Lapatinib-Related Rash and Breast Cancer Outcome in the ALTTO Phase III Randomized Trial
Bibliographic record
Abstract
BACKGROUND: Previously we have shown that early development of rash is associated with a higher chance of achieving pathological complete response to neoadjuvant lapatinib. In the current analysis, we investigate its impact on survival in the ALTTO phase III adjuvant trial. METHODS: In ALTTO, patients with human epidermal growth factor receptor 2 (HER2)-positive early breast cancer were randomly assigned to adjuvant trastuzumab, lapatinib, their sequence, or their combination for a total duration of one year. We evaluated whether the development of early lapatinib-related rash (ie, within 6 weeks) is associated with disease-free (DFS) and overall survival (OS). Landmark analysis at eight weeks and time-dependent analysis were tested in a multivariable model stratifying on trial's stratification factors. All statistical tests were two-sided. RESULTS: Out of 6098 lapatinib-treated patients, 3973(65.2%) were included in the landmark analysis, of whom 1389 (35.0%) had developed early rash. After median follow-up of 4.5 years, the development of early rash was associated with a trend of improved DFS (multivariable: hazard ratio [HR] = 0.87, 95% confidence interval [CI] = 0.73 to 1.03,P= .10) and statistically significantly improved OS (multivariable: HR = 0.63, 95% CI = 0.48 to 0.82,P< .001) compared with subjects without early rash. Compared with patients randomly assigned to trastuzumab (n = 2051), patients who were randomly assigned to trastuzumab/lapatinib combination and developed early rash (n = 692) had superior DFS (multivariable: HR = 0.72, 95% CI = 0.55 to 0.92,P= .01) and OS (multivariable: HR = 0.59, 95% CI = 0.39 to 0.90,P= .01). Time-dependent analysis suggests that the occurrence of rash is predictive of lapatinib benefit, both when given in combination or sequential to trastuzumab. CONCLUSIONS: Our results indicate that early development of rash identifies patients who derive superior benefit from lapatinib-based therapy.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 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".