Log Odds Of Positive Lymph Nodes Research Articles

Prognostic impact of log odds of positive lymph nodes (LODDS) in the stratification of patients with rectal cancer

IntroductionThe use of the N category of the TNM staging system, lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) in predicting overall survival (OS) and disease-free survival (DFS) in patients with rectal cancer is still controversial. Material and methodsA retrospective study of 445 patients with rectal cancer who underwent surgery between 2008 and 2017 in the University Complex Hospital was performed. Patients were stratified according to number of lymph nodes examined (NLNE), N staging, LNR and LODDS. The analysis was performed using the log-rank test, Kaplan-Meier functions, Cox regression and ROC curves. ResultsFive-year OS and DFS were 73.7% and 62.5%, respectively. No statistically significant differences were observed depending on NLNE. Increased LNR and LODDS were associated with shorter OS and DFS, independently of NLNE.Multivariate analysis showed that N stage, LNR and LODDS were independently associated with OS and DFS; however, the LODDS system obtained the best area under the curve, with greater predictive capacity for OS (AUC: 0.679) and DFS (AUC: 0.711). ConclusionLODDS and LNR give prognostic information that is not related to NLNE. LODDS provides better prognostic accuracy in patients with negative nodes than LNR and N stage.

Evaluation of lymph node ratios and log odds of positive nodes as prognostic indicators in primary organ malignancy

BackgroundStaging of malignant tumours based on positive lymph node number and not taking into account the actual number of examined lymph nodes during surgery may lead to bias and fallacious results. The ratio of positive and resected lymph nodes (LNR) and log odds of positive nodes (LODDS) emerged as novel prognostic markers in deciding the future course of management better than the parameter pN in predicting cancer-specific survival. We aim to evaluate and compare the prognostic value of pN, LNR and LODDS in common primary organ malignancies like breast, head and neck, gastric and cervical cancers. MethodsThis was an ambidirectional observational study conducted from September 2018 to August 2021 with one year (from 2017 to 2018) for retrospective data collection archived from records. It included patients affected by breast, head and neck, gastric and cervical cancers and were followed up for a period of 3 years from the date of diagnosis to perform a holistic survival analysis. The sample was grouped by American Joint Committee on Cancer N stage, LNR and LODDS, and analysed using Kaplan–Meier and multivariate Cox proportional hazard models. ResultsThe study included 202 breast cancer patients, 85 head and neck cancer patients, 100 gastric cancer patients and 52 cervical cancer patients. Multivariate Cox regressions analysis demonstrated a lower Akaike Information Criterion (AIC) value for LODDS and LNR followed by pN stage. ConclusionThe novel indicators LNR and LODDS better predicted the biological behaviour irrespective of lymph node number and allowed clinicians to correctly stratify patients for better postoperative management.

A log odds of positive lymph nodes-based predictive model effectively forecasts prognosis and guides postoperative adjuvant chemotherapy duration in stage III colon cancer: a multi-center retrospective cohort study

