The Impact of Brain Metastases and Associated Neurocognitive Aspects on Health Utility Scores in EGFR Mutated and ALK Rearranged NSCLC: A Real World Evidence Analysis
Bibliographic record
Abstract
BACKGROUND: In lung cancer, brain metastases (BM) and their treatment are associated with high economic burden and inferior health-related quality of life. In the era of targeted therapy, real world evidence through health utility scores (HUS) is critical for economic analyses. MATERIALS AND METHODS: In a prospective observational cohort study (2014-2016), outpatients with stage IV lung cancer completed demographic and EQ-5D-3L surveys (to derive HUS). Health states and clinicopathologic variables were obtained from chart abstraction. Patients were categorized by the presence or absence of BM; regression analyses identified factors that were associated with HUS. A subset of patients prospectively completed neurocognitive function (NCF) tests and/or the FACT-brain (FACT-Br) questionnaire, which were then correlated with HUS (Spearman coefficients; regression analyses). RESULTS: < .01). HUS correlated with multiple elements of the FACT-Br and tests of NCF. CONCLUSION: r. Patients exhibiting disease control and those with oncogene-addicted tumors have superior HUS. IMPLICATIONS FOR PRACTICE: rearrangement non-small cell lung cancer (NSCLC), a diagnosis of brain metastases no longer consigns the patient to an inferior health state suggesting that new economic analyses in NSCLC are needed in the era of targeted therapies. Additionally, the EQ-5D questionnaire is associated with measures of health-related quality of life and neurocognitive scores suggesting this tool should be further explored in prospective clinical studies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".