Impact of Intercurrent Introduction of Steroids on Clinical Outcomes in Advanced Non-Small-Cell Lung Cancer (NSCLC) Patients under Immune-Checkpoint Inhibitors (ICI)
Bibliographic record
Abstract
Background: Baseline steroids before ICI have been associated with poor outcomes, particularly when introduced due to cancer symptoms. Methods: Retrospective analysis of advanced NSCLC patients treated with ICI. We collected the use of intercurrent steroids (≥10 mg of prednisone-equivalent) within the first eight weeks of ICI. We correlated steroid use with patient outcomes according to the indications. Results: 413 patients received ICI, 299 were steroids-naïve at baseline. A total of 49 patients received intercurrent steroids (16%), of whom 38 for cancer-related symptoms and 11 for other indications, such as immune-related events. Overall, median (m) progression-free survival (PFS) was 1.9 months (mo.) [95% CI, 1.8-2.4] and overall survival (OS) 10 mo. [95% CI, 8.1–12.9]. Intercurrent steroids under ICI correlated with a shorter PFS/OS (1.3 and 2.3 mo. respectively, both p < 0.0001). Intercurrent steroids for cancer-related symptoms correlated with poorest mPFS [1.1 mo.; 95% CI, 0.9–1.5] and mOS [1.9 mo.; 95%CI, 1.5–2.4; p < 0.0001)]. No mOS and mPFS differences were found between cancer-unrelated-steroid group and no-steroid group. Steroid use for cancer-related symptoms was an independent prognostic factor for poor PFS [HR 2.64; 95% CI, 1.2–5.6] and OS [HR 4.53; 95% CI, 1.8–11.1], both p < 0.0001. Conclusion: Intercurrent steroids during ICI had no detrimental prognostic impact if the indication was unrelated to cancer symptoms.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".