Background and Aims:Breast-conserving surgery,which balances tumor excision with preservation of breast tissue,has become a widely adopted surgical approach for breast cancer.However,postoperative tumor recurrence remains a major factor affecting patient prognosis.Accurate risk prediction tools are urgently needed to guide personalized treatment strategies.This study aimed to develop a risk prediction model for tumor recurrence after BCS based on admission clinical data and to evaluate its predictive performance to provide a scientific and practical tool for clinical decision-making.Methods:A total of 224 breast cancer patients who underwent breast-conserving surgery between May 2017 and May 2019 were enrolled.Postoperative recurrence was recorded during follow-up.Multivariate Logistic regression analysis was used to identify independent risk factors for recurrence and to construct a risk prediction model.The model's discriminative ability was assessed using the receiver operating characteristic(ROC)curve,and its calibration was evaluated using a calibration curve.Results:208 patients completed follow-up,ranging from 32 to 84 months,with a mean duration of(58.41±7.33)months.The recurrence rate was 17.79%.Multivariate Logistic regression analysis revealed that TNM stage Ⅲ(OR=2.029),tumor diameter≥4 cm(OR=1.782),≥4 lymph node metastases(OR=1.958),lymphovascular invasion(OR=1.984),and HER2 positivity(OR=1.774)were independent risk factors for recurrence(all P<0.05).The Logistic regression model was established as follows:Y=-12.788+0.707X?+0.578X?+0.672X?+0.685X?+0.573X?.The model yielded an area under the ROC curve(AUC)of 0.934(95%CI=0.891-0.963),with a sensitivity of 86.49%and specificity of 96.49%.The calibration curve demonstrated good agreement between predicted and observed outcomes(χ2=0.501,P=0.392).Conclusion:TNM stage Ⅲ,tumor diameter≥4 cm,≥4 lymph node metastases,lymphovascular invasion,and HER2 positivity are independent risk factors for tumor recurrence after breast-conserving surgery.The risk prediction model based on these factors demonstrates favorable discrimination and calibration,offering valuable guidance for postoperative risk assessment and clinical intervention.

Background and Aims:Breast-conserving surgery,which balances tumor excision with preservation of breast tissue,has become a widely adopted surgical approach for breast cancer.However,postoperative tumor recurrence remains a major factor affecting patient prognosis.Accurate risk prediction tools are urgently needed to guide personalized treatment strategies.This study aimed to develop a risk prediction model for tumor recurrence after BCS based on admission clinical data and to evaluate its predictive performance to provide a scientific and practical tool for clinical decision-making.Methods:A total of 224 breast cancer patients who underwent breast-conserving surgery between May 2017 and May 2019 were enrolled.Postoperative recurrence was recorded during follow-up.Multivariate Logistic regression analysis was used to identify independent risk factors for recurrence and to construct a risk prediction model.The model's discriminative ability was assessed using the receiver operating characteristic(ROC)curve,and its calibration was evaluated using a calibration curve.Results:208 patients completed follow-up,ranging from 32 to 84 months,with a mean duration of(58.41±7.33)months.The recurrence rate was 17.79%.Multivariate Logistic regression analysis revealed that TNM stage Ⅲ(OR=2.029),tumor diameter≥4 cm(OR=1.782),≥4 lymph node metastases(OR=1.958),lymphovascular invasion(OR=1.984),and HER2 positivity(OR=1.774)were independent risk factors for recurrence(all P<0.05).The Logistic regression model was established as follows:Y=-12.788+0.707X?+0.578X?+0.672X?+0.685X?+0.573X?.The model yielded an area under the ROC curve(AUC)of 0.934(95%CI=0.891-0.963),with a sensitivity of 86.49%and specificity of 96.49%.The calibration curve demonstrated good agreement between predicted and observed outcomes(χ2=0.501,P=0.392).Conclusion:TNM stage Ⅲ,tumor diameter≥4 cm,≥4 lymph node metastases,lymphovascular invasion,and HER2 positivity are independent risk factors for tumor recurrence after breast-conserving surgery.The risk prediction model based on these factors demonstrates favorable discrimination and calibration,offering valuable guidance for postoperative risk assessment and clinical intervention.

Cardiovascular disease is a severe threat to human health and life. Among many risk factors of cardiovascular disease, genetic or gene-based ones are drawing more and more attention in recent years. Accumulated evidence has demonstrated that the loss or mutation of ataxia telangiectasia mutated (ATM) gene can result in DNA damage repair dysfunctions, telomere shortening, decreased antioxidant capacity, insulin resistance, increased lipid levels, etc., and thus can promote the occurrence of cardiovascular risk factors, such as aging, atherosclerosis and metabolic syndrome. In this review, we discusses the possible mechanisms between ATM gene and cardiovascular risk factors, which could be helpful to the related research and clinical application.
Aging ; Ataxia Telangiectasia Mutated Proteins ; genetics ; Cardiovascular Diseases ; genetics ; DNA Damage ; DNA Repair ; Humans ; Mutation ; Risk Factors