- ICH GCP
- US Clinical Trials Registry
- Clinical Trial NCT06922708
Implementing Polygenic Risk Scores for Breast Cancer Prevention: a Feasibility Study (MIG)
Implementing Polygenic Risk Scores for Breast Cancer Prevention: Protocol for a Feasibility Study in a Real-world Clinical Setting
Study Overview
Status
Conditions
Intervention / Treatment
Detailed Description
This study will test the feasibility of integrating polygenic risk scores (PRS) into the CanRisk breast cancer risk model in a real-world clinical setting at Fondazione Policlinico Universitario Agostino Gemelli IRCCS. By embedding PRS testing into routine genetic counseling and patient care, the study aims to examine organizational, logistical, and patient-centered aspects of incorporating genomic data into breast cancer risk assessment.
Eligible participants include women with a family history of breast cancer, carriers of pathogenic variants included in CanRisk (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1), and women with unilateral breast cancer for controlateral risk assessment. Carriers of pathogenic variants not included in CanRisk (e.g., PTEN, TP53, CDH1) as well as women with bilateral breast cancer or ductal carcinoma in situ (DCIS), will be excluded, as CanRisk does not estimate risk for this condition.
All participants will provide a blood sample (9 mL in three K2EDTA tubes) for DNA extraction and SNP genotyping. PRS will be calculated using a 313-SNP array with ThermoFisher GeneTitan and the Axiom Precision Medicine Diversity Array, followed by standard quality control and genotype imputation. Results will be integrated into the CanRisk model previously calculated without PRS, to provide individualized risk estimates, in combination with clinical, anthropometric, and family history variables systematically collected for every participant.
Participants who request their CanRisk with PRS results will receive an email report approximately within one month of sample collection, summarizing their CanRisk estimates with and without PRS, and will be invited to complete a questionnaire on comprehension, perception, and emotional impact of the result. If the PRS leads to a change in risk classification, the case will be reviewed in a multidisciplinary discussion and the prevention plan may be modified accordingly. Participants who accept to be enrolled in the study but decline to receive their PRS results will be asked their reason, which will be documented verbatim.
Primary outcome:
Feasibility of CanRisk+PRS pathway assessment, measured by a 27-item Care Process Self-Evaluation Tool (CPSET) validated questionnaire, completed by both participants and healthcare staff at the end of the study.
Secondary outcomes:
- Uptake of CanRisk+PRS pathway
- Risk understanding and emotional impact, assessed using a validated questionnaire (Woof et al.)
- Risk reclassification rate, after PRS integration in the CanRisk model assessment
- Changes in breast cancer preventive pathway, recommended following multidisciplinary evaluation after CanRisk+PRS-based risk reclassification
- Impact on overall distribution across risk categories after PRS integration
This study will generate evidence on the clinical, technical, and organizational feasibility of integrating PRS into breast cancer risk assessment, informing the future implementation of personalized prevention programs.
Study Type
Enrollment (Estimated)
Phase
- Not Applicable
Contacts and Locations
Study Contact
- Name: Sara Farina, MD
- Phone Number: 0039 + 0630156808
- Email: sarafarins96@gmail.com
Study Contact Backup
- Name: Francesco A Causio, MD
- Email: francescoandrea.causio@unicatt.it
Study Locations
-
-
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Roma, Italy
- Recruiting
- Policlinico Universitario Fondazione Agostino Gemelli
-
Contact:
- Sara Farina, MD
- Phone Number: 063015
- Email: sara.farina@unicatt.it
-
-
Participation Criteria
Eligibility Criteria
Ages Eligible for Study
- Adult
- Older Adult
Accepts Healthy Volunteers
Description
Inclusion Criteria:
- Ability to provide informed consent
- Voluntary consent to participate
- Estimated risk of carrying an inherited pathogenic variant (in BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1) > 5%, (calculated on www.canrisk.org)
Healthy women with:
- Known family history of breast cancer, or
- Known familiarity with carriers of pathogenic variants for genes included in the CanRisk model (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1), or
- Known carriers of pathogenic variants for genes included in the CanRisk model (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1)
Affected women with:
- Diagnosis of unilateral breast cancer
- Personal history of ovarian cancer
Exclusion Criteria:
- Diagnosis or history of bilateral breast cancer
- Diagnosis of ductal carcinoma in situ
- Previous bilateral mastectomy
- Life expectancy < 12 months due to other medical conditions
- Participation in interventional clinical trials for breast cancer prevention in the last 12 months
- Carriers or relatives of carriers of pathogenic variants in genes not included in the CanRisk model (genes other than BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1)
- Inability to provide informed consent
Study Plan
How is the study designed?
