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Ahmed S, Lévesque E, Garland R, Knoppers B, Dorval M, Simard J, Loiselle CG. Women's perceptions of PERSPECTIVE: a breast cancer risk stratification e-platform. Hered Cancer Clin Pract 2022; 20:8. [PMID: 35209930 PMCID: PMC8867776 DOI: 10.1186/s13053-022-00214-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 02/03/2022] [Indexed: 12/14/2022] Open
Abstract
Background Breast cancer risk stratification categorizes a woman’s potential risk of developing the disease as near-population, intermediate, or high. In accordance, screening and follow up for breast cancer can readily be tailored following risk assessment. Recent efforts have focussed on developing more accessible means to convey this information to women. This study sought to document the relevance of an informational e-platform developed for these purposes. Objective To begin to assess a newly developed breast cancer risk stratification and decision support e-platform called PERSPECTIVE (PErsonalised Risk Stratification for Prevention and Early deteCTIon of breast cancer) among women who do not know their personal breast cancer risk (Phase 1). Changes (pre- and post- e-platform exposure) in knowledge of breast cancer risk and interest in undergoing genetic testing were assessed in addition to perceptions of platform usability and acceptability. Methods Using a pre-post design, women (N = 156) of differing literacy and education levels, aged 30 to 60, with no previous breast cancer diagnosis were recruited from the general population and completed self-report e-questionnaires. Results Mean e-platform viewing time was 18.67 min (SD 0.65) with the most frequently visited pages being breast cancer-related risk factors and risk assessment. Post-exposure, participants reported significantly higher breast cancer-related knowledge (p < .001). Increases in knowledge relating to obesity, alcohol, breast density, menstruation, and the risk estimation process remained even when sociodemographic variables age and education were controlled. There were no significant changes in genetic testing interest post-exposure. Mean ratings for e-platform acceptability and usability were high: 26.19 out of 30 (SD 0.157) and 42.85 out of 50 (SD 0.267), respectively. Conclusions An informative breast cancer risk stratification e-platform targeting healthy women in the general population can significantly increase knowledge as well as support decisions around breast cancer risk and assessment. Currently underway, Phase 2, called PERSPECTIVE, is seeking further content integration and broader implementation .
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Affiliation(s)
- Saima Ahmed
- Division of Experimental Medicine, McGill University, Montréal, QC, Canada.,CIUSSS Centre-Ouest Montréal, Segal Cancer Centre, Jewish General Hospital, Montreal, QC, Canada
| | | | - Rosalind Garland
- Medical Surgical Intensive Care Unit, Jewish General Hospital, Montreal, QC, Canada
| | - Bartha Knoppers
- McGill University Centre of Genomics and Policy, Montréal, QC, Canada
| | - Michel Dorval
- Université Laval, Québec City, QC, Canada.,CHU de Québec-Université Laval Research Centre, Québec City, QC, Canada
| | - Jacques Simard
- Université Laval, Québec City, QC, Canada.,CHU de Québec-Université Laval Research Centre, Québec City, QC, Canada
| | - Carmen G Loiselle
- CIUSSS Centre-Ouest Montréal, Segal Cancer Centre, Jewish General Hospital, Montreal, QC, Canada. .,Department of Oncology and Ingram School of Nursing, Faculty of Medicine and Health Sciences, McGill University, 680 Sherbrooke Ouest, Office 1812, Montréal, QC, H3A 2M7, Canada.