BackgroundThe log odds of positive lymph nodes (LODDS) was considered a superior staging system to N stage in colon cancer, yet its value in determining the optimal duration of adjuvant chemotherapy for stage III colon cancer patients has not been evaluated. This study aims to assess the prognostic value of a model that combines LODDS with clinicopathological information for stage III colon cancer patients and aims to stratify these patients using the model, identifying individuals who could benefit from varying durations of adjuvant chemotherapy.MethodA total of 663 consecutive patients diagnosed with stage III colon cancer, who underwent colon tumor resection between November 2007 and June 2020 at Sun Yat-sen University Cancer Center and Longyan First Affiliated Hospital of Fujian Medical University, were enrolled in this study. Survival outcomes were analyzed using Kaplan–Meier, Cox regression. Nomograms were developed to forecast patient DFS, with the Area Under the Curve (AUC) values of time-dependent Receiver Operating Characteristic (timeROC) and calibration plots utilized to assess the accuracy and reliability of the nomograms.ResultsMultivariate analysis revealed that perineural invasion (HR = 1.776, 95% CI: 1.052–3.003, P = 0.032), poor tumor differentiation (HR = 1.638, 95% CI: 1.084–2.475, P = 0.019), and LODDS groupings of 2 and 1 (HR = 1.920, 95% CI: 1.297–2.842, P = 0.001) were independent predictors of disease-free survival (DFS) in the training cohort. Nomograms constructed from LODDS, perineural invasion, and poor tumor differentiation demonstrated robust predictive performance for 3-year and 5-year DFS in both training (3-year AUC = 0.706, 5-year AUC = 0.678) and validation cohorts (3-year AUC = 0.744, 5-year AUC = 0.762). Stratification according to this model showed that patients in the high-risk group derived significant benefit from completing 8 cycles of chemotherapy (training cohort, 82.97% vs 67.17%, P = 0.013; validation cohort, 89.49% vs 63.97%, P = 0.030).ConclusionThe prognostic model, integrating LODDS, pathological differentiation, and neural invasion, demonstrates strong predictive accuracy for stage III colon cancer prognosis. Moreover, stratification via this model offers valuable insights into optimal durations of postoperative adjuvant chemotherapy.

Application and subgroup analysis of competing risks model based on different lymph node staging systems in differentiated thyroid cancer.

Differentiated thyroid cancer (DTC) is the most common endocrine malignancy, with a rising incidence worldwide. Accurate prognostic models are essential for effective patient management. This study evaluates the prognostic value of various lymph node staging systems in DTC using a competing risks model. We used SEER database records (1998-2016) of 16,527 DTC patients, analyzing N stage, positive lymph node numbers (PLNNs), metastatic lymph node ratio (MLNR), log odds of positive lymph nodes (LODDS), and log odds of the negative lymph node (NLN)/T stage ratio (LONT). Univariate and multivariate analyses in a competing risks model were performed, along with subgroup analyses based on demographic and clinical characteristics. In this study of 16,527 patients with DTC, different lymph node staging systems showed different prognostic correlations in univariate and multivariate analyses. In particular, PLNNs showed significant prognostic correlations in several subgroups. Additionally, PLNNs were more suitable as a lymph node staging system for DTC than LODDS and MLNR in N1 stage subgroups, with an optimal cut-off of 13. Receiver operating characteristic curves, calibration curves and nomograms improved the clinical utility of the prognostic model based on PLNNs. Using competing risks model and subgroup analyses, we found that PLNNs had the best prognostic discriminatory efficacy for patients with DTC, especially those with N1 stage disease, and had an optimal cut-off value of 13.

Establishment of a nomogram model for predicting distant metastasis in pancreatic ductal adenocarcinoma: a comparative analysis of different lymph node staging systems based on the SEER database

The purpose of this study was to compare the predictive value of different lymph node staging systems and to develop an optimal prognostic nomogram for predicting distant metastasis in pancreatic ductal adenocarcinoma (PDAC). Our study involved 6364 patients selected from the Surveillance, Epidemiology, and End Results (SEER) database and 126 patients from China. Independent risk factors for distant metastasis were screened by univariate and multivariate logistic regression analyses, and a model-based comparison of different lymph node staging systems was conducted. Furthermore, we developed a nomogram for predicting distant metastasis using the optimal performance lymph node staging system. The lymph node ratio (LNR), log odds of positive lymph nodes (LODDS), age, primary site, grade, tumor size, American Joint Committee on Cancer (AJCC) 7th Edition T stage, and radiotherapy recipient status were significant predictors of distant metastasis in PDAC patients. The model with the LODDS was a better fit than the model with the LNR. We developed a nomogram model based on LODDS and six clinical parameters. The area under the curve (AUC) and concordance index (C-index) of 0.753 indicated that this model satisfied the discrimination criteria. Kaplan–Meier curves indicate a significant difference in OS among patients with different metastasis risks. LODDS seems to have a superior ability to predict distant metastasis in PDAC patients compared with the AJCC 8th Edition N stage, PLN and LNR staging systems. Moreover, we developed a nomogram model for predicting distant metastasis. Clinicians can use the model to detect patients at high risk of distant metastasis and to make further clinical decisions.

