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Prospective multicenter observational study of an integrated Artificial Intelligence system with live monitoring

Prospective multicenter observational study of an integrated Artificial Intelligence system with live monitoring - PRAIM

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
DRKS
Registry ID
DRKS00027322
Enrollment
400000
Registered
2022-03-07
Start date
2021-07-01
Completion date
Unknown
Last updated
2025-04-07

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

C50 D05

Interventions

Group 1: Live AI: Studies read in a double-reader setting, where one or both involved readers use Vara software for workflow and AI predictions. Group 2: Shadow mode: Studies read as usual in a double

Sponsors

Vara (MX Healthcare GmbH)
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
50 Years to 69 Years

Inclusion criteria

Inclusion criteria: Attending biennial breast cancer screening at a screening unit participating in the German national breast cancer screening program.

Exclusion criteria

Exclusion criteria: None

Design outcomes

Primary

MeasureTime frame
I. Screen-detected cancer rate Defined as the number of true-positive examinations divided by the total number of screening mammograms, per 1000 women screened. True-positive mammogram is a positive mammogram (BI-RADS assessment =3) followed by the biopsy-confirmed diagnosis of breast cancer within the timeframe as defined by the mammography screening program. II. Recall rate Defined as the number of surveillance imaging examinations with BI-RADS assessment =3 at consensus conference and recalled for further imaging, per 1000 women screened.

Secondary

MeasureTime frame
1. Number of studies sent to consensus conference per 1000 women screened 2. Biopsy recommendation rate: number of diagnostic imaging studies with BI-RADS assessment 4 or 5 per 1000 women screened 3. Biopsy rate: number of women with diagnostic biopsies per 1000 women screened 4. False positive rate: a. Number of negative diagnostic imaging studies, per 1000 women screened b. Number of negative diagnostic biopsies, per 1000 women screened 5. AI metrics: a. Number of times safety net is triggered, per 1000 women b. Number of times safety net is triggered and concordant with user prediction, per 1000 women c. Number of times safety net is triggered, shown and waived, per 1000 women d. Number of times safety net is triggered, shown and accepted, per 1000 women e. Number of times safety net is triggered, shown and accepted, resulting in malignant biopsy, per 1000 women f. Number of triaged negative studies, per 1000 women 6. Interval cancer metrics (where possible according Exploratory objective). a. Number of interval cancer diagnoses within 24 months after a normal screening mammogram, per 1000 women b. Number of times safety net is triggered and waived, and resulted in an interval cancer, per 1000 women c. Number of times study was marked as "normal" by AI and resulted in interval cancer diagnosis, per 1000 women d. AI model scores for subsequent interval cancer diagnoses 7. Screening sensitivity (where possible according to Exploratory objective). Defined as the number of screen-detected cancers, over the total number of cancers detected during 24-month period 8. Screening specificity (where possible according to Exploratory objective). Defined as the number of true negatives, over the total number of negatives. 9. Reader sensitivity. Defined as the number of cases a reader recommended to consensus conference during the first and second read, over the total number of screen-detected cancers. 10. Reader specificity. Defined as the number of cas

Countries

Germany

Contacts

Public ContactFridtjof Storde

Country Manager Germany, MX Healthcare GmbH (Vara)

Fridtjof.Storde@vara.ai+49 151 2084 2538

Outcome results

None listed

Source: DRKS (via WHO ICTRP) · Data processed: Feb 9, 2026