The value of positive lymph nodes ratio combined with negative lymph node count in prediction of breast cancer survival

Clinical, Histopathological, and Immunohistochemical Characteristics of Predictive Biomarkers of Breast Cancer: A Retrospective Study

Background/Aim

Breast cancer is a complex disease with variability in clinical manifestation, response to current therapy, and biochemical and histological features among various subgroups. Histologic grading and immuno-histochemical evaluation of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER-2), and Ki-67 proliferation index play a crucial role in increasing the differential diagnostic value among various types of breast carcinoma. The aim of this study was to determine the histopathological and immuno-histochemical characteristics of breast tumors from a University Laboratory of Pathology in Greece.

Patients and Methods

The study included female patients over 18 years of age, whose histopathological and immunohistochemical reports were stored in the archives of the First Department of Pathology of National and Kapodistrian University of Athens. The study involved 197 female patients with a median age of 70 years and median tumor size of 2.6 cm.

Results

Most tumors were located at the left breast and ductal carcinoma was the most common histologic type (35.5%). Most tumors had histologic grade 2 (106, 53.8%), and were classified as TNM stage IIA (65, 33%). Most grade 1 and 2 tumors exhibited high expression of PR, whereas most grade 3 tumors had no PR expression. Moreover, patients with triple-negative cancer presented with grades 2 and 3 at a lower percentage compared to patients without a triple-negative phenotype (p=0.001).

Conclusion

The study provided valuable insights into the histopathological and immuno-histochemical characteristics involved in the development and progression of breast cancer.

Prognostic role of the number of resected and negative lymph nodes in Spanish patients with gastric cancer

INTRODUCTION

Lymph node (LN) involvement is one of the most critical prognostic factors in resected gastric cancer (GC). Some analyses, mainly conducted in Asian populations, have found that patients with a higher number of total lymph nodes (NTLN) and/or negative lymph nodes (NNLN) have a better prognosis, although other authors have failed to confirm these results.

MATERIALS AND METHODS

Retrospective study including all patients with GC resected in a tertiary hospital in Spain between 2001 and 2019 (n = 315). Clinicopathological features were collected and patients were categorized according to the NTLN and the NNLN. Statistical analyses were performed.

RESULTS

Mean NNLN was 17. The NNLN was significantly related to multiple clinicopathological variables, including recurrence and tumor-related death. The classification based on the NNLN (N1: ≥16, N2: 8-15, N3: ≤7) effectively stratified the entire cohort into three distinct prognostic groups and maintained its prognostic value within both the pN0 and pN+ patient subsets. Furthermore, it was an independent prognostic indicator for both overall and disease-free survival. Conversely, the mean NTLN was 21.9. Patients with ≤16 LN retrieved exhibited distinct clinicopathological features compared to those with >16 LN, but no significant differences were observed in terms of recurrence or disease-associated death. The application of alternative cut-off points for NTLN (10, 20, 25, 30, and 40) showed no prognostic significance.

CONCLUSIONS

In Spanish patients with resected GC the NNLN hold prognostic significance, while the NTLN does not appear to be prognostically significant. Incorporating the NNLN into GC staging may enhance the accuracy of the TNM system.

Predicting breast cancer-specific survival in metaplastic breast cancer patients using machine learning algorithms

Metaplastic breast cancer (MpBC) is a rare and aggressive subtype of breast cancer, with data emerging on prognostic factors and survival prediction. This study aimed to develop machine learning models to predict breast cancer-specific survival (BCSS) in MpBC patients, utilizing a dataset of 160 patients with clinical, pathological, and biological variables. An in-depth variable selection process was carried out using gain ratio and correlation-based methods, resulting in 10 variables for model estimation. Five models (decision tree with bagging; logistic regression; multilayer perceptron; naïve Bayes; and, random forest algorithms) were evaluated using 10-fold cross-validation. Despite the constraints posed by the absence of therapeutic information, the random forest model exhibited the highest performance in predicting BCSS, with an ROC area of 0.808. This study emphasizes the potential of machine learning algorithms in predicting prognosis for complex and heterogeneous cancer subtypes using clinical datasets, and their potential to contribute to patient management. Further research that incorporates additional variables, such as treatment response, and more advanced machine learning techniques will likely enhance the predictive power of MpBC prognostic models.

