Predicting Long-Term Clinical Outcomes in Chinese Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Machine Learning Models for Predicting Long-Term Clinical Outcomes in Chinese Female Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

Status

Active, not recruiting

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT06856616

Enrollment

6000

Registered

2025-03-04

Start date

2025-05-13

Completion date

2026-06-01

Last updated

2025-05-31

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Breast Neoplasms

Brief summary

At present, the majority of studies on neoadjuvant chemotherapy (NAC) in patients with breast cancer (BC) use pathological complete response (pCR) as a surrogate marker for patient prognosis, with significant improvements in pCR indicating better long-term survival. However, there is still a lack of non-invasive tools for accurately predicting the prognosis and pCR of BC patients undergoing NAC. Recent research has introduced emerging artificial intelligence machine learning (ML) and deep learning (DL) algorithms such as Bayesian methods, K-nearest neighbors (KNN), decision trees, support vector machines (SVM), XGBoost, ResNet, convolutional neural networks, and Transformer models, which have brought new avenues of exploration for cancer researchers. The integration of AI with imaging, pathology, genomics, and other multi-omics has non-invasively improved preoperative diagnosis of breast cancer and, when combined with clinical factors, can assess postoperative survival. Moreover, current research data is limited, and reliable predictive models require extensive data for training. Therefore, establishing a multi-center database is essential.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

RETROSPECTIVE

Eligibility

Sex/Gender

FEMALE

Age

18 Years to 80 Years

Healthy volunteers

Inclusion criteria

1. Women with invasive breast cancer who received neoadjuvant chemotherapy (NAC) treatment in various hospitals from 2008 to 2019 (follow-up endpoint December 31, 2024) 2. Women with primary breast cancer (Stage II-III) confirmed by pre-NAC needle biopsy, along with recorded clinical, pathological, and prognostic information 3. With MR images before the first cycle of NAC and before surgery 4. With pathological HE staining images, including biopsy pathology and postoperative major pathology

Exclusion criteria

1. Any form of treatment was received before NAC, including endocrine therapy, radiotherapy, and chemotherapy 2. Disease metastasis occurred during NAC 3. Breast cancer patients with secondary malignancies from other cancers 4. Patients did not complete surgery and were lost to follow-up

Design outcomes

Primary

Measure	Time frame	Description
5-10 year survival rate	2008-2019	5-10 year survival rate of female breast cancer patients treated with neoadjuvant chemotherapy

Countries

China

Outcome results