A Randomized Trial Comparing Concurrent versus Sequential Radiation and Endocrine Therapy in Early-Stage, Hormone-Responsive Breast Cancer
Bibliographic record
Abstract
Concerns exist regarding increased toxicities, including endocrine therapy toxicity, with concurrent radiation and endocrine therapy in early breast cancer (EBC). We present a pragmatic, randomized trial comparing concurrent versus sequential endocrine and radiotherapy in hormone-responsive EBC. In this multicenter trial, patients were randomized to receive adjuvant endocrine therapy concurrent with, or sequential to, radiotherapy. The primary outcome was change in endocrine therapy toxicity from baseline to 3 months post radiotherapy using the Functional Assessment of Cancer Therapy–Endocrine Symptom (FACT-ES) score. From September 2019 to January 2021, 133 patients were randomized to concurrent endocrine and radiotherapy, and 127 to sequential treatment. Most patients were post-menopausal (72.7%, 189/260) with stage 1 disease (65.8%, 171/260). Tamoxifen was the endocrine therapy of choice for 69.6% (181/260) of patients, and an aromatase inhibitor for the remainder. The median total radiation dose and fractions were 40.1 Gray (range 26–50) and 15 fractions (range 5–25), respectively. For the primary outcome of change in endocrine therapy toxicity per FACT-ES scores from baseline to 3 months post radiotherapy, no significant difference was found between the groups (median [range] = −4.9 (−82, 38.8) for concurrent and −5.1 (−42, 40) for sequential, p = 0.87). This is the first trial to investigate the impact of concurrent versus sequential adjuvant endocrine and radiotherapy on endocrine therapy-related toxicities. The findings provide further support to allow the optimal timing of radiation and endocrine therapy to be tailored for the individual patient.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".