Machine learning and cox model-based prediction of CDK4/6 inhibitor outcomes in HR+/HER2 - metastatic breast cancer: a multicenter real-world study.

Liu B, Wu T, Ding S, Liu X, Zeng X, Liu Z, Lu K, She J, Chen J, Tian H, Tong Q, Tang K, Yu J, Wang J, Ding L, Li Y, Peng L, Zhou Q, Zhou H, Chao T, Ouyang Q, Xie N

Open source

DOI
10.1007/s10549-026-08019-y
Published
2026 Jul 31
Container
Breast cancer research and treatment
Publisher
Not recorded
Open access
unknown

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BibTeX

@article{allodium:10.1007/s10549-026-08019-y,
  title = {Machine learning and cox model-based prediction of CDK4/6 inhibitor outcomes in HR+/HER2 - metastatic breast cancer: a multicenter real-world study.},
  author = {Liu B and Wu T and Ding S and Liu X and Zeng X and Liu Z and Lu K and She J and Chen J and Tian H and Tong Q and Tang K and Yu J and Wang J and Ding L and Li Y and Peng L and Zhou Q and Zhou H and Chao T and Ouyang Q and Xie N},
  year = {2026},
  journal = {Breast cancer research and treatment},
  doi = {10.1007/s10549-026-08019-y},
  url = {https://doi.org/10.1007/s10549-026-08019-y}
}

RIS

TY  - JOUR
TI  - Machine learning and cox model-based prediction of CDK4/6 inhibitor outcomes in HR+/HER2 - metastatic breast cancer: a multicenter real-world study.
AU  - Liu B
AU  - Wu T
AU  - Ding S
AU  - Liu X
AU  - Zeng X
AU  - Liu Z
AU  - Lu K
AU  - She J
AU  - Chen J
AU  - Tian H
AU  - Tong Q
AU  - Tang K
AU  - Yu J
AU  - Wang J
AU  - Ding L
AU  - Li Y
AU  - Peng L
AU  - Zhou Q
AU  - Zhou H
AU  - Chao T
AU  - Ouyang Q
AU  - Xie N
PY  - 2026
JO  - Breast cancer research and treatment
DO  - 10.1007/s10549-026-08019-y
UR  - https://doi.org/10.1007/s10549-026-08019-y
ER  - 

APA

B, L., T, W., S, D., X, L., X, Z., Z, L., K, L., J, S., J, C., H, T., Q, T., K, T., J, Y., J, W., L, D., Y, L., L, P., Q, Z., H, Z., T, C., Q, O., & N, X. (2026). Machine learning and cox model-based prediction of CDK4/6 inhibitor outcomes in HR+/HER2 - metastatic breast cancer: a multicenter real-world study.. Breast cancer research and treatment. https://doi.org/10.1007/s10549-026-08019-y

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