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Hopper JL, Li S, MacInnis RJ, Dowty JG, Nguyen TL, Bui M, Dite GS, Esser VFC, Ye Z, Makalic E, Schmidt DF, Goudey B, Alpen K, Kapuscinski M, Win AK, Dugué PA, Milne RL, Jayasekara H, Brooks JD, Malta S, Calais-Ferreira L, Campbell AC, Young JT, Nguyen-Dumont T, Sung J, Giles GG, Buchanan D, Winship I, Terry MB, Southey MC, Jenkins MA. Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies. Genet Epidemiol 2024. [PMID: 38504141 DOI: 10.1002/gepi.22555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/29/2024] [Accepted: 02/23/2024] [Indexed: 03/21/2024]
Abstract
Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.
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Affiliation(s)
- John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Minh Bui
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Genetic Technologies Ltd., Fitzroy, Victoria, Australia
| | - Vivienne F C Esser
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Zhoufeng Ye
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Daniel F Schmidt
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia
| | - Benjamin Goudey
- ARC Training Centre in Cognitive Computing for Medical Technologies, University of Melbourne, Carlton, Victoria, Australia
- The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Karen Alpen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Miroslaw Kapuscinski
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Aung Ko Win
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
- Genetic Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Pierre-Antoine Dugué
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Harindra Jayasekara
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Jennifer D Brooks
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Sue Malta
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Lucas Calais-Ferreira
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Alexander C Campbell
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia
| | - Jesse T Young
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia
- Justice Health Group, Curtin School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Tu Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Joohon Sung
- Department of Public Health Sciences, Division of Genome and Health Big Data, Graduate School of Public Health, Seoul National University, Seoul, South Korea
- Genome Medicine Institute, Seoul National University, Seoul, South Korea
- Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Daniel Buchanan
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Ingrid Winship
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
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2
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Abstract
Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.
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Affiliation(s)
- Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D P Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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3
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Saya S, Boyd L, Chondros P, McNamara M, King M, Milton S, Lourenco RDA, Clark M, Fishman G, Marker J, Ostroff C, Allman R, Walter FM, Buchanan D, Winship I, McIntosh J, Macrae F, Jenkins M, Emery J. The SCRIPT trial: study protocol for a randomised controlled trial of a polygenic risk score to tailor colorectal cancer screening in primary care. Trials 2022; 23:810. [PMID: 36163034 PMCID: PMC9513012 DOI: 10.1186/s13063-022-06734-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Accepted: 09/12/2022] [Indexed: 11/10/2022] Open
Abstract
Background Polygenic risk scores (PRSs) can predict the risk of colorectal cancer (CRC) and target screening more precisely than current guidelines using age and family history alone. Primary care, as a far-reaching point of healthcare and routine provider of cancer screening and risk information, may be an ideal location for their widespread implementation. Methods This trial aims to determine whether the SCRIPT intervention results in more risk-appropriate CRC screening after 12 months in individuals attending general practice, compared with standard cancer risk reduction information. The SCRIPT intervention consists of a CRC PRS, tailored risk-specific screening recommendations and a risk report for participants and their GP, delivered in general practice. Patients aged between 45 and 70 inclusive, attending their GP, will be approached for participation. For those over 50, only those overdue for CRC screening will be eligible to participate. Two hundred and seventy-four participants will be randomised to the intervention or control arms, stratified by general practice, using a computer-generated allocation sequence. The primary outcome is risk-appropriate CRC screening after 12 months. For those in the intervention arm, risk-appropriate screening is defined using PRS-derived risk; for those in the control arm, it is defined using family history and national screening guidelines. Timing, type and results of the previous screening are considered in both arms. Objective health service data will capture screening behaviour. Secondary outcomes include cancer-specific worry, risk perception, predictors of CRC screening behaviour, screening intentions and health service use at 1, 6 and 12 months post-intervention delivery. Discussion This trial aims to determine whether a PRS-derived personalised CRC risk estimate delivered in primary care increases risk-appropriate CRC screening. A future population risk-stratified CRC screening programme could incorporate risk assessment within primary care while encouraging adherence to targeted screening recommendations. Trial registration Australian and New Zealand Clinical Trial Registry ACTRN12621000092897p. Registered on 1 February 2021. Supplementary Information The online version contains supplementary material available at 10.1186/s13063-022-06734-7.
