Treatment patterns and outcomes of acneiform skin eruptions from anti-epidermal growth factor receptor (EGFR) therapies for metastatic colorectal cancer (mCRC).
Bibliographic record
Abstract
e19547 Background: Use of anti-EGFR therapies, such as cetuximab (Cmab) and panitumumab (Pmab), is associated with acneiform eruptions. Because research suggests a correlation between rash severity and outcomes in unselected patients, concerns remain that prophylactic treatment of rash may interfere with anti-tumor activities of these drugs. Our aims were to 1) characterize the treatment patterns for rash due to Cmab and Pmab and 2) evaluate if a prophylactic vs reactive approach to rash management modifies outcomes. Methods: All patients diagnosed with wild-type K-ras mCRC from July 2009 to June 2011 in British Columbia, Canada and prescribed either Cmab or Pmab were reviewed to describe patterns of prophylactic (before rash) and reactive (after rash) use of antibiotics and steroid creams. Using Cox regression, the relationship between rash management and overall survival was characterized. Results: In total, 119 patients were analyzed: median age at diagnosis was 63 years, 61% were men, 34% received Cmab and 66% Pmab, and median number of anti-EGFR treatment was 9 cycles. Rash occurred in over 90% of patients. Among them, reactive was favored over prophylactic treatment (66 vs 34%). Older patients (60+ years) and those with ECOG 0/1 were more likely to receive prophylactic creams (44 vs 20%, p=0.01) and antibiotics (62 vs 12%, p=0.01), respectively. There were no further differences in rash management based on other patient or tumor characteristics (all p>0.05). Median OS was 7.0 months. The number of treatment cycles and overall survival were similar in both prophylactic and reactive groups (both p>0.05). In Cox regression, ECOG 2+ correlated with worse survival than ECOG 0/1 (HR for death 5.25 95% CI 2.01- 9.23, p<0.01). However, survival outcomes were statistically similar between patients prescribed antibiotics prophylactically vs. reactively (HR=1.10, 95% CI 0.43-2.80, p=0.85) and between patients given steroid creams prophylactically vs. reactively (HR=2.00, 95% CI 0.58-6.92, p=0.27). Conclusions: Prophylactic treatment of anti-EGFR related rash is associated with similar outcomes as compared to reactive rash treatment in mCRC patients.
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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 | 0.002 |
| 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 | 0.000 | 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".