Design Details
- Primary Purpose: Prevention
- Allocation: N/A
- Interventional Model: Single Group Assignment
- Masking: None (Open Label)
Arms and Interventions
Participant Group / Arm |
Intervention / Treatment |
|---|---|
|
Experimental: Integrated PRS-enhanced breast cancer risk assessment
Women attending a Medical Genetics Clinic for breast cancer risk assessment, all undergoing CanRisk evaluation with and without PRS, without allocation to different interventions.
|
Standard genetic counseling followed by a blood draw (0.5 mL) for DNA extraction.
The sample is processed using a high-throughput SNP genotyping platform, and the PRS, based on 313 SNPs, is calculated and integrated into the CanRisk model for refined breast cancer risk stratification.
In conjunction with result disclosure, participants complete structured questionnaires to assess psychological impact and risk comprehension (questionnaire by Woof et al.).
At the end of the study, both participants and healthcare professionals complete feasibility questionnaires to evaluate the implementation of the PRS-integrated clinical pathway (Care Process Self-Evaluation Tool, CPSET; Vanhaecht et al.).
|
What is the study measuring?
Primary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Feasibility of implementing an integrated clinical pathway including PRS
Time Frame: At 12 months from enrollment
|
The primary outcome is the feasibility of integrating polygenic risk score (PRS) testing into the CanRisk breast cancer risk model within a structured clinical pathway.
Feasibility will be assessed using the Care Process Self-Evaluation Tool (CPSET), that includes 27 items across 5 domains: patient-centeredness, coordination of care, communication, cooperation, and monitoring/follow-up.
The questionnaire will be administered at the end of the study to both enrolled women and involved healthcare professionals.
|
At 12 months from enrollment
|
Secondary Outcome Measures
Outcome Measure |
Measure Description |
Time Frame |
|---|---|---|
|
Uptake of CanRisk+PRS integrated pathway
Time Frame: At the time of enrollment, when eligible participants are offered PRS testing
|
Proportion of women accepting PRS testing among those offered: (Number accepting PRS / Number offered PRS) × 100 |
At the time of enrollment, when eligible participants are offered PRS testing
|
|
Proportion of women requesting their individual CanRisk+PRS result
Time Frame: At month 12.
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The percentage of enrolled women who actively request to receive their individualized breast cancer risk estimate generated by the CanRisk model integrated with PRS.
This outcome will measure the degree of patient interest in receiving personalized genomic risk information.
|
At month 12.
|
|
Percentage of women reclassified into different risk categories after PRS integration
Time Frame: At month 12
|
The percentage of women whose risk category (low, moderate, or high) changes when PRS information is added to their baseline CanRisk estimate.
This outcome will assess the clinical utility of PRS in refining breast cancer risk stratification and identifying women who may benefit from adjusted preventive strategies.
|
At month 12
|
|
Proportion of women with modified prevention pathways after PRS-informed reclassification
Time Frame: At month 12.
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The percentage of women whose preventive or follow-up pathway is modified following a multidisciplinary team review prompted by PRS-informed risk reclassification.
This outcome will capture the practical impact of PRS integration on clinical decision-making and preventive care planning.
|
At month 12.
|
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Perception of risk and psychological impact
Time Frame: At month 12
|
Evaluation of women's understanding and perception of their personal breast cancer risk, as well as the emotional and psychological impact of risk communication, after receiving their CanRisk+PRS result.
This will be assessed using the validated questionnaire by Woof et al., which specifically measures comprehension of risk estimates and associated emotional responses.
|
At month 12
|
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Global redistribution of risk categories after PRS integration
Time Frame: At month 12.
|
The overall distribution of women across predefined breast cancer risk categories (low, moderate, high) before and after incorporating PRS into CanRisk.
This outcome will provide a population-level view of how PRS influences breast cancer risk stratification and the extent of shifts in the global risk profile of the cohort.
|
At month 12.
