Tumor-related symptoms (TRS) assessment in patients (pts) with advanced non-small cell lung cancer (NSCLC) treated with gefitinib or erlotinib: Preliminary results of an observational study.
Bibliographic record
Abstract
e20619 Background: Edmonton Symptoms Assessment Scale (ESAS) is a validated tool in palliative care, which evaluates physical symptoms through a numeric scale (0-10). Symptoms improvement as a predictive factor for response rate (RR) in pts with advanced NSCLC treated with tyrosine-kinase inhibitors (TKIs) has not yet been evaluated. To this purpose, we performed an observational retrospective study. Methods: Pts with advanced NSCLC treated with gefitinib or erlotinib were eligible. Primary outcome was the association between treatment response and tumor-related symptoms (TRS) (pain, asthenia, dyspnea) improvement. ESAS was performed at day 1 and 14 of each 28-d cycle. Symptoms' scores were divided into: not clinically relevant (0-4, NCR) and clinically relevant (5-10, CR). Sample size estimation was 115 to 165 pts to be needed for the expected difference in the primary outcome. Differences between symptoms' groups were analyzed with the paired-data McNemar-test. All the associations were estimated using the Chi-Square test. Kaplan-Meier method was used for survival calculation. Uni- and multivariate survival analysis were carried out using the Cox regression model. Results: Here we report data about 73 consecutive pts; median age: 69 years, males 68%, ECOG PS 0-1 86%, smokers 68%, EGFR-mutated 22%. Treatment was gefitinib (23%) or erlotinib (77%). RR: RC/RP 14%, SD 20%, PD 66%. Median follow-up was 7 months. 63% of pts had at least one CR TRS at baseline. Among these pts, a significant reduction (p<0.0001) of TRS during treatment was observed (Table). Our preliminary data show a significant association between dyspnea/asthenia and RR (p=0.01). At the multivariate analysis, TRS improvement correlates with both PFS and OS. Also related with survival were PS, EGFR status (PFS) and RR (OS). Conclusions: Our preliminary data show that TRS improvement is significantly associated with treatment response and appears to be a prognostic factor during treatment with TKIs. [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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.001 | 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".