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Guo J, Liu D, Zhang X, Johnson H, Feng X, Zhang H, Wu AHB, Chen L, Fang J, Xiao Z, Xiao K, Persson JL, Zou C. Establishing a Urine-Based Biomarker Assay for Prostate Cancer Risk Stratification. Front Cell Dev Biol 2020; 8:597961. [PMID: 33363151 PMCID: PMC7758396 DOI: 10.3389/fcell.2020.597961] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Accepted: 11/09/2020] [Indexed: 11/13/2022] Open
Abstract
One of the major features of prostate cancer (PCa) is its heterogeneity, which often leads to uncertainty in cancer diagnostics and unnecessary biopsies as well as overtreatment of the disease. Novel non-invasive tests using multiple biomarkers that can identify clinically high-risk cancer patients for immediate treatment and monitor patients with low-risk cancer for active surveillance are urgently needed to improve treatment decision and cancer management. In this study, we identified 14 promising biomarkers associated with PCa and tested the performance of these biomarkers on tissue specimens and pre-biopsy urinary sediments. These biomarkers showed differential gene expression in higher- and lower-risk PCa. The 14-Gene Panel urine test (PMP22, GOLM1, LMTK2, EZH2, GSTP1, PCA3, VEGFA, CST3, PTEN, PIP5K1A, CDK1, TMPRSS2, ANXA3, and CCND1) was assessed in two independent prospective and retrospective urine study cohorts and showed high diagnostic accuracy to identify higher-risk PCa patients with the need for treatment and lower-risk patients for surveillance. The AUC was 0.897 (95% CI 0.939–0.855) in the prospective cohort (n = 202), and AUC was 0.899 (95% CI 0.964–0.834) in the retrospective cohort (n = 97). In contrast, serum PSA and Gleason score had much lower accuracy in the same 202 patient cohorts [AUC was 0.821 (95% CI 0.879–0.763) for PSA and 0.860 (95% CI 0.910–0.810) for Gleason score]. In addition, the 14-Gene Panel was more accurate at risk stratification in a subgroup of patients with Gleason scores 6 and 7 in the prospective cohort (n = 132) with AUC of 0.923 (95% CI 0.968–0.878) than PSA [AUC of 0.773 (95% CI 0.852–0.794)] and Gleason score [AUC of 0.776 (95% CI 0.854–0.698)]. Furthermore, the 14-Gene Panel was found to be able to accurately distinguish PCa from benign prostate with AUC of 0.854 (95% CI 0.892–0.816) in a prospective urine study cohort (n = 393), while PSA had lower accuracy with AUC of 0.652 (95% CI 0.706–0.598). Taken together, the 14-Gene Panel urine test represents a promising non-invasive tool for detection of higher-risk PCa to aid treatment decision and lower-risk PCa for active surveillance.
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Affiliation(s)
- Jinan Guo
- Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, China.,The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Public Service Platform on Tumor Precision Medicine and Molecular Diagnosis, Shenzhen, China
| | - Dale Liu
- Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, China.,The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, China
| | - Xuhui Zhang
- Department of Bio-Diagnosis, Institute of Basic Medical Sciences, Beijing, China
| | | | - Xiaoyan Feng
- Department of Bio-Diagnosis, Institute of Basic Medical Sciences, Beijing, China
| | - Heqiu Zhang
- Department of Bio-Diagnosis, Institute of Basic Medical Sciences, Beijing, China
| | - Alan H B Wu
- Clinical Laboratories, San Francisco General Hospital, San Francisco, CA, United States
| | - Lingwu Chen
- Department of Urology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Jiequn Fang
- Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, China.,The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Public Service Platform on Tumor Precision Medicine and Molecular Diagnosis, Shenzhen, China
| | - Zhangang Xiao
- Laboratory of Molecular Pharmacology, Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, China
| | - Kefeng Xiao
- Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, China.,The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Public Service Platform on Tumor Precision Medicine and Molecular Diagnosis, Shenzhen, China
| | - Jenny L Persson
- Department of Molecular Biology, Umeå University, Umeå, Sweden.,Division of Experimental Cancer Research, Department of Translational Medicine, Lund University, Malmö, Sweden
| | - Chang Zou
- Shenzhen People's Hospital, The Second Clinical Medical College, Jinan University, Shenzhen, China.,The First Affiliated Hospital, Southern University of Science and Technology, Shenzhen, China.,Shenzhen Public Service Platform on Tumor Precision Medicine and Molecular Diagnosis, Shenzhen, China
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