85 research outputs found

    The InterLACE study: design, data harmonization and characteristics across 20 studies on women's health

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    The International Collaboration for a Life Course Approach to Reproductive Health and Chronic Disease Events (InterLACE) project is a global research collaboration that aims to advance understanding of women's reproductive health in relation to chronic disease risk by pooling individual participant data from several cohort and cross-sectional studies. The aim of this paper is to describe the characteristics of contributing studies and to present the distribution of demographic and reproductive factors and chronic disease outcomes in InterLACE

    Additional file 1: of Coffee consumption and the risk of malignant melanoma in the Norwegian Women and Cancer (NOWAC) Study

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    Table S1. Hazard ratios (HRs) with 95 % confidence intervals (CI) of malignant melanoma (n = 762) according to total, filtered, instant, and boiled coffee consumption in the Norwegian Women and Cancer Study, 1991–2013 (omitted adjustment for phenotypic and sun related factors, N = 104,080). Table S2. Hazard ratios (HRs) with 95 % confidence intervals (CI) of malignant melanoma (n = 762) according to, filtered, instant, and boiled coffee consumption with ≀3 cups/month as the reference cut-off in the Norwegian Women and Cancer Study, 1991–2013, N = 104,080. (DOCX 16 kb

    A prospective investigation of oral contraceptive use and breast cancer mortality: findings from the Swedish women’s lifestyle and health cohort

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    The association between oral contraceptive (OC) use and long-term mortality remains uncertain and previous studies have reported conflicting findings. We aim to assess the long-term impact of OC use on all-cause and cancer-specific mortality. Out of 49,259 participants, we analysed data on 2120 (4.3%) women diagnosed with first primary breast cancer between 1993 and 2012, in the Swedish Women’s Lifestyle and Health Study. Kaplan–Meier plots were used to graph the hazard of mortality in association with oral contraceptives use, stage of disease and hormone receptors status at diagnosis. Cox proportional hazard model were used to estimate hazard ratios (HR) between OC use and all-cause mortality. The same association was studied for breast cancer-specific mortality by modelling the log cumulative mortality risk, adjusting for clinical stage at diagnosis, hormone receptor status, body mass index and smoking. Among 2120 women with breast cancer, 1268 (84%) reported ever use of OC and 254 died within 10 years of diagnosis. The risk of death for OC ever-users relative to never-users was: HR = 1.13 (95% CI: 0.66–1.94) for all-cause mortality and HR = 1.29 (95% CI: 0.53–3.18) for breast cancer-specific mortality. A high percentage of women (42.9%) were diagnosed at early stage disease (stage I). Among women with primary breast cancer, OC ever-users compared to never- users did not have a higher all-cause or breast cancer specific-mortality, after the adjustment of risk factors.Other Information Published in: BMC Cancer License: http://creativecommons.org/licenses/by/4.0/See article on publisher's website: http://dx.doi.org/10.1186/s12885-019-5985-6</p

    Relative risk of disease in case of a positive test (relative PPV) and in case of a negative test (relative cNPV) of APTIMA compared to other tests in the ASCUS and LSIL groups for the outcomes CIN2+ and CIN3+<sup>a</sup>.

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    <p>HPV: human papillomavirus, ASCUS: typical squamous cells of undertermined significance, LSIL: low-grade squamous intraepithelial lesions, CIB: 95% confidence interval bound.</p>a<p>Significant differences in bold.</p

    Type-specific HPV DNA distribution in the ASCUS and LSIL groups by APTIMA status.

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    <p>HPV: human papillomavirus, ASCUS: atypical squamous cells of undetermined significance, LSIL: low-grade squamous intraepithelial lesions.</p

    Relative sensitivity and specificity of APTIMA compared to other tests to triage women with ASCUS or LSIL for the outcomes CIN2+ or CIN3+<sup>a</sup>.

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    <p>HPV: human papillomavirus, ASCUS: typical squamous cells of undetermined significance, LSIL: low-grade squamous intraepithelial lesions, CIB: 95% confidence interval bound.</p>a<p>Significant differences in bold.</p

    Examples of the analytical process.

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    <p>Omitted phrases are indicated by “(
)”, and hesitation indicated by “
”, whereas square brackets "[] " indicate authors’ comments. The FGDs are labelled [FGD A] to [FGD H] (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0107624#pone.0107624.t001" target="_blank">Table 1</a>) and the participants in each FGD are numbered P1 to P7.</p><p>Examples of the analytical process.</p

    Sensitivity & FPR (False positive rate) of the different tests used to triage women with ASCUS (upper) or LSIL (lower) to detect CIN2+ (left) or CIN3+ (right).

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    <p>Red circle: APTIMA, rhombus without color HPV DNA 16, rhombus blue HPV16/18 DNA, cross: cytology AS-CUS as cut-off, diagonal cross: cytology with LSIL as cut-off, double diagonal cross: cytology with HSIL as cut-off. ASCUS-atypical squamous cells of undetermined significance, LSIL-low-grade squamous intraepithelial lesions, HSIL− high-grade squamous intraepithelial lesions. CIN− cervical intraepithelial neoplasia. HR-HPV: High-risk human papillomavirus.</p

    Overview of the sensitivity and specificity, PPV, NPV, the risk of disease<sup>a</sup> in case of a negative test (cNPV-1-NPV), DOR and LR.

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    <p>PPV, positive predictive value, NPV: negative predictive value, DOR: diagnostic odds ratio, LR: likelihood ratio, TP: true positive, FN: false negative, FP: false positive, TN: true negative, N: number, ASCUS: atypical squamous cells of undetermined significance, CIN2+: cervical intraepithelial neoplasia grade 2 or worse, HPV: human papillomavirus, LSIL: low-grade squamous intraepithelial lesions, CIN3+: cervical intraepithelial neoplasia grade 3 or worse.</p>a<p>he risks of disease cNPV = 1-NPV.</p

    Characteristics of the participants.

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    <p><sup>a</sup>FGD: focus group discussion.</p><p><sup>b</sup>Based on the socioeconomic index classification used in Census data.</p><p><sup>c</sup>Based on the classification used inthe Swedish education system (SUN).</p><p>Characteristics of the participants.</p
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