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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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".