User‐only design to assess drug effectiveness in clinical practice: application to bisphosphonates and secondary prevention of fractures
Bibliographic record
Abstract
PURPOSE: Different strategies applicable to control for confounding by indication in observational studies were compared in a large population-based study regarding the effect of bisphosphonates (BPs) for secondary prevention of fractures. METHODS: The cohort was drawn from healthcare utilization databases of 13 Italian territorial units. Patients aged 55 years or more who were hospitalized for fracture during 2003-2005 entered into the cohort. A nested case-control design was used to compare BPs use in cohort members who did (cases) and who did not experience (controls) a new fracture until 2007 (outcome). Three designs were employed: conventional-matching (D1 ), propensity score-matching (D2 ), and user-only (D3 ) designs. They differed for (i) cohort composition, restricted to patients who received BPs straight after cohort entry (D3 ); (ii) using propensity score for case-control matching (D2 ); and (iii) compared groups of BPs users versus no users (D1 and D2 ) and long-term versus short-term users (D3 ). RESULTS: Bisphosphonate users had odds ratios (95% confidence interval) of 1.20 (1.01 to 1.44) and 0.95 (0.74 to 1.24) by applying D1 and D2 designs, respectively. Statistical evidence that long-term BPs use protects the outcome onset with respect to short-term use was observed for user-only design (D3 ) being the corresponding odds ratio (95% confidence interval) 0.64 (0.44 to 0.93). CONCLUSIONS: User-only design yielded closer results to those seen in RCTs. This approach is one possible strategy to account for confounding by indication.
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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 | 0.020 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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 | 0.001 |
| 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".