Value Of Lymph Node Ratio Research Articles

Value of lymph node ratio as a prognostic factor of recurrence in medullary thyroid cancer.

The purpose of this study is to evaluate the relationship between lymph node status (the number of resected lymph nodes; the number of metastatic lymph nodes, LNM, and lymph node ratio, LNR) and biochemical recurrence, disease-free survival (DFS), as well as overall survival (OS) in medullary thyroid carcinoma (MTC). This study enrolled MTC patients at Tianjin Medical University Cancer Institute and Hospital between 2011 and 2019. We used Logistic regression analysis, Cox regression models and Kaplan-Meier test to identify risk factors influencing biochemical recurrence, DFS, and OS. We identified 160 patients who satisfied the inclusion criteria from 2011 to 2019. We used ROC analysis to define the cut-off value of LNR with 0.24. Multifocality, preoperative calcitonin levels, pathologic N stage, resected lymph nodes, LNM, LNR, and the American Joint Committee on Cancer (AJCC) clinical stage were significant (P < 0.05) prognostic factors influencing biochemical cure. In univariable analyses, gross extrathyroidal extension, preoperative calcitonin levels, pathologic T classification, pathologic N stage, resected lymph nodes, LNM, LNR, AJCC clinical stage, and biochemical cure were significant (P < 0.05) factors of DFS. When the multivariable analysis was performed, LNR was identified as predictor of DFS (HR = 4.818, 95% CI [1.270-18.276]). Univariable Cox regression models reflected that tumor size, pathologic N stage, and LNR were predictor of OS. Furthermore, multivariable analysis manifested that LNR was predictor of OS (HR = 10.061, 95% CI [1.222-82.841]). This study illustrated that LNR was independent prognostic factor of DFS and OS in MTC. In addition, LNR influenced biochemical cure. Further investigations are needed to determine the optimal cut-off value for predicting prognosis.

A prediction model for the 5-year, 10-year and 20-year mortality of medullary thyroid carcinoma patients based on lymph node ratio and other predictors.

To explore the predictive value of lymph node ratio (LNR) for the prognosis of medullary thyroid carcinoma (MTC) patients, and constructed prediction models for the 5-year, 10-year and 20-year mortality of MTC patients based on LNR and other predictors. This cohort study extracted the data of 2,093 MTC patients aged ≥18 years undergoing total thyroidectomy and neck lymph nodes dissection. Kaplan-Meier curves and log-rank tests were performed to compare survival curves between LNR < 15% group and LNR ≥ 15% group. All data was divided into the training set (n = 1,465) and the testing set (n = 628). The random survival forest model was constructed in the training set and validated in the testing set. The area under the curve (AUC) was employed for evaluating the predictive ability of the model. The 5-year, 10-year and 20-year overall survival (OS) and cause-specific survival (CSS) of MTC patients with LNR <15% were higher than those with LNR ≥15%. The OS was 46% and the CSS was 75% after 20 years' follow-up. The AUC of the model for the 5-year, 10-year, and 20-year OS in MTC patients was 0.878 (95%CI: 0.856-0.900), 0.859 (95%CI: 0.838-0.879) and 0.843 (95%CI: 0.823-0.862) in the training set and 0.845 (95%CI: 0.807-0.883), 0.841 (95%CI: 0.807-0.875) and 0.841 (95%CI: 0.811-0.872) in the testing set. In the training set, the AUCs were 0.869 (95%CI: 0.845-0.892), 0.843 (95%CI: 0.821-0.865), 0.819 (95%CI: 0.798-0.840) for the 5-year, 10-year and 20-year CCS in MTC patients, respectively. In the testing set, the AUCs were 0.857 (95%CI: 0.822-0.892), 0.839 (95%CI: 0.805-0.873) and 0.826 (95%CI: 0.794-0.857) for the 5-year CCS, 10-year CCS and 20-year CCS in MTC patients, respectively. The models displayed good predictive performance, which might help identify MTC patients might have poor outcomes and appropriate interventions should be applied in these patients.

Analysis of factors associated with the prognosis of papillary thyroid cancer and the construction of a survival model.