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Affiliation(s)
- Sibel Saya
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia. .,Centre for Cancer Research, University of Melbourne, Melbourne, Australia.
| | - Lucy Boyd
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Patty Chondros
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia
| | - Mairead McNamara
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Michelle King
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Shakira Milton
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
| | - Richard De Abreu Lourenco
- Centre for Health Economics Research and Evaluation, University of Technology Sydney, Sydney, Australia
| | | | - George Fishman
- Consumer Advisory Group, Primary Care Collaborative Cancer Clinical Trials Group, Carlton, Australia
| | - Julie Marker
- Consumer Advisory Group, Primary Care Collaborative Cancer Clinical Trials Group, Carlton, Australia
| | - Cheri Ostroff
- Centre for Workplace Excellence, University of South Australia, Adelaide, Australia
| | - Richard Allman
- Genetic Technologies/Phenogen Sciences, Fitzroy, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - Fiona M Walter
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Wolfson Institute of Population Health, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Daniel Buchanan
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia.,Department of Clinical Pathology, University of Melbourne, Melbourne, Australia
| | - Ingrid Winship
- Department of Medicine, Melbourne Medical School, University of Melbourne, Melbourne, Australia.,Genetic Medicine, Royal Melbourne Hospital, Melbourne, Australia
| | - Jennifer McIntosh
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,HumaniSE Lab, Department of Software Systems and Cybersecurity, Monash University, Clayton, Australia
| | - Finlay Macrae
- Department of Medicine, Melbourne Medical School, University of Melbourne, Melbourne, Australia.,Colorectal Medicine and Genetics, The Royal Melbourne Hospital, Melbourne, Australia
| | - Mark Jenkins
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia.,Centre for Epidemiology and Biostatistics, The University of Melbourne, Melbourne, Australia
| | - Jon Emery
- Primary Care Cancer Research Group, Department of General Practice, Centre for Cancer Research, The University of Melbourne, Victorian Comprehensive Cancer Centre, Level 10, 305 Grattan Street, Melbourne, Victoria, 3000, Australia.,Centre for Cancer Research, University of Melbourne, Melbourne, Australia
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4
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Milton S, Emery JD, Rinaldi J, Kinder J, Bickerstaffe A, Saya S, Jenkins MA, McIntosh J. Exploring a novel method for optimising the implementation of a colorectal cancer risk prediction tool into primary care: a qualitative study. Implement Sci 2022; 17:31. [PMID: 35550164 PMCID: PMC9097304 DOI: 10.1186/s13012-022-01205-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Accepted: 04/14/2022] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND We developed a colorectal cancer risk prediction tool ('CRISP') to provide individualised risk-based advice for colorectal cancer screening. Using known environmental, behavioural, and familial risk factors, CRISP was designed to facilitate tailored screening advice to patients aged 50 to 74 years in general practice. In parallel to a randomised controlled trial of the CRISP tool, we developed and evaluated an evidence-based implementation strategy. METHODS Qualitative methods were used to explore the implementation of CRISP in general practice. Using one general practice in regional Victoria, Australia, as a 'laboratory', we tested ways to embed CRISP into routine clinical practice. General practitioners, nurses, and operations manager co-designed the implementation methods with researchers, focussing on existing practice processes that would be sustainable. Researchers interviewed the staff regularly to assess the successfulness of the strategies employed, and implementation methods were adapted throughout the study period in response to feedback from qualitative interviews. The Consolidated Framework for Implementation Research (CFIR) underpinned the development of the interview guide and intervention strategy. Coding was inductive and themes were developed through consensus between the authors. Emerging themes were mapped onto the CFIR domains and a fidelity checklist was developed to ensure CRISP was being used as intended. RESULTS Between December 2016 and September 2019, 1 interviews were conducted, both face-to-face and via videoconferencing (Zoom). All interviews were transcribed verbatim and coded. Themes were mapped onto the following CFIR domains: (1) 'characteristics of the intervention': CRISP was valued but time consuming; (2) 'inner setting': the practice was open to changing systems; 3. 'outer setting': CRISP helped facilitate screening; (4) 'individual characteristics': the practice staff were adaptable and able to facilitate adoption of new clinical processes; and (5) 'processes': fidelity checking, and education was important. CONCLUSIONS These results describe a novel method for exploring implementation strategies for a colorectal cancer risk prediction tool in the context of a parallel RCT testing clinical efficacy. The study identified successful and unsuccessful implementation strategies using an adaptive methodology over time. This method emphasised the importance of co-design input to make an intervention like CRISP sustainable for use in other practices and with other risk tools.