Prognostic Factors and a Model for Occult Breast Cancer: A Population-Based Cohort Study

Occult breast cancer (OBC) is a special type of breast cancer of an unknown primary origin. Early stage OBC is treated as stage II−III breast cancer. Currently, there are no models for predicting the survival outcomes. Hence, we aimed to evaluate the role of the positive lymph node ratio (PLNR) in OBC and further establish and validate a prognostic nomogram. Patients with stage T0N+M0 breast cancer were enrolled from the Surveillance, Epidemiology, and End Results database. Univariate and multivariate Cox analyses were used to evaluate the effects of prognostic factors on breast-cancer-specific survival (BCSS), and a nomogram was established and validated for OBC. Overall, 843 patients were included, and the 5-year BCSS rate was 92.4%. Patients with a PLNR < 0.54 had better BCSS rates than those with a PLNR ≥ 0.54. The nomogram combined clinicopathological parameters, including the PLNR, pN stage, and estrogen receptor status, and showed a higher accuracy than the TNM staging system in predicting the BCSS. The patients could be stratified into different risk groups based on their prognostic scores. Patients in the low-risk subgroup showed an improved BCSS compared those in the high-risk subgroup. In conclusion, the PLNR is an independent prognostic factor for OBC. The PLNR-based nomogram has a better predictive ability than the TNM staging system and could be of great value for the treatment of OBC and prediction of its prognosis.

Prognostic Nomogram for Postoperative Hypopharyngeal Squamous Cell Carcinoma to Assist Decision Making for Adjuvant Chemotherapy

We aimed to investigate the effect of lymph node parameters on postoperative hypopharyngeal squamous cell carcinoma (HSCC) and to establish a nomogram to predict its prognosis and assist in adjuvant chemotherapy decisions. A retrospective analysis of postoperative HSCC in the Surveillance, Epidemiology, and End Results database (2004-2019) was performed. Cutoff points for continuous variables were determined by X-tile software. Univariate and multivariate analyses were performed to identify prognostic factors on overall survival (OS), and these variables were used to construct a nomogram. The nomogram's accuracy was internally validated using concordance index, area under the curve, calibration plot, and decision curve analyses. Furthermore, the value of chemotherapy in each risk subgroup was assessed separately based on individualized scores from the nomogram. In total, 404 patients were eligible for analysis, and the median OS was 39 months. Age, origin, primary site, T stage, number of lymph nodes examined, lymph node ratio, and radiotherapy were identified as prognostic factors for OS and incorporated into the nomogram. In both the training and validation cohorts, favorable performance was exhibited compared with the other stage systems, and patients could be classified into low-, intermediate-, and high-risk subgroups. Chemotherapy significantly improved the OS in the high-risk subgroup, whereas chemotherapy did not confer a survival benefit in the low- or intermediate-risk groups. The lymph node parameter-based nomogram model can better stratify the prognosis of HSCC patients and screen out patients who would benefit from chemotherapy, suggesting that the model could be used as a reference for clinical decision making and to avoid overtreatment.

Breast Cancer Patients With Positive Apical or Infraclavicular/Ipsilateral Supraclavicular Lymph Nodes Should Be Excluded in the Application of the Lymph Node Ratio System

Aim: Increasing studies have demonstrated lymph node ratio (LNR) to be an accurate prognostic indicator in breast cancer and an alternative to pN staging; however, the AJCC-TNM staging system classified apical or infraclavicular/ipsilateral supraclavicular lymph node-positive (APN(+)) patients with a worse prognosis as the pN3 stage. Until now, different reports on LNR in breast cancer have ignored this possibility. Consequently, it is necessary to discuss the role of APN(+) patients in the LNR system to obtain a precise LNR that predicts the prognosis accurately.