Comparison of the predictive performance of three lymph node staging systems for late-onset gastric cancer patients after surgery.

Lymph node (LN) status is a vital prognostic factor for patients. However, there has been limited focus on predicting the prognosis of patients with late-onset gastric cancer (LOGC). This study aimed to investigate the predictive potential of the log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN stage in assessing the prognosis of patients diagnosed with LOGC. The LOGC data were obtained from the Surveillance, Epidemiology, and End Results database. This study evaluated and compared the predictive performance of three LN staging systems. Univariate and multivariate Cox regression analyses were carried out to identify prognostic factors for overall survival (OS). Three machine learning methods, namely, LASSO, XGBoost, and RF analyses, were subsequently used to identify the optimal LN staging system. A nomogram was built to predict the prognosis of patients with LOGC. The efficacy of the model was demonstrated through receiver operating characteristic (ROC) curve analysis and decision curve analysis. A total of 4,743 patients with >16 removed lymph nodes were ultimately included in this investigation. Three LN staging systems demonstrated significant performance in predicting survival outcomes (P < 0.001). The LNR exhibited the most important prognostic ability, as evidenced by the use of three machine learning methods. Utilizing independent factors derived from multivariate Cox regression analysis, a nomogram for OS was constructed. The calibration, C-index, and AUC revealed their excellent predictive performance. The LNR demonstrated a more powerful performance than other LN staging methods in LOGC patients after surgery. Our novel nomogram exhibited superior clinical feasibility and may assist in patient clinical decision-making.

Construction of a novel nomogram for predicting overall survival in patients with Siewert type II AEG based on LODDS: a study based on the seer database and external validation.

In recent years, the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing globally. Despite advances in the diagnosis and treatment of AEG, the overall prognosis for AEG patients remains concerning. Therefore, analyzing prognostic factors for AEG patients of Siewert type II and constructing a prognostic model for AEG patients is important. Data of primary Siewert type II AEG patients from the SEER database from 2004 to 2015 were obtained and randomly divided into training and internal validation cohort. Additionally, data of primary Siewert type II AEG patients from the China Medical University Dandong Central Hospital from 2012 to 2018 were collected for external validation. Each variable in the training set underwent univariate Cox analysis, and variables with statistical significance (p < 0.05) were added to the LASSO equation for feature selection. Multivariate Cox analysis was then conducted to determine the independent predictive factors. A nomogram for predicting overall survival (OS) was developed, and its performance was evaluated using ROC curves, calibration curves, and decision curves. NRI and IDI were calculated to assess the improvement of the new prediction model relative to TNM staging. Patients were stratified into high-risk and low-risk groups based on the risk scores from the nomogram. Age, Differentiation grade, T stage, M stage, and LODDS (Log Odds of Positive Lymph Nodes)were independent prognostic factors for OS. The AUC values of the ROC curves for the nomogram in the training set, internal validation set, and external validation set were all greater than 0.7 and higher than those of TNM staging alone. Calibration curves indicated consistency between the predicted and actual outcomes. Decision curve analysis showed moderate net benefit. The NRI and IDI values of the nomogram were greater than 0 in the training, internal validation, and external validation sets. Risk stratification based on the nomogram's risk score demonstrated significant differences in survival rates between the high-risk and low-risk groups. We developed and validated a nomogram for predicting overall survival (OS) in patients with Siewert type II AEG, which assists clinicians in accurately predicting mortality risk and recommending personalized treatment strategies.

