Cost Effectiveness of Intrathecal Drug Therapy in Management of Chronic Nonmalignant Pain
Bibliographic record
Abstract
OBJECTIVE: To evaluate the cost effectiveness of intrathecal drug therapy (IDT) compared with conventional medical management (CMM) for patients with refractory chronic noncancer pain. METHODS: A probabilistic Markov model was developed to evaluate the cost effectiveness of IDT versus CMM from the perspective of a Canadian provincial Ministry of Health using data from our pain clinic. The model followed costs and outcomes in 6-month cycles. Health effects were expressed as quality-adjusted life years (QALYs) gained. Resources use included drugs, physician visits, laboratory tests, scans, and hospitalizations. Unit costs were gathered from public sources and were expressed in 2011 Canadian dollars. Costs and effects were evaluated over a time horizon of 10 years and discounted at 5% per annum after the first year. Cost effectiveness was identified by deterministic and probabilistic sensitivity analyses (50,000 Monte Carlo iterations). RESULTS: Over 10 years, total costs were $61,442 for IDT and $48,408 for CMM. Thus, the incremental effectiveness of IDT was 1.1508 QALYs at an incremental cost of $13,034, resulting in an incremental cost-effectiveness ratio of $11,326/QALY gained. The probability of IDT providing a cost-effective alternative to CMM was 50% and 84% at a willingness-to-pay threshold of $14,200 and $20,000/QALY, respectively. The results were most sensitive to the cost of CMM, the probability of reaching an optimal health state with dual-drug IDT, and the effectiveness of CMM therapy. Sensitivity analyses showed that results were robust to plausible variations in model costs and effectiveness inputs. DISCUSSION: IDT is cost effective compared with CMM in the management of chronic noncancer pain.
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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 | 0.043 | 0.001 |
| 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 | 0.000 |
| 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".