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Affiliation(s)
- Shakira Milton
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
| | - Jon D. Emery
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
- The Primary Care Unit, Institute of Public Health, University of Cambridge School of Clinical Medicine, Box 113, Cambridge Biomedical Campus, Cambridge, CB2 0SR UK
| | - Jane Rinaldi
- University of Melbourne Shepparton Medical Centre, Melbourne Teaching Health Clinics Ltd, 49 Graham Street, Shepparton, VIC 3630 Australia
| | - Joanne Kinder
- University of Melbourne Shepparton Medical Centre, Melbourne Teaching Health Clinics Ltd, 49 Graham Street, Shepparton, VIC 3630 Australia
| | - Adrian Bickerstaffe
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria Australia
| | - Sibel Saya
- Centre for Cancer Research, University of Melbourne, Melbourne, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
| | - Mark A. Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Victoria Australia
| | - Jennifer McIntosh
- Department of General Practice, University of Melbourne, Melbourne, Australia
- HumaniSE Lab, Department of Software Systems and Cybersecurity, Monash University, Clayton, Victoria Australia
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Milton S, McIntosh J, Boyd L, Karnchanachari N, Macrae F, Emery JD. Commentary: Pivoting during a pandemic: developing a new recruitment model for a randomised controlled trial in response to COVID-19. Trials 2021; 22:605. [PMID: 34496930 PMCID: PMC8424147 DOI: 10.1186/s13063-021-05567-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2021] [Accepted: 08/24/2021] [Indexed: 11/25/2022] Open
Abstract
BACKGROUND Many non-COVID-19 trials were disrupted in 2020 and either struggled to recruit participants or stopped recruiting altogether. In December 2019, just before the pandemic, we were awarded a grant to conduct a randomised controlled trial, the Should I Take Aspirin? (SITA) trial, in Victoria, the Australian state most heavily affected by COVID-19 during 2020. MAIN BODY We originally modelled the SITA trial recruitment method on previous trials where participants were approached and recruited in general practice waiting rooms. COVID-19 changed the way general practices worked, with a significant increase in telehealth consultations and restrictions on in person waiting room attendance. This prompted us to adapt our recruitment methods to this new environment to reduce potential risk to participants and staff, whilst minimising any recruitment bias. We designed a novel teletrial model, which involved calling participants prior to their general practitioner appointments to check their eligibility. We delivered the trial both virtually and face-to-face with similar overall recruitment rates to our previous studies. CONCLUSION We developed an effective teletrial model which allowed us to complete recruitment at a high rate. The teletrial model is now being used in our other primary care trials as we continue to face the impacts of the COVID-19 pandemic.
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Affiliation(s)
- Shakira Milton
- Centre for Cancer Research, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3000, Australia.
- Department of General Practice, University of Melbourne, Melbourne, Australia.
