ClinicalTrials.gg
RecruitingNCT06922708MIGUpdated Aug 3, 2026

Implementing Polygenic Risk Scores for Breast Cancer Prevention: a Feasibility Study

An interventional study of Clinical pathway for breast cancer prevention based on PRS-integrated CanRisk assessment in Breast Cancer, sponsored by Catholic University of the Sacred Heart. Recruiting at 1 site in Italy. Open to female participants aged 18 Years to 79 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2026-08-03.

Sponsored by Catholic University of the Sacred Heart · Not applicable, Interventional, and Prevention

From the registry’s dates

  • Started Jun 2025; still recruiting 1 year 5 months later.
Phase
Not applicable
Study type
Interventional
Enrollment
100
Allocation
Not applicable
Ages
18 Years to 79 Years
Sex
Female
01

Study summary

This single-arm interventional feasibility study will evaluate whether integrating polygenic risk scores (PRS) into the CanRisk model can improve breast cancer risk prediction and personalized prevention in women at risk of breast cancer. The study will assess the organizational feasibility, patient acceptance, emotional impact and satisfaction of an integrated pathway combining PRS testing with standard genetic counseling and other risk factors at Fondazione Policlinico Universitario Agostino Gemelli IRCCS.

Read the 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:

  1. Uptake of CanRisk+PRS pathway
  2. Risk understanding and emotional impact, assessed using a validated questionnaire (Woof et al.)
  3. Risk reclassification rate, after PRS integration in the CanRisk model assessment
  4. Changes in breast cancer preventive pathway, recommended following multidisciplinary evaluation after CanRisk+PRS-based risk reclassification
  5. 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.

02

Conditions studied

  • Breast Cancer

Keywords

  • breast cancer
  • risk stratification
  • polygenic risk score
  • CanRisk model
  • feasibility study
  • personalized prevention
03

In context

Breast Neoplasms

14,825 studies on the registry are indexed under Breast Neoplasms; 3,319 are open to participants now.

This study's planned enrollment of 100 is above the median of 72 across 10,896 interventional studies indexed under Breast Neoplasms.

Browse Breast Neoplasms studies →

Lead sponsor

Catholic University of the Sacred Heart is the lead sponsor of 237 studies on the registry; 29 are open to participants now.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
18 Years to 79 Years
Sexes eligible
Female
Accepts healthy volunteers
Yes

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Ability to provide
  • 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:

    1. Known family history of breast cancer, or
    2. Known familiarity with carriers of pathogenic variants for genes included in the CanRisk model (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1), or
    3. Known carriers of pathogenic variants for genes included in the CanRisk model (BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51D, RAD51C, BARD1)
  • Affected women with:

    1. Diagnosis of unilateral breast cancer
    2. Personal history of ovarian cancer

Exclusion criteria

Exclusion Criteria:

  • Diagnosis or history of bilateral breast cancer
  • Diagnosis of ductal carcinoma in situ
  • Previous bilateral mastectomy
  • \< 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
Terms in these criteria, in plain language(2)

Underlined terms in the criteria open these too. Explained by clinicaltrials.gg, not part of the registry record. The study team decides who can take part.

Informed consent

Before you join, the study team explains what taking part involves — its purpose, what happens, the risks and possible benefits — and answers your questions, so you can decide freely. Consent is usually recorded on a form (the informed consent form, ICF) signed by you or, where the law allows, by someone legally authorised to decide for you.

You can keep asking questions during the study, you are told of new information that matters, and you can choose to leave at any time.

Life expectancy

The study doctor’s estimate of how long someone is likely to live. Criteria use it so that people can stay in the study long enough for it to answer its question.

05

Study design

Phase
Not applicable
Primary purpose
Prevention
Allocation
Not applicable
Intervention model
Single group
Masking
None (open label)
Enrollment
100 participants (estimated)

Study arms

  • 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.

    Genetic: Clinical pathway for breast cancer prevention based on PRS-integrated CanRisk assessment

Interventions

  • GeneticClinical pathway for breast cancer prevention based on PRS-integrated CanRisk assessment

    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.).

06

What researchers measure

Primary outcomes

  1. Feasibility of implementing an integrated clinical pathway including PRS

    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.

    Time frame: At 12 months from enrollment

Secondary outcomes

  1. Uptake of CanRisk+PRS integrated pathway

    Proportion of women accepting PRS testing among those offered: (Number accepting PRS / Number offered PRS) × 100

    Time frame: At the time of enrollment, when eligible participants are offered PRS testing

  2. Proportion of women requesting their individual CanRisk+PRS result

    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.

