Treatment outcomes after methylphenidate in adults with attention-deficit/hyperactivity disorder treated with lisdexamfetamine dimesylate or atomoxetine
Bibliographic record
Abstract
PURPOSE: To compare treatment adherence, discontinuation, add-on, and daily average consumption (DACON) among adults with attention-deficit/hyperactivity disorder receiving second-line lisdexamfetamine dimesylate (LDX) or atomoxetine (ATX), following methylphenidate. PATIENTS AND METHODS: A retrospective cohort study using US commercial claims databases (Q2/2009-Q3/2013). RESULTS: At month 12, the LDX cohort (N=2,718) had a higher adherence level (proportion of days covered: 0.48 versus 0.30, P<0.001) and was less likely to discontinue (Kaplan-Meier estimate: 63% versus 85%, P<0.001) than the ATX cohort (N=674). There were no statistical differences in treatment add-on rates between cohorts (Kaplan-Meier estimate: 26% versus 25%, P=0.297). The LDX cohort had a lower DACON (1.10 versus 1.31, P<0.001) and was less likely to have a DACON >1 (adjusted odds ratio: 0.20, 95% confidence interval: 0.15-0.25, P<0.001) than the ATX cohort. CONCLUSION: Adults with attention-deficit/hyperactivity disorder treated with LDX following methylphenidate had a higher treatment adherence and lower discontinuation and DACON relative to those treated with ATX following methylphenidate.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; 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".