Evaluating the prognostic performance of a polygenic risk score for breast cancer risk stratification

被引:5
作者
Olsen, Maria [1 ]
Fischer, Krista [2 ,3 ]
Bossuyt, Patrick M. [1 ]
Goetghebeur, Els [4 ]
机构
[1] Amsterdam Univ Med Ctr, Amsterdam Publ Hlth Res Inst, Dept Clin Epidemiol Biostat & Bioinformat, Meibergdreef 9, NL-1105 AZ Amsterdam, Netherlands
[2] Univ Tartu, Inst Math & Stat, Narva Mnt 18, EE-51009 Tartu, Estonia
[3] Univ Tartu, Estonian Genome Ctr, Inst Genom, Tartu, Estonia
[4] Univ Ghent, Inst Continuing Educ, Dept Appl Math Comp Sci & Stat, Ctr Stat, Campus Sterre,S9,Krijgslaan 281, B-9000 Ghent, Belgium
关键词
Prognostic; Breast cancer; Polygenic risk score; Precision screening; Risk stratification; Medical test evaluation; Biomarker evaluation; Performance measures; GENOME-WIDE ASSOCIATION; POPULATION-BASED SERIES; PREDICTION MODELS; LIMITATIONS; MEDICINE; LOCUS; BRCA1;
D O I
10.1186/s12885-021-08937-8
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Background Polygenic risk scores (PRS) could potentially improve breast cancer screening recommendations. Before a PRS can be considered for implementation, it needs rigorous evaluation, using performance measures that can inform about its future clinical value. Objectives To evaluate the prognostic performance of a regression model with a previously developed, prevalence-based PRS and age as predictors for breast cancer incidence in women from the Estonian biobank (EstBB) cohort; to compare it to the performance of a model including age only. Methods We analyzed data on 30,312 women from the EstBB cohort. They entered the cohort between 2002 and 2011, were between 20 and 89 years, without a history of breast cancer, and with full 5-year follow-up by 2015. We examined PRS and other potential risk factors as possible predictors in Cox regression models for breast cancer incidence. With 10-fold cross-validation we estimated 3- and 5-year breast cancer incidence predicted by age alone and by PRS plus age, fitting models on 90% of the data. Calibration, discrimination, and reclassification were calculated on the left-out folds to express prognostic performance. Results A total of 101 (3.33 parts per thousand) and 185 (6.1 parts per thousand) incident breast cancers were observed within 3 and 5 years, respectively. For women in a defined screening age of 50-62 years, the ratio of observed vs PRS-age modelled 3-year incidence was 0.86 for women in the 75-85% PRS-group, 1.34 for the 85-95% PRS-group, and 1.41 for the top 5% PRS-group. For 5-year incidence, this was respectively 0.94, 1.15, and 1.08. Yet the number of breast cancer events was relatively low in each PRS-subgroup. For all women, the model's AUC was 0.720 (95% CI: 0.675-0.765) for 3-year and 0.704 (95% CI: 0.670-0.737) for 5-year follow-up, respectively, just 0.022 and 0.023 higher than for the model with age alone. Using a 1% risk prediction threshold, the 3-year NRI for the PRS-age model was 0.09, and 0.05 for 5 years. Conclusion The model including PRS had modest incremental performance over one based on age only. A larger, independent study is needed to assess whether and how the PRS can meaningfully contribute to age, for developing more efficient screening strategies.
引用
收藏
页数:11
相关论文
共 46 条
  • [1] [Anonymous], Estonian Genome Center 2001-2011
  • [2] [Anonymous], BREAST CANC INCIDENC
  • [3] [Anonymous], ESTONIA HOUSES BIGGE
  • [4] [Anonymous], 2016, AHRQ PUBLICATION
  • [5] BBMRI.ee, EST BIOB HAS NOW REC
  • [6] Developing and evaluating polygenic risk prediction models for stratified disease prevention
    Chatterjee, Nilanjan
    Shi, Jianxin
    Garcia-Closas, Montserrat
    [J]. NATURE REVIEWS GENETICS, 2016, 17 (07) : 392 - 406
  • [7] Breast cancer risk prediction and individualised screening based on common genetic variation and breast density measurement
    Darabi, Hatef
    Czene, Kamila
    Zhao, Wanting
    Liu, Jianjun
    Hall, Per
    Humphreys, Keith
    [J]. BREAST CANCER RESEARCH, 2012, 14 (01):
  • [8] Single nucleotide polymorphisms and cancer susceptibility
    Deng, Na
    Zhou, Heng
    Fan, Hua
    Yuan, Yuan
    [J]. ONCOTARGET, 2017, 8 (66) : 110635 - 110649
  • [9] The WISDOM Study: breaking the deadlock in the breast cancer screening debate
    Esserman, Laura J.
    [J]. NPJ BREAST CANCER, 2017, 3
  • [10] Estonian Genome Centre, U TART I GEN