Underreporting of Symptomatic Adverse Events in Phase I Clinical Trials
Bibliographic record
Abstract
BACKGROUND: Clinician reporting of symptomatic adverse events (AEs) in phase I trials uses the Common Terminology Criteria for Adverse Events (CTCAE). The utility of the patient-reported outcomes (PROs) version of the CTCAE (PRO-CTCAE) in this setting is unknown. This prospective, observational study compared patient- and clinician-reported symptomatic AEs in phase I patients. METHODS: Phase I study-eligible patients at Princess Margaret were surveyed with the PRO-CTCAE full-item library (78 symptomatic AEs) at baseline (BL), mid-cycle 1, and mid-cycle 2 (C2). Patient and trial characteristics, best response, and survival data were collected. Presence or absence of patient- (PRO-CTCAE) or clinician-reported symptomatic AEs were compared (kappa) at defined timepoints and overall (BL+ mid-cycle 1 + C2). RESULTS: Of 292 patients approached from May 2017 to January 2019, a total of 265 (90.8%) were consented, with 243 (91.7%) evaluable and 552 PRO-CTCAE surveys (completion rate = 98.7%) included in analyses. Evaluation of overall patient-reported symptomatic AEs identified 50 PRO-CTCAE and 11 CTCAE items with 10% or greater reporting frequency. Nineteen CTCAE items were reported as 1% or less despite matched PRO-CTCAE items reporting as 10% or greater. Underreported categories included sexual health, bodily emissions, and cognition. Clinician- relative to patient-reporting frequency (ratio) demonstrated 9 symptomatic AEs with a 50-fold or more lower clinician reporting rate. Overall patient-clinician agreement for individual symptomatic AEs ranged from poor (κ = 0.00-0.19) to moderate (κ = 0.40-0.59), with discordance driven by lack of clinician reporting. Dyspnea (κ = 0.54) and peripheral neuropathy (κ = 0.63) at BL and limb edema (κ = 0.55) at C2 demonstrated the highest patient-clinician agreement. CONCLUSIONS: Poor to moderate patient-clinician agreement for symptomatic AEs suggests clinician underreporting in phase I trials. Analyses of severity and interference PRO categories are ongoing.
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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 | 0.381 | 0.529 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".