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Collaborators and Investigators
Collaborators
Investigators
- Principal Investigator: Stefania Boccia, Phd, Life Sciences and Public Health Department, Università Cattolica del Sacro Cuore, Rome, Italy
Publications and helpful links
General Publications
- Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021 May;71(3):209-249. doi: 10.3322/caac.21660. Epub 2021 Feb 4.
- Vanhaecht K, De Witte K, Depreitere R, Van Zelm R, De Bleser L, Proost K, Sermeus W. Development and validation of a care process self-evaluation tool. Health Serv Manage Res. 2007 Aug;20(3):189-202. doi: 10.1258/095148407781395964.
- Du Z, Gao G, Adedokun B, Ahearn T, Lunetta KL, Zirpoli G, Troester MA, Ruiz-Narvaez EA, Haddad SA, PalChoudhury P, Figueroa J, John EM, Bernstein L, Zheng W, Hu JJ, Ziegler RG, Nyante S, Bandera EV, Ingles SA, Mancuso N, Press MF, Deming SL, Rodriguez-Gil JL, Yao S, Ogundiran TO, Ojengbe O, Bolla MK, Dennis J, Dunning AM, Easton DF, Michailidou K, Pharoah PDP, Sandler DP, Taylor JA, Wang Q, Weinberg CR, Kitahara CM, Blot W, Nathanson KL, Hennis A, Nemesure B, Ambs S, Sucheston-Campbell LE, Bensen JT, Chanock SJ, Olshan AF, Ambrosone CB, Olopade OI, Yarney J, Awuah B, Wiafe-Addai B, Conti DV; GBHS Study Team; Palmer JR, Garcia-Closas M, Huo D, Haiman CA. Evaluating Polygenic Risk Scores for Breast Cancer in Women of African Ancestry. J Natl Cancer Inst. 2021 Sep 4;113(9):1168-1176. doi: 10.1093/jnci/djab050.
- Lakeman IMM, Rodriguez-Girondo M, Lee A, Ruiter R, Stricker BH, Wijnant SRA, Kavousi M, Antoniou AC, Schmidt MK, Uitterlinden AG, van Rooij J, Devilee P. Validation of the BOADICEA model and a 313-variant polygenic risk score for breast cancer risk prediction in a Dutch prospective cohort. Genet Med. 2020 Nov;22(11):1803-1811. doi: 10.1038/s41436-020-0884-4. Epub 2020 Jul 6.
- Archer S, Donoso FS, Carver T, Yue A, Cunningham AP, Ficorella L, Tischkowitz M, Easton DF, Antoniou AC, Emery J, Usher-Smith J, Walter FM. Exploring the barriers to and facilitators of implementing CanRisk in primary care: a qualitative thematic framework analysis. Br J Gen Pract. 2023 Jul 27;73(733):e586-e596. doi: 10.3399/BJGP.2022.0643. Print 2023 Aug.
- Vassy JL, Brunette CA, Lebo MS, MacIsaac K, Yi T, Danowski ME, Alexander NVJ, Cardellino MP, Christensen KD, Gala M, Green RC, Harris E, Jones NE, Kerman BJ, Kraft P, Kulkarni P, Lewis ACF, Lubitz SA, Natarajan P, Antwi AA. The GenoVA study: Equitable implementation of a pragmatic randomized trial of polygenic-risk scoring in primary care. Am J Hum Genet. 2023 Nov 2;110(11):1841-1852. doi: 10.1016/j.ajhg.2023.10.001.
- Tsoulaki O, Tischkowitz M, Antoniou AC, Musgrave H, Rea G, Gandhi A, Cox K, Irvine T, Holcombe S, Eccles D, Turnbull C, Cutress R; Meeting Attendees; Archer S, Hanson H. Joint ABS-UKCGG-CanGene-CanVar consensus regarding the use of CanRisk in clinical practice. Br J Cancer. 2024 Jun;130(12):2027-2036. doi: 10.1038/s41416-024-02733-4. Epub 2024 Jun 4.
- Mbuya-Bienge C, Pashayan N, Kazemali CD, Lapointe J, Simard J, Nabi H. A Systematic Review and Critical Assessment of Breast Cancer Risk Prediction Tools Incorporating a Polygenic Risk Score for the General Population. Cancers (Basel). 2023 Nov 12;15(22):5380. doi: 10.3390/cancers15225380.
