Evaluation of Adverse Events Experienced by Older Patients Participating in Studies of Molecularly Targeted Agents Alone or in Combination
Bibliographic record
Abstract
BACKGROUND: The tolerability of molecularly targeted agents in older patients has not been specifically examined. Adverse event data from clinical trials in the Princess Margaret Hospital Phase II Consortium database were analyzed to address this question. METHODS: The Consortium database collects trial information on all patients treated with either a molecularly targeted agent alone or in combination since 2001. The frequency of adverse events was determined and analyzed by two different age groups, <65 years and >/=65 years. Toxicity indices (TI) and frequencies of dose-limiting toxicities (DLT), based on adverse events of all causalities (TI(ALL) and DLT(ALL)), and on adverse events that were at least possibly related to the molecularly targeted agent (TI(MTA) and DLT(MTA)), were calculated for both age groups. RESULTS: Four hundred and one patients who received 1,252 treatment cycles were analyzed from 19 different studies. Baseline performance status was similar between both age groups, but fewer older patients have had multiple prior regimens of chemotherapy or prior radiation therapy. A comparison of the proportions of younger and older patients experiencing DLT(ALL) and DLT(MTA) showed similar results. The TI(MTA) values were comparable between the two age groups in both single agent (3.25 versus 3.00, for <65 versus >/=65 years) and multi-agent (3.65 versus 3.00, for <65 versus >/=65 years) trials. CONCLUSIONS: Older patients seem to tolerate molecularly targeted therapies either alone or in combination with chemotherapy as well as younger patients. Age alone should not be a barrier in the administration of targeted agents.
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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 | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".