Bi-institutional spline curve analysis of lymph node mapping in gallbladder cancer operated over 12 years: Impact of location and number of lymph nodal stations.

e16274 Background: Current staging system for gallbladder cancers (GBC) takes into account only the number of metastatic lymph nodes without addressing their location. The current study evaluates the prognostic impact of lymph node mapping (number and location) in node positive GBCs. Methods: Prospectively maintained operative database of GBC patients with positive lymph nodes were analysed from two tertiary cancer care centers in a retrospective cohort study design between April 2010 till March 2022. Nodal burden was assessed including both, the number of metastatic nodes and the lymph node station. Impact of lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS) was evaluated using regression and spline curve analysis. Results: Amongst 1312 operated GBC patients, 272 patients with node positive disease were included. The median nodal yield was 8. The median LNR and LODDS was 0.222 and -0.48 respectively. The 5-year DFS and OS for patients with only cystic node metastases was 52.3% and 50.8% respectively (median: not reached), as compared to 24.6% and 35.2% for involvement of regional nodal stations beyond cystic nodes. Higher LODDS was associated with inferior DFS and OS when compared to the LNR. On multivariate analysis, multi-station involvement was the only factor associated with inferior DFS (p &lt; 0.001) and OS (p = 0.007). Conclusions: Station wise pathological assessment of lymph nodal involvement could potentially provide superior prognostic information, in addition to number of involved nodes. Involvement of cystic lymph node alone has relatively superior prognosis as compared to multi-station involvement.

Different lymph node staging systems for predicting the prognosis of colorectal neuroendocrine neoplasms.

Colorectal neuroendocrine neoplasms (NENs) are a rare malignancy that primarily arises from the diffuse distribution of neuroendocrine cells in the colon and rectum. Previous studies have pointed out that the status of lymph node may be used to predict the prognosis. To investigate the predictive values of lymph node ratio (LNR), positive lymph node (PLN), and log odds of PLNs (LODDS) staging systems on the prognosis of colorectal NENs treated surgically, and compare their predictive values. This cohort study included 895 patients with colorectal NENs treated surgically from the Surveillance, Epidemiology, and End Results database. The endpoint was mortality of patients with colorectal NENs treated surgically. X-tile software was utilized to identify most suitable thresholds for categorizing the LNR, PLN, and LODDS. Participants were selected in a random manner to form training and testing sets. The prognosis of surgically treating colorectal NENs was examined using multivariate cox analysis to assess the associations of LNR, PLN, and LODDS with the prognosis of colorectal NENs. C-index was used for assessing the predictive effectiveness. We conducted a subgroup analysis to explore the different lymph node staging systems' predictive values. After adjusting all confounding factors, PLN, LNR and LODDS staging systems were linked with mortality in patients with colorectal NENs treated surgically (P < 0.05). We found that LODDS staging had a higher prognostic value for patients with colorectal NENs treated surgically than PLN and LNR staging systems. Similar results were obtained in the different G staging subgroup analyses. Furthermore, the area under the receiver operating characteristic curve values for LODDS staging system remained consistently higher than those of PLN or LNR, even at the 1-, 2-, 3-, 4-, 5- and 6-year follow-up periods. LNR, PLN, and LODDS were found to significantly predict the prognosis of patients with colorectal NENs treated surgically.

Log odds of positive lymph nodes (LODDS)-based novel nomogram for survival estimation in patients with invasive micropapillary carcinoma of the breast

BackgroundInvasive micropapillary carcinoma (IMPC) of the breast is known for its high propensity for lymph node (LN) invasion. Inadequate LN dissection may compromise the precision of prognostic assessments. This study introduces a log odds of positive lymph nodes (LODDS) method to address this issue and develops a novel LODDS-based nomogram to provide accurate prognostic information.MethodsThe study analyzed data from 1,901 patients with breast IMPC from the Surveillance, Epidemiology, and End Results database. It assessed the relationships between LODDS and the number of excised LN (eLN), positive LN (pLN), and the pLN ratio (pLNR), identifying an optimal threshold value using a restricted cubic spline method. Predictive factors were identified by the Cox least absolute shrinkage and selection operator (Cox-LASSO) regression and validated through multivariate Cox regression to construct a nomogram. The model's accuracy, discrimination, and utility were assessed. The study also explored the consequences of excluding LODDS from the nomogram and compared its effectiveness with the tumor-node-metastasis (TNM) staging system.ResultsLODDS improved N status classification by identifying heterogeneity in patients with pLN ratios of 0% (pLN =0) or 100% (pLN =eLN) and setting -1.08 as the ideal cutoff. Five independent prognostic factors for breast cancer-specific survival (BCSS) were identified: tumor size, N status, LODDS, progesterone receptor status, and histological grade. The LODDS-based nomogram achieved a strong concordance index of 0.802 (95% CI: 0.741-0.863), surpassing both the version without LODDS and the conventional TNM staging in all tests.ConclusionsFor breast IMPC, LODDS served as an independent prognostic factor, its effectiveness unaffected by the anatomical LN count, enhancing the accuracy of N staging. The LODDS-based nomogram showed promise in offering more personalized prognostic information.

