Reporting quality of N-of-1 trials published between 1985 and 2013: a systematic review
Bibliographic record
Abstract
OBJECTIVES: To evaluate the quality of reporting of single-patient (N-of-1) trials published in the medical literature based on the CONSORT Extension for N-of-1 Trials (CENT) statement and to examine factors that influence reporting quality in these trials. STUDY DESIGN AND SETTING: Through a search of 10 electronic databases, we identified N-of-1 trials in clinical medicine published between January 1, 1985, and December 31, 2013. Two reviewers screened articles for eligibility and independently extracted data. Quality assessment was performed using the CENT statement. Discrepancies were resolved by consensus. RESULTS: We identified 112 eligible N-of-1 trials published in 87 journals and involving a total of 2,278 patients. Overall, kappa agreement between the two evaluators for compliance with CENT criteria was 0.80 (95% confidence interval: 0.79, 0.82). Trials assessed pharmacology and therapeutics (87%), behavior (11%), or diagnosis (2%). Although 87% of articles described the trial design (including the planned number of subjects and length of treatment period), the median percentage of specific CENT elements reported in the Methods was 41% (range, 16-87%), and the median percentage in the Results was 38% (range, 32-93%). First authors were predominantly from North America (46%), Europe (29%), and Australia (17%). Quality of reporting was higher in articles published in journals with relatively high-impact factors (P = 0.004). CONCLUSION: The quality of reporting of published N-of-1 trials is variable and in need of improvement. Because the CENT guidelines were not published until near the end of the period of this review, these results represent a baseline from which improvement may be expected in the future.
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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 | 0.980 | 0.996 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.292 | 0.052 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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; 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".