Neoadjuvant chemotherapy combined with endocrine therapy for hormone receptor-positive breast cancer: A systematic review and meta-analysis

Ma, Hong-Fang; Shen, Jun; Xu, Bin; Shen, Jian-Guo

doi:10.1097/md.0000000000035928

Cited by 1 publication

(1 citation statement)

References 28 publications

(104 reference statements)

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“…Currently, the primary modalities used in breast cancer treatment encompass surgery, targeted therapy, endocrine therapy, chemotherapy, and radiotherapy [ 3 , 4 ]. For patients exhibiting positive estrogen receptor (ER) or progestogen receptor (PR), supplementary endocrine therapy is recommended to manage tumor progression and enhance prognosis [ 5 ]. Moreover, patients with HER-2 overexpression may undergo additional targeted therapy [ 6 ].…”

Section: Introductionmentioning

confidence: 99%

Use of ultrasound imaging Omics in predicting molecular typing and assessing the risk of postoperative recurrence in breast cancer

Song,

Xu,

Wang

et al. 2024

BMC Women's Health

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Background The aim of this study is to assess the efficacy of a multiparametric ultrasound imaging omics model in predicting the risk of postoperative recurrence and molecular typing of breast cancer. Methods A retrospective analysis was conducted on 534 female patients diagnosed with breast cancer through preoperative ultrasonography and pathology, from January 2018 to June 2023 at the Affiliated Cancer Hospital of Xinjiang Medical University. Univariate analysis and multifactorial logistic regression modeling were used to identify independent risk factors associated with clinical characteristics. The PyRadiomics package was used to delineate the region of interest in selected ultrasound images and extract radiomic features. Subsequently, radiomic scores were established through Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM) methods. The predictive performance of the model was assessed using the receiver operating characteristic (ROC) curve, and the area under the curve (AUC) was calculated. Evaluation of diagnostic efficacy and clinical practicability was conducted through calibration curves and decision curves. Results In the training set, the AUC values for the postoperative recurrence risk prediction model were 0.9489, and for the validation set, they were 0.8491. Regarding the molecular typing prediction model, the AUC values in the training set and validation set were 0.93 and 0.92 for the HER-2 overexpression phenotype, 0.94 and 0.74 for the TNBC phenotype, 1.00 and 0.97 for the luminal A phenotype, and 1.00 and 0.89 for the luminal B phenotype, respectively. Based on a comprehensive analysis of calibration and decision curves, it was established that the model exhibits strong predictive performance and clinical practicability. Conclusion The use of multiparametric ultrasound imaging omics proves to be of significant value in predicting both the risk of postoperative recurrence and molecular typing in breast cancer. This non-invasive approach offers crucial guidance for the diagnosis and treatment of the condition.

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Section: Introductionmentioning

confidence: 99%