scholarly journals A Risk Factor Analysis of Axillary Web Syndrome in Patients After Breast Cancer Surgery: A Single Center Study in Korea

2021 ◽  
Vol 45 (5) ◽  
pp. 401-409
Author(s):  
Sangah Jeong ◽  
Byung Joo Song ◽  
Jiyoung Rhu ◽  
Cheolki Kim ◽  
Sun Im ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Underlying Disease ◽  
Disease Type ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Univariable Analysis ◽  
Axillary Web Syndrome ◽  
Single Center Study ◽  
Type Of Surgery

Objective To investigate the prevalence and risk factors of axillary web syndrome (AWS) in Korean patients.Methods This retrospective study included a total of 189 women who underwent breast cancer surgery and received physical therapy between September 2019 and August 2020. We analyzed AWS and the correlation between the patients’ demographics, underlying disease, type of surgery and chemotherapy or radiation therapy, and lymphedema.Results The prevalence of AWS was found to be 30.6%. In the univariable analysis, age, chemotherapy, and hypertension were related to AWS. Finally, the multivariable logistic regression revealed that chemotherapy (odds ratio [OR]=2.84; 95% confidence interval [CI], 1.46–5.53) and HTN (OR=2.72; 95% CI, 1.18–6.30) were the strongest risk factors of AWS.Conclusion To the best of our knowledge, this was the first study that explored the risk factors of AWS in a Korean population after breast cancer surgery. As almost one-third of patients suffer from AWS after breast cancer surgery, it is essential to closely monitor the development of AWS in patients with hypertension or undergoing chemotherapy.

Incidence and risk factors for axillary web syndrome after breast cancer surgery

2011 ◽  
Vol 131 (3) ◽  
pp. 987-992 ◽  
Author(s):  
Anke Bergmann ◽  
Valéria Vasconcellos Mendes ◽  
Ricardo de Almeida Dias ◽  
Blenda do Amaral e Silva ◽  
Maria Giseli da Costa Leite Ferreira ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Axillary Web Syndrome

scholarly journals Risk Factors for Chronic Pain Following Breast Cancer Surgery: A Prospective Study

2006 ◽  
Vol 7 (9) ◽  
pp. 626-634 ◽  
Author(s):  
Ellen L. Poleshuck ◽  
Jennifer Katz ◽  
Carl H. Andrus ◽  
Laura A. Hogan ◽  
Beth F. Jung ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Chronic Pain ◽  
Prospective Study ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
A Prospective Study

scholarly journals The incidence and risk factors of frozen shoulder in patients with breast cancer surgery

2019 ◽  
Vol 26 (4) ◽  
pp. 825-828 ◽  
Author(s):  
Chul‐Hyun Cho ◽  
Kyoung‐Lak Lee ◽  
Jihyoung Cho ◽  
Duhan Kim
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Frozen Shoulder ◽  
Cancer Surgery ◽  
Breast Cancer Surgery

scholarly journals Development of a screening instrument for risk factors of persistent pain after breast cancer surgery

2012 ◽  
Vol 107 (9) ◽  
pp. 1459-1466 ◽  
Author(s):  
R Sipilä ◽  
A-M Estlander ◽  
T Tasmuth ◽  
M Kataja ◽  
E Kalso
Keyword(s):  
Breast Cancer ◽  
Risk Factors ◽  
Screening Instrument ◽  
Persistent Pain ◽  
Cancer Surgery ◽  
Breast Cancer Surgery

scholarly journals Breast Cancer Surgery 10-Year Survival Prediction by Machine Learning: A Large Prospective Cohort Study

Biology ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 47
Author(s):  
Shi-Jer Lou ◽  
Ming-Feng Hou ◽  
Hong-Tai Chang ◽  
Hao-Hsien Lee ◽  
Chong-Chi Chiu ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Machine Learning ◽  
Risk Factors ◽  
Summary Score ◽  
Cancer Surgery ◽  
Machine Learning Algorithms ◽  
Breast Cancer Surgery ◽  
Support Vector ◽  
Survival Prediction ◽  
Sf 36

