Predictors of and longitudinal assessment of health utility scores in patients with small cell lung cancer using real-world data.
Bibliographic record
Abstract
e19306 Background: Recent advances in small cell lung cancer (SCLC) treatments necessitate a better understanding of health utility scores (HUS) of patients treated under standard regimens to facilitate robust pharmaco-economic assessments. HUS collected in clinical trials may be inherently skewed due to restrictive eligibility criteria, highlighting the need for real-world data. Methods: In this cohort observational study, HUS were evaluated in SCLC patients through EQ-5D surveys. We also evaluated patient reported (pr) ECOG performance status (PS)), treatment toxicities (modified patient reported (mpr) CTCAE) and symptoms (Edmonton Symptom Assessment System, ESAS). Clinical data were abstracted from electronic medical records. The impact of these variables on HUS was explored using regression. Results: Of 282 clinical encounters (12% newly diagnosed; 37% stable on treatment; 22% progressing; 29% stable off therapy/other) in 111 SCLC patients (58% male; 64% extensive stage), 29% had pr-ECOG PS ≥ 2 at the first encounter. Mean HUS in treatment naïve patients with limited disease was 0.848 (SEM = 0.028); for extensive stage, mean HUS = 0.715 (SEM = 0.046). Extensive stage (β = -0.12; p = 0.03), bone metastases (β = -0.10; p = 0.04), females (β = -0.07; p = 0.006), and pr-ECOG PS ≥ 2 (β = -0.21; p < 0.001) were each associated with decreased HUS in multivariable analyses. When excluding pr-ECOG PS from the model (highly correlated with HUS), progressive disease (β = -0.07; p = 0.02) was also associated with decreased HUS. Longitudinally, in patients with disease stability, HUS were unchanged in limited disease, but slowly decreased for extensive stage over time. HUS were inversely associated with increasing severity of most measured toxicities (mpr-CTCAE rho values ranged from -0.34 to -0.47) and symptoms (rho values -0.27 to -0.54). Conclusions: HUS in SCLC is impacted by the presence of extensive stage and bone metastases, in addition to cancer symptoms and treatment toxicities. The values reported from this real-world sample provides a basis in which to compare with new SCLC therapies in health technology assessments. [Table: see text]
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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 | 0.008 | 0.028 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".