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  • 1. Chen, M-J
    et al.
    Wu, Wendy Yi-Ying
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper. Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
    Yen, A. M-F
    Fann, J. C-Y
    Chen, S. L-S
    Chiu, S. Y-H
    Chen, H-H
    Chiou, S-T
    Body mass index and breast cancer: analysis of a nation-wide population-based prospective cohort study on 1 393 985 Taiwanese women2016Ingår i: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 40, nr 3, s. 524-530Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    BACKGROUND: Asian women have a younger age at onset of breast cancer and a lower body mass index (BMI) than Western women. The link between obesity and risk of breast cancer in Asian women is still elusive. We aimed to investigate the effect of BMI on the risk of incident breast cancer in Taiwanese women.

    METHODS: A total of 1 393 985 women who had been cancer-free before recruitment and attended a nation-wide Taiwanese breast cancer-screening program between 1999 and 2009 were enrolled using a prospective cohort study. Obesity and other relevant variables (such as menopause status and other biochemical markers) were collected through in-person interviews, anthropometric measurements and blood samples at first screen. Incident breast cancers during follow-up were ascertained through the linkage of the cohort with the National Cancer Registry and the National Death Certification System.

    RESULTS: A total of 6969 and 7039 incident breast cancer cases were identified among women enrolled before and after menopause, respectively. Compared with a BMI range of 18.5-23.9 kgm(-2), the incremental level of BMI in the enrolled women before menopause revealed a lack of statistically significant association with the risk of incident breast cancer (adjusted hazard ratio = 0.94, 0.98, 1.02, 1.01 and 0.82 for BMI < 18.5, 24-26.9, 27-29.9, 30-34.9 and >= 35, respectively), but the incremental level of BMI in the enrolled women after menopause led to a statistically significant incremental increase in the risk of breast cancer (adjusted hazard ratio = 0.78, 1.19, 1.31, 1.53 and 1.65 for BMI < 18.5, 24-26.9, 27-29.9, 30-34.9 and >= 35, respectively) after adjusting for other explanatory risk factors.

    CONCLUSION: Obesity acts mainly as an influential promoter of the development of late-onset breast cancer after menopause in Taiwanese women.

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  • 2. Kabat, G. C.
    et al.
    Wu, Wendy Yi-Ying
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi. Graduate School of Epidemiology and Department of Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
    Bea, J. W.
    Chen, C.
    Qi, L.
    Stefanick, M. L.
    Chlebowski, R. T.
    Lane, D. S.
    Wactawski-Wende, J.
    Wassertheil-Smoller, S.
    Rohan, T. E.
    Metabolic phenotypes of obesity: frequency, correlates and change over time in a cohort of postmenopausal women2017Ingår i: International Journal of Obesity, ISSN 0307-0565, E-ISSN 1476-5497, Vol. 41, nr 1, s. 170-177Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objective: The possibility that a subset of persons who are obese may be metabolically healthy—referred to as the ‘metabolically healthy obese’ (MHO) phenotype—has attracted attention recently. However, few studies have followed individuals with MHO or other obesity phenotypes over time to assess change in their metabolic profiles. The aim of the present study was to examine transitions over a 6-year period among different states defined simultaneously by body mass index (BMI) and the presence/absence of the metabolic syndrome (MetS).

    Methods: We used repeated measurements available for a subcohort of participants enrolled in the Women’s Health Initiative (N=3512) and followed for an average of 6 years to examine the frequency of different metabolic obesity phenotypes at baseline, the 6-year transition probabilities to other states and predictors of the risk of different transitions. Six phenotypes were defined by cross-tabulating BMI (18.5–<25.0, 25.0–<30.0, 30.0 kg m−2) by MetS (yes, no). A continuous-time Markov model was used to estimate 6-year transition probabilities from one state to another.

    Results: Over the 6 years of follow-up, one-third of women with the healthy obese phenotype transitioned to the metabolically unhealthy obese (MUO) phenotype. Overall, there was a marked tendency toward increased metabolic deterioration with increasing BMI and toward metabolic improvement with lower BMI. Among MHO women, the 6-year probability of becoming MUO was 34%, whereas among unhealthy normal-weight women, the probability of ‘regressing’ to the metabolically healthy normal-weight phenotype was 52%.

