Biomarker Expression and Risk of Subsequent Tumors After Initial Ductal Carcinoma In Situ Diagnosis
Bibliographic record
Abstract
BACKGROUND: Studies have failed to identify characteristics of women who have been diagnosed with ductal carcinoma in situ (DCIS) and have a high or low risk of subsequent invasive cancer. METHODS: We conducted a nested case-control study in a population-based cohort of 1162 women who were diagnosed with DCIS and treated by lumpectomy alone from 1983 to 1994. We collected clinical characteristics and information on subsequent tumors, defined as invasive breast cancer or DCIS diagnosed in the ipsilateral breast containing the initial DCIS lesion or at a regional or distant site greater than 6 months after initial treatment of DCIS (N = 324). We also conducted standardized pathology reviews and immunohistochemical staining for the estrogen receptor (ER), progesterone receptor, Ki67 antigen, p53, p16, epidermal growth factor receptor-2 (ERBB2, HER2/neu oncoprotein), and cyclooxygenase-2 (COX-2) on the initial paraffin-embedded DCIS tissue. Competing risk models were used to determine factors associated with risk of subsequent invasive cancer vs DCIS, and cumulative incidence survival functions were used to estimate 8-year risk. RESULTS: Factors associated with subsequent invasive cancer differed from those associated with subsequent DCIS. Eight-year risk of subsequent invasive cancer was statistically significantly (P = .018) higher for women with initial DCIS lesions that were detected by palpation or that were p16, COX-2, and Ki67 triple positive (p16(+)COX-2(+)Ki67(+)) (19.6%, 95% confidence interval [CI] = 18.0% to 21.3%) than for women with initial lesions that were detected by mammography and were p16, COX-2, and Ki67 triple negative (p16(-)COX-2(-)Ki67(-)) (4.1%, 95% CI = 3.4% to 5.0%). In a multivariable model, DCIS lesions that were p16(+)COX-2(+)Ki67(+) or those detected by palpation were statistically significantly associated with subsequent invasive cancer, but nuclear grade was not. Eight-year risk of subsequent DCIS was highest for women with DCIS lesions that had disease-free margins of 1 mm or greater combined with either ER(-)ERBB2(+)Ki67(+) or p16(+)COX-2(-)Ki67(+) status (23.6%, 95% CI = 18.1% to 34.0%). CONCLUSION: Biomarkers can identify which women who were initially diagnosed with DCIS are at high or low risk of subsequent invasive cancer, whereas histopathology information cannot.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".