| 11. |
- Houssami, Nehmat, et al.
(författare)
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Meta-analysis of prospective studies evaluating breast cancer detection and interval cancer rates for digital breast tomosynthesis versus mammography population screening
- 2021
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Ingår i: European Journal of Cancer. - : Elsevier BV. - 0959-8049. ; 148, s. 14-23
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Forskningsöversikt (refereegranskat)abstract
- Introduction: Breast cancer (BC) screening using digital breast tomosynthesis (DBT) has been shown to increase cancer detection compared with mammography; however, it is unknown whether DBT impacts interval cancer rate (ICR). Methods: We systematically identified prospective DBT studies reporting data on screen-detected and interval BCs to perform a study-level meta-analysis of the comparative effect of DBT on ICR in population screening. Meta-analysis of cancer detection rate (CDR), ICR, and the differences between DBT and mammography in CDR and ICR pooled estimates, included random-effects. Sensitivity analysis examined whether study methods (imaging used, comparison group design, interval BC ascertainment) affected pooled estimates. Results: Five eligible prospective (non-randomised) studies of DBT population screening reported on 129,969 DBT-screened participants and 227,882 mammography-only screens, including follow-up publications reporting interval BC data. Pooled CDR was 9.03/1000 (95% confidence interval [CI] 8.53–9.56) for DBT, and 5.95/1000 (95% CI 5.65–6.28) for mammography: the pooled difference in CDR was 3.15/1000 (95% CI 2.53–3.77), and was evident for the detection of invasive and in-situ malignancy. Pooled ICR was 1.56/1000 DBT screens (95% CI 1.22–2.00), and 1.75/1000 mammography screens (95% CI 1.46–2.11): the estimated pooled difference in ICR was −0.15/1000 (95% CI –0.59 to 0.29) and was not substantially altered in several sensitivity analyses. Conclusions: Meta-analysis shows consistent evidence that DBT significantly increased CDR compared with mammography screening; however, there was little difference between DBT and mammography in pooled ICR. This could suggest, but does not demonstrate, some over-detection. Meta-analysis using individual participant data, randomised trials and comparative studies quantifying cumulative detection and ICR over repeat DBT screen-rounds would provide valuable evidence to inform screening programs.
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| 12. |
- Hovda, Tone, et al.
(författare)
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Interval and Consecutive Round Breast Cancer after Digital Breast Tomosynthesis and Synthetic 2D Mammography versus Standard 2D Digital Mammography in BreastScreen Norway
- 2020
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 1527-1315 .- 0033-8419. ; 294:2, s. 256-264
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Tidskriftsartikel (refereegranskat)abstract
- Background: Screening that includes digital breast tomosynthesis (DBT) with two-dimensional (2D) synthetic mammography (SM) or standard 2D digital mammography (DM) results in detection of more breast cancers than does screening with DM alone. A decrease in interval breast cancer rates is anticipated but is not reported. Purpose: To compare rates and characteristics of (a) interval breast cancer in women screened with DBT and SM versus those screened with DM alone and (b) screen-detected breast cancer at consecutive screenings with DM. Materials and Methods: This prospective cohort study from BreastScreen Norway included women screened with DBT and SM (study group) or DM alone (control group) between February 2014 and December 2015 (baseline). All women, except nonattendees, women with breast cancer, and those who exceeded the upper age limit, were consecutively screened with DM after 2 years. Interval breast cancer, sensitivity, and specificity were estimated for women screened at baseline. Recall, screen-detected breast cancer, and positive predictive value were analyzed for consecutively screened women. A χ2 test, t test (P < .001 after Bonferroni correction indicated a significant difference), and binomial regression model were used to analyze differences across groups. Results: A total of 92 404 women who underwent baseline screening (mean age, 59 years ± 6 [standard deviation]) were evaluated; 34 641 women in the study group (mean age, 59 years ± 6) were screened with DBT and SM and 57 763 women in the control group (mean age, 59 years ± 6) were screened with DM. A total of 26 474 women in the study group (mean age, 60 years ± 5) and 45 543 women in the control group (mean age, 60 years ± 5) were consecutively screened with DM. Rates of interval breast cancer were 2.0 per 1000 screened women in the study group and 1.5 per 1000 screened women in the control group (P = .12). No differences in histopathologic characteristics of interval breast cancer were observed. In the consecutive screening round, rates of screen-detected breast cancer were 3.9 per 1000 screened women (study group) and 5.6 per 1000 screened women (control group) (P = .001). Rates of histologic grade 1 invasive cancer were 0.5 per 1000 screened women (study group) and 1.3 per 1000 screened women (control group) (P = .001). Conclusion: No differences in interval breast cancer rates or tumor characteristics were observed in women screened with DBT and SM compared with women screened with DM. Higher rates of low-grade screen-detected tumors were observed in the control group at consecutive screening.