Materials and Methods: We collected data on 10,120 breast cancer patients, including 3,936 lymph node-positive patients (3,283 APN(−) and 653 APN(+) patients), who visited our hospital from 2007 to 2012. Then we applied X-tile analysis to calculate cut-off values and conduct survival analysis and multivariate analysis to evaluate patients’ prognosis.

Results: We confirmed that some APN(+) patients were mis-subgrouped according to previously reported LNR, indicating that APN(+) patients should be excluded in the application of LNR to predict prognosis. Then we applied X-tile analysis to calculate two cut-off values (0.15 and 0.34) for LNR-APN(−) patients and conducted survival analysis and found that LNR-APN(−) staging was superior to pN staging in predicting the prognosis of APN(−) breast cancer patients.

Conclusion: From this study, we conclude that excluding APN(+) patients is the most necessary condition for effective implementation of the LNR system. LNR-APN(−) staging could be a more comprehensive approach in predicting prognosis and guiding clinicians to provide accurate and appropriate treatment.

The prognostic value of lymph node ratio in comparison to positive lymph node count in penile squamous cell carcinoma

PURPOSE

Penile cancer is a rare male neoplasm with a wide variation in its global incidence. In this study, the prognostic value of lymph node ratio (LNR) was compared to that of positive lymph node count (PLNC) in penile squamous cell carcinoma.

METHODS

A total of 249 patients with penile squamous cell carcinoma were enrolled from The Surveillance, Epidemiology, and End Results (SEER) database between 2010 and 2015. The X-tile program was used to calculate the optimal cut-off values of LNR and PLNC that discriminate survival. We used the χ2 or the Fisher exact probability test to assess the association between clinical-pathological characteristics and LNR or PLNC. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors for survival. Spearman correlation analysis was used to determine the correlation between LNR and PLNC.

RESULTS

We found that patients with high LNR tended to have advanced N stage, the 7th AJCC stage, and higher pathological grade, while patients with high PLNC had advanced N stage and the 7th AJCC stage. Univariate Cox regression analysis revealed that the N stage, M stage, the 7th AJCC stage, lymph-vascular invasion, LNR, and PLNC were significantly associated with prognosis. Multivariate Cox regression analysis demonstrated that LNR rather than PLNC was an independent prognostic factor for cancer-specific survival. Subgroup analysis of node-positive patients showed that LNR was associated with CSS, while PLNC was not.

CONCLUSION

LNR was a better predictor for long-term prognosis than PLNC in patients with penile squamous cell carcinoma.

Characterizing impact of positive lymph node number in endometrial cancer using machine-learning: A better prognostic indicator than FIGO staging?

BACKGROUND

Number of involved lymph nodes (LNs) is a crucial stratification factor in staging of numerous disease sites, but has not been incorporated for endometrial cancer. We evaluated whether number of involved LNs provide improved prognostic value.

PATIENTS AND METHODS

Patients diagnosed with node-positive endometrial adenocarcinoma without distant metastasis were identified in the National Cancer Database. We trained a machine-learning based model of overall survival. Shapley additive explanation values (SHAP) based on the model were used to identify cutoffs of number of LNs involved. Results were validated using a Cox proportional hazards regression model.

RESULTS

We identified 11,381 patients with endometrial cancer meeting the inclusion criteria. Using the SHAP values, we selected the following thresholds: 1-3 LNs, 4-5 LNs, and 6+ LNs. The 3-year OS was 82.0% for 1-3 LNs, 74.3% for 4-5 LNs (hazard ratio [HR] 1.38; p < 0.001), and 59.9% for 6+ LNs (HR 2.23; p < 0.001). On univariate Cox regression, PA nodal involvement was a significant predictor of OS (HR 1.20; p < 0.001) but was not significant on multivariate analysis when number of LNs was included (HR 1.05; p = 0.273). Additionally, we identified an interaction between adjuvant therapy and number of involved LNs. Patients with 1-3 involved LNs had 3-year OS of 85.2%, 78.7% and 74.2% with chemoradiation (CRT), chemotherapy, and radiation, respectively. Patients with 6+ involved LNs had 3-yr OS of 67.8%, 49.6%, and 48.9% with CRT, chemotherapy, and radiation, respectively (p < 0.001).

