Abstract P1-01-11: The impact of a critical look at the consequences of preoperative MRI in breast cancer patients
Bibliographic record
Abstract
Abstract BACKGROUND: Despite the fact that routine use of preoperative breast MRI for breast cancer has not been shown to improve oncologic outcomes, it is still an exceedingly popular test. Due to low MRI specificity, patients may be subjected to additional invasive test. There have been few studies specifically evaluating the outcomes from these additional tests and its implications on the health care system. The objective of this study was to critically evaluate the impact of performing a preoperative MRI on breast cancer patients at our institution. METHODS: A retrospective chart review was performed on all female breast cancer patients diagnosed and awaiting surgery (2010-2012). Based on extracted data, indications for preoperative breast MRI were established for our institution (2013). Adherence to these guidelines was then assessed over the next year. RESULTS: In 2010-2012, 1159/1674 breast cancer patients underwent a preoperative breast MRI. The MRI group was younger (p<0.0001), but not different in histologic subtype (p=0.06) or biomarker status (0.61). 421/1159 (36%) of MRI patients underwent at least one additional MRI induced imaging test (ultrasound, mammogram, 6 month MRI) following the MRI. 35% (415/1159) of patients underwent an additional MRI-induced biopsies, 52% of which were benign in the breast and 62% of which were benign in the axilla. Post-MRI biopsies resulted in upstaging (DCIS to invasive cancer; node negative to node positive) in 25/1159 (2%) of patients. Preliminary data assessing local guideline adherence demonstrated that 188/349 (54%) of new breast cancer patients underwent a preoperative MRI. Locally accepted indications for MRI use included: dense breast (26%); assessment of tumor extent; (19%); lobular carcinoma (16%); assessment of locally advanced cancer (16%). 71% of MRI studies were ordered by the radiologist. 22% of patients had no obvious indication for MRI according to our local guidelines. MRI-induced biopsies occurred in 76/189 (40.2%) of patients, 60% of which were benign in the breast and 71% of which were benign in the axilla. CONCLUSION: We have critically evaluated the impact of preoperative breast MRI on a large volume of patients. Often, MRI results did not result in significant treatment change. Barriers to guideline evidence based care implementation continue to exist in the setting of multidisciplinary breast cancer care. We must continue to work together to best counsel our patients and effectively manage our health care cost, in keeping with the Choosing Wisely Campaign Canada. Citation Format: I Ching Yeung, Mehrzad Namazi, Valerie Deslauriers, Fatima Haggar, Angel Arnaout. The impact of a critical look at the consequences of preoperative MRI in breast cancer patients [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-01-11.
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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 | 0.003 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.004 | 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".