| 1. |
- Spjuth, Ola, 1977-, et al.
(författare)
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E-Science technologies in a workflow for personalized medicine using cancer screening as a case study
- 2017
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Ingår i: JAMIA Journal of the American Medical Informatics Association. - : Oxford University Press. - 1067-5027 .- 1527-974X. ; 24:5, s. 950-957
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Tidskriftsartikel (refereegranskat)abstract
- Objective: We provide an e-Science perspective on the workflow from risk factor discovery and classification of disease to evaluation of personalized intervention programs. As case studies, we use personalized prostate and breast cancer screenings.Materials and Methods: We describe an e-Science initiative in Sweden, e-Science for Cancer Prevention and Control (eCPC), which supports biomarker discovery and offers decision support for personalized intervention strategies. The generic eCPC contribution is a workflow with 4 nodes applied iteratively, and the concept of e-Science signifies systematic use of tools from the mathematical, statistical, data, and computer sciences.Results: The eCPC workflow is illustrated through 2 case studies. For prostate cancer, an in-house personalized screening tool, the Stockholm-3 model (S3M), is presented as an alternative to prostate-specific antigen testing alone. S3M is evaluated in a trial setting and plans for rollout in the population are discussed. For breast cancer, new biomarkers based on breast density and molecular profiles are developed and the US multicenter Women Informed to Screen Depending on Measures (WISDOM) trial is referred to for evaluation. While current eCPC data management uses a traditional data warehouse model, we discuss eCPC-developed features of a coherent data integration platform.Discussion and Conclusion: E-Science tools are a key part of an evidence-based process for personalized medicine. This paper provides a structured workflow from data and models to evaluation of new personalized intervention strategies. The importance of multidisciplinary collaboration is emphasized. Importantly, the generic concepts of the suggested eCPC workflow are transferrable to other disease domains, although each disease will require tailored solutions.
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| 2. |
- Holm, Johanna, et al.
(författare)
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Assessment of breast cancer risk factors reveals subtype heterogeneity
- 2017
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Ingår i: Cancer Research. - Stockholm : Karolinska Institutet, Dept of Medical Epidemiology and Biostatistics. - 0008-5472. ; 77:13, s. 3708-3717
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Tidskriftsartikel (refereegranskat)abstract
- Subtype heterogeneity for breast cancer risk factors has been suspected, potentially reflecting etiological differences and implicating risk prediction. Reports are conflicting regarding presence of heterogeneity for many exposures. To examine subtype heterogeneity across known breast cancer risk factors, we conducted a case-control analysis of 2,632 breast cancers and 15,945 controls in Sweden. Molecular subtype was predicted from pathology-record derived immunohistochemistry markers by a classifier trained on PAM50 subtyping. Multinomial logistic regression estimated separate odds ratios for each subtype by the exposures parity, age at first birth, breastfeeding, menarche, HRT use, somatotype at age 18, benign breast disease, mammographic density, polygenic risk score, family history of breast cancer and BRCA mutations. We found clear subtype heterogeneity for genetic factors and breastfeeding. The polygenic risk score was associated with risk of all subtypes except for the basal-like (p heterogeneity < 0.0001). Parous women who never breastfed were at higher risk of basal-like subtype (OR 4.17; 95% CI 1.89 to 9.21) compared to both nulliparous (reference) and breastfeeding women. Breastfeeding was not associated with risk of HER2-overexpressing type, but protective for all other subtypes. The observed heterogeneity in risk of distinct breast cancer subtypes for germline variants supports heterogeneity in etiology and has implications for their use in risk prediction. The increased risk of basal-like subtype among women who never breastfed merits more research into potential causal mechanisms and confounders.
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| 3. |
- Jiao, Xiang, et al.
(författare)
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PHIP - a novel candidate breast cancer susceptibility locus on 6q14.1
- 2017
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Ingår i: Oncotarget. - : IMPACT JOURNALS LLC. - 1949-2553. ; 8:61, s. 102769-102782
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Tidskriftsartikel (refereegranskat)abstract
- Most non-BRCA1/2 breast cancer families have no identified genetic cause. We used linkage and haplotype analyses in familial and sporadic breast cancer cases to identify a susceptibility locus on chromosome 6q. Two independent genome-wide linkage analysis studies suggested a 3 Mb locus on chromosome 6q and two unrelated Swedish families with a LOD > 2 together seemed to share a haplotype in 6q14.1. We hypothesized that this region harbored a rare high-risk founder allele contributing to breast cancer in these two families. Sequencing of DNA and RNA from the two families did not detect any pathogenic mutations. Finally, 29 SNPs in the region were analyzed in 44,214 cases and 43,532 controls from BCAC, and the original haplotypes in the two families were suggested as low-risk alleles for European and Swedish women specifically. There was also some support for one additional independent moderate-risk allele in Swedish familial samples. The results were consistent with our previous findings in familial breast cancer and supported a breast cancer susceptibility locus at 6q14.1 around the PHIP gene.
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| 4. |
- Leu, Monica, 1977, et al.
(författare)
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Evaluation of bias in familial risk estimates: a study of common cancers using Swedish population-based registers
- 2008
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Ingår i: Journal of the National Cancer Institute. - 0027-8874. ; 100:18, s. 1318-25
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Tidskriftsartikel (refereegranskat)abstract
- Background Bias in estimates of familial cancer may result if population-based registers fail to identify relatives as affected when disease occurs before the start-up of registration (ie, “left-truncation” of family history). Methods Apparent familial relative risks (among offspring of parents with cancer) of colorectal, lung, breast, and prostate cancers and melanoma in a Swedish cohort were compared with relative risks in a simulated population. The study cohort (approximately 7 million individuals) was based on the Swedish MultiGenerational Register linked to the Swedish Cancer Register for the period 1961–2002. A similar population of related individuals (approximately 7 million) with complete family information was simulated by using the R-package PopLab and used to estimate the sensitivity of the observed family history. This sensitivity was then used to calculate corrected age group–specific and overall risks, which were compared with the apparent familial risks of cancer in the cohort. Result The apparent familial risks for colorectal, lung, breast, and prostate cancers and melanoma were 1.99 (95% confidence interval [CI] = 1.85 to 2.14), 2.05 (95% CI = 1.86 to 2.26), 1.84 (95% CI = 1.76 to 1.92), 2.33 (95% CI = 2.19 to 2.48), and 2.68 (95% CI = 2.35 to 3.07), with corresponding absolute rates of 3.69, 2.59, 16.05, 10.38, and 2.96 per 10 000 person-years, among offspring of parents diagnosed with the same cancer. Corrected age group–specific and overall estimates of the familial risks were close to these apparent risks for all studied cancers (all approximately 2.0), except for melanoma. For melanoma, the corrected estimate of 3.18 (95% CI = 2.73 to 3.64) was somewhat larger than the apparent estimate and was not included in the confidence interval for the apparent estimate. When the exposure of interest was a parent affected at a younger age, this bias was more pronounced; the apparent estimate for melanoma changed from 4.07 (95% CI = 3.21 to 5.16) to 5.67 (95% CI = 4.51 to 6.83) after correction. Conclusions For common cancers, risk estimates from the Swedish MultiGenerational cohort do not generally appear to be biased by left-truncation.
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