CONCLUSION

Number of involved LNs is a stronger prognostic and predictive factor compared to PA node involvement.

Predictive Value of Pretreatment Peripheral Neutrophil-to-Lymphocyte Ratio for Response to Neoadjuvant Chemotherapy and Breast Cancer Prognosis

Background

Neutrophil-to-lymphocyte ratio (NLR) is connected with the response to neoadjuvant chemotherapy (NAC) and prognosis. In addition, residual lymph node burden after NAC is likely important for prognosis. However, most studies have focused on the predictive value of NLR for NAC pathological complete response (pCR) rate. The relationship between NLR and post-operative residual lymph node ratio (LNR), and their prognostic values remain to be determined.

Methods

We retrospectively studied 282 patients with breast cancer who underwent curative surgery after NAC from 2008 to 2018. We collected pretreatment NLR in peripheral blood, the response to NAC, and the amount of axillary lymph nodes (positive and total) from patients who received axillary lymph node dissection (ALND). We followed up all patients from 2 to 116 months, with an average of 63 months. We analyzed the predictive value of pretherapeutic NLR in peripheral blood on the response of NAC, including pCR rate and postoperative LNR. The prognostic value of NLR and LNR was also analyzed.

Results

A pCR was achieved in 20 (27.0%) of 74 patients with low NLR, and 34 (16.3%) of 208 with high NLR (P = 0.045). In luminal A and luminal B tumors, patients with high NLR tended to have elevated LNR (LNR>0.5; P=0.041). In Kaplan–Meier analysis, overall survival of patients with low NLR (NLR < 1.8; P = 0.033) was longer than that of patients with high NLR (NLR ≥ 1.8). Moreover, by multivariable analysis, LNR was negatively correlated with overall survival (P < 0.05) and disease-free survival (DFS) (P < 0.05).

Conclusion

pCR rate, post-operative remaining lymph node involvement and overall survival in all patients who received NAC may be predicted by NLR. Low NLR and LNR may suggest favorable outcomes.

Impact of the extent of negative lymph nodes in gastric adenocarcinoma undergoing primary surgical resection: An institutional report

BACKGROUND

Sub-total/total gastrectomy with lymph node dissection (LND) remains an effective therapeutic strategy for resectable gastric adenocarcinomas (GACs). Despite the prognostic significance of positive lymph nodes (PLNs) defined in N-status, few have appraised the impacts of negative lymph nodes (NLNs) and the percentage of NLN (=number of NLNs/number of total lymph nodes [TLNs], %), as well as the extent of TLNs to be dissected in GACs.

METHODS

We retrospectively analyzed 62 GAC patients (mean age of 67.1 years; 41 men) undergoing primary sub-total/total gastrectomy from a single institute. Candidate variables, including the number of NLNs (≤9 and >9) and the percentage of NLN (≤37.5, 37.5-80.6 and >80.6, %), were evaluated to determine their prognostic impacts and hazard ratios (HRs).