    Conclusions: The present study demonstrated substantial change in metabolic obesity phenotypes over a 6-year period. There was a marked tendency toward metabolic deterioration with greater BMI and toward metabolic improvement with lower BMI.

  • 3.
    Sjöberg, Rickard L
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för klinisk vetenskap, Neurovetenskaper. Department of Neurosurgery, University Hospital of Northern Sweden, 901 85 Umeå, Sweden.
    Wu, Wendy Yi-Ying
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Dahlin, Anna M.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Tsavachidis, Spiridon
    Bondy, Melissa L.
    Melin, Beatrice S.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Role of monoamine-oxidase-A-gene variation in the development of glioblastoma in males: a case control study2019Ingår i: Journal of Neuro-Oncology, ISSN 0167-594X, E-ISSN 1573-7373, Vol. 145, nr 2, s. 287-294Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: The Mono-amine oxidase-A (MAO-A) enzyme is involved in the degradation and regulation of catecholamines such as serotonin, dopamine, epinephrine and nor-epinephrine. Preclinical studies suggest that this enzyme may contribute to an environment favorable for growth of malignant glioma. The MAO-A gene is located on the X-chromosome and has at least one functional genetic polymorphism. The aim of the present study was to explore possible effects of MAO-A genotype on development of glioblastoma in males.

    Methods: Genotypes for 437 glioma cases and 876 population-based controls from the Swedish Glioma International Case–Control study (GICC) were compared. We analyzed the germline DNA using the Illumina Oncoarray. We selected seven single nucleotide polymorphisms (SNPs) located in the MAO-A gene, and imputed genotypes based on data from the 1000 genomes project. We used 1579 male glioblastoma cases and 1875 controls comprising the whole GICC cohort for subsequent validation of findings.

    Results: The rs144551722 SNP was a significant predictor of development of glioblastoma in males (p-value = 0.0056) but not in females even after correction for multiple testing. We conducted haplotype analysis to confirm an association between MAO-A gene and risk of glioblastoma (p-value = 0.016). We found similar results in the validation sample.

    Conclusions: These results suggest the possibility of a role for the MAO-A enzyme and the MAO-A gene in the development of glioblastoma in males.

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  • 4. Tabar, Laszlo
    et al.
    Chen, Tony Hsiu-Hsi
    Yen, Amy Ming-Fang
    Chen, Sam Li-Sheng
    Fann, Jean Ching-Yuan
    Chiu, Sherry Yueh-Hsia
    Ku, May M. S.
    Wu, Wendy Yi-Ying
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Hsu, Chen-Yang
    Chen, Yu-Ying
    Beckmann, Kerri
    Smith, Robert A.
    Duffy, Stephen W.
    Effect of Mammography Screening on Mortality by Histological Grade2018Ingår i: Cancer Epidemiology, Biomarkers and Prevention, ISSN 1055-9965, E-ISSN 1538-7755, Vol. 27, nr 2, s. 154-157Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: It has been asserted that mammography screening preferentially benefits those with less aggressive cancers, with lesser or no impact on more rapidly progressing and therefore more life-threatening tumors. Methods: We utilized data from the Swedish Two-County Trial, which randomized 77,080 women ages 40 to 74 to invitation to screening and 55,985 for usual care. We tabulated cancers by histologic grade and then compared mortality from cancers specific to histologic grade between the invited and control group using Poisson regression, with specific interest in the effect on mortality from grade 3 cancers. We used incidence-based mortality from tumors diagnosed within the screening phase of the trial. Finally, we cross-tabulated grade with tumor size and node status, to assess downstaging within tumor grades. Results: There was a major reduction in mortality from grade 3 tumors (RR = 0.65; 95% CI, 0.53-0.80; P < 0.001), and more deaths prevented from grade 3 tumors (n = 95) than grade 1 and 2 tumors combined (n = 48) in the invited group. The proportions of tumors >= 15 mm or larger and node-positive tumors were substantially reduced in the grade 3 tumors in the invited group. Conclusions: The combination of prevention of tumors progressing to grade 3 and detection at smaller sizes and lesser rates of lymph node metastases within grade 3 tumors results in a substantial number of deaths from grade 3 cancers being prevented by invitation to mammographic screening. Impact: Mammography screening prevents deaths from aggressive cancers. 

