Do older and younger patients derive similar survival benefits from novel oncology drugs? A systematic review and meta-analysis
Bibliographic record
Abstract
Background: older patients are commonly believed to derive less benefit from cancer drugs, even if they fulfil clinical trial eligibility [Talarico et al. (2004, J Clin Oncol, 22(22):4626-31)]. We aim to examine if novel oncology drugs provide differential age-based treatment outcomes for patients on clinical trials. Methods: a systematic review of randomised control trials (RCTs) cited for clinical efficacy evidence in novel oncology drug approvals by the Food and Drug Administration, European Medicines Agency and Health Canada between 2006 and 2017 was conducted. Studies reporting age-based subgroup analyses for overall or progression-free survival (OS/PFS) were included. Hazard ratios (HRs) and confidence intervals (CIs) for age-based subgroups were extracted. Meta-analyses with random effects were conducted, examining patient subgroups <65 and ≥65 years separately and pooled HRs of studies primary endpoints (OS or PFS) compared to examine if differences existed between age-based subgroups. Sensitivity analyses were conducted for cancer type, primary endpoint and systemic treatment. Results: one-hundred-two RCTs, including 65,122 patients, met the inclusion criteria. One study reported age-based toxicity and none reported age-based quality of life (QOL) results. Pooled HRs [95% CIs] for patients <65 and ≥65 years were 0.61 [0.57-0.65] and 0.65 [0.61-0.70], respectively, with no difference between them (P = 0.14). Sensitivity analyses revealed similar results. Conclusion: our results suggest that older and young patients, who fulfil clinical trial eligibility, may derive similar relative survival benefits from novel oncology drugs. There is, however, a need to report age-based toxicity and QOL results to support patient discussions regarding the balance of treatment benefit and harm, to encourage informed decision-making.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".