Development and external validation of a breast cancer absolute risk prediction model in Chinese population,Breast Cancer Research

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Development and external validation of a breast cancer absolute risk prediction model in Chinese population
Breast Cancer Research ( IF 6.1 ) Pub Date : 2021-05-29 , DOI: 10.1186/s13058-021-01439-2
Yuting Han ₁ , Jun Lv _{1,

2,

3} , Canqing Yu ₁ , Yu Guo ₄ , Zheng Bian ₄ , Yizhen Hu ₁ , Ling Yang _{5,

6} , Yiping Chen _{5,

6} , Huaidong Du _{5,

6} , Fangyuan Zhao ₇ , Wanqing Wen ₈ , Xiao-Ou Shu ₈ , Yongbing Xiang ₉ , Yu-Tang Gao ₉ , Wei Zheng ₈ , Hong Guo ₁₀ , Peng Liang ₁₁ , Junshi Chen ₁₂ , Zhengming Chen ₆ , Dezheng Huo ₇ , Liming Li ₁ ,

Affiliation

Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, 38 Xueyuan Road, Beijing, 100191, China.
Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, China.
Peking University Institute of Environmental Medicine, Beijing, China.
Chinese Academy of Medical Sciences, Beijing, China.
Medical Research Council Population Health Research Unit at the University of Oxford, Oxford, UK.
Clinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Department of Public Health Sciences, The University of Chicago, 5841 S. Maryland Ave., MC2000, Chicago, IL, 60637, USA.
Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA.
State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Medical department, Liuyang Hospital of Traditional Chinese Medicine, Liuyang, China.
People's Hospital of Liuyang, Liuyang, China.
China National Center for Food Safety Risk Assessment, Beijing, China.

In contrast to developed countries, breast cancer in China is characterized by a rapidly escalating incidence rate in the past two decades, lower survival rate, and vast geographic variation. However, there is no validated risk prediction model in China to aid early detection yet. A large nationwide prospective cohort, China Kadoorie Biobank (CKB), was used to evaluate relative and attributable risks of invasive breast cancer. A total of 300,824 women free of any prior cancer were recruited during 2004–2008 and followed up to Dec 31, 2016. Cox models were used to identify breast cancer risk factors and build a relative risk model. Absolute risks were calculated by incorporating national age- and residence-specific breast cancer incidence and non-breast cancer mortality rates. We used an independent large prospective cohort, Shanghai Women’s Health Study (SWHS), with 73,203 women to externally validate the calibration and discriminating accuracy. During a median of 10.2 years of follow-up in the CKB, 2287 cases were observed. The final model included age, residence area, education, BMI, height, family history of overall cancer, parity, and age at menarche. The model was well-calibrated in both the CKB and the SWHS, yielding expected/observed (E/O) ratios of 1.01 (95% confidence interval (CI), 0.94–1.09) and 0.94 (95% CI, 0.89–0.99), respectively. After eliminating the effect of age and residence, the model maintained moderate but comparable discriminating accuracy compared with those of some previous externally validated models. The adjusted areas under the receiver operating curve (AUC) were 0.634 (95% CI, 0.608–0.661) and 0.585 (95% CI, 0.564–0.605) in the CKB and the SWHS, respectively. Based only on non-laboratory predictors, our model has a good calibration and moderate discriminating capacity. The model may serve as a useful tool to raise individuals’ awareness and aid risk-stratified screening and prevention strategies.

更新日期：2021-05-30

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