  • 5. Tabar, Laszlo
    et al.
    Dean, Peter B.
    Chen, Tony Hsiu-Hsi
    Yen, Amy Ming-Fang
    Chen, Sam Li-Sheng
    Fann, Jean Ching-Yuan
    Chiu, Sherry Yueh-Hsia
    Ku, May Mei-Sheng
    Wu, Wendy Yi-Ying
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper.
    Hsu, Chen-Yang
    Chen, Yu-Ching
    Beckmann, Kerri
    Smith, Robert A.
    Duffy, Stephen W.
    The incidence of fatal breast cancer measures the increased effectiveness of therapy in women participating in mammography screening2019Ingår i: Cancer, ISSN 0008-543X, E-ISSN 1097-0142, Vol. 125, nr 4, s. 515-523Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Women and their health care providers need a reliable answer to this important question: If a woman chooses to participate in regular mammography screening, then how much will this choice improve her chances of avoiding a death from breast cancer compared with women who choose not to participate? Methods: To answer this question, we used comprehensive registries for population, screening history, breast cancer incidence, and disease-specific death data in a defined population in Dalarna County, Sweden. The annual incidence of breast cancer was calculated along with the annual incidence of breast cancers that were fatal within 10 and within 11 to 20 years of diagnosis among women aged 40 to 69 years who either did or did not participate in mammography screening during a 39-year period (1977-2015). For an additional comparison, corresponding data are presented from 19 years of the prescreening period (1958-1976). All patients received stage-specific therapy according to the latest national guidelines, irrespective of the mode of detection. Results: The benefit for women who chose to participate in an organized breast cancer screening program was a 60% lower risk of dying from breast cancer within 10 years after diagnosis (relative risk, 0.40; 95% confidence interval, 0.34-0.48) and a 47% lower risk of dying from breast cancer within 20 years after diagnosis (relative risk, 0.53; 95% confidence interval, 0.44-0.63) compared with the corresponding risks for nonparticipants. Conclusions: Although all patients with breast cancer stand to benefit from advances in breast cancer therapy, the current results demonstrate that women who have participated in mammography screening obtain a significantly greater benefit from the therapy available at the time of diagnosis than do those who have not participated.

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  • 6.
    Wu, Wendy Yi-Ying
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Johansson, Gunnar
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Wibom, Carl
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Brännström, Thomas
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Patologi.
    Malmström, Annika
    Henriksson, Roger
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Golovleva, Irina
    Umeå universitet, Medicinska fakulteten, Institutionen för medicinsk biovetenskap, Medicinsk och klinisk genetik.
    Bondy, Melissa L.
    Andersson, Ulrika
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Dahlin, Anna M.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Melin, Beatrice S.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    The Genetic Architecture of Gliomagenesis-Genetic Risk Variants Linked to Specific Molecular Subtypes2019Ingår i: Cancers, ISSN 2072-6694, Vol. 11, nr 12, artikel-id 2001Artikel, forskningsöversikt (Refereegranskat)
    Abstract [en]

    Genome-wide association studies have identified 25 germline genetic loci that increase the risk of glioma. The somatic tumor molecular alterations, including IDH-mutation status and 1p/19q co-deletion, have been included into the WHO 2016 classification system for glioma. To investigate how the germline genetic risk variants correlate with the somatic molecular subtypes put forward by WHO, we performed a meta-analysis that combined findings from 330 Swedish cases and 876 controls with two other recent studies. In total, 5,103 cases and 10,915 controls were included. Three categories of associations were found. First, variants in TERT and TP53 were associated with increased risk of all glioma subtypes. Second, variants in CDKN2B-AS1, EGFR, and RTEL1 were associated with IDH-wildtype glioma. Third, variants in CCDC26 (the 8q24 locus), C2orf80 (close to IDH), LRIG1, PHLDB1, ETFA, MAML2 and ZBTB16 were associated with IDH-mutant glioma. We therefore propose three etiopathological pathways in gliomagenesis based on germline variants for future guidance of diagnosis and potential functional targets for therapies. Future prospective clinical trials of patients with suspicion of glioma diagnoses, using the genetic variants as biomarkers, are necessary to disentangle how strongly they can predict glioma diagnosis.

