Quality of adverse event reporting in phase III randomized controlled trials of breast and colorectal cancer: A systematic review
Bibliographic record
Abstract
BACKGROUND: Clinical trial reports often emphasize efficacy over harms, leading to misinterpretation of the risk-to-benefit ratio of new therapies. Clear and sufficiently detailed reporting of methods and results is especially important in the abstracts of trial reports, as readers often base their assessment of a trial on such information. In this study, we evaluated the quality of adverse event (AE) reporting and abstract quality in phase III randomized controlled trials (RCTs) of systemic therapies in breast and colorectal cancer. METHODS: Medline, EMBASE, Cochrane Database of RCTs, and Cochrane Database of Systematic Reviews were searched from November 2005 to September 2018. Phase III RCTs evaluating systemic therapies in breast or colorectal cancer were included. Each article was independently reviewed by two investigators using a standardized data extraction form based on guidelines developed by the Consolidated Standards of Reporting Trials (CONSORT) group. Descriptive statistics, bivariate analysis, and multivariable linear regression were used to analyze data. All statistical tests were two-sided. RESULTS: Of 166 RCTs identified, 99.4% reported harms in the manuscript body, and 59.6% reported harms in the abstract. Reporting was restricted to severe harms in 15.6% of RCTs. Statistical comparison of AE rates went unreported in 59.0% of studies. Information regarding AEs leading to dose reductions, treatment discontinuations, or study withdrawals went unreported in 59.3%, 18.7%, and 86.8% of studies, respectively. Recently published RCTs (P = .009) and those sponsored at least partially by for-profit companies (P = .003) had higher abstract quality scores. CONCLUSIONS: Breast and colorectal cancer phase III RCTs inadequately report CONSORT-compliant AE data. Improved guideline adherence and abstract reporting is required to properly weigh benefits and harms of new oncologic therapies. SYSTEMATIC REVIEW REGISTRATION NUMBER: CRD42019140673.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.194 | 0.652 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.087 | 0.003 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; both teacher heads 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".