BackgroundClinical factors are used to estimate late complication risk in adults after atrial switch operation (AtrSO) for transposition of the great arteries (TGA), but heterogeneity in clinical... Show moreBackgroundClinical factors are used to estimate late complication risk in adults after atrial switch operation (AtrSO) for transposition of the great arteries (TGA), but heterogeneity in clinical course remains. We studied whether common genetic variants are associated with outcome and add value to a clinical risk score in TGA-AtrSO patients.Methods and resultsThis multicenter study followed 133 TGA-AtrSO patients (aged 28 [IQR 24–35] years) for 13 (IQR 9–16) years and examined the association of genome-wide single-nucleotide polymorphisms (SNPs) with a composite endpoint of symptomatic ventricular arrhythmia, heart failure hospitalization, ventricular assist device implantation, heart transplantation, or mortality. Thirty-two patients (24%) reached the endpoint. The genome-wide association study yielded one genome-wide significant (p < 1 × 10−8) locus and 18 suggestive loci (p < 1 × 10−5). A genetic risk score constructed on the basis of independent SNPs with p < 1 × 10−5 was associated with outcome after correction for the clinical risk score (HR = 1.26/point increase [95%CI 1.17–1.35]). Risk stratification improved with a combined risk score (clinical score + genetic score) compared to the clinical score alone (p = 2 × 10−16, C-statistic 0.95 vs 0.85). In 51 patients with a clinical intermediate (5–20%) 5-year risk of events, the combined score reclassified 32 patients to low (<5%) and 5 to high (>20%) risk. Stratified by the combined score, observed 5-year event-free survival was 100%, 79% and 31% for low, intermediate, and high-risk patients, respectively.ConclusionsCommon genetic variants may explain some variation in the clinical course in TGA-AtrSO and improve risk stratification over clinical factors alone, especially in patients at intermediate clinical risk. These findings support the hypothesis that including genetic variants in risk assessment may be beneficial. Show less
Background: Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model ... Show moreBackground: Prediction of contralateral breast cancer (CBC) risk is challenging due to moderate performances of the known risk factors. We aimed to improve our previous risk prediction model (PredictCBC) by updated follow-up and including additional risk factors.Methods: We included data from 207,510 invasive breast cancer patients participating in 23 studies. In total, 8225 CBC events occurred over a median follow-up of 10.2 years. In addition to the previously included risk factors, PredictCBC-2.0 included CHEK2 c.1100delC, a 313 variant polygenic risk score (PRS-313), body mass index (BMI), and parity. Fine and Gray regression was used to fit the model. Calibration and a time-dependent area under the curve (AUC) at 5 and 10 years were assessed to determine the performance of the models. Decision curve analysis was performed to evaluate the net benefit of PredictCBC-2.0 and previous PredictCBC models.Results: The discrimination of PredictCBC-2.0 at 10 years was higher than PredictCBC with an AUC of 0.65 (95% prediction intervals (PI) 0.56-0.74) versus 0.63 (95%Pl 0.54-0.71). PredictCBC-2.0 was well calibrated with an observed/ expected ratio at 10 years of 0.92 (95%Pl 0.34-2.54). Decision curve analysis for contralateral preventive mastectomy (CPM) showed the potential clinical utility of PredictCBC-2.0 between thresholds of 4 and 12% 10-year CBC risk for BRCA1/2 mutation carriers and non-carriers.Conclusions: Additional genetic information beyond BRCA1/2 germline mutations improved CBC risk prediction and might help tailor clinical decision-making toward CPM or alternative preventive strategies. Identifying patients who benefit from CPM, especially in the general breast cancer population, remains challenging. Show less
Due to the increased incidence of breast cancer and improved survival, more women are at risk of developing contralateral breast cancer (CBC). The aim of this thesis was to explore risk factors... Show moreDue to the increased incidence of breast cancer and improved survival, more women are at risk of developing contralateral breast cancer (CBC). The aim of this thesis was to explore risk factors associated with CBC. We observed significant associations for a polygenic risk score of common germline variants (PRS313) and for different adjuvant systemic therapy regimens with (subtype-specific) CBC risk. These factors may be incorporated in CBC risk prediction models together with other known and available risk factors. For support of clinical decision making more biological information is needed to understand CBC development in women with invasive breast cancer and DCIS. As a first step towards implementation of a risk prediction model, we performed an exploratory interview study, which showed that patients had varying preferences for graphical presentation of probabilities in a CBC prediction model. In future studies, the prediction model should be incorporated in a decision support tool and implemented in clinical practice. This tool can then help to better identify women at high risk of CBC who may benefit from prophylactic surgery, while the estimates can also be used to reassure patients who are at low risk of developing CBC. Show less
Lakeman, I.M.M.; Schmidt, M.K.; Asperen, C.J. van; Devilee, P. 2019
Purpose of ReviewBreast cancer is the most common cancer among females in developed countries. Strategies such as early detection by breast cancer screening can reduce the burden of disease but... Show morePurpose of ReviewBreast cancer is the most common cancer among females in developed countries. Strategies such as early detection by breast cancer screening can reduce the burden of disease but have disadvantages including overdiagnosis and increased cost. Stratification of women according to the risk of developing breast cancer, based on genetic and lifestyle risk factors, could improve risk-reduction and screening strategies by targeting those most likely to benefit.Recent FindingsBreast cancer risk is partly determined by genetic factors including rare pathogenic variants in susceptibility genes and common low-risk variants. Other risk factors include alcohol use, smoking, reproductive factors, hormonal factors, family history, mammographic density, BMI, and body height. Ideally, all risk factors are combined into an individual breast cancer lifetime risk score, but this requires knowledge about their interactions as well as accurate effect sizes. A few risk models seem to be sufficiently developed to inform clinical risk management to minimise cancer risk of those at increased risk and avoid overtreatment of those at decreased risk.SummaryIn this review, we briefly summarise the breast cancer susceptibility factors and discuss avenues towards combining all these factors to create individual risk scores. Show less
