Contralateral Breast Screening with Preoperative MRI: Long-Term Outcomes for Newly Diagnosed Breast Cancer
Bibliographic record
Abstract
Background The diagnostic value of screening the contralateral breast with MRI in patients with newly diagnosed breast cancer is poorly understood. Purpose To assess the impact of MRI for screening the contralateral breast on long-term outcomes in patients with newly diagnosed breast cancer and to determine whether subgroups with unfavorable prognoses would benefit from MRI in terms of survival. Materials and Methods Data on consecutive patients with newly diagnosed breast cancer seen from January 2008 to December 2010 were reviewed retrospectively. Patients with neoadjuvant chemotherapy, previous breast cancer, distant metastasis, absence of contralateral mammography at diagnosis, and no planned surgical treatment were excluded. Groups that did and did not undergo preoperative MRI were compared. Survival analysis was performed using the Kaplan-Meier method for propensity score–matched groups to estimate cause-specific survival (CSS) and overall survival (OS). A marginal Cox proportional hazards model was used to evaluate association of MRI and clinicopathologic variables with OS. Results Of 1846 patients, 1199 fulfilled the inclusion criteria. Median follow-up time was 10 years (range, 0–14 years). The 2:1 matched sample comprised 705 patients (470 in the MRI group and 235 in the no-MRI group); median ages at surgery were 59 years (range, 31–87 years) and 64 years (range, 37–92 years), respectively. MRI depicted contralateral synchronous disease more frequently (27 of 470 patients [5.7%] vs five of 235 patients [2.1%]; P = .047) and was associated with a higher OS (hazard ratio [HR], 2.51; 95% CI: 1.25, 5.06; P = .01). No differences were observed between groups in metachronous disease rate (MRI group: 21 of 470 patients [4.5%]; no-MRI group: 10 of 235 patients [4.3%]; P > .99) or CSS (HR, 1.34; 95% CI: 0.56, 3.21; P = .51). MRI benefit was greater in patients with larger tumor sizes (>2 cm) (HR, 2.58; 95% CI: 1.11, 5.99; P = .03) and histologic grade III tumors (HR, 2.94; 95% CI: 1.18, 7.32; P = .02). Conclusion Routine MRI screening of the contralateral breast after first diagnosis of breast cancer improved overall survival; the most pronounced benefit was found in patients with larger primary tumor size and primary tumors of histologic grade III. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Taourel in this issue.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".