Abstract
Background
Breast cancer patients with brain metastasis (BM) have a poor prognosis. This study aims to identify the risk factors of BM in patients with metastatic breast cancer (MBC) and establish a competing risk model for predicting the risk of brain metastases at different time points along the course of disease.
Methods
Patients with MBC admitted to the breast disease center of Peking University First Hospital from 2008 to 2019 were selected and retrospectively analyzed to establish a risk prediction model for brain metastases. Patients with MBC admitted to eight breast disease centers from 2015 to 2017 were selected for external validation of the competing risk model. The competing risk approach was used to estimate cumulative incidence. Univariate Fine-Gray competing risk regression, optimal subset regression, and LASSO Cox regression were used to screen potential predictors of brain metastases. Based on the results, a competing risk model for predicting brain metastases was established. The discrimination of the model was evaluated using AUC, Brier score, and C-index. The calibration was evaluated by the calibration curves. The model was assessed for clinical utility by decision curve analysis (DCA), as well as by comparing the cumulative incidence of brain metastases between groups with different predicted risks.
Results
From 2008 to 2019, a total of 327 patients with MBC in the breast disease center of Peking University First Hospital were admitted into the training set for this study. Among them, 74 (22.6%) patients developed brain metastases. From 2015 to 2017, a total of 160 patients with MBC in eight breast disease centers were admitted into the validation set for this study. Among them, 26 (16.3%) patients developed brain metastases. BMI, age, histological type, breast cancer subtype, and extracranial metastasis pattern were included in the final competing risk model for BM. The C-index of the prediction model in the validation set was 0.695, and the AUCs for predicting the risk of brain metastases within 1, 3, and 5 years were 0.674, 0.670, and 0.729, respectively. Time-dependent DCA curves demonstrated a net benefit of the prediction model with thresholds of 9–26% and 13–40% when predicting the risk of brain metastases at 1 and 3 years, respectively. Significant differences were observed in the cumulative incidence of brain metastases between groups with different predicted risks (P < 0.05 by Gray’s test).
Conclusions
In this study, a competing risk model for BM was innovatively established, with the multicenter data being used as an independent external validation set to confirm the predictive efficiency and universality of the model. The C-index, calibration curves, and DCA of the prediction model indicated good discrimination, calibration, and clinical utility, respectively. Considering the high risk of death in patients with metastatic breast cancer, the competing risk model of this study is more accurate in predicting the risk of brain metastases compared with the traditional Logistic and Cox regression models.
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Data availability
The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.
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Funding
This study was supported by National Key R&D Program of China (2016YFC0901302) and Interdisciplinary Clinical Research Project of Peking University First Hospital (2019CR38).
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All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by QW and M-SS. The first draft of the manuscript was written by QW and M-SS, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.
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The authors have no relevant financial or non-financial interests to disclose.
Ethical approval
This study was performed in line with the principles of the Declaration of Helsinki. The ethical approval of this retrospective study was divided into two parts. First, for patients from the Breast Disease Center of Peking University First Hospital, this study was approved by the Ethics Review Committee of Peking University First Hospital (No.2021-283), and informed consent was obtained by telephone during the follow-up. For patients collected from the Breast Cancer Multicenter Clinical Cohort (2016YFC0901302), the study was approved by each participating institution's ethics review committee. Given the retrospective and anonymous nature of the study, additional informed consent specific to this study was not required.
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Wu, Q., Sun, MS., Liu, YH. et al. Development and external validation of a prediction model for brain metastases in patients with metastatic breast cancer. J Cancer Res Clin Oncol 149, 12333–12353 (2023). https://doi.org/10.1007/s00432-023-05125-y
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DOI: https://doi.org/10.1007/s00432-023-05125-y