To study the survival prediction value of lymph node ratio (LNR) and preoperative thyroglobulin (Tg) in the prognosis of thyroid papillary carcinoma (PTC). A total of 495 patients with PTC and lymph node metastasis treated at the Cancer Hospital of Xinjiang Medical University were selected for a retrospective study. The disease-free survival (DFS) of patients was the follow-up endpoint. DFS was calculated for all patients. The Cox proportional risk regression model and nomogram were used to predict the survival prognosis of PTC with lymph node metastasis by index. LNR and preoperative Tg level cutoff values were obtained using ROC curves. To express DFS, Kaplan-Meier survival curves were created. Using 3- and 5-year calibration curves and AUC values, the prognostic models' precision and discrimination were assessed. Clinical decision curve analysis was used to forecast clinical benefitability. Finally, the results were validated using internal cross-validation. The cutoff values of LNR and preoperative Tg level were 0.295 and 50.24, respectively, and they were divided into two groups according to the cutoff values. Multifactorial Cox regression models showed that NLNM, LNR, and preoperative Tg level (all p< 0.05) were independent risk factors affecting the prognosis of PTC with lymph node metastasis. Kaplan-Meier curves showed higher DFS rates in the group with low NLNM (<10), LNR (<0.295), and preoperative Tg level (<50.24) groups. The 3-year and 5-year calibration curves showed good agreement. A ROC curve analysis was performed on the nomogram model, and its AUC values at 3 and 5 years were, respectively, 0.805 and 0.793. Clinical decision curves indicate good clinical benefit. Finally, internal cross-validation demonstrated the legitimacy of the prognostic model. The LNR and preoperative Tg levels, in combination with other independent factors, were effective in predicting the survival prognosis for patients with PTC.

Impact of regional positive lymph node ratio of gallbladder carcinoma on prognosis

Objective: To study the impact of regional positive lymph node ratio (LNR) on prognosis of patients with gallbladder carcinoma. Methods: The clinicopathological and survival data of 53 patients with gallbladder carcinoma who underwent radical resection with regional lymph node metastasis in Ningbo University Affiliated Lihuili Hospital from May 2012 to December 2020 were collected, and receiver operating characteristic curve (ROC) was used to determine the optimal cut-off value of LNR for predicting postoperative survival status in patients with gallbladder carcinoma. According to the critical value, the patients were divided into low LNR group and high LNR group. The clinicopathological features and prognosis of the two groups were compared. Log rank test was used for univariate analysis of prognostic factors in patients with gallbladder carcinoma, and Cox proportional hazards model was used for multivariate analysis. Results: A total of 417 regional lymph nodes were dissected in 53 patients, of which 144 lymph nodes were positive, with a positive rate of 34.5%. The optimal cut-off value of LNR for predicting postoperative survival status of patients with gallbladder carcinoma was 0.33. According to this cut-off value, patients were divided into low LNR group (LNR≤0.33, 28 cases) and high LNR group (LNR>0.33, 25 cases). The recurrence rates were 64.3% (18/28) and 88.0 % (22/25) in low LNR group and high LNR group, respectively. The median recurrence-free survival (RFS) was 8 and 7 months, respectively (P=0.032). In the low LNR group, the 1-, 3-, and 5-year survival rates were 56.2%, 38.4%, and 32.0%, respectively, and the median overall survival (OS) was 16 months. In the high LNR group, the 1-, 3-, and 5-year survival rates were 37.9%, 5.4%, and 0, respectively, and the median OS was 9 months. The postoperative survival rate of patients in the low LNR group was better than that in the high LNR group (P=0.008). Univariate analysis showed that LNR was even associated with RFS and OS in patients with gallbladder carcinoma (P<0.05). Multivariate analysis showed that LNR>0.33 was an independent risk factor for postoperative RFS (HR=1.977, 95% CI: 1.045-3.740), but not for OS (HR=1.561, 95% CI: 0.685-3.553). Conclusion: On the basis of clearing a sufficient number of regional lymph nodes, patients with gallbladder carcinoma with regional LNR>0.33 are more likely to relapse after operation, but the predictive value of LNR>0.33 OS is insufficient.

The prognostic role of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy: A dose-response meta-analysis.

