PURPOSE: Previous oncological studies showed that lymph node ratio (LNR) (ratio of number of lymph nodes that tested positive for metastasis to the total number of lymph nodes examined) is a negative indicator of cancer survival. The American Joint Committee on Cancer (AJCC) staging system incorporates tumor size, lymph node involvement, and metastasis in a comprehensive model of cancer progression, but LNR alone has been shown to outperform the AJCC system in prognostic and survival predictions for various types of cancer. The effectiveness of LNR has not been evaluated in breast cancer staging. Evaluating LNR for predicting cancer staging in breast cancer has the potential to improve treatment recommendations. METHODS: The Surveillance, Epidemiology, and End Results dataset was used to identify 10,655 breast cancer patients who underwent nodal evaluation from 2010 to 2013, and their LNRs were calculated. Descriptive statistics of lymph node evaluation in the patients are provided. Logistic regression with LNR as the continuous independent variable was conducted to determine whether LNR could predict cancer progression, coded as regional or distant. Analysis was conducted using SPSS version 24. RESULTS: Patient's mean age was 59.43±18.62. Logistic regression analysis revealed that for every 1.3% increase in LNR, the odds of falling into the distant stage of the TNM staging system increased by 13.7% (odds ratio, 14.73; 95% confidence interval, 12.00–18.08). CONCLUSION: LNR, while correlated with breast cancer staging, serves as a better predictor of survival. Precision staging can influence treatment modality, and improved treatments can significantly improve quality of life. Additional research and diagnostic examinations using LNR as a potential tool for accurate staging in breast cancer patients are warranted.
Falling ; Breast Neoplasms* ; Breast* ; Dataset ; Epidemiology ; Humans ; Logistic Models ; Lymph Nodes* ; Neoplasm Staging ; Quality of Life

In this study,DNA molecular identification technology and chemical fingerprint method were adopted to evaluate the quality system of precise powder decoction pieces (PPDP) of S.suberectus dunn (SSD).ITS2 sequence was taken as DNA barcode to indentify SSD.Different specifications of PPDP were prepared,their dry extract contents were quantified in contrast with that of original slices.Three batches of SSD original slices were gleaned and the content uniformity,fingerprint and similarity evaluation before and after the mixing and pulverization were valued by HPLC-DAD.As a result,ITS2 successfully and accurately identified the SSD in this study.The extract rate of PPDP was 15.5％,1.11 times as much as the original slices.RSD of inter-assay dissolution of cepicatechin from the original slices was 11.0％,which was reduced to 1.0％ after mixing and preparing into PPDP.The relative peak area of the 14 common peaks identified by fingerpringts were larger,while the RSD values significantly decreased.It was concluded that the PPDP of SSD improved the extraction efficiency and uniformity of the original slices,featuring quite prospective in more reasonable and scientific clinical use.