Early intervention of skin toxicities by panitumumab and clinical outcomes in the clinical setting.
Bibliographic record
Abstract
e20673 Background: Dermatologic toxicities from panitumumab can interfere with consistent cancer treatment. While treatment algorithms have been proposed for managing dermatologic toxicities, they are only stringently followed within a clinical trial setting. We assessed the impact of early versus late intervention of rash by initial grade in a cohort of patients treated outside of a clinical trial setting. Methods: We evaluated retrospectively the assessment and management of skin toxicities related to panitumumab in a consecutive cohort of patients receiving panitumumab for the treatment of metastatic colorectal cancer outside of a clinical trial from April 2009-August 2012. Results: Of 34 patients, 32 (94%) had a reported panitumumab-related skin toxicity (papulopustular rash). 85% developed the rash by the end of the second infusion cycle. A severity grading system was reported for 65% of patients: 31% used the CTCAE grading system, while 34% used mild/moderate/severe terminology; the remaining 34%, grading was performed by rash description in medical records. Rash was not related to clinicodemographic data. Among patients who initially presented with a mild rash (41%), the majority progressed when just observed without intervention, but all who received at least topical ointment (steroids or antimicrobial) remained stable or improved. The majority of patients presenting with a moderate rash (38%) were likely to get worse if they did not receive oral antimicrobials. Alternatively, among those presenting with a severe rash (21%), all improved to moderate rash after receiving oral antimicrobials (+/- topicals) but dose reductions and delays were also required. Conclusions: Dermatologic toxicities related to panitumumab are common. Early intervention, even with mild rash, reduces the risk of progression to more severe grades of skin toxicities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.007 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".