RESULTS

Under the multivariate Cox proportional-hazards regression model, tumor length exceeding 4 cm (p = 0.017; HR = 2.828), perineural invasion (p = 0.037; HR = 3.182), and lower percentage of NLN (p = 0.016 and p = 0.060; HRs = 1.000, 0.327, and 0.333 for subgroups ≤37.5, 37.5-80.6, and >80.6, respectively) were three independent predictors with elevated HRs for poor prognosis. GAC patients with the percentage of NLN > 80.6 were highly related to those with NLNs > 9 (p < 0.001), and GAC patients with NLNs > 9 were highly related to those with TLNs > 15 (p < 0.001). For all 62 GAC or 42 N(+) GAC patients, those who underwent LND with TLNs>15 tended to have more PLNs (p = 0.018, p = 0.003) and more NLNs (p < 0.001, p = 0.029) than did those with TLNs ≤ 15. Among the 42 GAC patients with TLNs > 15, a lower percentage of NLN (p = 0.026 and p = 0.015; HRs = 1.000, 0.272, and 0.180 for subgroups ≤37.5, 37.5-80.6, and >80.6, respectively) remained an independent predictor of poor prognosis.

CONCLUSION

The percentage of NLN could predict the prognosis of GAC patients properly. However, an accurate percentage of NLN needs a minimal requirement of TLNs > 15 to detect an adequate number of PLNs and sufficient number of NLNs.

Negative lymph node count is an independent prognostic factor for female patients with node positive breast cancer

Background

Negative lymph node (NLN) count has been reported to associate with the prognosis of various cancers. This study aims to reveal the prognostic value of NLN count in breast cancer.

Methods

Clinical characteristics of patients were collected from the Surveillance, Epidemiology, and End Results (SEER) database. The X-tile program was used to determine the optimal cutoffs for NLN count. Univariate and multivariate analysis were used to assess the risk factors for breast cancer-specific survival (BCSS).

Results

The X-tile program identified that cutoff value of 2 and 10 could divide the patients into high, middle and low risk subgroups. According to multivariate analysis, patients with NLN count ≤1, over 60 years old, being black, higher tumor grade, higher T or N stage, negative hormone receptor, no radiotherapy or no chemotherapy would more likely suffer poor survival outcome. Subgroup analysis showed that NLN count could still predict survival independently.

Conclusions

NLN count is a potentially effective predictor of breast cancer and is a good supplement for N stage and TNM stage. Combining NLN count with other prognostic factors will be a better predictor for the survival of breast cancer patients.

Predictive value of tumor-infiltrating lymphocytes for response to neoadjuvant chemotherapy and breast cancer prognosis

BACKGROUND

Tumor-infiltrating lymphocytes (TILs) are predictive for the response to neoadjuvant chemotherapy (NAC) of breast cancer. However, little is known about the predictive value of TILs for axillary lymph node involvement after NAC.

METHODS

We analyzed 282 breast cancer patients who were operated following NAC and curative surgery from 2008 to 2018. TILs were assessed in core needle biopsies before NAC, and the biopsies were divided into three groups: low (0%-10% immune cells in stromal tissue within the tumor), intermediate (11%-59%), and high (≥60%). The patients were followed for an average of 63 months (range, 2-116 months). We analyzed retrospectively the predictive value of TILs for the response to NAC, including pathological complete response (pCR) and axillary lymph node involvement (positive lymph node ratio (LNR; the ratio of the number of nodes involved to the total number of nodes dissected)). The prognostic values of TILs and LNR were assessed.

RESULTS

A pCR was achieved in 27 of 188 patients (14.4%) in the low-TIL group, in 14 of 57 patients (24.6%) in the intermediate-TIL group, and in 13 of 37 (35.1%) in the high-TIL group (p = .007). Among patients who underwent axillary lymph node dissection after NAC, patients with high TILs had lower LNR (p = 0021) compared with the other groups. Kaplan-Meier analysis showed that overall survival (OS; p < .001) and disease-free survival (p < .001) were significantly longer for patients with low LNR (≤0.2). TILs were positively correlated with disease-free survival (p = .028), but TILs did not correlate with OS (p = .171). Moreover, by multivariable analysis, LNR independently affected disease-free survival (p < .001).

CONCLUSIONS

TILs may be predictive for pCR rate, postoperative residual lymph node involvement, and disease-free survival of breast cancer patients. High TILs may suggest favorable outcomes.

