Is health-related quality of life (HRQoL) reporting keeping pace with new drug approvals in hematology and oncology: A five-year analysis of 245 drug approvals.
Bibliographic record
Abstract
6519 Background: HRQoL data in cancer clinical trials can inform tolerability of new drugs, facilitate informed decision-making, and influence health care and policy decisions, but are frequently underreported. We reviewed all registration trials that informed Food and Drug Administration (FDA) approval between 2015-2020 for latency and quality of HRQoL reporting. Methods: HRQoL data for each clinical trial associated with FDA drug approval between 7/2015-5/2020 was collected retrospectively from multiple sources including the FDA and clinicaltrials.gov website, conference abstracts, and journal manuscripts. The aim of the study was to analyze the proportion of trials reporting HRQoL, quality of HRQoL data, latency between FDA approval and first reporting of HRQoL data, and association between changes in HRQOL and overall survival (OS) and progression-free survival (PFS) outcomes. Results: Of the 259 trials involving 245 drug approvals, majority involved solid tumors (61.4%), were phase III (59.1%), and led to approval based on a non-PFS/OS endpoint (52.9%). HRQoL was a pre-specified endpoint in 55.2% and reported in 49.8% trials. HRQoL data was published by the time of FDA approval in only 41.8% cases, 24.8% reported HRQoL data > 12 mo after approval. Further, among trials reporting HRQoL (n = 129), HRQoL data was first reported in the primary paper in only 34.1%, and either in an ancillary paper in 41.9% or an ancillary abstract in 24% trials. Of the 129 trials with HRQoL data, an improvement in HRQoL was seen in 44.2%, no significant change in 41.9%, mixed results in 11.6%, and worsening in 2.3% of trials. Overall, by the time of FDA approval, OS and PFS data were reported in 59% (152/259) and 65% (168/259) trials respectively with an OS benefit seen in 23.9% (62/259) trials, and PFS benefit in 38.6% (100/259) trials. Of the 84 trials that led to FDA approvals based solely on response rate, HRQoL was reported in only 23.8% (n = 24) with a HRQoL benefit seen in only 9.5% (n = 8) trials. Trials reporting either no significant impact on HRQoL or a mixed impact on HRQoL reported median OS benefit of 4.6 months and 4.2 months respectively. In trials reporting HRQoL data > 6 mo from FDA approval, OS benefit of < 3 mo was seen in 17.8% (8/45) trials. No significant time trends were noted during the study period. Conclusions: There was significant underreporting of HRQoL outcomes in trials ( < 50%) associated with FDA drug approvals between 2015-2020 with majority of trials reporting HRQoL data in an ancillary paper/abstract, and at a much later time than the FDA approval. While it is widely accepted that timely dissemination of HRQoL data from cancer drug trials are vital for clinical and regulatory decisions, no improvement in reporting rates were noted over past 5 years. Only 10% of drugs approved on the basis of response rates showed improvement in HRQoL in the registration trials.
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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 | 0.048 | 0.070 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.005 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".