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| 13. |
- Johansson, Henrik J., et al.
(författare)
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Breast cancer quantitative proteome and proteogenomic landscape
- 2019
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.
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| 14. |
- Larsen, Marthe, et al.
(författare)
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Mammographic density and interval cancers in mammographic screening : Moving towards more personalized screening
- 2023
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Ingår i: Breast. - : Elsevier BV. - 0960-9776. ; 69, s. 306-311
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: The European Society on Breast Imaging has recommended supplemental magnetic resonance imaging (MRI) every two to four years for women with mammographically dense breasts. This may not be feasible in many screening programs. Also, the European Commission Initiative on Breast Cancer suggests not implementing screening with MRI. By analyzing interval cancers and time from screening to diagnosis by density, we present alternative screening strategies for women with dense breasts. Methods: Our BreastScreen Norway cohort included 508 536 screening examinations, including 3125 screen-detected and 945 interval breast cancers. Time from screening to interval cancer was stratified by density measured by an automated software and classified into Volpara Density Grades (VDGs) 1–4. Examinations with volumetric density ≤3.4% were categorized as VDG1, 3.5%–7.4% as VDG2, 7.5%–15.4% as VDG3, and ≥15.5% as VDG4. Interval cancer rates were also determined by continuous density measures. Results: Median time from screening to interval cancer was 496 (IQR: 391–587) days for VDG1, 500 (IQR: 350–616) for VDG2, 482 (IQR: 309–595) for VDG3 and 427 (IQR: 266–577) for VDG4. A total of 35.9% of the interval cancers among VDG4 were detected within the first year of the biennial screening interval. For VDG2, 26.3% were detected within the first year. The highest annual interval cancer rate (2.7 per 1000 examinations) was observed for VDG4 in the second year of the biennial interval. Conclusions: Annual screening of women with extremely dense breasts may reduce the interval cancer rate and increase program-wide sensitivity, especially in settings where supplemental MRI screening is not feasible.
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| 15. |
- Libesman, Sol, et al.
(författare)
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An individual participant data meta-analysis of breast cancer detection and recall rates for digital breast tomosynthesis versus digital mammography population screening
- 2022
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Ingår i: Clinical Breast Cancer. - : Elsevier BV. - 1526-8209. ; 22:5, s. 647-654
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Forskningsöversikt (refereegranskat)abstract
- Background: Although digital breast tomosynthesis (DBT) improves breast cancer screen-detection compared to digital mammography (DM), there is less evidence on comparative screening outcomes by age and breast density, and inconsistent evidence on its effect on recall rate. Method: We performed an individual participant data (IPD) meta-analysis from DBT screening studies (identified to November, 30 2019) that contributed to the study protocol. We estimated and compared cancer detection rate (CDR), recall rate, and positive predictive value (PPV) for recall for DBT and DM screening. Two-stage random-effects meta-analyses of detection outcomes adjusted for study and age, and were estimated in age and density subgroups. Screen-detected cancer characteristics were summarized descriptively within studies and screening-groups. Results: Four prospective studies, from European population-based programs, contributed IPD for 66,451 DBT-screened participants and 170,764 DM-screened participants. Age-adjusted pooled CDR difference between DBT and DM was 25.49 of 10,000 (95% CI:6.73-44.25). There was suggestive evidence of a higher CDR for DBT compared to DM in the high-density (35.19 of 10,000; 95% CI:17.82-56.56) compared to low-density (17.4 of 10,000; 95% CI:7.62-27.18) group (P =.08). Pooled CDR difference between DBT and DM did not differ across age-groups (P =.71). Age-adjusted recall rate difference was 0.18% (95% CI:-0.80–1.17), indicating no difference between DBT and DM- this finding did not differ across age-groups (P =.96). Recall PPV was higher for DBT than DM with an estimated rate ratio of 1.31 (95% CI:1.07-1.61). Discussion: DBT improved CDR compared to DM in all age and density groups. DBT also had higher recall PPV than DM, although further research is needed to explore the heterogeneity in recall rates across studies.
