Real world outcomes in extensive stage small cell lung cancer (ES-SCLC) treated with consolidative thoracic radiation (cTRT) and chemoimmunotherapy (CIT): A population level study.
Bibliographic record
Abstract
e20111 Background: Despite recent survival improvements from the combination of immune checkpoint inhibitors (ICI) with chemotherapy for patients with ES-SCLC, outcomes remain limited for the majority of patients. Addition of cTRT may elicit a synergistic response and contribute to improved disease control and survival, but there is limited data supporting routine use from either the trial or real world contexts. This study aims to investigate the safety and time-to-event outcomes of patients treated with CIT and cTRT. Methods: Demographic, clinical, treatment and outcome details were extracted from the Glans-Look Lung Cancer Research Database, a province-wide real-world outcomes registry of patients treated in routine practice. A population-level cohort of ES-SCLC patients receiving CIT and cTRT between 2019 and 2023 were identified. Results: 30 patients were identified. Median age was 68y. At CIT initiation; 63% had ECOG performance status ≤ 1, 17% had brain metastases; 20% received prophylactic cranial irradiation. CIT was comprised of platinum-etoposide and ICI: durvalumab (67%) or atezolizumab (33%), followed by maintenance ICI (median 5.8 months). cTRT was administered a median 4.8 months after CIT initiation; n=13 (43%) received 30Gy/10, n=2 (7%) received dose escalation to 40-45Gy in 14-20 fractions, and n= 15 (50%) received 20Gy-25Gy over 5-10 fractions. Reasons for discontinuation of CIT were primarily to progressive disease (n=18, 75%); with n=16 patients receiving second line systemic treatment (94% chemotherapy, 6% durvalumab rechallenge), and n=1 receiving additional thoracic stereotactic ablative body radiation. Post-cTRT pneumonitis was recorded in n=3 (10%) of patients, ranging from (CTCAE v5.0 Grade 1-3 severity), requiring hospitalization + treatment break (n=1), ICI termination (n=1), or resolving without intervention (n=1). Time-to-event outcomes are presented in the table. Receiving durvalumab as opposed to atezolizumab did not impact either mPFS (10 vs. 12 months, log rank=0.4; HR: 1.3 [95% CI: 0.8 - 5.9], p=0.12) or OS (17 vs. 13.2 months, log rank p=0.87; HR: 2.2 [95% CI: 0.4 – 4.4], p=0.67). Conclusions: ES-SCLC treatment comprised of both CIT and cTRT appears feasible and effective in among real-world patients. Pneumonitis, a potential complication of combined ICI and thoracic radiation, was infrequently observed in this cohort. Use of cTRT in addition to CIT appears to numerically surpass the ~13-month mOS observed within clinical trials which used first-line CIT without additional cTRT for ES-SCLC. [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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".