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  • 7.
    Wu, Wendy Yi-Ying
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Tabar, Laszlo
    Tot, Tibor
    Fann, Ching-Yuan
    Yen, Amy Ming-Fang
    Chen, Sam Li-Sheng
    Chiu, Sherry Yueh-Hsia
    Ku, May Mei-Sheng
    Hsu, Chen-Yang
    Beckmann, Kerri R.
    Smith, Robert A.
    Duffy, Stephen W.
    Chen, Hsiu-Hsi
    Imaging Biomarkers as Predictors for Breast Cancer Death2019Ingår i: Journal of Oncology, ISSN 1687-8450, E-ISSN 1687-8469, artikel-id 2087983Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background. To differentiate the risk of breast cancer death in a longitudinal cohort using imaging biomarkers of tumor extent and biology, specifically, the mammographic appearance, basal phenotype, histologic tumor distribution, and conventional tumor attributes. Methods. Using a prospective cohort study design, 498 invasive breast cancer patients diagnosed between 1996 and 1998 were used as the test cohort to assess the independent effects of the imaging biomarkers and other predictors on the risk of breast cancer death. External validation was performed with a cohort of 848 patients diagnosed between 2006 and 2010. Results. Mammographic tumor appearance was an independent predictor of risk of breast cancer death (P=0.0003) when conventional tumor attributes and treatment modalities were controlled. The casting type calcifications and architectural distortion were associated with 3.13-fold and 3.19-fold risks of breast cancer death, respectively. The basal phenotype independently conferred a 2.68-fold risk compared with nonbasal phenotype. The observed deaths did not differ significantly from expected deaths in the validation cohort. The application of imaging biomarkers together with other predictors classified twelve categories of risk for breast cancer death. Conclusion. Combining imaging biomarkers such as the mammographic appearance of the tumor with the histopathologic distribution and basal phenotype, accurately predicted long-term risk of breast cancer death. The information may be relevant for determining the need for molecular testing, planning treatment, and determining the most appropriate clinical surveillance schedule for breast cancer patients.

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  • 8.
    Wu, Wendy Yi-Ying
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Törnberg, Sven
    Elfström, Klara Miriam
    Liu, Xijia
    Umeå universitet, Teknisk-naturvetenskapliga fakulteten, Institutionen för matematik och matematisk statistik.
    Nyström, Lennarth
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Epidemiologi och global hälsa.
    Jonsson, Håkan
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Overdiagnosis in the population-based organized breast cancer screening program estimated by a non-homogeneous multi-state model: a cohort study using individual data with long-term follow-up2018Ingår i: Breast Cancer Research, ISSN 1465-5411, E-ISSN 1465-542X, Vol. 20, artikel-id 153Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: Overdiagnosis, defined as the detection of a cancer that would not become clinically apparent in a woman’s lifetime without screening, has become a growing concern. Similar underlying risk of breast cancer in the screened and control groups is a prerequisite for unbiased estimates of overdiagnosis, but a contemporary control group is usually not available in organized screening programs.

    Methods: We estimated the frequency of overdiagnosis of breast cancer due to screening in women 50–69 years old by using individual screening data from the population-based organized screening program in Stockholm County 1989–2014. A hidden Markov model with four latent states and three observed states was constructed to estimate the natural progression of breast cancer and the test sensitivity. Piecewise transition rates were used to consider the time-varying transition rates. The expected number of detected non-progressive breast cancer cases was calculated.

    Results: During the study period, 2,333,153 invitations were sent out; on average, the participation rate in the screening program was 72.7% and the average recall rate was 2.48%. In total, 14,648 invasive breast cancer cases were diagnosed; among the 8305 screen-detected cases, the expected number of non-progressive breast cancer cases was 35.9, which is equivalent to 0.43% (95% confidence interval (CI) 0.10%–2.2%) overdiagnosis. The corresponding estimates for the prevalent and subsequent rounds were 15.6 (0.87%, 95% CI 0.20%–4.3%) and 20.3 (0.31%, 95% CI 0.07%–1.6%), respectively. The likelihood ratio test showed that the non-homogeneous model fitted the data better than an age-homogeneous model (P<0.001).

    Conclusions: Our findings suggest that overdiagnosis in the organized biennial mammographic screening for women 50–69 in Stockholm County is a minor phenomenon. The frequency of overdiagnosis in the prevalent screening round was higher than that in subsequent rounds. The non-homogeneous model performed better than the simpler, traditional homogeneous model.

