Modified lymph node ratio improves the prognostic predictive ability for breast cancer patients compared with other lymph node staging systems

Prediction of axillary lymph node metastasis using tumor volume to breast volume ratio: retrospective cohort study

Background

Tumour size appear to be a risk factor of axillary lymph node metastasis in breast cancer. Recent evidence shows that higher the T staging is associated with higher rate of axillary lymph node metastasis. However, no studies shows that in the same T staging or tumour size but different breast size or breast volume the incidence of axillary lymph node metastasis differ or not .

Objectives

This Study aimed to investigate the association between tumour to breast ratio in breast cancer as a predictive factor of axillary lymph node metastasis.

Methods

This study included 200 consecutive patients diagnosed with breast cancer between January 2012 to march 2022. The authors retrospectively reviewed medical data pathologic report and Ultrasonography and mammography of breast. Tumour diameter reported in pathologic report was used to calculate tumour volume using formula for ellipse. Breast volume was calculate using formula referencing from study of Jack W. Rostas et all by formula Breast Volume=1/3׶×Radius2ccview×Heightccview by measuring from mammography of patient. Tumour volume to breast volume ratio was calculated and analyzed.

Result

Of 200 patient included in this study, 84 patient (42%) was in lymph node positive group and 116 patient (58%) was in lymph node-negative group. Median for tumour and breast volume ratio in node positive group was higher [median 0.0093 (interquartile range=0.0047-0.023)] than in node-negative group [median 0.0065 (interquartile range (0.0028-0.0199)]. P=0.0414 receiver operating characteristic curve for tumour to breast ratio showed AUC of 0.7389 (95% CI 0.67993-0.82335) Which seems to be a significance as predictive factors for Axillary lymph node metastasis.

Conclusion

Higher tumour volume to breast volume ratio tends to be a significance predictive factors for axillary lymph node metastasis in breast cancer patients.

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

OBJECTIVES

To compare the prognostic values of three lymph node staging systems in renal cell carcinoma (RCC), including the number of positive lymph nodes (NPLN), lymph node ratio (LNR) and log odds of positive lymph nodes (LODDS).

DESIGN

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

SETTING AND PARTICIPANTS

1904 patients with pathological N1 RCC, diagnosed from 2004 to 2015 and underwent nephrectomy combined with lymph node dissection, were identified from the SEER database.

PRIMARY OUTCOME MEASURE

The primary outcome of this study was overall survival (OS). Restricted cubic spline functions and multivariable Cox regression analyses were employed to characterise the associations of OS with NPLN, LNR and LODDS, respectively.

RESULTS

Data of 1904 eligible RCC patients were extracted from the SEER database. The mortality risks of RCC patients increased with the increasing of NPLN, LNR and LODDS. NPLN (NPLN3 vs NPLN1, HR 1.22, 95% CI 1.05 to 1.43, p=0.001), LNR (LNR3 vs LNR1, HR 1.46, 95% CI 1.28 to 1.67, p<0.001; LNR2 vs LNR1, HR 1.28, 95% CI 1.09 to 1.50, p=0.002) and LODDS (LODDS3 vs LODDS1, HR 1.48, 95% CI 1.28 to 1.72, p<0.001; LODDS2 vs LODDS1, HR 1.34, 95% CI 1.17 to 1.53, p<0.001) were all independent prognostic factors of OS. The predictive abilities of LNR (Akaike information criterion, AIC: 19576.3, optimism-corrected C-index: 0.677) and LODDS (AIC: 19579.2, optimism-corrected C-index: 0.676) were comparable, superior to NPLN (AIC: 19603.7, optimism-corrected C-index: 0.673). In subgroup analyses, the LODDS classification could better stratify survival of RCC patients, in particular for those with the number of dissected lymph nodes <13 or NPLN≤2.

CONCLUSIONS

NPLN, LNR and LODDS were all independent predictors of OS in RCC. When compared with NPLN and LNR, LODDS had a better performance in survival prediction and risk stratification. The three metrics all had the potential to be integrated into future versions of the American Joint Committee on Cancer staging manual.

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

OBJECTIVE

To study the survival prediction value of lymph node ratio (LNR) and preoperative thyroglobulin (Tg) in the prognosis of thyroid papillary carcinoma (PTC).

METHODS

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.

RESULTS

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.

CONCLUSION

The LNR and preoperative Tg levels, in combination with other independent factors, were effective in predicting the survival prognosis for patients with PTC.

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.

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

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

Metastatic Lymph Node Ratio for Predicting Recurrence in Medullary Thyroid Cancer

Simple Summary

The anatomical staging system for thyroid cancer only contains categories for lymph node compartments. The metastatic lymph node ratio (LNR), which is the ratio of metastasized lymph nodes to the total number of evaluated lymph nodes, is suggested as a quantitative evaluation tool for lymph node metastasis in patients with medullary thyroid cancer in this study. The initial stratification implemented in this study was helpful in predicting structural recurrence, and LNR was identified as a predictor of disease-free survival.

