Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models

Li, Sherly X.; Milne, Roger L.; Nguyen-Dumont, Tú; Wang, Xiaochuan; English, Dallas R.; Giles, Graham G.; Southey, Melissa C.; Antoniou, Antonis C.; Lee, Andrew; Li, Shuai; Winship, Ingrid; Hopper, John L.; Terry, Mary Beth; MacInnis, Robert J.

doi:10.1093/jncics/pkab021

Cited by 22 publications

(26 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We have previously demonstrated a doubling of discriminatory accuracy for IBIS and BOADICEA (C-statistic from 0.56-0.57 to 0.62) with the addition of a polygenic risk score to predictors examined (age, family history, and lifestyle factors) using a subsample of the MCCS [5]. These results were also in line with published data from the UK [18].…”

Section: Discussionsupporting

confidence: 87%

“…4 Type of hormone replacement therapy based on assumption of oestrogen for those who have had a hysterectomy and combined oestrogen and progesterone for those on HRT but have not had a hysterectomy. 5 Women in this category included those that were not asked or those where former use (between follow-up 1 and 2) could not be fully confirmed. 6 Family history in first-or second-degree relatives.…”

Section: Resultsmentioning

confidence: 99%

“…Risk models that incorporate pertinent risk factors that are easily obtained from questionnaires, including a woman's breast cancer family history and lifestyle factors, may provide valuable information for this group of women to optimise early detection and management. Previously, we demonstrated the potential for two models (International Breast Cancer Intervention Study model (IBIS) and the breast and ovarian analysis of disease incidence and carrier estimation algorithm model: BOADICEA) to estimate 10-year risks using an Australian prospective cohort study [5]. Other commonly applied and validated risk models exist (the breast cancer risk assessment tool (BCRAT) [6], individualised coherent absolute risk estimators-literature model (iCARE-lit) [7], and BayesMendel (BRCAPRO and BRCAPRO-BCRAT) [8]), but there is a lack of studies comparing their performance, particularly over longer follow-up durations (>10 years), which is important for individual and population health care planning for conditions that have a long lead time [9].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

Milne

Nguyen-Dumont

et al. 2021

Cancers

Self Cite

View full text Add to dashboard Cite

Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50–65 years and unaffected at commencement of follow-up two (conducted in 2003–2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50–54, 55–59, 60–65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56–0.62) and IBIS (0.57, 95% CI 0.54–0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum.

show abstract

Section: Discussionsupporting

confidence: 87%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

Milne

Nguyen-Dumont

et al. 2021

Cancers

Self Cite

View full text Add to dashboard Cite

show abstract

“…Accordingly, PRSs are predictive of colorectal cancer in the general population but not in the Lynch syndrome [ 35 ]. Further, PRS was not able to have a great impact on discrimination models in some diseases, e.g., breast cancer [ 36 ].…”

Section: Discussionmentioning

confidence: 99%

Applicability of polygenic risk scores in endometriosis clinical presentation

et al. 2022

View full text Add to dashboard Cite

Background Risk prediction is an essential part of preventative medicine and in recent years genomic information has become an interesting factor in risk models. Polygenic risk scores (PRS) combine the effect of many genetic variations into a single score which has been shown to have predictive value for many diseases. This study aimed to investigate the association between PRS for endometriosis and the clinical presentation of the disease. Methods Women with endometriosis (N = 172) were identified at the Department of Gynecology. All participants answered questionnaires regarding sociodemographic factors, lifestyle habits and medical history, registered bowel symptoms on the Visual Analog Scale for Irritable Bowel Syndrome and passed blood samples. DNA was extracted and samples were genotyped, and a PRS was calculated based on previous genome-wide association studies of endometriosis. Inflammatory proteins and TSH receptor antibodies (TRAb) in serum were analyzed. Results Inverse associations were identified between PRS and spread of endometriosis, involvement of the gastrointestinal tract and hormone treatment. However, significance was lost when calculated as p for trend and the specificity and sensitivity were low. There were no correlations between PRS and TRAb or inflammatory proteins. Conclusion The findings indicate that specific PRS should be developed to predict clinical presentations in patient with endometriosis.

show abstract

“…Calibration of unadjusted (age‐and‐sex‐specific) and PRS‐adjusted predicted absolute risks was evaluated by comparing the expected (‘ E ’) with the observed (‘ O ’) numbers of melanoma cases (‘ E/O ’ ratio) for all participants and separately for male and female participants, overall and for each risk quintile (Appendix S1). Robust 95% CIs were used for the MCCS case‐cohort design 22 . Calibration of risk quintiles was further evaluated after rescaling of risks to achieve E/O = 1 overall (separately for male and female participants).…”

Section: Methodsmentioning

confidence: 99%

Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts*

et al. 2022

Self Cite

View full text Add to dashboard Cite

Summary Background Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS‐based risk prediction, particularly assessment of calibration (comparing predicted to observed risks). Objectives To evaluate PRS‐based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry. Methods We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case‐cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single‐nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta‐analysis (PRS68), 50 SNPs significant in the 2020 meta‐analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten‐year melanoma risks were calculated from population‐level cancer registry data by age group and sex, with and without PRS adjustment. Results Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62–0·68] and MCCS (E/O = 0·63, 95% CI 0·56–0·72). For UKB, calibration was improved by PRS adjustment, with PRS50‐adjusted risks E/O = 0·91, 95% CI 0·87–0·95. The discriminative ability for PRS68‐ and PRS50‐adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07–0·10, P < 0·0001), and higher than for PRS45‐adjusted risks (Δ area under the curve 0·02–0·04, P < 0·001). Conclusions A PRS derived from a larger, more diverse meta‐analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.

show abstract

Prospective Evaluation of the Addition of Polygenic Risk Scores to Breast Cancer Risk Models

Cited by 22 publications

References 32 publications

Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models

Applicability of polygenic risk scores in endometriosis clinical presentation

Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts*

Contact Info

Product

Resources

About