SPECT/CT versus planar imaging to determine treatment strategy for non-small-cell lung cancer: a cost–effectiveness analysis
Bibliographic record
Abstract
Aim: SPECT/CT has been found to improve predicted postoperative forced expiratory volume in one second (ppoFEV 1 ) assessments in patients with non-small-cell lung cancer (NSCLC). Methods: An economic simulation was developed comparing the cost–effectiveness of SPECT/CT versus planar scintigraphy for a US payer. Clinical outcomes and cost data were obtained through review of the published literature. Results: SPECT/CT increased the accuracy ppoFEV 1 assessment, changing the therapeutic decision for 1.3% of nonsurgical patients to a surgical option, while 3.3% of surgical patients shifted to more aggressive procedures. SPECT/CT led to an expected cost of $4694 per life year gained, well below typical thresholds. Conclusion: SPECT/CT resulted in substantially improved health outcomes and was found to be highly cost-effective.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".