Laminoplasty compared to laminectomy and fusion for degenerative cervical myelopathy: a cost-utility analysis
Bibliographic record
Abstract
Background: Degenerative cervical myelopathy (DCM) is a leading cause of spinal cord dysfunction in adults. Posterior surgical options include laminoplasty (LP), a motion-preserving procedure, and laminectomy with fusion (LF), which offers stabilization but at higher cost. A cost-utility comparison of these approaches is lacking. Methods: We conducted a cost-utility analysis using a 5-year Markov state-transition model from a healthcare payer perspective. The study cohort was drawn from 3 multicenter prospective studies of patients with DCM. To reduce baseline confounding, patients who underwent LF or LP were matched 2:1 using propensity score matching. Quality-adjusted life years (QALYs) were derived from SF-6D utilities calculated from SF-36 scores at baseline and 12 months. Costs and transition probabilities were derived from meta-analysis and registry data. We calculated incremental cost-utility ratios (ICURs) and net monetary benefit (NMB) using a willingness-to-pay (WTP) threshold of $100,000 per QALY. Sensitivity analyses included deterministic variation and 1,000-iteration Monte Carlo microsimulation. Results: 240 matched patients were included (87 LP, 153 LF). Baseline mJOA, NDI and SF6D scores were similar between groups. In the base-case, LP cost $24,283, yielding 3.53 QALYs, while LF cost $35,902, yielding 3.72 QALYs, resulting in an incremental cost-utility ratio (ICUR) of $59,796 per QALY, favouring LF. In probabilistic microsimulation, LP had a mean cost of $24,579 (95% confidence interval (CI): $23,933-$25,225) and a mean NMB of $326,281 (95% CI: $322,672-$329,891), while LF cost $35,936 (95% CI: $35,583-$36,288) with a mean NMB of $333,189 (95% CI: $328,629-$337,748). LP was the optimal strategy in 47% of simulations versus 53% for LF. Conclusions: Both LP and LF can be cost-effective for DCM. While the base-case favored LF, probabilistic sensitivity analysis revealed no clear cost-utility advantage with comparable NMBs. Economic considerations alone should not drive surgical decision-making and treatment choice should be tailored to individual patient factors and local resource contexts.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.003 |
| 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".