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| 16. |
- Lång, Kristina, et al.
(författare)
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Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI) : a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study
- 2023
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Ingår i: The Lancet. Oncology. - 1474-5488. ; 24:8, s. 936-944
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Retrospective studies have shown promising results using artificial intelligence (AI) to improve mammography screening accuracy and reduce screen-reading workload; however, to our knowledge, a randomised trial has not yet been conducted. We aimed to assess the clinical safety of an AI-supported screen-reading protocol compared with standard screen reading by radiologists following mammography.METHODS: In this randomised, controlled, population-based trial, women aged 40-80 years eligible for mammography screening (including general screening with 1·5-2-year intervals and annual screening for those with moderate hereditary risk of breast cancer or a history of breast cancer) at four screening sites in Sweden were informed about the study as part of the screening invitation. Those who did not opt out were randomly allocated (1:1) to AI-supported screening (intervention group) or standard double reading without AI (control group). Screening examinations were automatically randomised by the Picture Archive and Communications System with a pseudo-random number generator after image acquisition. The participants and the radiographers acquiring the screening examinations, but not the radiologists reading the screening examinations, were masked to study group allocation. The AI system (Transpara version 1.7.0) provided an examination-based malignancy risk score on a 10-level scale that was used to triage screening examinations to single reading (score 1-9) or double reading (score 10), with AI risk scores (for all examinations) and computer-aided detection marks (for examinations with risk score 8-10) available to the radiologists doing the screen reading. Here we report the prespecified clinical safety analysis, to be done after 80 000 women were enrolled, to assess the secondary outcome measures of early screening performance (cancer detection rate, recall rate, false positive rate, positive predictive value [PPV] of recall, and type of cancer detected [invasive or in situ]) and screen-reading workload. Analyses were done in the modified intention-to-treat population (ie, all women randomly assigned to a group with one complete screening examination, excluding women recalled due to enlarged lymph nodes diagnosed with lymphoma). The lowest acceptable limit for safety in the intervention group was a cancer detection rate of more than 3 per 1000 participants screened. The trial is registered with ClinicalTrials.gov, NCT04838756, and is closed to accrual; follow-up is ongoing to assess the primary endpoint of the trial, interval cancer rate.FINDINGS: Between April 12, 2021, and July 28, 2022, 80 033 women were randomly assigned to AI-supported screening (n=40 003) or double reading without AI (n=40 030). 13 women were excluded from the analysis. The median age was 54·0 years (IQR 46·7-63·9). Race and ethnicity data were not collected. AI-supported screening among 39 996 participants resulted in 244 screen-detected cancers, 861 recalls, and a total of 46 345 screen readings. Standard screening among 40 024 participants resulted in 203 screen-detected cancers, 817 recalls, and a total of 83 231 screen readings. Cancer detection rates were 6·1 (95% CI 5·4-6·9) per 1000 screened participants in the intervention group, above the lowest acceptable limit for safety, and 5·1 (4·4-5·8) per 1000 in the control group-a ratio of 1·2 (95% CI 1·0-1·5; p=0·052). Recall rates were 2·2% (95% CI 2·0-2·3) in the intervention group and 2·0% (1·9-2·2) in the control group. The false positive rate was 1·5% (95% CI 1·4-1·7) in both groups. The PPV of recall was 28·3% (95% CI 25·3-31·5) in the intervention group and 24·8% (21·9-28·0) in the control group. In the intervention group, 184 (75%) of 244 cancers detected were invasive and 60 (25%) were in situ; in the control group, 165 (81%) of 203 cancers were invasive and 38 (19%) were in situ. The screen-reading workload was reduced by 44·3% using AI.INTERPRETATION: AI-supported mammography screening resulted in a similar cancer detection rate compared with standard double reading, with a substantially lower screen-reading workload, indicating that the use of AI in mammography screening is safe. The trial was thus not halted and the primary endpoint of interval cancer rate will be assessed in 100 000 enrolled participants after 2-years of follow up.FUNDING: Swedish Cancer Society, Confederation of Regional Cancer Centres, and the Swedish governmental funding for clinical research (ALF).