As neoadjuvant chemotherapy is widely used in breast cancer patients, the lymph node ratio has not been fully validated as a prognostic indicator of breast cancer received neoadjuvant chemotherapy. This study was conducted to investigate the prognostic value of lymph node ratio in breast cancer patients received neoadjuvant chemotherapy. Systematic searches were performed in the PubMed, Embase, and Cochrane Library databases until 15 December 2021 for studies on the association between lymph node ratio and the prognosis of breast cancer after neoadjuvant chemotherapy. Overall survival and disease-free survival were used as outcome events, and hazard ratio was chosen as the parameter to evaluate the correlation. The dose-response relationship was assessed by restricted cubic splines. In the subgroup analyses, which were used to explore potential heterogeneity among the included studies according to study region and sample size. Sensitivity analysis was performed to assess the stability of individual studies, and publication bias was determined with funnel plots, Begg's test, and Egger&apos;s test. All statistical analyses were performed using Stata 15.1. A total of 12 studies with 4,864 patients were included in this meta-analysis. In this study, high lymph node ratio was significantly associated with decreased overall survival (HR: 4.74; 95%CI: 3.36-6.67; P < 0.001) and disease-free survival (HR: 4.77; 95%CI: 3.69-6.17; P < 0.001). Moreover, the dose-response meta-analysis showed a linear association between higher lymph node ratio and shorter overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy. The meta-analysis suggested that high lymph node ratio was significantly associated with short overall survival and disease-free survival in breast cancer patients after neoadjuvant chemotherapy. Therefore, lymph node ratio is an independent predictive factor for the prognosis of breast cancer patients after neoadjuvant chemotherapy, which may better refine the cancer staging system.

Prognostic impact of number of examined lymph nodes on survival of patients with appendiceal neuroendocrine tumors.

The prognosis of patients with appendiceal neuroendocrine tumors (ANETs) is related to lymph node (LN) metastasis and other factors. However, it is unclear how the number of examined LNs (ELNs) impact on survival. To determine the factors affecting the cancer-specific survival (CSS) of patients with ANET and to evaluate the impact of the number of ELNs on survival. A total of 4583 ANET patients were analyzed in the Surveillance, Epidemiology, and End Results database. Univariate survival analysis was used to identify factors related to survival and the optimal number of ELNs and lymph node ratio (LNR) were determined by the Kaplan-Meier method. The survival difference was determined by CSS. Except for sex, the other factors, such as age, year, race, grade, histological type, stage, tumor size, ELNs, LNR, and surgery type, were associated with prognosis. The 3-, 5-, and 10-year CSS rates of ANET patients were 91.2%, 87.5, and 81.7%, respectively (median follow-up period of 31 mo and range of 0-499 mo). There was no survival difference between the two surgery types, namely, local resection and colectomy or greater, in both stratifications of tumor size ≥ 2 cm (P = 0.523) and < 2 cm (P = 0.068). In contrast to patients with a tumor size < 2 cm, those with a tumor size ≥ 2 cm were more likely to have LN metastasis (χ 2 = 378.16, P < 0.001). The optimal number of ELNs was more than 11, 7, and 18 for all patients, node-negative patients, and node-positive patients, respectively. CSS rates of patients with a larger number of ELNs were significantly improved (≤ 10 vs ≥ 11, χ 2 = 20.303, P < 0.001; ≤ 6 vs ≥ 7, χ 2 = 11.569, P < 0.001; ≤ 17 vs ≥ 18, χ 2 = 21.990, P < 0.001; respectively). ANET patients with an LNR value ≤ 0.16 were more likely to have better survival than those with values of 0.17-0.48 (χ 2 = 48.243, P < 0.001) and 0.49-1 (χ 2 = 168.485, P < 0.001). ANET ≥ 2 cm are more likely to develop LN metastasis. At least 11 ELNs are required to better evaluate the prognosis. For patients with positive LN metastasis, 18 or more LNs need to be detected and lower LNR values (LNR ≤ 0.16) indicate a better survival prognosis.

Prognostic value of lymph node ratio in cervical cancer: A meta-analysis.