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

PurposeConsidering 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.MethodsUsing 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.ResultsA 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.ConclusionThe 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.

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. 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. 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. 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.

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.

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. 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. 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. 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.

Log odds of positive nodes as a prognostic factor for rectal cancer: a retrospective study.

Rectal cancer is an important cause of mortality and morbidity globally. The aim of this study was to investigate whether the log odds of positive nodes system is a better indicator than tumor node metastasis and lymph node ratio systems to determine rectum cancer prognosis, which is an important cause of mortality and morbidity globally. This was a single-center retrospective cross-sectional study. Data were obtained from the medical records of patients with rectum adenocarcinoma followed at Gazi University Hospital. The clinicopathological data of 128 patients with rectum adenocarcinoma who underwent low anterior resection or abdominoperineal resection between January 2010 and December 2018 was retrospectively reviewed. Patients with rectum adenocarcinoma as the first and only primary diagnosis, which was confirmed by histopathological examination, than those who had undergone complete curative resection via low anterior resection or abdominoperineal resection were included. Those with familial adenomatous polyposis or Lynch syndrome, those under 18 years of age, with a synchronous tumor, peritoneal spread, or metastatic disease at the time of diagnosis, and those with <12 lymph nodes dissected from the resection material were excluded from the study. In multivariate analysis, age, perineural invasion, tumor node metastasis stage, lymph node ratio stage, and log odds of positive nodes stage were found to be independent prognostic factors (p<0.05). LODDS2 patients' mortality rates were 9.495 times higher than LODDS0 patients [hazard ratio=9.495, (95%CI 4.155-21.694), p<0.001] while LNR2 stage patients' mortality rates were 7.016 times higher than LNR0 stage patients [hazard ratio=7.016, (95%CI 3.123-15.765), p<0.001] and N2 stage patients had a 5.135 times higher risk of mortality than those who were in N0 stage [hazard ratio=5.135 (95%CI 2.451-10.756), p<0.001]. Log odds of positive nodes is a more valuable prognostic factor for rectal cancer patients than tumor node metastasis and lymph node ratio systems to determine rectum cancer prognosis.

Prognostic prediction and comparison of three staging programs for patients with advanced (T2-T4) esophageal squamous carcinoma after radical resection.

Lymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC). This cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell's concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach. Independent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability. LODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.

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

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

Prognostic role of the log odds of positive lymph nodes in Western patients with resected gastric cancer: A comparison with the 8th edition of the TNM staging system.

