Utilization of Percutaneous Needle Biopsy for Breast Diagnosis in a Comprehensive Breast Center: Implications for Development of Quality Indicators
Bibliographic record
Abstract
INTRODUCTION: Percutaneous needle biopsy (PNB) is the standard of care for diagnosis of breast lesions. Rates of excisional biopsy for breast diagnosis in North America have been reported at approximately 35 %, although significant regional variation exists. A target rate of PNB for diagnosis of breast abnormalities is needed to facilitate quality improvement. We sought to describe the use of PNB in a referral practice, the clinical scenarios prompting PNB or surgical biopsy (SB), and the accuracy and rate of PNB to inform the ultimate development of a benchmark rate of PNB in breast diagnosis. MATERIALS AND METHODS: Female patients age 18-90 years, referred to Sunnybrook Health Sciences Centre, a large teaching hospital affiliated with the University of Toronto, with a breast lesion prompting tissue diagnosis with SB and/or PNB between 2002 and 2009 were studied. Each biopsied lesion was characterized by method of biopsy: PNB, SB, or PNB followed by SB. For each lesion, we collected data on patient demographics and breast cancer risk, reason for referral, imaging characteristics (breast imaging-reporting and data system classification, full description, final impression before biopsy), and pathology from each biopsy method. We report concordance between the final impression pre-biopsy and the PNB diagnosis with final surgical diagnosis where applicable. RESULTS: One thousand and twenty-six lesions were biopsied, 987 (96 %) with PNB. The benign:malignant ratio for the entire cohort was 1.2:1. Final impression was concordant with final pathology in 674/862 (78 %) and PNB diagnosis was concordant with SB pathology in 487/556 (88 %). The reasons for SB without PNB were required pathologic evaluation of the entire lesion (n = 19), patient choice (n = 5), other biopsy technique used (n = 6), technical (n = 4), planned mastectomy (n = 3), and enlarging mass (n = 2). 155/559 (28 %) of lesions without evidence of malignancy on PNB ultimately underwent SB. Papillary lesions and radial scars were more likely to undergo SB with or without prior PNB. Lesions deemed to be suspicious or malignant on final impression were more likely to be excised after a benign diagnosis at PNB. CONCLUSION: The vast majority of lesions requiring tissue diagnosis can be accurately diagnosed with PNB. Benchmarks for rates of PNB of 90 % or greater may be considered for performance measurement in appropriate populations.
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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 | 0.019 | 0.064 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".