Lymph Node Ratio (LNR): Predicting Prognosis after Neoadjuvant Chemotherapy (NAC) in Breast Cancer Patients

Optimal Extent of Neck Dissection for a Head and Neck Lymph Node Metastasis from a Remote Primary Site

BACKGROUND

Despite its rarity and limited documentation, therapeutic neck dissection (ND) for cervical lymph node (LN) metastases from distant primary sites is increasingly practiced, potentially enhancing survival rates. However, the optimal ND extent remains unclear. This study aimed to determine the safety of excluding upper neck levels from ND.

METHODS

We retrospectively analyzed 25 patients who underwent ND for cervical LN metastases from remote primary tumors between 2015 and 2021 (12 with primary lung tumors, four with ovary, three with mammary gland, three with esophagus, two with thymus, and one with colon).

RESULTS

Assessing clinical characteristics and occult metastasis rates, we observed LN metastases predominantly at levels III and IV. Occult metastases occurred in 14 out of 25 patients, primarily at neck levels III and IV (55.0% and 50.0%, respectively). The five-year disease-specific survival rate for all patients was 44.3%. While no statistically significant impact of occult metastasis on prognosis was confirmed, an association between the postoperative LN ratio and poor prognosis was revealed.

CONCLUSIONS

Our findings suggest that prophylactic NDs at levels I, II, and Va may not be essential for managing cervical LN metastases from remote primary malignancies. This could lead to a more tailored and less invasive therapeutic strategy.

Lymph Node Ratio Enhances Predictive Value for Treatment Outcomes in Patients with Non-Small Cell Lung Cancer Undergoing Surgery: A Retrospective Cohort Study

Purpose: To compare the prognostic value of lymph node ratio (LNR) and pN in patients with non-small cell lung cancer (NSCLC) undergoing surgery. Materials and methods: NSCLC patients were investigated between 2004 and 2015 from the Surveillance, Epidemiology, and End Results databases. The X-tile software was used to determine LNR cut-off values. Kaplan-Meier analysis was employed to assess cancer-specific survival (CSS) and overall survival (OS). Results: The identified cut-off values of LNR were 0.19 and 0.73. Median CSS for LNR1 (LNR < 0.19), LNR2 (0.19 ≤ LNR ≤ 0.73), and LNR3 (LNR > 0.73) were 71, 41, and 17 months. Both LNR2 (HR = 1.46, 95% CI: 1.36-1.57; P < 0.001) and LNR3 (HR = 2.85, 95% CI: 2.58-3.15; P < 0.001) demonstrated poorer median CSS compared to LNR1. Similarly, median OS for LNR1, LNR2, and LNR3 were 50, 35, and 16 months. LNR2 (HR = 1.36, 95% CI: 1.27-1.45; P < 0.001) and LNR3 (HR = 2.60, 95% CI: 2.37-2.85; P < 0.001) exhibited worse median OS compared to LNR1. A revised pN (r-pN) classification incorporating LNR and pN demonstrated superior penalized goodness-of-fit and discriminative ability in predicting CSS and OS compared to both LNR and pN. Conclusion: LNR outperformed pN in predicting CSS and OS in NSCLC patients undergoing surgery, potentially leading to more precise adjuvant treatment decisions.

The Role of Nodes and Nodal Assessment in Diagnosis, Treatment and Prediction in ER+, Node-Positive Breast Cancer

The majority of breast cancers are oestrogen receptor-positive (ER+). In ER+ cancers, oestrogen acts as a disease driver, so these tumours are likely to be susceptible to endocrine therapy (ET). ET works by blocking the hormone's synthesis or effect. A significant number of patients diagnosed with breast cancer will have the spread of tumour cells into regional lymph nodes either at the time of diagnosis, or as a recurrence some years later. Patients with node-positive disease have a poorer prognosis and can respond less well to ET. The nodal metastases may be genomically similar or, as is becoming more evident, may differ from the primary tumour. However, nodal metastatic disease is often not assessed, and treatment decisions are almost always based on biomarkers evaluated in the primary tumour. This review will summarise the evidence in the field on ER+, node-positive breast cancer, including diagnosis, treatment, prognosis and predictive tools.