Background:The role of the lymph node ratio (LNR) in the existing tumor node metastasis classification system should be verified as one of the prognosis prediction factors. This work evaluated LNR’s performance in predicting cervical cancer (CC) prognosis through a meta-analysis.Method:Related studies were retrieved from the Cochrane Library, EMBASE, and PubMed databases. The language was restricted to English. The combined hazard ratios (HRs) were utilized to analyze the prognostic value of LNR.Results.Our study included 8 articles with 3325 subjects published after 2015. Based on our analysis, high LNR was the adverse prognostic factor for overall survival (OS, HR = 1.45; 95% CI = 1.23–1.73; P = .238) and disease-free survival (DFS, HR = 2.69; 95% CI = 1.98–3.66; P = .597) among the CC cases. Furthermore, as revealed by subgroup analysis, in CC patients, median LNR of about 0.0625 and 0.066 served as the prominent risk factor for DFS and OS.Conclusions:The current work illustrates that elevated LNR is related to the dismal prognosis of CC. More well-designed clinical studies are warranted for assessing whether LNR is a factor independently predicting the prognosis of CC.

A modified mTNM staging system based on lymph node ratio for colon neuroendocrine tumors: A recursive partitioning analysis.

In the current tumor-lymph node-metastasis (TNM) staging system for colon neuroendocrine tumors, lymph node status is divided into N1 and N0. An assessment of the lymph node ratio (LNR) and a proposal for a modified mTNM staging system were the objectives of this study. Selecting the optimal cut-off value of LNR was done using X-tile. A Cox regression model and the Kaplan-Meier method were performed to calculate patient cancer-specific survival in the Surveillance, Epidemiology and End Results cohort. Recursive partitioning analysis was used to improve TNM staging. The study included 674 patients. The current TNM staging system showed inadequate discriminatory power between stage I and stage II patients (p = 0.088). The optimal cut-off value was determined as 0.6 for LNR. Based on multivariate Cox regression analysis, the modified mN classification could be classified into mN 0 (LNR = 0.00), mN 1 (LNR = 0.01-0.60), and mN 2 (LNR > 0.60), and was found to be an independent factor affecting prognosis (p < 0.001). Using the American Joint Committee on Cancer T and modified mN classifications, the modified mTNM system was constructed, and it exhibited better prognostic discriminatory power ability than the traditional TNM system (C-index: 0.587 vs. 0.665). Our study determined that LNR is a prognostic factor in colon NET patients. In addition, to more accurately assess the prognosis of colon NET patients, we proposed a modified mTNM staging system.

Lymph Node Ratio Nomogram-Based Prognostic Model for Resected Distal Cholangiocarcinoma.

Several variables have been described as prognostic factors for resected distal cholangiocarcinoma (dCC), including lymph node metastases (N status) and lymph node ratio (LNR). The present study aimed to evaluate the prognostic value of LNR on survival and to establish a novel prognostic nomogram to predict the cancer-specific recurrence-free survival (RFS) of dCC. Between December 2006 and September 2020, 415 consecutive patients who underwent pancreaticoduodenectomy (PD) for dCC in 10 centers were identified. Multivariate Cox analysis was used to identify all independent risk factors among several prognostic factors. A nomogram was then developed and assessed by integrating the independent prognostic factors into the model, and the concordance index (C-index) was used to evaluate its performance. According to Cox regression multivariate analysis, a nomogram based on independent prognostic factor for RFS was performed including LNR 15 (hazard ratio [HR] 2.442, 95% CI 1.348-4.425, p = 0.003), perineural invasion (HR 3.100, 95% CI 1.183-8.122, p = 0.025), differentiation grade (HR 2.100, 95% CI 1.172-4.143, p = 0.021), and radicality of PD (HR 2.276, 95% CI 1.223-4.234, p = 0.009). The C-index of the nomogram, tailored based on the previous significant factors, was 0.8. LNR15 yields a high prognostic efficiency for RFS. The nomogram based on LNR can provide an accurate prognosis assessment for patients with resected dCC.

A Lymph Node Ratio Nomogram Based Prognostic Model for Resected Distal Cholangiocarcinoma

Introduction: Several factors have been described as prognostic factor for resected distal cholangiocarcinoma (dCC), among which lymph node metastasis that can be presented as pN0-N1-N2 and lymph node ratio (LNR). This study aimed to evaluate the prognostic value of LNR on survival and to establish a novel prognostic nomogram to predict the cancer-specific recurrence-free survival (RFS) of dCC. Methods: Between December 2006 and September 2020, patients who underwent pancreaticoduodenectomy (PD) for dCC in 10 centers were identified. Multivariate Cox analysis was used to screen independent risk factors among several prognostic factors. A nomogram prognostic staging model was established, and precision was verified by C-index. Results: A total of 415 cases have been included. Cox regression multivariate analysis indicated the LNR15% (hazard ratio [HR] 2.442, 95% CI 1.348-4.425, p = 0.003), as an independent prognostic factor for recurrence-free survival (RFS) with perineural invasion (HR 3.100, 95% CI 1.183-8.122, p = 0.021) and the radicality of PD (HR 2.276, 95% CI 1.223-4.234, p = 0.009). The C-index of the nomogram, based on the above factors, in the validation set was 0.8. Conclusion: LNR yielded a better prognostic efficiency for RFS than the American Joint Committee on Cancer N stage. The nomogram based on LNR can provide a more accurate prognosis for patients with resected dCC.