| | - Jennifer McIntosh
- Department of General Practice, University of Melbourne, Melbourne, Australia
- HumaniSE Lab, Department of Software Systems and Cybersecurity, Monash University, Melbourne, Victoria, Australia
| | - Lucy Boyd
- Centre for Cancer Research, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3000, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
| | - Napin Karnchanachari
- Centre for Cancer Research, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3000, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
| | - Finlay Macrae
- Department of Medicine, The University of Melbourne, Melbourne, Australia
- Colorectal Medicine and Genetics, The Royal Melbourne Hospital, Melbourne, Australia
| | - Jon David Emery
- Centre for Cancer Research, University of Melbourne, Level 10, 305 Grattan Street, Melbourne, VIC, 3000, Australia
- Department of General Practice, University of Melbourne, Melbourne, Australia
- The Primary Care Unit, University of Cambridge, Cambridge, UK
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Dunlop K, Rankin NM, Smit AK, Salgado Z, Newson AJ, Keogh L, Cust AE. Acceptability of risk-stratified population screening across cancer types: Qualitative interviews with the Australian public. Health Expect 2021; 24:1326-1336. [PMID: 33974726 PMCID: PMC8369084 DOI: 10.1111/hex.13267] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/12/2021] [Accepted: 04/10/2021] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND There is mounting evidence of the benefit of risk-stratified (risk-tailored) cancer population screening, when compared to standard approaches. However, shifting towards this approach involves changes to practice that may give rise to implementation challenges. OBJECTIVES To explore the public's potential acceptance of risk-stratified screening across different cancer types, including reducing screening frequency if at low risk and the use of personal risk information, to inform implementation strategies. METHOD Semi-structured interviews were conducted with 40 public participants; half had received personal genomic risk information and half had not. Participants were prompted to consider different cancers. Data were analysed thematically as one dataset. RESULTS Themes included the following: (a) a sense of security; (b) tailored screening is common sense; (c) risk and the need to take action; (d) not every cancer is the same; and (e) trust and belief in health messages. Both groups expressed similar views. Participants were broadly supportive of risk-stratified screening across different cancer types, with strong support for increased screening frequency for high-risk groups. They were less supportive of reduced screening frequency or no screening for low-risk groups. Findings suggest the public will be amenable to reducing screening when the test is invasive and uncomfortable; be less opposed to forgo screening if offered the opportunity to screen at some stage; and view visible cancers such as melanoma differently. CONCLUSIONS Approaching distinct cancer types differently, tailoring messages for different audiences and understanding reasons for participating in screening may assist with designing future implementation strategies for risk-stratified cancer screening.
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Affiliation(s)
- Kate Dunlop
- Daffodil CentreThe University of Sydney, a joint venture with Cancer Council NSWSydneyNSWAustralia
- Melanoma Institute AustraliaThe University of SydneySydneyNSWAustralia
| | - Nicole M. Rankin
- Sydney School of Public Health, The Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
| | - Amelia K. Smit
- Daffodil CentreThe University of Sydney, a joint venture with Cancer Council NSWSydneyNSWAustralia
- Melanoma Institute AustraliaThe University of SydneySydneyNSWAustralia
| | - Zofia Salgado
- Daffodil CentreThe University of Sydney, a joint venture with Cancer Council NSWSydneyNSWAustralia
| | - Ainsley J. Newson
- Sydney Health Ethics, Sydney School of Public Health, The Faculty of Medicine and HealthThe University of SydneySydneyNSWAustralia
| | - Louise Keogh
- Melbourne School of Population and Global HealthThe University of MelbourneMelbourneVICAustralia
| | - Anne E. Cust
- Daffodil CentreThe University of Sydney, a joint venture with Cancer Council NSWSydneyNSWAustralia
- Melanoma Institute AustraliaThe University of SydneySydneyNSWAustralia
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An RCT of a decision aid to support informed choices about taking aspirin to prevent colorectal cancer and other chronic diseases: a study protocol for the SITA (Should I Take Aspirin?) trial. Trials 2021; 22:452. [PMID: 34266464 PMCID: PMC8280579 DOI: 10.1186/s13063-021-05365-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Accepted: 06/09/2021] [Indexed: 12/21/2022] Open
Abstract
Background Australian guidelines recommend that all people aged 50–70 years old actively consider taking daily low-dose aspirin (100–300 mg per day) for 2.5 to 5 years to reduce their risk of colorectal cancer (CRC). Despite the change of national CRC prevention guidelines, there has been no active implementation of the guidelines into clinical practice. We aim to test the efficacy of a health consultation and decision aid, using a novel expected frequency tree (EFT) to present the benefits and harms of low dose aspirin prior to a general practice consultation with patients aged 50–70 years, on informed decision-making and uptake of aspirin. Methods Approximately five to seven general practices in Victoria, Australia, will be recruited to participate. Patients 50–70 years old, attending an appointment with their general practitioner (GP) for any reason, will be invited to participate in the trial. Two hundred fifty-eight eligible participants will be randomly allocated 1:1 to intervention or active control arms using a computer-generated allocation sequence stratified by general practice, sex, and mode of trial delivery (face-to-face or teletrial). There are two co-primary outcomes: informed decision-making at 1-month post randomisation, measured by the Multi-dimensional Measure of Informed Choice (MMIC), and self-reported daily use of aspirin at 6 months. Secondary outcomes include decisional conflict at 1-month and other behavioural changes to reduce CRC risk at both time points. Discussion This trial will test the efficacy of novel methods for implementing national guidelines to support informed decision-making about taking aspirin in 50–70-year-olds to reduce the risk of CRC and other chronic diseases. Trial registration The Australian New Zealand Clinical Trials Registry (ANZCTR) ACTRN12620001003965. Registered on 10 October 2020. Supplementary Information The online version contains supplementary material available at 10.1186/s13063-021-05365-8.