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  • 9.
    Wu, Wendy Y-Y
    et al.
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper.
    Nyström, Lennarth
    Umeå universitet, Medicinska fakulteten, Institutionen för folkhälsa och klinisk medicin, Epidemiologi och global hälsa.
    Jonsson, Håkan
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper, Onkologi.
    Estimation of overdiagnosis in breast cancer screening using a non-homogeneous multi-state model: a simulation study2018Ingår i: Journal of Medical Screening, ISSN 0969-1413, E-ISSN 1475-5793, Vol. 25, nr 4, s. 183-190Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Objectives: Overdiagnosis is regarded as a harm of screening. We aimed to develop a non-homogeneous multi-state model to consider the age-specific transition rates for estimation of overdiagnosis, to validate the model by a simulation study where the true frequency of overdiagnosis can be calculated, and to compare our estimate with the cumulative incidence method. Methods: We constructed a four-state model to describe the natural history of breast cancer. The latent disease progression and the observed states for each individual were simulated in a trial with biennial screening of women aged 51-69 and a control group of the same size without screening. We performed 100 repetitions of the simulation with one million women to evaluate the performance of estimates. A sensitivity analysis with reduced number of controls was performed to imitate the data from the service screening programme. Results Based on the 100 repetitions, the mean value of the true frequency of overdiagnosis was 12.5% and the average estimates by the cumulative incidence method and the multi-state model were 12.9% (interquartile range: 2.46%) and 13.4% (interquartile range: 2.16%), respectively. The multi-state model had a greater bias of overdiagnosis than the cumulative incidence method, but the variation in the estimates was smaller. When the number of unscreened group was reduced, the variation of multi-state model estimates increased. Conclusions: The multi-state model produces a proper estimate of overdiagnosis and the results are comparable with the cumulative incidence method. The multi-state model can be used in the estimation of overdiagnosis, and might be useful for the ongoing service screening programmes.

  • 10. Yen, Amy Ming-Fang
    et al.
    Wu, Wendy Yi-Ying
    Umeå universitet, Medicinska fakulteten, Institutionen för strålningsvetenskaper. Graduate Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan.
    Tabar, Laszlo
    Duffy, Stephen W.
    Smith, Robert A.
    Chen, Hsiu-Hsi
    Initiators and promoters for the occurrence of screen-detected breast cancer and the progression to clinically-detected interval breast cancer2017Ingår i: Journal of Epidemiology, ISSN 0917-5040, E-ISSN 1349-9092, Vol. 27, nr 3, s. 98-106Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Background: The risk factors responsible for breast cancer have been well documented, but the roles of risk factors as initiators, causing the occurrence of screen-detected breast cancer, or promoters, responsible for the progression of the screen-detected to the clinically-detected breast cancer, have been scarcely evaluated.

    Methods: We used data from women in a cohort in Kopparberg (Dalarna), Sweden between 1977 and 2010. Conventional risk factors, breast density, and tumor-specific biomarkers are superimposed to the temporal course of the natural history of the disease.

    Results: The results show that older age at first full-term pregnancy, dense breast, and a family history of breast cancer increased the risk of entering the preclinical screen-detectable phase of breast cancer by 23%, 41%, and 89%, respectively. Overweight/obesity (body mass index >= 25 kg/m(2)) was a significant initiator (adjusted relative risk [aRR] 1.15; 95% confidence interval [CI], 0.99-1.33), but was inversely associated with the role of promoter (aRR 0.65; 95% CI, 0.51-0.82). Dense breast (aRR 1.46; 95% CI, 1.12 -1.91), triple-negative (aRR 2.07; 95% CI, 1.37-3.15), and Ki-67 positivity (aRR 1.66; 95% CI, 1.19-2.30) were statistically significant promoters. When the molecular biomarkers were considered collectively as one classification, the basal-like subtype was the most influential subtype on promoters (aRR 4.24; 95% CI, 2.56-7.02) compared with the Luminal A subtype.

    Discussion: We ascertained state-dependent covariates of initiators and promoters to classify the risk of the two-step progression of breast cancer. The results of the current study are useful for individually-tailored screening and personalized clinical surveillance of patients with breast cancer that was detected at an early stage.

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