Machine learning algorithms have proven to be effective for predicting survival after surgery, but their use for predicting 10-year survival after breast cancer surgery has not yet been discussed. This study compares the accuracy of predicting 10-year survival after breast cancer surgery in the following five models: a deep neural network (DNN), K nearest neighbor (KNN), support vector machine (SVM), naive Bayes classifier (NBC) and Cox regression (COX), and to optimize the weighting of significant predictors. The subjects recruited for this study were breast cancer patients who had received breast cancer surgery (ICD-9 cm 174–174.9) at one of three southern Taiwan medical centers during the 3-year period from June 2007, to June 2010. The registry data for the patients were randomly allocated to three datasets, one for training (n = 824), one for testing (n = 177), and one for validation (n = 177). Prediction performance comparisons revealed that all performance indices for the DNN model were significantly (p < 0.001) higher than in the other forecasting models. Notably, the best predictor of 10-year survival after breast cancer surgery was the preoperative Physical Component Summary score on the SF-36. The next best predictors were the preoperative Mental Component Summary score on the SF-36, postoperative recurrence, and tumor stage. The deep-learning DNN model is the most clinically useful method to predict and to identify risk factors for 10-year survival after breast cancer surgery. Future research should explore designs for two-level or multi-level models that provide information on the contextual effects of the risk factors on breast cancer survival.

Value of Ultrasound for Postoperative Surveillance of Asian Patients with History of Breast Cancer Surgery: A Single-Center Study

2013 ◽  
Vol 20 (11) ◽  
pp. 3461-3468 ◽  
Author(s):  
Young Joo Suh ◽  
Min Jung Kim ◽  
Eun-Kyung Kim ◽  
Hee Jung Moon ◽  
Seung-Il Kim ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Single Center ◽  
Postoperative Surveillance ◽  
Asian Patients ◽  
Single Center Study ◽  
History Of ◽  
Center Study

Postoperative oxycodone in breast cancer surgery: What factors associate with analgesic plasma concentrations?

2016 ◽  
Vol 12 (1) ◽  
pp. 118-119
Author(s):  
Kristiina Cajanus ◽  
Mikko Neuvonen ◽  
Mari Kaunisto ◽  
Outi Koskela ◽  
Pertti J. Neuvonen ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Postoperative Pain ◽  
Pain Intensity ◽  
Demographic Data ◽  
Geometric Mean ◽  
Plasma Concentrations ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Satisfactory Analgesia ◽  
Type Of Surgery

AbstractAimsParenteral oxycodone is increasingly used worldwide to manage perioperative pain. Oxycodone doses required for adequate analgesia vary significantly between individuals. Our study investigated whether an analgesic plasma concentration could be determined for oxycodone and which factors affect it.Methods1000 women undergoing breast cancer surgery were recruited to the study. Demographic data were collected and their cold and heat pain sensitivity and anxiety scores were measured preoperatively. After surgery, rest and motion pain intensities were measured. Intravenous oxycodone was administered until the patients reported satisfactory pain relief (NRS <4/10). At this point, plasma concentrations of oxycodone and its metabolites were determined. A second plasma sample for oxycodone deter-mination was taken when the patient requested a new dose of oxycodone. Genomic DNA was extracted from whole blood samples and the patients were genotyped for CYP2D6, CYP3A4 and CYP3A5 variants.ResultsThe two oxycodone concentrations showed a strong correlation (r =0.84). The pain intensity measured during motion before oxycodone dosing correlated significantly with the plasma oxycodone concentration (geometric mean 35.3 ng/ml and CV % 66.4) required to achieve satisfactory analgesia (r = 0.38, p = 1.5 x 10-33). The most important factors associating with postoperative pain intensity were type of surgery (breast conserving or mastectomy with or without axillary clearance) and the age of the patient. Older patients reported lower pain scores and required smaller oxycodone concentrations for satisfactory analgesia. CYP2D6, CYP3A5 or CYP3A4 genotypes did not significantly affect the oxycodone concentrations, but CYP2D6 genotype significantly affected the formation of the metabolites oxymorphone and noroxymorphone. CYP3A4 and CYP3A5 genotypes did not affect the metabolite formation.ConclusionsOur results indicate that the more pain the patient experiences postoperatively the greater her minimum plasma oxycodone concentration must be to achieve satisfactory analgesia. Type of surgery and age significantly affect postoperative pain intensity.

scholarly journals Blurred lines between axillary web syndrome and Mondor's disease after breast cancer surgery: A case report

2020 ◽  
Vol 63 (4) ◽  
pp. 365-367 ◽  
Author(s):  
Alessandro de Sire ◽  
Marco Invernizzi ◽  
Lorenzo Lippi ◽  
Carlo Cisari ◽  
Levent Özçakar ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Case Report ◽  
Cancer Surgery ◽  
Breast Cancer Surgery ◽  
Axillary Web Syndrome ◽  
Mondor’S Disease ◽  
Mondor's Disease
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