Integrated Analysis of the RASH Study with the Use of the “Burden of Therapy” (BOTh®TM) Methodology—A Novel Tool for Assessing Adverse Events in Metastatic Pancreatic Cancer
Bibliographic record
Abstract
This analysis of the RASH trial (NCT01729481) aimed at gaining a better understanding of the “Burden of Therapy” (BOTh®TM) in pancreatic ductal adenocarcinoma (PDAC). In the RASH study, 150 patients with newly diagnosed metastatic PDAC were treated with gemcitabine plus erlotinib (gem/erlotinib) for four weeks. Patients who developed a skin rash during this four-week run-in phase continued with the gem/erlotinib treatment, while rash-negative patients were switched to FOLFIRINOX. The study demonstrated a 1-year survival rate of rash-positive patients who received gem/erlotinib as first-line treatment that was comparable to previous reports of patients receiving FOLFIRINOX. To understand whether these comparable survival rates may be accompanied by better tolerability of the gem/erlotinib treatment compared to FOLFIRINOX, the BOTh®TM methodology was used to continuously quantify and depict the burden of therapy generated by treatment emergent events (TEAEs). Sensory neuropathy was significantly more common in the FOLFIRINOX arm, and prevalence as well as severity increased over time. In both arms, the BOTh®TM associated with diarrhea decreased over the course of treatment. The BOTh®TM caused by neutropenia was comparable in both arms but decreased in the FOLFIRINOX arm over time, possibly due to chemotherapy dose reductions. Overall, gem/erlotinib was associated with a slightly higher overall BOTh®TM, but the difference was not statistically significant (p = 0.6735). In summary, the BOTh®TM analysis facilitates the evaluation of TEAEs. In patients fit for intense chemotherapeutic regimens, FOLFIRINOX is associated with a lower BOTh®TM than gem/erlotinib.
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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 | 0.015 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".