Lymph Node Ratio Improves Prediction of Overall Survival in Esophageal Cancer Patients Receiving Neoadjuvant Chemoradiotherapy: A National Cancer Database Analysis

OBJECTIVE

This study aimed to propose a revised ypN (r-ypN) classification based on lymph node ratio (LNR) and to examine its prognostic value in postneoadjuvant esophageal cancer.

BACKGROUND

A new postneoadjuvant pathologic (ypTNM) staging classification has been introduced for esophageal cancer. However, the ypN classification currently defined by the number of positive lymph nodes is influenced by the extent of lymphadenectomy.

METHODS

Data on 7195 esophageal cancer patients receiving neoadjuvant chemoradiation were extracted from the National Cancer Database (NCDB). Four r-ypN stages were defined by 3 LNR thresholds (0%, 10%, and 20% using X-tile software). A revised ypTNM (r-ypTNM) classification was developed by solely changing N categories. Kaplan-Meier method and Cox proportional hazards models were used for survival analyses. Akaike information criterion (AIC) and Harrell's concordance index ( C -index) were used to compare the predictive performance of the current and the revised classification. External validation was performed using an independent cohort from the NEOCRTEC5010 clinical trial.

RESULTS

Both ypN ( P <0.001) and r-ypN ( P <0.001) were independent prognostic factors of overall survival (OS) for esophageal cancer patients. Kaplan-Meier curves demonstrated a better discrimination with r-ypN than ypN categories. Within each ypN category (except ypN3), OS was significantly different comparing r-ypN strata; however, there were no differences between ypN strata within each r-ypN category (except r-ypN3). r-ypN (AIC: 60752 vs 60782; C -index: 0.591 vs 0.587) and r-ypTNM (AIC: 60623 vs 60628; C -index: 0.613 vs 0.610) showed better predictive performance than the current staging system, with a lower AIC (better calibration) and higher C -index (improved discrimination). This advantage was also confirmed by external validation using the NEOCRTEC5010 cohort.

CONCLUSIONS

LNR showed better performance than ypN in predicting OS of esophageal cancer patients after neoadjuvant chemoradiation and may be an improvement on the current staging system.

Predictive Factors for Unnecessary Axillary Dissection According to SLN Metastasis in T1, T2 Stage Breast Cancer

The axillary nodes' status is essential in determining the treatment algorithm according to complete clinical staging. Unnecessary axillary lymph node dissection (ALND) has been prevented after sentinel lymph node biopsy (SLNB) has occurred in current practice. However, approximately half of patients with positive SLNB do not have axillary metastatic lymph nodes. Our study aims to predict unnecessary ALND in patients with SLN metastases by evaluating the patients' clinicopathological data. In total, 221 patients with macrometastasis in SLNB who underwent completion ALND were evaluated retrospectively. Patients were divided into two groups: patients with metastases only in the sentinel lymph node and additional axillary lymph nodes. Univariate and multivariate logistic regression analyses were used to analyze the correlation between SLN metastasis and axillary lymph node metastasis; clinicopathological characteristics, including patient age, menopause status, tumor size and grade, receptor status proliferative marker status, and molecular subtypes of the tumor. In the evaluation of T1-2, cN0 breast cancer patients with SLNB in the form of macrometastasis, only SLNB metastasis was found in 118 (53.4%) patients. In 103 (46.6%) patients, additional axillary node metastasis was observed. The risk of additional nodal spread correlated with patient age older than fertility age (age of 49) (p = 0.015, OR: 1.96, 95% CI: 1.14-3.39) and the number of increased metastatic sentinel nodes (p < 0.001). In line with the data shown by our study, the rate of axillary metastases increases in patients over the age of fertility and as the number of metastatic SLNs increases.

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

BACKGROUND

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.

METHODS

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.

RESULTS

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.

CONCLUSIONS

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.

Lymph node ratio predicts overall survival in patients with stage II non-small cell lung cancer: a population-based SEER analysis

BACKGROUND

In non-small-cell lung cancer (NSCLC), there are many factors that affect prognosis, and the lymph node ratio (LNR) may play a significant role. Our study aimed to confirm the value of the LNR in the prognosis of patients with stage II NSCLC.

