4-Year Cost Trajectories in Real-World Patients Matched to the Metabolic Profiles of Trial Subjects Before/After Treatment with Phentermine-Topiramate
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: Our objective was to estimate 4-year healthcare costs associated with the metabolic profile of patients before and after 1 year of treatment with phentermine (15 mg) and topiramate extended-release (92 mg) [phentermine-topiramate ER]. DESIGN AND METHODS: Using a medical records database, we created two patient cohorts reflecting metabolic profiles of subjects before and after phentermine-topiramate ER therapy during the 1-year CONQUER trial. We matched database patients with trial subjects by age, sex, body mass index (BMI), and hypertension, glycemic, and triglyceride status. We collected real-world data on emergency department and outpatient visits, hospitalizations, and drug prescriptions over 4 years, linking them to reimbursements to estimate US private insurance costs for post-trial (n = 2295) versus pre-trial intention-to-treat (ITT) patients (n = 2295). Secondary analysis assessed responders (completers losing ≥5 % body weight [n = 1285]). RESULTS: Over 4 years, the mean cost per patient in the post- versus pre-trial ITT-group was $US32,432 versus $US34,725 (mean difference -2292; 95 % confidence interval [CI] -4776 to 209). In responders, corresponding costs were $US30,558 versus $US33,936 (mean difference -3378; 95 % CI -6496 to -464). Costs for post- versus pre-trial responders were lower for outpatient visits, emergency visits, and medications (all P < 0.05). CONCLUSION: Excluding treatment cost and potential side effects, patients matched to profiles of phentermine-topiramate ER responders had lower costs than patients matched to pre-treatment profiles.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it