DNA Methylation and Gene Expression with Clinical Covariates Explain Variation in Aggressiveness and Survival of Pancreatic Cancer Patients

Pancreatic cancer (PC) is associated with a high mortality rate. We explored the interindividual variation of cancer outcomes, attributable to DNA methylation, gene expression, and clinical factors among PC patients. We aim to determine whether we could differentiate subjects with greater nodal involvement, higher cancer staging, and subsequent survival. We modeled every response variable as a function of a linear predictor involving the effects of clinical variables, methylation, and gene expression in a Bayesian framework. Our results highlight the overall importance of wide-spread alterations in methylation and gene expression patterns associated with survival, nodal metastasis, and staging.

The prognostic value of lymph node ratio in survival of non-metastatic breast carcinoma patients

PURPOSE

This study was conducted to assess the correlation between lymph node ratio (LNR) and prognosis of non-metastatic invasive breast carcinoma.

METHOD

This retrospective study examined 455 patients who were diagnosed with non-metastatic, unilateral invasive breast carcinoma and underwent either breast conservative surgery (BCS) or modified radical mastectomy (MRM) with axillary lymph node dissection (ALND) with at least one lymph node identified in the ALND specimen. Receiver operating characteristics (ROC) curve analysis was used to find out predictive cut-off values of the LNR and negative lymph nodes (NLN).

RESULTS

The median follow-up duration was 38 months. The median DFS and OS were 68 months and 72 months, respectively. 25.1% of patients had reported recurrence. The optimal cut-off value of LNR was 0.40. LNR was found to correlate significantly with pathological T (p < 0.001), pathological N (p < 0.001), and NLN (p < 0.001). Univariate analysis of the patients showed that the age group ≤ 35 years, menstrual status, pathological T, nodal status, lymphovascular invasion (LVI), perineural invasion (PNI), tumor grade, estrogen receptor (ER), progesterone receptor (PR), molecular subtypes, LNR, and NLN can affect disease-free survival (DFS) (p < 0.05) and OS (p < 0.05). Multivariate analysis showed that the pathological T (p < 0.001), menstrual status (p = 0.030), and LNR (p < 0.001) were the independent prognostic factors for DFS. Pathological T (p < 0.001) and LNR (p < 0.001) were the independent prognostic factors affecting OS.

CONCLUSION

LNR is the independent prognostic factor of DFS and OS for non-metastatic breast carcinoma.

Frequency and Association Of GSTM1 and GSTT1 Gene Polymorphisms with Survival in Breast Cancer Patients

Objective:

Glutathione S-transferase M1 and T1 (GSTM1 and GSTT1) are the key detoxification enzymes of xenobiotics, including chemotherapeutic drugs. The deletion polymorphisms of GSTM1 and GSTT1 genes are associated with reduced enzyme activity that influenced clinical outcomes of chemotherapeutic agents in breast cancer. However, there is limited information among Thai patients. This research aims to explore the frequency and role of GSTM1 and GSTT1 polymorphisms on survival among Thai patients with breast cancer.

Methods:

The retrospective cohort study was performed. Demographic data and clinicopathology characteristics were collected from hospital base registry data and medical records. A multiplex qualitative real-time PCR method was used to detect the presence or absence of the GSTM1 and GSTT1 gene in the genomic DNA samples of the participants.

Results:

The frequencies of the GSTM1 and GSTT1 null genotypes in 198 breast cancer patients were 65.70% and 33.30%, respectively. The overall survival at 1, 3 and 5 years were 95.00%, 83.00%, 71.00% respectively. The log rank test and Cox proportional hazards revealed a significant different in the 5-years overall survival according to lymph node metastasis and tumor stage (P = 0.014 and P < 0.001). No associations between overall survival and GSTM1 or GSTT1 genotype were found in single or combined genotypes analyses (P = 0.76 and P= 0.15).

Conclusion:

The results of our study provided the epidemiological information for prognostic of survival in breast cancer patients treated with chemotherapy.