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8
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Eysenbach G. Adherence of Internet-Based Cancer Risk Assessment Tools to Best Practices in Risk Communication: Content Analysis. J Med Internet Res 2021; 23:e23318. [PMID: 33492238 PMCID: PMC7870349] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 11/19/2020] [Accepted: 12/19/2020] [Indexed: 10/31/2022] Open
Abstract
BACKGROUND Internet-based risk assessment tools offer a potential avenue for people to learn about their cancer risk and adopt risk-reducing behaviors. However, little is known about whether internet-based risk assessment tools adhere to scientific evidence for what constitutes good risk communication strategies. Furthermore, their quality may vary from a user experience perspective. OBJECTIVE This study aims to understand the extent to which current best practices in risk communication have been applied to internet-based cancer risk assessment tools. METHODS We conducted a search on August 6, 2019, to identify websites that provided personalized assessments of cancer risk or the likelihood of developing cancer. Each website (N=39) was coded according to standardized criteria and focused on 3 categories: general website characteristics, accessibility and credibility, and risk communication formats and strategies. RESULTS Some best practices in risk communication were more frequently adhered to by websites. First, we found that undefined medical terminology was widespread, impeding comprehension for those with limited health literacy. For example, 90% (35/39) of websites included technical language that the general public may find difficult to understand, yet only 23% (9/39) indicated that medical professionals were their intended audience. Second, websites lacked sufficient information for users to determine the credibility of the risk assessment, making it difficult to judge the scientific validity of their risk. For instance, only 59% (23/39) of websites referenced the scientific model used to calculate the user's cancer risk. Third, practices known to foster unbiased risk comprehension, such as adding qualitative labels to quantitative numbers, were used by only 15% (6/39) of websites. CONCLUSIONS Limitations in risk communication strategies used by internet-based cancer risk assessment tools were common. By observing best practices, these tools could limit confusion and cultivate understanding to help people make informed decisions and motivate people to engage in risk-reducing behaviors.