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| 17. |
- Lång, Kristina, et al.
(författare)
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Can artificial intelligence reduce the interval cancer rate in mammography screening?
- 2021
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Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 31:8, s. 5940-5947
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Tidskriftsartikel (refereegranskat)abstract
- Objectives To investigate whether artificial intelligence (AI) can reduce interval cancer in mammography screening. Materials and methods Preceding screening mammograms of 429 consecutive women diagnosed with interval cancer in Southern Sweden between 2013 and 2017 were analysed with a deep learning–based AI system. The system assigns a risk score from 1 to 10. Two experienced breast radiologists reviewed and classified the cases in consensus as true negative, minimal signs or false negative and assessed whether the AI system correctly localised the cancer. The potential reduction of interval cancer was calculated at different risk score thresholds corresponding to approximately 10%, 4% and 1% recall rates. Results A statistically significant correlation between interval cancer classification groups and AI risk score was observed (p < .0001). AI scored one in three (143/429) interval cancer with risk score 10, of which 67% (96/143) were either classified as minimal signs or false negative. Of these, 58% (83/143) were correctly located by AI, and could therefore potentially be detected at screening with the aid of AI, resulting in a 19.3% (95% CI 15.9–23.4) reduction of interval cancer. At 4% and 1% recall thresholds, the reduction of interval cancer was 11.2% (95% CI 8.5–14.5) and 4.7% (95% CI 3.0–7.1). The corresponding reduction of interval cancer with grave outcome (women who died or with stage IV disease) at risk score 10 was 23% (8/35; 95% CI 12–39). Conclusion The use of AI in screen reading has the potential to reduce the rate of interval cancer without supplementary screening modalities.
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| 18. |
- Moshina, Nataliia, et al.
(författare)
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Comparing screening outcomes for digital breast tomosynthesis and digital mammography by automated breast density in a randomized controlled trial : Results from the to-be trial
- 2020
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Ingår i: Radiology. - : Radiological Society of North America (RSNA). - 0033-8419 .- 1527-1315. ; 297:3, s. 522-531
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Tidskriftsartikel (refereegranskat)abstract
- Background: Digital breast tomosynthesis (DBT) is considered superior to digital mammography (DM) for women with dense breasts. Purpose: To identify differences in screening outcomes, including rates of recall, false-positive (FP) findings, biopsy, cancer detection rate, positive predictive value of recalls and biopsies, and histopathologic tumor characteristics by density using DBT combined with two-dimensional synthetic mammography (SM) (hereafter, DBT+SM) versus DM. Materials and Methods: This randomized controlled trial comparing DBT+SM and DM was performed in Bergen as part of BreastScreen Norway, 2016-2017. Automated software measured density (Volpara Density Grade [VDG], 1-4). The outcomes were compared for DBT+SM versus DM by VDG in descriptive analyses. A stratified log-binomial regression model was used to estimate relative risk of outcomes in subgroups by screening technique. Results: Data included 28 749 women, 14 380 of whom were screened with DBT+SM and 14 369 of whom were screened with DM (both groups: median age, 59 years; interquartile range [IQR], 54-64 years). The recall rate was lower for women screened with DBT+SM versus those screened with DM for VDG 1 (2.1% [81 of 3929] vs 3.3% [106 of 3212]; P = .001) and VDG 2 (3.2% [200 of 6216] vs 4.3% [267 of 6280]; P = .002). For DBT+SM, adjusted relative risk of recall (VDG 2: 1.8; P < .001; VDG 3: 2.4; P < .001; VDG 4: 1.8; P = .02) and screen-detected breast cancer (VDG 2: 2.4; P = .004; VDG 3: 2.8; P = .01; VDG 4: 2.8; P = .05) increased with VDG, whereas no differences were observed for DM (relative risk of recall for VDG 2: 1.3; P = .06; VDG 3: 1.1; P = .41; VDG 4: 1.1; P = .71; and relative risk of screen-detected breast cancer for VDG 2: 1.7; P = .13; VDG 3: 2.1; P = .06; VDG 4: 2.2; P = .15). Conclusion: Screening with digital breast tomosynthesis combined with synthetic two-dimensional mammograms (DBT+SM) versus digital mammography (DM) yielded lower recall rates for women with Volpara Density Grade (VDG) 1 and VDG 2. Adjusted relative risk of recall and screen-detected breast cancer increased with denser breasts for DBT+SM but not for DM.