Real-world survival of colon cancer after radical surgery: A single-institutional retrospective analysis.

The survival rate for colon cancer after radical surgery has been the focus of extensive debate. To assess the postoperative survival and prognostic factors for overall survival (OS), we collected clinicopathological information for 2,655 patients. The survival time and potential risk factors for OS were analyzed by using Kaplan–Meier curves, Cox proportional hazards models, best subset regression (BSR), and least absolute shrinkage and selection operator (LASSO). The 5-year survival rates of stage I–IV colon cancer were 96.6%, 88.7%, 69.9%, and 34.3%, respectively. Adjuvant chemotherapy improved the survival rate (90.4% vs. 82.4%, with versus without adjuvant chemotherapy, respectively) in stage II patients with high-risk factors. Elevated preoperative carcinoembryonic antigen (CEA) and carbohydrate antigen 19-9 (CA19-9) were significantly associated with worse OS compared with patients without these elevations. Less than 12 versus more than 12 harvested lymph nodes (LNs) affected prognosis (84.6% vs. 89.7%, respectively). Regarding the lymph node ratio (LNR), the 5-year OS rate was 89.2%, 71.5%, 55.8%, and 34.5% in patients with LNR values of 0, 0.3, 0.3–0.7, and >0.7, respectively. We constructed a nomogram comprising the independent factors associated with survival to better predict prognosis. On the basis of these findings, we propose that stage II colon cancer patients without high-risk factors and with both elevated preoperative CEA and CA199 should receive adjuvant therapy. Furthermore, the LNR could complement TNM staging in patients with <12 harvested LNs. Our nomogram might be useful as a new prognosis prediction system for colon cancer patients.

Lymph node ratio is a prospective prognostic indicator for locally advanced gastric cancer patients after neoadjuvant chemotherapy

BackgroundThe accuracy of lymph node ratio (LNR) as a prognostic index remains to be proven for gastric cancer patients after neoadjuvant chemotherapy (NACT). This study sought to investigate the prognostic value of LNR in locally advanced gastric cancer (LAGC) patients after NACT.MethodsLAGC patients with clinical TNM stages 2–3, Her2(−), and Eastern Cooperative Oncology Group, scores 0–2 are routinely scheduled with NACT. Patients with LAGC after NACT and surgical operation between January 2012 and October 2020 were retrospectively reviewed. The correlation between LNR and survival was investigated.ResultsOverall, 148 patients were enrolled: 103 with low-LNR (LNR ≤ 30%) and 45 with high-LNR (LNR > 30%). Approximately, 50.5% and 24.4% patients responded to NACT at the primary site in the low-LNR and high-LNR groups, respectively. The overall survival (OS) and progression-free survival (PFS) of low-LNR group were considerably better than those of high-LNR group (3-year OS: 81.9% vs 18.5%, P < 0.001; 3-year PFS: 72.6% vs 13.5%, P < 0.001). In the low-LNR group, OS and PFS were superior in patients with tumor regression grade (TRG) 0–2 than in those with TRG 3 (3-year OS: 89.2% vs 73.2%, P = 0.086; 3-year PFS: 80.3% vs 66.5%, P = 0.036). In association with OS and PFS, the degree of tumor differentiation, TRG, and LNR were identified as predictive factors, and LNR was identified as the independent prognostic factor in univariate and multivariate analyses, respectively.ConclusionsLNR is a prospective index of prognosis in patients with LAGC after NACT.

Central Lymph Node Ratio Predicts Recurrence in Patients with N1b Papillary Thyroid Carcinoma.

