A clinical pilot study for personalized risk?based breast cancer screening utilizing the polygenic risk score

This clinical pilot study demonstrates that incorporating polygenic risk scores into breast cancer screening for women aged 40–49 can effectively stratify risk and personalize screening recommendations without inducing significant anxiety among participants.

The Gist

Imagine you are walking through a massive forest, and the goal is to find a few hidden treasures (breast cancer) before they cause trouble. Right now, the forest rangers (doctors) have a very simple rule: "Everyone who is between 50 and 69 years old gets a map and a flashlight to check for treasure every two years."

This rule is fair and easy to follow, but it has a flaw: some people are walking through a much more dangerous part of the forest at age 40, while others are walking through a safe, empty meadow at age 70. The current system treats everyone exactly the same, regardless of their personal risk.

This study is like a pilot test for a new, high-tech GPS system that tries to give everyone a personalized map based on their specific DNA.

The Experiment: A "Test Drive" for Personalized Maps

The researchers invited 80 women (aged 40–49) who were already visiting a doctor for a breast check-up to try out this new GPS. They didn't just look at their age; they took a simple cheek swab (like a cotton ball rubbed inside the mouth) to read their DNA.

The "Genetic Score" (PRS):
Think of your DNA as a deck of cards. Most cards are harmless, but some are slightly "heavy" (risk factors).

• The Polygenic Risk Score (PRS) is like counting how many "heavy cards" you have in your deck.
• The test looked at 2,805 specific cards (tiny genetic variations) to calculate a score.
• This score told the researchers: "Is this woman's risk of finding treasure in the next 10 years the same as an average 50-year-old, higher, or lower?"

What Happened?

The results showed that the "one-size-fits-all" rule misses the mark for many people:

1. The "Early Starters" (40 women): Half of the women had a genetic score that meant they were already as risky as an average 50-year-old, even though they were only in their 40s.
   • The New Advice: Instead of waiting until 50, these women were told to start their screenings immediately or earlier than usual. Some even needed to check more often (every year instead of every two years).
2. The "Standard Group" (40 women): The other half had scores similar to the average person.
   • The New Advice: They could stick to the standard plan: wait until 50 and check every two years.
3. The "High Alert" Group: A few women had such high scores that they were advised to start annual screenings immediately, just to be safe.

Did It Work? (The Human Side)

The researchers also asked the women how they felt about this new, personalized approach.

• No Panic: Surprisingly, most women did not feel more anxious after getting their results. Even those with "high risk" scores mostly felt reassured that they were getting a plan tailored to them.
• The "Wait, What?" Moment: A small group (about 10%) who got bad news felt a bit uneasy and wished they had been told over the phone instead of in a letter. This suggests that when the news is heavy, a gentle voice is better than a piece of paper.
• Family History Check: The study also checked if these women had a family history of cancer. Interestingly, the genetic score (PRS) and the family history often pointed in the same direction, giving doctors a double confirmation on who needs extra care.

The Big Picture: Why Does This Matter?

Think of the current system as a uniform: everyone wears the same size.
This new approach is like tailoring a suit: it fits each person perfectly.

• For the "High Risk" women: They get a tighter, more protective suit (earlier and more frequent checks) so they don't miss a problem.
• For the "Low Risk" women: They might eventually be able to wear a lighter suit (checking less often), saving them from unnecessary stress and false alarms.

The Catch

The researchers admit this was just a small pilot test (like a prototype car).

• Sample Size: Only 80 women tried it. We need to test this on thousands to be sure it works for everyone.
• The "Opt-Out" Problem: Not everyone will want to know their genetic risk. If a woman says, "I don't want to know my DNA score," the system must still give her a good, safe plan.
• Cost and Logistics: Sending cheek swabs and analyzing DNA costs money and takes time. The system needs to be efficient enough to handle millions of people, not just 80.

The Bottom Line

This study suggests that we can stop guessing and start knowing. By using a simple DNA test, we can move away from a "one-size-fits-all" screening schedule to a personalized plan that fits each woman's unique genetic makeup. It's about giving the right amount of protection to the right people at the right time.

Technical Summary

1. Problem Statement

Current population-based breast cancer screening programs, such as BreastScreen Norway, rely primarily on age (inviting women aged 50–69) as the sole criterion for screening. This "one-size-fits-all" approach fails to account for individual risk profiles, leading to challenges such as:

• Overdiagnosis and false positives in low-risk women.
• Missed interval cancers or advanced-stage diagnoses in high-risk women who are not yet in the screening age bracket.
• Inefficiency: Approximately 4–5% of breast cancers are caused by high-risk pathogenic variants (e.g., BRCA1/2), while another ~30% are linked to the cumulative effect of numerous low-risk genetic variations (Single Nucleotide Polymorphisms or SNPs).
• Gap: Polygenic Risk Scores (PRS), which aggregate these SNPs, are not currently integrated into clinical screening guidelines in Norway, despite their potential to stratify risk more accurately than age alone.