Greater negative lymph node count predicts favorable survival of patients with breast cancer in the setting of neoadjuvant chemotherapy and mastectomy

Aim: Adequate lymph node evaluation is recommended in patients with malignant tumors. However, the role of negative lymph nodes (NLNs) remains unclear in breast cancer (BC), especially in patients who have received neoadjuvant chemotherapy and mastectomy. Materials & methods: A total of 435 patients were included in the analysis. On multivariate analysis, NLN count was an independent predictor of 5 year disease-free survival and 5 year overall survival. Results: Patients with NLN count <10 showed significantly worse 5 year disease-free survival than those with NLN count ≥10 (34.8 and 78.2%; p = 0.000); the corresponding 5 year overall survival rates were also significantly different (52.0 and 82.7%; p = 0.000). Conclusion: This is the first study that confirms the relationship between NLN count and prognosis of patients in the setting of neoadjuvant chemotherapy and mastectomy. More NLNs imply better prognosis.

Bayesian Inference of Lymph Node Ratio Estimation and Survival Prognosis for Breast Cancer Patients

OBJECTIVE

We evaluated the prognostic value of lymph node ratio (LNR) for the survival of breast cancer patients using Bayesian inference.

METHODS

Data on 5,279 women with infiltrating duct and lobular carcinoma breast cancer, diagnosed from 2006-2010, was obtained from the NCI SEER Cancer Registry. A prognostic modeling framework was proposed using Bayesian inference to estimate the impact of LNR in breast cancer survival. Based on the proposed model, we then developed a web application for estimating LNR and predicting overall survival.

RESULTS

The final survival model with LNR outperformed the other models considered (C-statistic 0.71). Compared to directly measured LNR, estimated LNR slightly increased the accuracy of the prognostic model. Model diagnostics and predictive performance confirmed the effectiveness of Bayesian modeling and the prognostic value of the LNR in predicting breast cancer survival.

CONCLUSION

The estimated LNR was found to have a significant predictive value for the overall survival of breast cancer patients.

SIGNIFICANCE

We used Bayesian inference to estimate LNR which was then used to predict overall survival. The models were developed from a large population-based cancer registry. We also built a user-friendly web application for individual patient survival prognosis. The diagnostic value of the LNR and the effectiveness of the proposed model were evaluated by comparisons with existing prediction models.

Positive relationship between number of negative lymph nodes and duration of gallbladder cancer cause-specific survival after surgery

Background

Although the prognostic implications of negative lymph nodes (NLNs) has been reported for a variety of tumors, little information has been published about the NLNs in gallbladder cancer (GBC).

Patients and methods

In this study, clinicopathological characteristics and survival times of patients who had undergone surgery for GBC were collected from the Surveillance, Epidemiology, and End Results Program-registered TNM stage database and analyzed. Univariate and multivariate Cox proportional hazards models were used to identify the predictors of survival.

Results

It was found that a cutoff of one to two NLNs is optimal when assessing the association with survival, survival rates being consistently better with two or more NLNs than with fewer than two. This optimal cutoff value of 2 was identified as an independent prognostic factor by univariate and multivariate analyses (all P<0.001). Specifically, patients with two or more NLNs had better 5-year gallbladder cancer cause-specific survival than those with fewer than NLNs examined for stage I/II, stage III/IV, and all TNM stages (all P<0.001).

Conclusion

Our findings indicate that the number of NLNs is an independent prognostic factor after GBC surgery, and, together with the number of positive lymph nodes, this will provide better prognostic information than the number of positive lymph nodes alone.

Negative Lymph Node Count and Lymph Node Ratio Are Associated With Survival in Male Breast Cancer

BACKGROUND

Male breast cancer (MBC) is usually diagnosed at late stages and therefore has a worse prognosis than female breast cancer (FBC). MBC is also more likely to have lymph node (LN) involvement than FBC.

