibration curve, a consistency index (C-index), and an area under the curve (AUC).

Results

A total of 14,039 cases were obtained from the database. They were separated into two groups (9828 cases for constructing the model and 4211 cases for validation). Logistic and Cox regression analyses were then conducted. Factors such as log odds of positive lymph nodes (LODDS) were utilized. Then, a personalized prediction model was established. The C-index in the construction and validation groups was 0.770. The 1-, 3-, and 5-year AUCs were 0793, 0.828, and 0.830 in the construction group, respectively, and 0.796, 0.833, and 0.832 in the validation group, respectively. The calibration curves showed well consistency in the 1-, 3- and 5-year OS between prediction and reality in both groups.

Conclusion

The nomogram built based on LODDS exhibited considerable reliability and accuracy.

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.

Beyond N staging in colorectal cancer: Current approaches and future perspectives

Traditionally, lymph node metastases (LNM) evaluation is essential to the staging of colon cancer patients according to the TNM (tumor–node–metastasis) system. However, in recent years evidence has accumulated regarding the role of emerging pathological features, which could significantly impact the prognosis of colorectal cancer patients. Lymph Node Ratio (LNR) and Log Odds of Positive Lymph Nodes (LODDS) have been shown to predict patients’ prognosis more accurately than traditional nodal staging and it has been suggested that their implementation in existing classification could help stratify further patients with overlapping TNM stage. Tumor deposits (TD) are currently factored within the N1c category of the TNM classification in the absence of lymph node metastases. However, studies have shown that presence of TDs can affect patients’ survival regardless of LNM. Moreover, evidence suggest that presence of TDs should not be evaluated as dichotomic but rather as a quantitative variable. Extranodal extension (ENE) has been shown to correlate with presence of other adverse prognostic features and to impact survival of colorectal cancer patients. In this review we will describe current staging systems and prognostic/predictive factors in colorectal cancer and elaborate on available evidence supporting the implementation of LNR/LODDS, TDs and ENE evaluation in existing classification to improve prognosis estimation and patient selection for adjuvant treatment.

Relationship Between Neoadjuvant Chemotherapy and Log Odds of Positive Lymph Nodes and Their Prognostic Role in Advanced Ovarian Cancer Patients With Optimal Cytoreductive Surgery

Purpose

To analyze the relationship between neoadjuvant chemotherapy (NACT) and log odds of positive lymph nodes (LODDS), as well as their prognostic role in advanced ovarian cancer (AOC) patients with optimal cytoreductive surgery.

Patients and Methods

From the SEER database during 2010-2016, we identified 1,012 AOC patients with optimal cytoreductive surgery. Univariable and multivariable logistic regression was performed to identify the relationship between NACT and LODDS. Overall survival (OS) and cancer-specific survival (CSS) were assessed using the Kaplan-Meier method and log-rank test. Univariable and multivariable Cox regression was conducted to determine the independent prognostic factors for OS and CSS.

Results

Factors associated with significantly higher NACT odds included older (≥60 years old), married, tumor size ≥ 15 cm, FIGO IV, and LODDS ≤ 0.1. Multivariable Cox regression model confirmed older (≥60 years old), unmarried, separated, divorced, widowed, mucinous histology type, tumor size ≥ 15 cm, and LODDS > 0.1 were correlated with increased risks of OS and CSS. NACT was not an independent prognostic factor for OS and CSS. In the subgroup analyses, LODDS was an independent prognostic factor for OS and CSS in patients with < 75 years old, married, unmarried, FIGO III, and tumor size < 15 cm.

Conclusion

NACT did not show any survival benefit in AOC patients with optimal cytoreductive surgery, but it may be beneficial in reducing LODDS. Meanwhile, clinicians can use grade of LODDS to predict the prognosis of AOC patients with optimal cytoreductive surgery.