A Randomized Phase IIb Study of Low-dose Tamoxifen in Chest-irradiated Cancer Survivors at Risk for Breast Cancer
Bibliographic record
Abstract
Abstract Purpose: Low-dose tamoxifen reduces breast cancer risk, but remains untested in chest-irradiated cancer survivors—a population with breast cancer risk comparable with BRCA mutation carriers. We hypothesized that low-dose tamoxifen would be safe and efficacious in reducing radiation-related breast cancer risk. Patients and Methods: We conducted an investigator-initiated, randomized, phase IIb, double-blinded, placebo-controlled trial (FDA IND107367) between 2010 and 2016 at 15 U.S. sites. Eligibility included ≥12 Gy of chest radiation by age 40 years and age at enrollment ≥25 years. Patients were randomized 1:1 to low-dose tamoxifen (5 mg/day) or identical placebo tablets for 2 years. The primary endpoint was mammographic dense area at baseline, 1 and 2 years. IGF-1 plays a role in breast carcinogenesis; circulating IGF-1 and IGF-BP3 levels at baseline, 1 and 2 years served as secondary endpoints. Results: Seventy-two participants (low-dose tamoxifen: n = 34, placebo: n = 38) enrolled at a median age of 43.8 years (35–49) were evaluable. They had received chest radiation at a median dose of 30.3 Gy. Compared with the placebo arm, the low-dose tamoxifen arm participants had significantly lower mammographic dense area (P = 0.02) and IGF1 levels (P < 0.0001), and higher IGFBP-3 levels (P = 0.02). There was no difference in toxicity biomarkers (serum bone-specific alkaline phosphatase, lipids, and antithrombin III; urine N-telopeptide cross-links) between the treatment arms. We did not identify any grade 3–4 adverse events related to low-dose tamoxifen. Conclusions: In this randomized trial in chest-irradiated cancer survivors, we find that low-dose tamoxifen is effective in reducing established biomarkers of breast cancer risk and could serve as a risk-reduction strategy.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".