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Saya S, Emery JD, Dowty JG, McIntosh JG, Winship IM, Jenkins MA. The Impact of a Comprehensive Risk Prediction Model for Colorectal Cancer on a Population Screening Program. JNCI Cancer Spectr 2020; 4:pkaa062. [PMID: 33134836 PMCID: PMC7583148 DOI: 10.1093/jncics/pkaa062] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Revised: 06/17/2020] [Accepted: 07/01/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND In many countries, population colorectal cancer (CRC) screening is based on age and family history, though more precise risk prediction could better target screening. We examined the impact of a CRC risk prediction model (incorporating age, sex, lifestyle, genomic, and family history factors) to target screening under several feasible screening scenarios. METHODS We estimated the model's predicted CRC risk distribution in the Australian population. Predicted CRC risks were categorized into screening recommendations under 3 proposed scenarios to compare with current recommendations: 1) highly tailored, 2) 3 risk categories, and 3) 4 sex-specific risk categories. Under each scenario, for 35- to 74-year-olds, we calculated the number of CRC screens by immunochemical fecal occult blood testing (iFOBT) and colonoscopy and the proportion of predicted CRCs over 10 years in each screening group. RESULTS Currently, 1.1% of 35- to 74-year-olds are recommended screening colonoscopy and 56.2% iFOBT, and 5.7% and 83.2% of CRCs over 10 years were predicted to occur in these groups, respectively. For the scenarios, 1) colonoscopy was recommended to 8.1% and iFOBT to 37.5%, with 36.1% and 50.1% of CRCs in each group; 2) colonoscopy was recommended to 2.4% and iFOBT to 56.0%, with 13.2% and 76.9% of cancers in each group; and 3) colonoscopy was recommended to 5.0% and iFOBT to 54.2%, with 24.5% and 66.5% of cancers in each group. CONCLUSIONS A highly tailored CRC screening scenario results in many fewer screens but more cancers in those unscreened. Category-based scenarios may provide a good balance between number of screens and cancers detected and are simpler to implement.
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Affiliation(s)
- Sibel Saya
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Jon D Emery
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
| | - Jennifer G McIntosh
- Department of General Practice and Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Ingrid M Winship
- Genomic Medicine and Family Cancer Clinic, Royal Melbourne Hospital, Melbourne, Australia
- Department of Medicine, Faculty of Medicine, Dentistry and Health Sciences, University of Melbourne, Melbourne, Australia
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Melbourne, Australia
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Waters EA, Foust JL, Scherer LD, McQueen A, Taber JM. To what extent do Internet-based cancer risk assessment tools adhere to best practices in risk communication: A content analysis (Preprint). J Med Internet Res 2020. [DOI: 10.2196/23318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
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Harty EC, McIntosh JG, Bickerstaffe A, Hewabandu N, Emery JD. The CRISP-P study: feasibility of a self-completed colorectal cancer risk prediction tool in primary care. Fam Pract 2019; 36:730-735. [PMID: 31237329 DOI: 10.1093/fampra/cmz029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/14/2023] Open
Abstract
OBJECTIVE Australia and New Zealand have the highest incidence of colorectal cancer (CRC) globally. Our research team has developed a CRC risk prediction tool for use in primary care to increase targeted screening. This study, Colorectal cancer RISk Prediction tool - patient ('CRISP-P'), aimed to determine the following to inform a future trial design: (i) the feasibility of self-reporting; (ii) the feasibility of recruitment methods; and (iii) the prevalence of CRC risk. METHODS Participants aged between 40 and 75 years were recruited consecutively from three primary care waiting rooms. Participants input data into CRISP on a tablet without receiving clinical advice. Feasibility was evaluated using recruitment rate, timely completion, a self-reported 'ease-of-use', score and field notes. Prevalence of CRC risk was calculated using the CRISP model. RESULTS Five hundred sixty-one (90%) patients agreed to use the tool and 424 (84%) rated the tool easy to use. Despite this, 41% of people were unable to complete the questions without assistance. Patients who were older, without tertiary education or with English as their second language were more likely to require assistance (P < 0.001). Thirty-nine percent of patients were low risk, 58% at slightly increased and 2.4% were at moderately increased risk of developing colorectal cancer in the next 5 years. CONCLUSIONS The tool was perceived as easy to use, although older, less educated people, and patients with English as their second language needed help. The data support the recruitment methods but not the use of a self-completed tool for an efficacy trial.
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Affiliation(s)
- Elena C Harty
- Department of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, Victorian Comprehensive Cancer Centre, University of Melbourne, Victoria, Australia
| | - Jennifer G McIntosh
- Department of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, Victorian Comprehensive Cancer Centre, University of Melbourne, Victoria, Australia
| | - Adrian Bickerstaffe
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
| | - Nadira Hewabandu
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Victoria, Australia
| | - Jon D Emery
- Department of General Practice, Centre for Cancer Research, Faculty of Medicine, Dentistry and Health Sciences, Victorian Comprehensive Cancer Centre, University of Melbourne, Victoria, Australia
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