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Risk prediction for breast Cancer in Han Chinese women based on a cause-specific Hazard model
Lu Wang1, Liyuan Liu2,3, Zhen Lou4
1Department of Biostatistics, School of Public Health, Shandong University, 44 Wen Hua Xi Road, Jinan, 250012, China.
Insights
A new breast cancer risk prediction model was developed for Han Chinese women, identifying high-risk individuals for targeted prevention. Key factors include fertility history, benign breast disease, and body mass index (BMI).
Area of Science:
- Oncology
- Epidemiology
- Biostatistics
Background:
- Lack of efficient breast cancer prediction models for general population screening in China.
- Need for targeted primary prevention strategies for breast cancer among Han Chinese women.
Purpose of the Study:
- To develop and validate a breast cancer risk prediction model for Han Chinese women.
- To identify high-risk populations for enhanced breast cancer screening and prevention.
Main Methods:
- Utilized a cause-specific competing risk model for model development.
- Employed data from the Shandong Case-Control Study and Taixing Prospective Cohort Study for development and validation.
- Evaluated model calibration and discriminative accuracy using expected/observed (E/O) ratio and C-statistic.
Main Results:
- Identified significant risk factors: number of abortions (RR=6.3), age at first live birth (RR=3.6), history of benign breast disease (RR=4.3), body mass index (BMI) (RR=1.9), family history of breast cancer (RR=3.3), and life satisfaction scores (RR=2.4).
- The developed model demonstrated good calibration (E/O ratio=1.03) and discriminatory accuracy (C-statistic=0.64).
Conclusions:
- A novel risk prediction model for breast cancer was successfully developed for the Han Chinese population.
- The model incorporates fertility status, disease history, and modifiable risk factors.
- The model exhibits satisfactory calibration and discrimination, suitable for clinical application in risk assessment.
Background:
Considering the lack of efficient breast cancer prediction models suitable for general population screening in China. We aimed to develop a risk prediction model to identify high-risk populations, to help with primary prevention of breast cancer among Han Chinese women.
Methods:
A cause-specific competing risk model was used to develop the Han Chinese Breast Cancer Prediction model. Data from the Shandong Case-Control Study (328 cases and 656 controls) and Taixing Prospective Cohort Study (13,176 participants) were used to develop and validate the model. The expected/observed (E/O) ratio and C-statistic were calculated to evaluate calibration and discriminative accuracy of the model, respectively.
Results:
Compared with the reference level, the relative risks (RRs) for highest level of number of abortions, age at first live birth, history of benign breast disease, body mass index (BMI), family history of breast cancer, and life satisfaction scores were 6.3, 3.6, 4.3, 1.9, 3.3, 2.4, respectively. The model showed good calibration and discriminatory accuracy with an E/O ratio of 1.03 and C-statistic of 0.64.
Conclusions:
We developed a risk prediction model including fertility status and relevant disease history, as well as other modifiable risk factors. The model demonstrated good calibration and discrimination ability.
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