Abstract A026: Use of recommended diagnostic breast imaging among women under 40 in a community-based registry
Bibliographic record
Abstract
Abstract Diagnostic imaging is a critical step in obtaining a timely breast cancer diagnosis. The American College of Radiology (ACR) recommends initial diagnostic evaluation with breast ultrasound for women 18-29 with focal breast symptoms and initial diagnostic evaluation with mammography and/or ultrasound for women 30-39 with symptoms. These guidelines are evidence-based and deviation from them has the potential to lead to performance of unnecessary exams and/or delayed diagnosis. We evaluated the prevalence of appropriate diagnostic imaging among breast cancer patients <40 years. Data were from the Carolina Mammography Registry (CMR), a community-based registry of breast imaging in North Carolina that links to cancer diagnoses from the North Carolina Central Cancer Registry. The analysis included CMR women aged 18-39 years who were diagnosed with breast cancer between 2005-2021 and had at least one breast imaging exam (any type or indication) in the year before diagnosis (n=311). Women with a self-reported first-degree family history of breast cancer or imaging facility-reported increased risk were excluded due to differing guidelines for high-risk women. Presence of self-reported symptoms (lump, nipple discharge, pain or other) were obtained from pre-diagnosis exams. Use of appropriate imaging was based on the ACR Appropriateness Criteria for women with symptoms (described above). Between-group differences were assessed using the Fisher exact text. The majority of patients were 35-39 years old (63%), with fewer in 30-34 year (27%) and 18-29 year (10%) age groups. Symptom data was available for 98% of women, with symptoms present for 59% (18-29: 60%; 30-34: 70%; 35-39: 54%). The most common diagnostic approach in the year prior to diagnosis was ultrasound alone (50%) followed by mammography alone (28%). Use of multiple diagnostic modalities was uncommon (ultrasound plus mammogram: 10%; ultrasound plus MRI: 1%). 97% of patients with diagnostic imaging received an exam consistent with ACR guidelines, though appropriate imaging was lower among women 18-29 (76%) compared with women 30-34 (100%) or 35-39 (99%) (P<0.0001). This pattern was consistent for women with symptoms (18-29: 65%; 30-34: 100%; 35-39: 100%; P<0.0001), but there was no difference by age among women without symptoms (18-29: 100%; 30-34: 100%; 35-39: 97%; P>0.99). Limitations of our analysis include that some women may have obtained exams at facilities outside the CMR, which may lead to under-ascertainment of appropriate imaging or of symptoms if ongoing symptoms were not documented on subsequent exams. In sum, 35% of women 18-29 with self-reported symptoms received diagnostic imaging that was not consistent with ACR recommendations. Departures from ACR guidelines may be due to unique clinical situations, non-receipt of a recommended exam, or other factors. Future research will investigate provider, patient, and health system factors that influence breast imaging patterns among women 18-39 and the impact of different imaging approaches on prognosis among young breast cancer patients. Citation Format: Sarah J. Nyante, Thad Benefield, Anisha P. Ganguly, Caroline A. Thompson, Sasha Anderson, Erin J. Aiello Bowles, Genevieve A. Woodard. Use of recommended diagnostic breast imaging among women under 40 in a community-based registry [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr A026.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".