Simple SummaryThe lymph node ratio (LNR) is an emerging predictive marker for recurrence in papillary thyroid carcinoma (PTC). The purpose of this study was to investigate the association between LNR and disease-free survival (DFS) in patients with N1b PTC. Unlike that in the lateral or whole neck, LNR in the central compartment (CLNR) was found to have prognostic significance. The high-CLNR group (CLNR ≥ 0.7) had worse DFS and was 4.5 times more likely to experience recurrence in patients with N1b PTC.The lymph node ratio (LNR) indicates the number of metastatic lymph nodes (LNs) to the total number of LNs. The prognostic value of LNR in papillary thyroid carcinoma (PTC) and other solid tumors is known. This study aimed to investigate the relationship between LNR and disease-free survival (DFS) in patients with PTC with lateral LN metastases (N1b PTC). A total of 307 patients with N1b PTC who underwent total thyroidectomy and therapeutic central and lateral LN dissection were retrospectively analyzed. The DFS and recurrence risk in the patients with LNR, central-compartment LNR (CLNR), and lateral-compartment LNR (LLNR) were compared. The mean follow-up duration was 93.6 ± 19.9 months. Eleven (3.6%) patients experienced recurrence. Neither LNR nor LLNR affected the recurrence rate in our analysis (p = 0.058, p = 0.106, respectively). However, there was a significant difference in the recurrence rates between the patients with low and high CLNR (2.1% vs. 8.8%, p = 0.017). In the multivariate analysis, CLNR ≥ 0.7 and perineural invasion were independent predictors of tumor recurrence. High CLNR was associated with an increased risk of recurrence, and was shown to be a significant predictor of prognosis in patients with N1b PTC.

Prognostic value of lymph node involvement in oral squamous cell carcinoma

ObjectivesDifferent parameters have been identified in patients with oral squamous cell carcinomas (OSCC) that have a serious impact on survival, including residual tumour and extracapsular spread. Moreover, other factors, including the lymph node ratio (LNR) and lymph node yield (LNY), have been suggested as prognostic markers.Material and methodsThis retrospective study included patients diagnosed with OSCC and cervical lymph node metastases during the years 2010–2020. Patients’ records were evaluated regarding lymph node status, final therapy regime, tumour recurrence, time to death, tumour association with death, disease-free survival (DSF), and overall survival (OS).ResultsIn 242 patients with a mean age of 63.57 ± 11.24 years, treated either by selective neck dissection (SND; n = 70) or by modified radical neck dissection (MRND; n = 172), 5772 lymph nodes were detected. The LNR and LNY were identified as independent risk factors in OS and DFS. The optimal cut-off point for the LNY was ≥ 17 lymph nodes in the SND and ≥ 27 lymph nodes in the MRND group.The metastatic lymph node clearance (MLNC) was established as a score to relate the LNR and LNY to the extent of lymph node removal. Survival analysis showed statistically significant differences among score levels.ConclusionsAs information about the extent of nodal dissection is excluded from LNR and LNY, we propose the use of a new scoring system comprising individual cut-off values for LNY and LNR with regard to the extent of neck dissection.Clinical RelevanceMLNC might help to identify high-risk OSCC patients with metastatic lymph nodes.

Prognostic Diagnosis for Breast Cancer Patients Using Probabilistic Bayesian Classification.

The diagnosis and treatment of patients in the healthcare industry are greatly aided by data analytics. Massive amounts of data should be handled using machine learning approaches to provide tools for prediction and categorization to support practitioner decision-making. Based on the kind of tumor, disorders like breast cancer can be categorized. The difficulties associated with evaluating vast amounts of data should be overcome by discovering an efficient method for categorization. Based on the Bayesian method, we analyzed the influence of clinic pathological indicators on the prognosis and survival rate of breast cancer patients and compared the local resection value directly using the lymph node ratio (LNR) and the overall value using the LNR differences in effect between estimates. Logistic regression was used to estimate the overall LNR of patients. After that, a probabilistic Bayesian classifier-based dynamic regression model for prognosis analysis is built to capture the dynamic effect of multiple clinic pathological markers on patient prognosis. The dynamic regression model employing the total estimated value of LNR had the best fitting impact on the data, according to the simulation findings. In comparison to other models, this model has the greatest overall survival forecast accuracy. These prognostic techniques shed light on the nodal survival and status particular to the patient. Additionally, the framework is flexible and may be used with various cancer types and datasets.

