Invasive Ductal Carcinoma of the Breast: Correlation Between Tumor Grade Determined by Ultrasound-Guided Core Biopsy and Surgical Pathology
Bibliographic record
Abstract
OBJECTIVE: The purpose of this article is to evaluate the concordance between tumor grade found on ultrasound-guided core biopsies of invasive ductal carcinomas of the breast and subsequent excision specimens. MATERIALS AND METHODS: We retrospectively studied 300 consecutive invasive ductal carcinomas (274 women) that were biopsied under sonographic guidance, using 14-gauge core needles exclusively, and that were subsequently excised surgically. A minimum of four cores were taken per lesion. Core biopsy grades were compared with final surgical grades (reference standard). Tumor grade was assigned using the standard modified Scarff-Bloom-Richardson system. The agreement rate was expressed in percentages and in kappa statistics; the rates of overestimation and underestimation were also assessed. The correlation between tumor size (small, ≤ 0.5 cm; medium, 0.6-2.4 cm; and large, ≥ 2.5 cm) and agreement rate was also evaluated. RESULTS: The overall agreement between core biopsy and surgical pathology grade was 69% (simple κ = 0.46; 95% CI, 0.36-0.54). Agreement by biopsy grade was 86% (55/64) for grade 3, 66% (118/180) for grade 2, and 55% (23/42) for grade 1. Core biopsy underestimated 24% (70/286) and overestimated 7% (20/286) of the lesions. When discordant, core biopsy differed from excision by no more than one grade. Large tumors were more likely to show underestimation rather than overestimation when discordant (rate of underestimation, 92% for large, 81% for medium, and 33% for small tumors; p < 0.0031). CONCLUSION: Ultrasound-guided core biopsy accurately predicts high-grade breast tumors but is moderately accurate for lower-grade lesions. Large tumor size negatively impacts the accuracy of tumor grade found on biopsy and is associated with underestimation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".