MATERIALS AND METHODS

We sought to determine the prognostic role of the examined lymph node (LN), negative LN (NLN), and positive LN counts and the LN ratio (LNR), defined as (positive LNs/ENLs), on the survival rate among MBC patients. We performed a large population-based study using the data from the Surveillance, Epidemiology, and End Results program.

RESULTS

Older age, black race, stage IV disease, ≤ 1 NLN, and a > 31.3% LNR were significantly associated with worse survival across all prediction models. Moreover, we demonstrated a decreased risk of mortality in MBC patients across the MBC-specific survival model (hazard ratio, 0.98; 95% confidence interval, 0.96-0.998; P = .03) and 10-year MBC-specific survival model (hazard ratio, 0.98; 95% confidence interval, 0.96-0.999; P = .04).

CONCLUSION

MBC has had an augmented incidence over the years. We found several independent predictors of MBC survival, including age, race, stage, NLNs, and the LNR. We strongly suggest adding the NLN count and/or LNR into the current staging system. Further studies are needed to provide information on the mechanisms underlying the association between the NLN count and MBC survival and the LNR and MBC survival.

Clinical significance of tumor necrosis factor receptor 2 in middle and lower thoracic esophageal squamous cell carcinoma

High expression and role of tumor necrosis factor receptor 2 (TNFR2) in cancer progression and prognosis has been reported in several types of tumors. However, its role in esophageal carcinoma (EC) remains unknown. In the present study, TNFR2 expression in middle and lower thoracic esophageal squamous cell carcinoma (ESCC) was detected using immunohistochemistry (IHC). Chi-square test revealed that TNFR2 was positively correlated with invasion depth, advanced clinical stage and low differentiation degree. Furthermore, survival analysis revealed that TNFR2 was positively correlated with poor overall survival (OS). Moreover, univariate COX regression analysis revealed that clinical stage, lymph node involvement, and invasion depth can affect the OS of ESCC patients, while multivariate COX regression analysis revealed that lymph node involvement and invasion depth can affect the OS of ESCC patients. In middle thoracic ESCC patients, TNFR2 was positively correlated with invasion depth, advanced clinical stage and poor OS. Furthermore, univariate and multivariate COX regression analysis both revealed that clinical stage, lymph node involvement, and invasion depth can affect OS. In lower thoracic ESCC patients, TNFR2 was positively correlated with low differentiation degree. Furthermore, the positive correlation of TNFR2 with poor OS did not reach statistical significance. In addition, univariate COX regression analysis revealed that only lymph node involvement could affect OS. All the results suggest that TNFR2 can play an important role in the progression and poor prognosis of ESCC patients. Moreover, the role of TNFR2 in the prognosis of middle thoracic ESCC patients was earlier and stronger than in lower thoracic ESCC patients.

SSH1 expression is associated with gastric cancer progression and predicts a poor prognosis

Background

Slingshot homolog-1 (SSH1) plays an important role in pathological processes, including in the occurrence and development of tumours. The purpose of this study was to determine whether SSH1 is a key biomarker with prognostic value for survival in patients with gastric cancer.

Methods

We performed immunohistochemistry (IHC) on tissue microarrays containing 100 gastric cancer specimens to evaluate SSH1 protein expression. The association of pathological characteristics with cumulative survival was determined by Kaplan-Meier analysis. A Cox proportional hazards model was generated in the multi-factorial survival analysis to identify univariate prognostic factors of GC.

Results

SSH1 expression level in gastric cancer tissues was significantly associated with lymph node metastasis (P = 0.032). Additionally, multivariate regression analysis clearly indicated that SSH1 expression was significantly correlated with poor clinical outcomes of patients with gastric cancer (P = 0.016). Multivariate analyses showed that SSH1 was the best predictor of poor prognosis in patients with gastric cancer (P = 0.030).

Conclusions

SSH1 expression is associated with gastric cancer progression and predicts a poor prognosis. SSH1 may play an important role in the development of gastric cancer, and it is a promising target for prevention and/or treatment of gastric cancer.