Prognostic value of the lymph node ratio in surgically treated stage III colorectal cancer patients with high numbers of harvested lymph nodes

Background The lymph node ratio (LNR), defined as the number of positive lymph nodes (LN) divided by the total number of harvested LN, has been demonstrated to be an independent factor in the prognosis of surgically treated colorectal cancer (CRC) patients. This study aims to establish the prognostic value of LNR in stage III CRC patients with high numbers of LN removed. Methods Stage III CRC patients who underwent curative resections over an 8-year period were included to the study. Demographics, clinicopathological features, surgical as well as recurrence and survival outcomes were recorded and statistically analyzed. Calculations for LNR were carried out as a function of percentage rates and Cox proportional hazards regression analyses were performed to determine its effect on disease-free and overall survival. Results Among a total of 493 surgically treated CRC cases, 104 patients were included to the study consisting of 68 (65.4%) men and 36 (34.6%) women with a median age of 64 (inter-quartile range: 55–74) years. The mean number of harvested LN was 31.6 ± 21.0 (range: 12–103). Multivariate Cox regression analyses proved LNR to be a significant factor in both disease-free and overall survival (p = 0.007 and p = 0.003, respectively). Forward elimination analyses showed that a 1% increase in LNR resulted with a 2% increase in both the risks of recurrence and mortality. Conclusions The LNR may be assessed as an adjunct to the current staging systems for the prediction of oncological outcomes and survival of surgically treated stage III CRC patients.

Optimal value of lymph node ratio and metastatic lymph node size to predict risk of recurrence in pediatric thyroid cancer with lateral neck metastasis

BackgroundNo specific guideline exists for risk stratification based on lymph node (LN) status in pediatric thyroid cancer. The purpose of our study is to identify optimal values of lymph node ratio (LNR) and largest metastatic LN size for predicting recurrent/persistent disease, especially in children with lateral neck metastasis (N1b). MethodsWe conducted a retrospective study from January 1997 to June 2018 at Samsung Medical Center. A total of 50 papillary thyroid carcinoma (PTC) patients who underwent total thyroidectomy + both central neck dissection (CND) + modified radical neck dissection (MRND) (unilateral or bilateral) was enrolled. ResultsThe median follow-up duration was 60.8 months (range, 6.2–247 months). The mean age was 14.6 years, and the mean tumor size was 2.9 cm. Mean size of the largest metastatic LN was 1.5 cm. Mean value of central LNR was 0.6, and mean value of lateral LNR was 0.3. Largest metastatic LN size [HR = 2.0 (95% CI 1.0–4.0), p = 0.040] and lateral LNR [HR = 43.6 (95% CI 2.2–871.0), p = 0.014] were significant prognostic factors for recurrence. The optimal combination of lateral LNR and largest metastatic LN size to predict recurrence were 0.3 and 2.5 cm, respectively, with the largest AUC (AUC at 60 months = 77.4) and significant p-value (p = 0.009 and p = 0.021) (Table 3). Kaplan-Meier curves showed significant differences in recurrence-free survival (RFS) rates among four groups (Fig. 2A,2B). ConclusionsIn pediatric PTC patients with N1b, lateral LNR and largest metastatic LN size are significant predictors for recurrence. Children with lateral LNR > 0.3 or any metastatic lymph node > 2.5 cm in the largest dimension have higher risk for recurrence. Children are classified as extensive N1b if lateral LNR > 0.3 or pathologic N1 with largest LN size > 2.5 cm, and vice versa.

Towards an Improved Pathological Node Classification for Prognostic Stratification of Patients With Oral Cavity Squamous Cell Carcinoma: Results From a Nationwide Registry Study.