METHODS

Patient data were obtained from the Surveillance, Epidemiology and End Results (SEER) database. The classification for the LNR was best determined using the X-tile method. The correlation between the LNR and overall survival (OS) was validated after the Kaplan-Meier analysis was performed. To determine the correlation between the LNR and survival, stratification and the Cox regression analysis were used.

RESULTS

In our study, 14,183 stage II NSCLC patients were included. Among them, 8303 patients had N1 disease. According to the X-tile analysis, the optimal critical points for the LNR in N1 patients with NSCLC was 0.21 and 0.38. We categorized the cohorts as low (LNR-L ≤ 0.21; n = 5158, 62.1%), medium (0.21 < LNR-M ≤ 0.38; n = 1736, 20.9%), and high (LNR-H > 0.38; n = 1409, 17.0%). According to the Kaplan-Meier analysis, the patients with a high LNR were considerably worse than those with a medium or low LNR (P < 0.001), which was also proven by stratified and multivariate analyses. The value of the LNR was reflected in all the subgroup analyses, especially in patients ages < 60 years. The multivariate competing risks regression analysis revealed that younger age, female sex, T1 disease, adenocarcinoma and N0 disease was associated with a better prognosis after controlling for potential confounders (P < 0.001).

CONCLUSIONS

For patients with stage II NSCLC, the LNR is valuable for assessing prognosis. A higher LNR indicates a worse prognosis.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Gini's mean difference and the long-term prognostic value of nodal quanta classes after pre-operative chemotherapy in advanced breast cancer

Gini's mean difference (GMD, mean absolute difference between any two distinct quantities) of the restricted mean survival times (RMSTs, expectation of life at a given time limit) has been proposed as a new metric where higher GMD indicates better prognostic value. GMD is applied to the RMSTs at 25 years time-horizon to evaluate the long-term overall survival of women with breast cancer who received neoadjuvant chemotherapy, comparing a classification based on the number (pN) versus a classification based on the ratio (LNRc) of positive nodes found at axillary surgery. A total of 233 patients treated in 1980-2009 with documented number of positive nodes (npos) and number of nodes examined (ntot) were identified. The numbers were categorized into pN0, npos = 0; pN1, npos = [1,3]; pN2, npos = [4,9]; pN3, npos ≥ 10. The ratios npnx = npos/ntot were categorized into Lnr0, npnx = 0; Lnr1, npnx = (0,0.20]; Lnr2, npnx = (0.20,0.65]; Lnr3, npnx > 0.65. The GMD for pN-classification was 5.5 (standard error: ± 0.9) years, not much improved over a simple node-negative vs. node-positive that showed a GMD of 5.0 (± 1.4) years. The GMD for LNRc-classification was larger, 6.7 (± 0.8) years. Among other conventional metrics, Cox-model LNRc's c-index was 0.668 vs. pN's c = 0.641, indicating commensurate superiority of LNRc-classification. The usability of GMD-RMSTs warrants further investigation.

Nomograms predict survival of patients with lymph node-positive, luminal a breast cancer

Background

To develop nomograms for the prediction of the 1-, 3-, and 5-year overall survival (OS) and breast cancer-specific survival (BCSS) for patients with lymph node positive, luminal A breast cancer.

Methods

Thirty-nine thousand fifty-one patients from The Surveillance, Epidemiology, and End Results (SEER) database were included in our study and were set into a training group (n = 19,526) and a validation group (n = 19,525). Univariate analysis and Cox proportional hazards analysis were used to select variables and set up nomogram models on the basis of the training group. Kaplan-Meier curves and the log-rank test were adopted in the survival analysis and curves plotting. C-index, calibration plots and ROC curves were used to performed internal and external validation on the training group and validation group.

Results

Following independent factors were included in our nomograms: Age, marital status, grade, ethnic group, T stage, positive lymph nodes numbers, Metastasis, surgery, radiotherapy, chemotherapy. In both the training group and testing group, the calibration plots show that the actual and nomogram-predicted survival probabilities are consistent greatly. The C-index values of the nomograms in the training and validation cohorts were 0.782 and 0.806 for OS and 0.783 and 0.804 for BCSS, respectively. The ROC curves show that our nomograms have good discrimination.

