Final findings from the CONTROL trial: Strategies to reduce the incidence and severity of neratinib-associated diarrhea in patients with HER2-positive early-stage breast cancer
Bibliographic record
Abstract
BACKGROUND: Neratinib is an irreversible pan-HER tyrosine kinase inhibitor approved for HER2-positive early-stage and metastatic breast cancer. Diarrhea is the most frequent side effect and the most common reason for early discontinuation. The phase II CONTROL trial investigated antidiarrheal prophylaxis or neratinib dose escalation (DE) for prevention of diarrhea. We present complete study results including final data for two DE strategies. METHODS: Patients who completed trastuzumab-based adjuvant therapy received neratinib 240 mg/day for 1 year. Early cohorts investigated mandatory prophylaxis with loperamide, then additional budesonide or colestipol. Final cohorts assessed neratinib DE over the first 2 (DE1) or 4 weeks (DE2). The primary endpoint was incidence of grade ≥3 diarrhea. Health-related quality of life (HRQoL) was assessed using FACT-B and EQ-5D-5L. RESULTS: 563 patients were enrolled into six cohorts. All strategies reduced grade ≥3 diarrhea with the lowest incidence in DE1 (DE1 13%; colestipol + loperamide [CL] 21%, DE2 27%; budesonide + loperamide [BL] 28%; loperamide [L] 31%; colestipol + loperamide as needed [CL-PRN] 33%). Diarrhea-related discontinuations occurred early and were lowest in DE1 (DE1 3%; CL 4%; DE2 6%; CL-PRN 8%; BL 11%; L 20%). More patients stayed on neratinib for the prescribed period versus historical controls. Prior pertuzumab use did not affect rates of grade ≥3 diarrhea, diarrhea-related discontinuations, or treatment duration. Early transient reductions in HRQoL scores were observed. CONCLUSIONS: These complete results from CONTROL show improved neratinib tolerability with proactive management at the start of therapy. Two-week neratinib DE with loperamide as needed was particularly effective. GOV REGISTRATION NUMBER: NCT02400476.
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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 | 0.001 | 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 | 0.001 |
| 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".