2. Methodology

The study was a prospective clinical pilot conducted at the Vestre Viken breast center in Norway between October 2022 and March 2023.

• Study Population:

  • Target: 80 women aged 40–49 (pre-screening age) referred for clinical mammography due to symptoms.
  • Exclusion Criteria: Prior breast cancer, premalignant disease, or previous genetic testing.
  • Recruitment: 320 eligible women were invited; 80 participated (25% response rate).

• Data Collection & Procedures:

  • Genetic Sampling: DNA was collected via buccal swabs and analyzed using the AnteBC test (Antegenes, Estonia), a CE-marked test utilizing 2,803 breast cancer-associated SNPs.
  • Risk Calculation: A 10-year breast cancer risk was estimated for each participant. Relative risk was calculated by dividing the individual's 10-year risk by the average 10-year risk of a Norwegian woman of the same age.
  • Clinical Data: Mammographic density was classified using BI-RADS categories (a–d). Family history was assessed via questionnaire.
  • Genetic Counseling: Participants meeting national criteria for hereditary cancer (based on family history) were referred for 29-gene panel testing.

• Intervention/Stratification Logic:
  Screening recommendations were tailored based on the PRS-derived relative risk:

  • Relative Risk ≤ 1: Standard biennial screening at age 50–69.
  • Relative Risk > 1 and ≤ 2: Biennial screening starting when the individual's 10-year risk equals that of an average 50-year-old.
  • Relative Risk > 2: Biennial screening from the age of risk equivalence, potentially moving to annual screening once risk doubles that of an average 50-year-old.

• Follow-up: A digital questionnaire was distributed 6–9 months post-inclusion to assess participant experiences, anxiety levels, and satisfaction.

3. Key Contributions

• Feasibility Assessment: Demonstrated the logistical feasibility of integrating PRS testing into a clinical workflow for women in the pre-screening age group (40–49).
• Risk Stratification Validation: Provided empirical data on how PRS reclassifies risk in a symptomatic, pre-screening cohort, showing that nearly half of women in this age group have a risk profile warranting earlier or more frequent screening than the standard protocol.
• Psychological Impact Analysis: Evaluated the psychological impact (anxiety, satisfaction) of receiving personalized genetic risk information, a critical component for future implementation.
• Integration with Family History: Analyzed the interplay between PRS and traditional family history-based referrals, showing that PRS often reinforces or adds nuance to existing guidelines.

4. Key Results

• Demographics: Mean age was 45.2 years.
• Risk Distribution:
  • Mean relative 10-year risk: 1.18 (SD 0.57).
  • 49% (39/80) had a relative risk ≤ 1 (standard risk).
  • 39% (31/80) had a relative risk between 1 and 2.
  • 12% (10/80) had a relative risk > 2.
• Screening Recommendations:
  • 50% (40/80) were advised to start standard biennial screening at age 50.
  • 49% (39/80) were advised to start screening before age 50.
  • Among those starting early, 7 women were recommended annual mammography due to high relative risk.
• Genetic Testing & Family History:
  • 21 women underwent gene panel testing; no pathogenic variants in high-risk breast cancer genes were found (one CDKN2A variant found, linked to melanoma/pancreatic cancer).
  • Women referred for genetic testing had significantly higher PRS values and relative risks (>1.5) compared to those not referred ($p=0.021$).
  • Five women were recommended annual screening (ages 40–60) based on family history criteria alone; all five also had elevated PRS.
• Correlations:
  • No statistically significant association was found between PRS and mammographic density (BI-RADS).
  • Women with higher PRS were more likely to be referred for genetic counseling.
• Patient Experience:
  • 98% found the buccal swab acceptable.
  • 79% were satisfied with result communication (letters); 10% were dissatisfied (all with high risk), preferring phone calls.
  • 66% reported no increased anxiety; 16% reported increased anxiety (all with relative risk > 1).
  • 97% intended to follow the new screening recommendations.

5. Significance and Implications

• Personalized Medicine: The study confirms that PRS can effectively identify women who reach the risk threshold for screening at a younger age than the current population-based standard (age 50). This supports a shift toward risk-adapted screening.
• Clinical Utility: Integrating PRS allows for the identification of high-risk women who would otherwise be missed until age 50, potentially improving early detection rates. Conversely, it identifies low-risk women who might benefit from less intensive screening (though the study focused on intensifying for high risk).
• Psychological Safety: The low rate of reported anxiety suggests that providing genetic risk information is generally acceptable and does not cause widespread distress, provided communication is clear and supportive.
• Future Directions: The authors highlight the need for larger prospective trials (like MyPeBS and WISDOM) to validate cost-effectiveness and long-term outcomes. They also note that future implementation must address logistical challenges (e.g., self-collection kits) and ethical considerations regarding equity for those who decline genetic testing.

Conclusion: The pilot study successfully demonstrates that PRS testing is a viable tool for personalizing breast cancer screening strategies, potentially shifting the paradigm from age-based to risk-based protocols in Norway.