Abstract P4-02-15: Preoperative MRI of the breast and ipsilateral breast tumor recurrence: Long-term follow up
Bibliographic record
Abstract
Abstract Introduction: Local recurrence after breast conserving surgery for invasive breast cancer is uncommon, reported in 5 to 10% of cases at 10 years after surgery. Prior studies with short term follow-up have shown that preoperative breast MRI does not reduce re-excision rates for positive margins or reduce local recurrence after lumpectomy and radiation therapy. This study aims to determine 1) if preoperative breast MRI is associated with reduced ipsilateral breast tumor recurrence (IBTR) rates in the longer term and 2) the IBTR rates of a high risk (triple negative (TN) and Her-2 positive) subgroup in those receiving or not receiving preoperative MRI. Methods: Between 1999 and 2005, a cohort of patients with invasive breast cancer undergoing breast conservative surgery and radiation therapy were identified from a prospectively collected database and followed. The primary endpoint was IBTR rate. Secondary outcomes included the determination of factors associated with the use of preoperative breast MRI and prognostic factors related to IBTR. IBTR rate was calculated by Kaplan-Meier method. Univariate analysis was calculated using log-rank test and chi-squared test. Results: The cohort consisted of 470 cases with invasive breast cancer undergoing lumpectomies with negative resection margins. All patients received adjuvant radiation therapy. 127 (27%) patients underwent preoperative breast MRI and 343 (73%) did not. Median follow-up was 97 months. The overall 10-year IBTR rate was 3.6%. Overall, there was no significant difference in IBTR rate at 10 years between those receiving preoperative MRI and those without (IBTR: 1.6% and 4.2%, respectively (p = 0.37). There were no differences in IBTR rate between MRI and no-MRI after adjusting for age, year of surgery, tumor size, and adjuvant treatments on univariate analysis. For patients who recurred, median time to recurrence was 26 months for MRI group vs. 25 months for no-MRI group. Factors associated with the receipt of preoperative MRI were age < 50 years, lesion > 2 cm and receipt of adjuvant chemotherapy. We also found that the TN and Her-2 positive combined subgroup had a higher IBTR rate than all others (9.8% vs. 3.1%, p= 0.03). In those that received preoperative MRI, there was no difference in IBTR between the high risk group (n= 33) and the remaining patients (3.3% vs 1.2%, p= 0.5), but in the group without an MRI, the IBTR rate of the high risk group (n= 75) was 11.8% compared to the remainder (vs. 4.0%, p= 0.0529). For the TN and Her-2 positive combined group, the difference in IBTR rate when this subgroup was subdivided if they had received preoperative MRI vs. no-MRI (3.3% vs. 11.8%, p= 0.3) was not significant. Conclusion: With long term 10-year follow up, there is no overall significant difference in IBTR rate whether preoperative breast MRI is performed versus not. However, the high risk triple negative breast cancers and Her-2 positive populations combined have shown an increased IBTR rate, and this was more marked in those who did not receive preoperative MRI. Citation Format: Gervais M-K, Maki E, Schiller DE, McCready DR. Preoperative MRI of the breast and ipsilateral breast tumor recurrence: Long-term follow up. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-02-15.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".