Impact of National Comprehensive Cancer Network Guidelines Inclusion of Level 1 Evidence on Insurance Denial for Randomized Controlled Trial Patients with Metastatic Spine Disease
Bibliographic record
Abstract
Background: The primary treatment of metastatic spine disease is radiation therapy (RT), traditionally conventional external beam RT (EBRT) or stereotactic body RT (SBRT). Until recently, there had been no Level 1 evidence supporting SBRT over EBRT, which has led to difficulties obtaining insurance approval. Publication of the first randomized controlled trial (RCT) comparing SBRT to EBRT for spine metastases [Canadian Cancer Trials Group (CCTG)] helped change this. The results showed superiority of SBRT in pain response; however, the results were not cited by The National Comprehensive Cancer Network (NCCN) until March 24, 2023. We present results from an ongoing RCT to assess the impact of this NCCN inclusion on insurance denials for trial-eligible patients. Materials and methods: The ongoing SPORTSMEN RCT randomizes metastatic spine cancer patients to SBRT versus EBRT. Trial-eligible patients during the first six months were examined to assess if SBRT was denied by insurance before March 24, 2023, versus afterwards. Fisher's exact test was used to assess for statistical significance. Results: Prior to CCTG NCCN inclusion, 25% of 12 trial-eligible patients experienced SBRT insurance denial. Following NCCN inclusion, of 8 patients, one (12.5%) has undergone insurance denial of SBRT. These differences were not statistically significant. Conclusions: The inclusion of Level 1 evidence in the NCCN guidelines has resulted in a numerical halving of spine SBRT insurance denials on a RCT, with the small sample size likely the largest culprit of not meeting statistical significance. These findings illustrate the importance of generating high-quality evidence, followed by timely inclusion into the NCCN guidelines.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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".