- Hovhannisyan M, Zemankova P, Nehasil P, Matejkova K, Borecka M, Cerna M, Dolezalova T, Dvorakova L, Foretova L, Horackova K, Jelinkova S, Just P, Kalousova M, Kral J, Machackova E, Nemcova B, Safarikova M, Springer D, Stastna B, Tavandzis S, Vocka M, Zima T, Soukupova J, Kleiblova P, Ernst C, Kleibl Z, Janatova M. Population-specific validation and comparison of the performance of 77- and 313-variant polygenic risk scores for breast cancer risk prediction. Cancer. 2024 Sep 1;130(17):2978-2987. doi: 10.1002/cncr.35337. Epub 2024 May 8.
- Yang X, Eriksson M, Czene K, Lee A, Leslie G, Lush M, Wang J, Dennis J, Dorling L, Carvalho S, Mavaddat N, Simard J, Schmidt MK, Easton DF, Hall P, Antoniou AC. Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study. J Med Genet. 2022 Dec;59(12):1196-1205. doi: 10.1136/jmg-2022-108806. Epub 2022 Sep 26.
- Canelo-Aybar C, Posso M, Montero N, Sola I, Saz-Parkinson Z, Duffy SW, Follmann M, Grawingholt A, Giorgi Rossi P, Alonso-Coello P. Benefits and harms of annual, biennial, or triennial breast cancer mammography screening for women at average risk of breast cancer: a systematic review for the European Commission Initiative on Breast Cancer (ECIBC). Br J Cancer. 2022 Mar;126(4):673-688. doi: 10.1038/s41416-021-01521-8. Epub 2021 Nov 26.
- Visvanathan K. USPSTF recommends biennial mammography for breast cancer screening in women aged 40 to 74 y. Ann Intern Med. 2024 Oct;177(10):JC110. doi: 10.7326/ANNALS-24-02229-JC. Epub 2024 Oct 1.
- Lee A, Mavaddat N, Wilcox AN, Cunningham AP, Carver T, Hartley S, Babb de Villiers C, Izquierdo A, Simard J, Schmidt MK, Walter FM, Chatterjee N, Garcia-Closas M, Tischkowitz M, Pharoah P, Easton DF, Antoniou AC. BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors. Genet Med. 2019 Aug;21(8):1708-1718. doi: 10.1038/s41436-018-0406-9. Epub 2019 Jan 15.
- Qaseem A, Lin JS, Mustafa RA, Horwitch CA, Wilt TJ; Clinical Guidelines Committee of the American College of Physicians; Forciea MA, Fitterman N, Iorio A, Kansagara D, Maroto M, McLean RM, Tufte JE, Vijan S. Screening for Breast Cancer in Average-Risk Women: A Guidance Statement From the American College of Physicians. Ann Intern Med. 2019 Apr 16;170(8):547-560. doi: 10.7326/M18-2147. Epub 2019 Apr 9.
Study record dates
Study Major Dates
Study Start (Actual)
Primary Completion (Estimated)
Study Completion (Estimated)
Study Registration Dates
First Submitted
First Submitted That Met QC Criteria
First Posted (Actual)
Study Record Updates
Last Update Posted (Actual)
Last Update Submitted That Met QC Criteria
Last Verified
More Information
Terms related to this study
Keywords
Additional Relevant MeSH Terms
- Pathologic Processes
- Neoplasms by Site
- Neoplasms
- Disease Attributes
- Skin Diseases
- Breast Diseases
- Disease Susceptibility
- Genetic Predisposition to Disease
- Pathological Conditions, Signs and Symptoms
- Skin and Connective Tissue Diseases
- Genetic Risk Score
- Breast Neoplasms
- Health Services Administration
- Patient Care Management
- Patient Care Planning
- Comprehensive Health Care
- Critical Pathways
Other Study ID Numbers
- 7310
- No. D.D. 931 (Other Grant/Funding Number: Italian National Complementary Plan PNC)
Plan for Individual participant data (IPD)
Plan to Share Individual Participant Data (IPD)?
IPD Plan Description
IPD Sharing Time Frame
IPD Sharing Access Criteria
IPD Sharing Supporting Information Type
- STUDY_PROTOCOL
- SAP
- ICF
Drug and device information, study documents
Studies a U.S. FDA-regulated drug product
Studies a U.S. FDA-regulated device product
product manufactured in and exported from the U.S.
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