Patient Benefit and Risk in Anticancer Drug Development: A Systematic Review of the Ixabepilone Trial Portfolio
Bibliographic record
Abstract
Abstract OBJECTIVE To describe the patient burden and benefit, and the dynamics of trial success in the development of ixabepilone—a drug that was approved in the US but not in Europe. DATA SOURCES Trials were captured by searching Embase and MEDLINE on July 27, 2015. STUDY SELECTION Inclusion: 1) primary trial reports, 2) interventional trials, 3) human subjects, 4) phase 1 to phase 3, 5) trials of ixabepilone in monotherapy or combination therapy of 6) pre-licensure cancer indications. Exclusion: 1) secondary reports, 2) interim results, 3) meta-analyses, 4) retrospective/observational studies, 5) laboratory analyses ( ex vivo tissues), 6) reviews, 7) letters, editorials, guidelines, interviews, abstract-only and poster presentations. DATA EXTRACTION AND SYNTHESIS Data were independently double-extracted and differences between coders were reconciled by discussion. MAIN OUTCOMES AND MEASURES We measured risk using the number of drug-related adverse events that were grade 3 or higher, benefit by objective response rate and trial outcomes by whether studies met their primary endpoint with acceptable safety. RESULTS We identified 39 publications of ixabepilone monotherapy and 23 primary publications of combination therapy, representing 5615 patients and 1598 patient-years of involvement over 11 years and involving 17 different malignancies. In total, 830 patients receiving ixabepilone experienced objective tumour response (16%, 95% CI 12.5%–20.1%), and 74 died from drug-related toxicites (2.2%, 95% CI 1.6%–2.9%). Responding indications and combinations were identified very quickly; thereafter, the search for additional responding indications or combinations did not lead to labelling additions. A total of 11 “uninformative” trials were found, representing 27% of studies testing efficacy, 208 grade 3–4 events and 226 patient-years of involvement (21% and 26% of the portfolio total, respectively). After the European Medicines Agency rejected ixabepilone for licensing, all further trial activity involving ixabepilone was pursued outside of Europe. DISCUSSION Risk/benefit for patients who enrolled in trials of non-approved indications of ixabepilone did not improve over the course of the drug’s development. Clinical value was discovered very quickly; however, a large fraction of trials were uninformative.
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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 | 0.037 | 0.127 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.009 |
| Bibliometrics | 0.015 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".