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| 19. |
- Muratov, Sergei, et al.
(författare)
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Monitoring and evaluation of breast cancer screening programmes : selecting candidate performance indicators
- 2020
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Ingår i: BMC Cancer. - : BioMed Central. - 1471-2407 .- 1471-2407. ; 20:1
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Tidskriftsartikel (refereegranskat)abstract
- Background: In the scope of the European Commission Initiative on Breast Cancer (ECIBC) the Monitoring and Evaluation (M&E) subgroup was tasked to identify breast cancer screening programme (BCSP) performance indicators, including their acceptable and desirable levels, which are associated with breast cancer (BC) mortality. This paper documents the methodology used for the indicator selection.Methods: The indicators were identified through a multi-stage process. First, a scoping review was conducted to identify existing performance indicators. Second, building on existing frameworks for making well-informed health care choices, a specific conceptual framework was developed to guide the indicator selection. Third, two group exercises including a rating and ranking survey were conducted for indicator selection using pre-determined criteria, such as: relevance, measurability, accurateness, ethics and understandability. The selected indicators were mapped onto a BC screening pathway developed by the M&E subgroup to illustrate the steps of BC screening common to all EU countries.Results: A total of 96 indicators were identified from an initial list of 1325 indicators. After removing redundant and irrelevant indicators and adding those missing, 39 candidate indicators underwent the rating and ranking exercise. Based on the results, the M&E subgroup selected 13 indicators: screening coverage, participation rate, recall rate, breast cancer detection rate, invasive breast cancer detection rate, cancers >20mm, cancers <= 10mm, lymph node status, interval cancer rate, episode sensitivity, time interval between screening and first treatment, benign open surgical biopsy rate, and mastectomy rate.Conclusion: This systematic approach led to the identification of 13 BCSP candidate performance indicators to be further evaluated for their association with BC mortality.
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| 20. |
- Sandvei, Marie Søfteland, et al.
(författare)
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Menopausal hormone therapy and breast cancer risk : effect modification by body mass through life
- 2019
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Ingår i: European Journal of Epidemiology. - : Springer Science and Business Media LLC. - 0393-2990 .- 1573-7284. ; 34:3, s. 267-278
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Tidskriftsartikel (refereegranskat)abstract
- It is not known whether increased breast cancer risk caused by menopausal hormone therapy (HT) depends on body mass patterns through life. In a prospective study of 483,241 Norwegian women aged 50–69 years at baseline, 7656 women developed breast cancer during follow-up (2006–2013). We combined baseline information on recalled body mass in childhood/adolescence and current (baseline) body mass index (BMI) to construct mutually exclusive life-course body mass patterns. We assessed associations of current HT use with breast cancer risk according to baseline BMI and life-course patterns of body mass, and estimated relative excess risk due to interaction (RERI). Within all levels of baseline BMI, HT use was associated with increased risk. Considering life-course body mass patterns as a single exposure, we used women who “remained at normal weight” through life as the reference, and found that being “overweight as young” was associated with lower risk (hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.76–0.94), whereas women who “gained weight” had higher risk (HR 1.20, 95% CI 1.12–1.28). Compared to never users of HT who were “overweight as young”, HT users who either “remained at normal weight” or “gained weight” in adulthood were at higher risk than expected when adding the separate risks (RERI 0.52, 95% CI 0.09–0.95, and RERI 0.37, 95% CI − 0.07–0.80), suggesting effect modification. Thus, we found that women who remain at normal weight or gain weight in adulthood may be more susceptible to the risk increasing effect of HT compared to women who were overweight as young.
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