    Time frame: At month 12.

  3. Percentage of women reclassified into different risk categories after PRS integration

    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.

    Time frame: At month 12

  4. Proportion of women with modified prevention pathways after PRS-informed reclassification

    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.

    Time frame: At month 12.

  5. Perception of risk and psychological impact

    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.

    Time frame: At month 12

  6. Global redistribution of risk categories after PRS integration

    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.

    Time frame: At month 12.

07

Study locations

1 of 1 sites recruiting
08

References and documents

Publications

  • 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. PubMed 17683658 ↗
  • 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. PubMed 33769540 ↗
  • 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. PubMed 32624571 ↗
  • 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. PubMed 37308304 ↗
  • 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. PubMed 37922883 ↗
  • 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. PubMed 38834743 ↗
  • 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. PubMed 38001640 ↗
  • 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. PubMed 38718029 ↗
  • 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. PubMed 36162852 ↗
  • 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. PubMed 30643217 ↗
  • 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. PubMed 30959525 ↗
  • 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. PubMed 34837076 ↗
  • 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. PubMed 33538338 ↗
  • 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. PubMed 39348703 ↗

Individual participant data

Plan to share: Yes — All de-identified individual participant data (IPD) that underlie the published results of the study will be shared. This includes baseline demographics, clinical assessments, PRS test results (based on 313 SNPs), and questionnaire responses. Data will be made available via a secure Figshare repository upon study completion, with access governed by standard data use agreements to ensure participant confidentiality.

Supporting information: Study protocol, Statistical analysis plan, Informed consent form

Time frame: After publication of the study results and will remain available indefinitely.

Access criteria: Researchers wishing to access the de-identified individual participant data (IPD) and supporting documentation must submit a formal request that includes a research proposal outlining the planned analyses and justification for data use. All requests will be reviewed by the study's Data Access Committee to ensure that the proposed research meets ethical and scientific criteria. A data sharing agreement, detailing the conditions for data use and protecting participant confidentiality, must be signed before access is granted. Detailed submission instructions and contact information will be provided on the secure repository platform.

09

Timeline

Tracking since Sep 25, 2026
ElapsedEstimatedEstimated, not yet reachedSimilar studies: half by the dot; the band is the middle halfHalf of similar studies reached it by the dot; the band is the middle half, from a quarter to three quarters

Started Jun 2025 (actual). Primary completion is estimated for Sep 2026, 15 months after the start.

Of 2,661 non-industry interventional studies with no phase under Breast Neoplasms, half reached primary completion within 33 months of starting (the median), counting those still running; a quarter within 16 and three quarters within 66. This study's planned 15 months is below that.

Counting every sponsor, half of 2,771 studies reached it within 33 months; a quarter within 15 and three quarters within 66.

How these figures are worked out, and which studies are left out of them.

Registered
Mar 27, 2025
First posted
Apr 10, 2025
StartActual
Jun 6, 2025
Primary completionEst.
Sep 30, 2026
CompletionEst.
Nov 30, 2026
Last update
Aug 3, 2026
What these dates mean
Start.
When the first participant enrolled; while estimated, when the study expects to open to recruitment.
Primary completion.
When the last participant was examined or treated to collect data for the study's main question, its primary outcome. A study that stopped early gives the date its data collection stopped.
Completion.
When the last participant's last visit took place, for every outcome, secondary ones and side effects included: the end of the study. Often later than primary completion, sometimes the same day.
Actual and Est.
Actual means the registry says the date has happened. Est. (estimated) is a date the sponsor plans or expects. It can still move, and the sponsor is expected to change it to actual once it has passed.
No changes since tracking began. The registry record was last updated on Aug 3, 2026, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
10

Registry details

Key details

Study ID
NCT06922708
Responsible party
Stefania Boccia (Professor of Hygiene and Preventive Medicine, Catholic University of the Sacred Heart) — Principal investigator
First posted
Apr 10, 2025
Start date
Jun 6, 2025
Primary completion
Sep 30, 2026 (estimated)
Completion
Nov 30, 2026 (estimated)
Last update
Aug 3, 2026

Study contacts

Sara Farina, MD
Contact
sarafarins96@gmail.com
0039 + 0630156808
Francesco A Causio, MD
Contact
francescoandrea.causio@unicatt.it
Stefania Boccia, Phd
principal investigator · Life Sciences and Public Health Department, Università Cattolica del Sacro Cuore, Rome, Italy

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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