Several alternative lymph node staging systems have recently been described for gastric cancer. The log odds of positive lymph nodes (LODDS) system may be superior to the pN stage (American Joint Committee on Cancer) and lymph node ratio systems in predicting outcomes for patients with gastric cancers, as indicated by some researchers. Most studies, however, have been conducted in Asian countries, and conflicting results have been reported by other investigators. We conducted a retrospective study of all 377 cases of gastric cancer resected at a tertiary hospital in Spain between 2000 and 2019. Clinicopathologic features were collected, LODDS were calculated and categorized into 5 groups (S1-S5), and statistical analysis was performed. The cases included (n = 315) were classified as S1 (25.6%), S2 (18.4%), S3 (21.3%), S4 (20.3%), and S5 (14.4%). The LODDS classification was significantly associated with tumor size, Laurén subtype, presence of signet ring cells, tumor grade, perineural infiltration, lymphovascular invasion, growth pattern, pT, tumor recurrence, and death. Kaplan-Meier analysis based on the LODDS classification demonstrated improved patient stratification compared with the pN stage for both overall survival (OS) and disease-free survival (DFS). Area under the curve values for recurrence and death were superior for the LODDS classification, and this classification was independently related to OS and DFS. In addition, the LODDS classification successfully divided patients without lymph node metastases (pN0) into subgroups with distinct prognoses. For our cohort, the LODDS system showed better prognostic performance than pN stage; it was an independent predictor of OS and DFS, and it provided valuable prognostic information in cases without lymph node metastases. Its prognostic accuracy, however, decreased in cases with fewer than 16 lymph nodes resected.

Nomogram incorporating log odds of positive lymph nodes improves prognostic prediction for ovarian serous carcinoma: a real-world retrospective cohort study

ObjectivesOvarian serous carcinoma (OSC) is a major cause of gynaecological cancer death, yet there is a lack of reliable prognostic models. To address this, we developed and validated a nomogram...

Exploring the most appropriate lymph node staging system for node-positive breast cancer patients and constructing corresponding survival nomograms.

The lymph node (LN) status is a crucial prognostic factor for breast cancer (BC) patients. Our study aimed to compare the predictive capabilities of three different LN staging systems in node-positive BC patients and develop nomograms to predict overall survival (OS). We enrolled 71,213 eligible patients from the SEER database, and 667 cases from our hospital were used for external validation. All patients were divided into two groups based on the number of removed lymph nodes (RLNs). The prognostic abilities of pN stage, positive LN ratio (LNR), and log odds of positive LN (LODDS) were compared using the C-indexes and AUC values. LASSO regression was performed to identify significant factors associated with prognosis and develop corresponding nomogram models. Our study found that LNR had superior predictive performance compared to pN and LODDS among patients with RLNs < 10, while pN performed better in patients with RLNs ≥ 10. In the training set, the nomogram models exhibited excellent clinical applicability, as evidenced by the C-indexes, ROC curves, calibration plots, and decision curve analysis curves. Moreover, the nomogram classification accurately differentiated risk subgroups and improved discrimination. These results were externally validated in the validation cohort. Physicians should select different LN staging systems based on the number of RLNs. Our novel nomograms demonstrated excellent performance in both internal and external validations, which may assist in patient counseling and guide treatment decision-making.

Prognostic Performance of Three Lymph-Node Staging Systems on Gastric Signet-Ring-Cell Carcinoma.

The lymph-node staging system can predict the prognosis of gastric signet-ring-cell carcinoma (SRCC). However, there are significant differences in lymph-node status between early SRCC and advanced SRCC. Additionally, the optimal system for early and advanced SRCC remains unknown. This study retrospectively analyzed 693 SRCC patients who underwent radical resection in the Department of Gastrointestinal Surgery, Harbin Medical University Cancer Hospital. The predicted performance of three lymph-node staging systems, including pN staging, lymph-node metastasis rate (LNR), and log odds of positive lymph nodes (LODDS), was compared using the receiver characteristic operating curve (ROC) and c-index. The Kaplan-Meier method and the log-rank test analyzed the overall survival of patients. The Cox risk regression model identified independent risk factors associated with patient outcomes. The nomogram was made by R studio. The 693 SRCC included 165 early SRCC and 528 advanced SRCC. ROC showed that LODDS had better predictive performance than pN and LNR in predicting prognosis regardless of early or advanced SRCC. LODDS can be used to predict the prognosis of early and advanced SRCC and was an independent risk factor associated with patient outcomes (p = 0.002, p < 0.001). Furthermore, the nomogram constructed by LODDS and clinicopathological features had good predictive performance. LODDS showed clear prognostic superiority over both pN and LNR in early and advanced SRCC.