Assessment of physical functioning in surgical candidates with non-small cell lung cancer: Preliminary comparison of performance status to symptom-limited cardiopulmonary exercise testing
Bibliographic record
Abstract
Background: Performance status (PS) scoring systems are used routinely by clinicians to guide management of patients with non-small cell lung cancer (NSCLC). However, PS scoring systems are subjective with poor inter-rater reliability and do not provide an objective measure of functional status. The aim of this study was to compare the variability in an objective measure of cardiorespiratory fitness (VO 2peak ), among surgical candidates with histologically confirmed NSCLC across different PS categories as assessed by the Eastern Cooperative Oncology Group (ECOG) score. Methods: Using a cross-sectional design, 389 subjects underwent an incremental cardiopulmonary exercise test with expired gas analysis to determine VO 2peak prior to surgical resection. Results: Mean VO 2peak significantly declined across increasing ECOG categories (Table 1). There was a wide range in VO 2peak in each ECOG category with similar ranges in VO 2peak within groups, in particular in subjects classified as ECOG 1 and 2. Table 1. Comparison of VO 2peak to ECOG PS in NSCLC Variable (n=187) (n=174) (n=28) ECOG 0 1 2 Mean VO 2peak (ml kg –1 min –1 ) 17.2±4.5 15.0±3.7 13.5±3.1 VO 2peak Range (ml kg –1 min –1 ) 5.0–31.5 4.3–24.8 8.9–21.9 Conclusions: VO 2peak may provide a more sensitive evaluation of physical functioning than ECOG. Accurate assessment of functional status may have important implications for mortality risk and therapeutic management in the oncology setting.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".