Conclusions

The nomograms may assist clinicians predict the 1-, 3-, and 5-year OS and BCSS of patients with lymph node positive, luminal A breast cancer.

Lymph node ratio as best prognostic factor in triple-negative breast cancer patients with residual disease after neoadjuvant chemotherapy

Although lymph node status (ypN) is one of the most important prognostic factors of survival, the lymph node ratio (LNR) has emerged as an equitable factor. We aimed to compare the prognostic value of both ypN and LNR in patients with residual triple-negative breast cancer (TNBC) after neo-adjuvant chemotherapy (NAC). This was a retrospective cohort study of patients treated in a tertiary care center during the period 2000-2014. We stratified the population based on LNR (≤0.20, 0.20-0.65, and >0.65) and ypN (N1, N2, and N3) status. The overall survival (OS) and progression-free survival (PFS) were estimated with Kaplan-Meier curves and the log-rank + test. We further compared patient mortality and disease recurrence using multivariate Cox regression analysis. We evaluated 169 patients with a median follow-up of 87 months. At 2 years of follow-up, patients with low-risk LNR compared to those with moderate and high risk had a higher PFS (54% vs 31% vs 18%, respectively; P < .001) and OS (74% vs 64% vs 45%, respectively; P < .001). Moreover, ypN1 patients compared to ypN2 and ypN3 showed similar results in PFS (53% vs 35% vs 19%, respectively; P = .001) and OS (73% vs 69% vs 43%, respectively; P < .001). Compared to the low-risk population, patients with moderate (hazard ratio [HR]: 3.50; 95% confidence interval [CI]: 1.41-8.71) and high risk (HR: 6.90; 95% CI: 2.29-20.77) had a worse PFS. Regarding OS, moderate-risk (HR: 2.85; 95% CI: 1.10-7.38) and high-risk patients (HR: 6.48; 95% CI: 2.13-19.76) showed considerably worse outcomes. On the other hand, ypN staging was not associated with PFS or OS in the multivariate analysis. The LNR is a better prognostic factor of survival than ypN. The LNR should be considered in the stratification of risk after NAC in patients with TNBC.

[Positive lymph node ratio ≥0.16 is an independent risk factor affecting the prognosis of patients with esophageal cancer]

OBJECTIVE

To investigate the value of positive lymph node ratio (LNR) in predicting the prognosis of patients with esophageal cancer.

METHODS

We retrieved the data of a total of 862 patients with esophageal cancer with complete clinical pathology data archived in SEER database in 2010 to 2015. The best cutoff point of LNR was selected using X-tile software. Univariate and multivariate COX proportional hazard models were used to assess the value of LNR in predicting the prognosis of patients after propensity score matching (PSM).

RESULTS

The best cut-off point of LNR determined using X-tile 3.6.1 software was 0.16. The patients with LNR < 0.16 and those with LNR≥0.16 showed significant differences in the number of positive lymph nodes, pathological type, T stage and M stage. After 1:1 propensity score matching, the two groups showed no significant difference in the clinical data or pathological parameters. Matched univariate and multivariate COX regression analyses showed that LNR, primary tumor site and M staging were all independent risk factors affecting the prognosis of patients, and among them LNR had the most significant predictive value (LNR < 0.16 vs LNR≥0.16: HR=1.827, 95% CI: 1.140-2.929; P=0.000). The median survival time of patients with LNR < 0.16 was 31 months (95%CI: 22.556-39.444 months), as compared with 16 months (95%CI: 12.989-19.011) in patient with LNR≥0.16 (Log Rank χ2=27.392, P < 0.0001). LNR had a better accuracy than N stage for assessing the patients' prognosis with an area under the ROC curve of 0.617 (95%CI: 0.567-0.666), as compared with 0.515 (95%CI: 0.463-0.565) of N stage (z=3.008, P=0.0026).

CONCLUSIONS

LNR≥0.16 is an independent risk factor affecting the prognosis of patients with esophageal cancer and has better prognostic value than N stage.