Abstract

The lymph node ratio (LNR) has been investigated as a prognostic factor in many different types of cancers, including differentiated thyroid cancer; however, reports regarding medullary thyroid cancer (MTC) are limited. Therefore, this study aims to evaluate LNR as a risk factor for structural recurrence in patients with MTC. Medical records of patients treated for MTC in a single tertiary center between 1995 and 2017 were retrospectively reviewed. LNR is defined as the number of metastatic lymph nodes or lymph node metastases (LNM) divided by the number of retrieved lymph nodes or lymph node yield (LNY). In the survival analysis, recurrence-free survival was defined as the time from the date of total thyroidectomy to recurrence or last follow-up. To identify risk factors influencing structural recurrence, univariable and multivariable Cox proportional hazard models were used. A total of 132 patients were enrolled. The mean age of study participants was 49.7 years, and 86 patients (65%) were women. Structural recurrence was identified in 39 patients at the end of the study period, and the median follow-up period was 8.7 years. In univariable analyses, gross extra thyroidal extension, N stage, postoperative serum calcitonin and carcinoembryonic antigen (CEA) levels, and LNR were significant (p < 0.05) predictors of structural recurrence. In multivariable analysis, postoperative serum calcitonin, postoperative serum CEA, and LNR were identified as a predictor of disease-free survival (p < 0.05). LNR can potentially predict structural recurrence as a quantitative evaluation tool for lymph node metastasis in patients with MTC.

The role of different lymph node staging systems in predicting prognosis and determining indications for postmastectomy radiotherapy in patients with T1-T2pN1 breast carcinoma

PURPOSE

Based on the risk of locoregional recurrence (LRR), postmastectomy radiotherapy (PMRT) is recommended in T1-T2pN1 breast carcinoma (BC). We aimed to elucidate our institutional strategies underlying selection of these patients for PMRT. In the no-PMRT subset, we compared various lymph node (LN) staging systems' abilities to predict 5‑year overall and locoregional-free survival (OS/LRFS).

METHODS

We retrospectively enrolled 548 women with T1-T2pN1 BC undergoing mastectomy and axillary LN dissection. Depending on PMRT delivery, the participants were divided into the PMRT and no-PMRT groups. Predictors of OS/LRFS were calculated for the no-PMRT group only. Based on Cox regression modelling, the number of positive LNs (PLN), negative LNs (NLN), LN ratio (LNR), log odds of PLN (LODDS), and modified LNR (mLNR) were modelled, each respectively, with OS model covariates (age, grade III, lymphovascular invasion [LVI], tumor size, hormone receptor [HR] status) and LRFS model covariates (age, grade III, LVI). The C‑statistic, Akaike information criterion, and likelihood ratio χ² of the models were compared.

RESULTS

Median follow-up was 60.5 (18-82), 61 (28-82), and 60 (18-80) months for the entire cohort, PMRT, and no-PMRT group, respectively. The PMRT and no-PMRT groups had comparable OS (p = 0.235). LRFS was better (p = 0.030) in the PMRT group comprising 105 subjects (19.16%) who were younger, more likely to have a higher-grade, HR-, HER2+ tumors, more PLNs, fewer NLNs, Ki-67 ≥ 20%, LVI, and extranodal extension (p ≤ 0.001). In the no-PMRT group, LNR-based OS/LRFS models exhibited superior prognostic performance.

CONCLUSION

In early-stage BC patients undergoing mastectomies, LN dissections and no PMRT, we propose LNR-based multivariable models to predict OS/LRFS with superior accuracy.

Nomogram prediction of overall survival based on log odds of positive lymph nodes for patients with penile squamous cell carcinoma

Purpose

This study aimed to establish a nomogram to predict the long‐term overall survival (OS) for patients with penile squamous cell carcinoma (PSCC).

Method

The PSCC patients receiving regional lymph node dissection (RLND) were enrolled from the Surveillance, Epidemiology, and End Results (SEER) database between 2004 and 2015. The dataset of all eligible patients were used to develop the predictive model. The significant independent predictors were identified through Cox regression modeling based on the Bayesian information criterion and then incorporated into a nomogram to predicted 1‐, 3‐, and 5‐year OS. Internal validation was performed using the bootstrap resampling method. The model performance was evaluated using Harrell's concordance index (C‐index), calibration plots, integrated discrimination improvement (IDI), net reclassification improvement (NRI), and decision curve analysis (DCA).

Results

Totally, 384 eligible PSCC patients were enrolled from the SEER database. A nomogram for OS prediction was developed, in which three clinical variables significantly associated with OS were integrated, including age, N classification, and log odds of positive lymph nodes (LODDS). The C‐index of the nomogram (0.746, 95% CI: 0.702‐0.790) was significantly higher than that of the American Joint Committee on Cancer (AJCC) staging system (0.692, 95% CI: 0.646‐0.738, P = .020). The bootstrap optimism‐corrected C‐index for the nomogram was 0.739 (95% CI: 0.690‐0.784). The bias‐corrected calibration plots showed the predicted risks were in good accordance with the actual risks. The results of NRI, IDI, and DCA exhibited superior predictive capability and higher clinical use of the nomogram compared with the AJCC staging system.

Conclusion

We successfully constructed a simple and reliable nomogram for OS prediction among PSCC patients receiving RLND, which would be beneficial to clinical trial design, patient counseling, and therapeutic modality selection.