BackgroundTo assess the prognostic significance of different nodal parameters [i.e., number of pathologically positive nodes, log odds of positive lymph nodes, lymph node ratio (LNR), and extra-nodal extension (ENE)] in Taiwanese patients with oral cavity squamous cell carcinoma (OCSCC), and to devise an optimized pN classification system for predicting survival in OCSCC.MethodsA total of 4287 Taiwanese patients with first primary OCSCC and nodal metastases were enrolled. Cox proportional hazards regression analysis with the spline method was applied to identify the optimal cut-off values for LNR, log odds of positive lymph nodes, and number of pathologically positive nodes.ResultsOn multivariable analysis, we identified a LNR ≥0.078/0.079, the presence of at least three pathologically positive nodes, and ENE as independent prognosticators for 5-year disease-specific survival (DSS) and overall survival (OS) rates. We therefore devised a four-point prognostic scoring system according to the presence or absence of each variable. The 5-year DSS and OS rates of patients with scores of 0−3 were 70%/62%/50%/36% (p <0.0001) and 61%/52%/40%25%, respectively (p <0.0001). On analyzing the AJCC 2017 pN classification, patients with pN3a displayed better survival rates than those with pN2 disease. The 5-year DSS and OS rates of patients with pN1/pN2/pN3a/pN3b disease were 72%/60%/67%/43% (p <0.0001) and 63%/51%/67%/33%, respectively (p <0.0001).ConclusionsThree nodal parameters (i.e., a LNR ≥0.078/0.079, the presence of at least three pathologically positive nodes, and ENE) assessed in combination provided a better prognostic stratification than the traditional AJCC pN classification.

The Effect of Examined Lymph Nodes and Lymph Node Ratio on Pathological Nodal Classification in the Lung Adenosquamous Carcinoma After Lobectomy.

ObjectiveThe effects of examined lymph nodes (LNs) and lymph node ratio (LNR) on pN classification and the prognosis are unclear in lung adenosquamous carcinoma (ASC) patients. Thus, this study aimed to investigate the significance of LNs and LNR in the prognosis of ASC and the impact of the abovementioned factors on the pN classification.MethodsPatients diagnosed with pathological stage T1-4N0-2M0 ASC from the Surveillance Epidemiology and End Results database were included in the study. The primary clinical endpoint was cancer-specific survival (CSS). The optimal cutoff values of the LNs and LNR were determined. An LN indicator, including pN0 #LNs ≤9, pN0 #LNs >9, pN+ #LNR ≤0.53, and pN+ #LNR > 0.53, was developed. Concordance index (C-index) was used to compare the prognostic predictive ability between N classification and LN indicator. The univariable and multivariable Cox regression analyses were used in this study.ResultsThe cohort of 1,416 patients were included in the study. The level of LNs stratified the patients without metastasis of lymph nodes (pN0 #LNs ≤9 vs. pN0 #LNs >9, unadjusted hazard ratio [HR] = 1.255, P = 0.037). Two groups based on the cutoff value of LNR differentiated prognosis of patients with metastasis of lymph nodes (pN+ #LNR >0.53 vs. pN+ #LNR ≤0.53, unadjusted HR = 1.703, P = 0.001). The LN indicator had a much better predictive ability over N classification in this cohort (LN indicator: C-index = 0.615; N classification: C-index = 0.602, P = 0.001).ConclusionsWe explored clinicopathological factors affecting prognosis in resected lung ASC patients. Besides, the LN indicator was confirmed to be played an essential role in affecting the survival rate in ASC patients. The high-level LNs or low-level LNR might be corelated to improved survival outcomes.

Survival Nomogram for Young Breast Cancer Patients Based on the SEER Database and an External Validation Cohort

BackgroundYoung breast cancer (YBC) patients are more prone to lymph node metastasis than other age groups. Our study aimed to investigate the predictive value of lymph node ratio (LNR) in YBC patients and create a nomogram to predict overall survival (OS), thus helping clinical diagnosis and treatment.MethodsPatients diagnosed with YBC between January 2010 and December 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled and randomly divided into a training set and an internal validation set with a ratio of 7:3. An independent cohort from our hospital was used for external validation. Univariate and least absolute shrinkage and selection operator (LASSO) regression were used to identify the significant factors associated with prognosis, which were used to create a nomogram for predicting 3- and 5-year OS.ResultsWe selected seven survival predictors (tumor grade, T-stage, N-stage, LNR, ER status, PR status, HER2 status) for nomogram construction. The C-indexes in the training set, the internal validation set, and the external validation set were 0.775, 0.778 and 0.817, respectively. The nomogram model was well calibrated, and the time-dependent ROC curves verified the superiority of our model for clinical usefulness. In addition, the nomogram classification could more precisely differentiate risk subgroups and improve the discrimination of YBC prognosis.ConclusionsLNR is a strong predictor of OS in YBC patients. The novel nomogram based on LNR is a reliable tool to predict survival, which may assist clinicians in identifying high-risk patients and devising individual treatments.