Early versus delayed bilateral subthalamic deep brain stimulation for parkinson's disease: A decision analysis
Bibliographic record
Abstract
The long-term benefits of subthalamic nucleus deep brain stimulation (STN DBS) applied earlier in the disease course, before significant disability accumulates, remain to be determined. We developed a Markov state transition decision analytic model to compare effectiveness in quality-adjusted life years (QALYs) of STN DBS applied to patients with PD at an "early" ("off time" 10-20%) versus "delayed" stage ("off time" >40%). A lifelong time horizon and societal perspective were assumed. Probabilities and rates were obtained from literature review; utilities were derived using the time trade-off technique and a computer-assisted utility assessment software tool applied to a cohort of 22 STN-DBS and 21 non-STN-DBS PD patients. Uncertainty was assessed through one- and two-way sensitivity analyses and probabilistic sensitivity analysis using second-order Monte Carlo simulations. Early STN DBS was preferred with a quality-adjusted life expectancy of 22.3 QALYs, a gain of 2.5 QALYs over those with delayed surgery (19.8 QALYs). Early STN DBS was preferred in 69% of 5,000 Monte Carlo simulations. Early surgery was robustly favored through most sensitivity analyses. Delayed STN DBS afforded greater QALYs when using utility estimates exclusively from non-STN-DBS patients and, for the entire group, if the rate of motor progression were to exceed 25% per year. Although decision modeling requires assumptions and simplifications, our exploratory analysis suggests that STN DBS performed in early PD may convey greater quality-adjusted life expectancy when compared to a delayed procedure. These findings support further evaluation of early STN DBS in a controlled clinical trial.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 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".