Real-world treatment patterns, clinical outcomes, and health care resource utilization in extensive-stage small cell lung cancer in Canada.
Bibliographic record
Abstract
e20575 Background: Extensive stage small cell lung cancer (ES-SCLC) patients face a high risk of recurrence and a uniformly poor prognosis. Real-world evidence related to treatment patterns, clinical outcomes, and healthcare resource utilization is needed to highlight the unmet clinical need and demand for novel therapies within this patient population. Methods: A population-based, retrospective, longitudinal study of adult ES-SCLC patients diagnosed in the province of Alberta, Canada between January 2010 and December 2018 was conducted using provincial electronic medical records and administrative claims data. Results: A total of 1,941 ES-SCLC patients were included of which 1,465 (75%) initially presented with ES-SCLC and 476 (25%) had recurrent disease. Among newly diagnosed ES-SCLC patients, front-line therapy was as follows: 523 (35.7%) chemotherapy and radiotherapy, 280 (19.1%) chemotherapy alone, 133 (9.1%) radiotherapy alone, and 529 (36.1%) best supportive care. The primary sites of radiation were the chest (67.1%) and the brain (45.7%). Median age at diagnosis was 70 years (range: 39-94) and 50.2% were men. In contrast to the de novo patients, the majority of recurrent cases (71.6%) received no front-line therapy. In the full cohort (de novo and recurrent cases), 46.5% of patients initiated first-line, 8.7% second-line, and 1.4% third-line chemotherapy. The majority of patients received either carboplatin plus etoposide (49.5%) or cisplatin plus etoposide (43.0%) in first-line. Median overall survival was higher for patients who were treated with chemotherapy and radiotherapy (10.59 months; 95% CI: 10.03-11.61) compared to patients who received chemotherapy alone (5.65 months; 95% CI: 5.06-6.12), radiotherapy alone (3.02 months; 95% CI: 2.47-4.01), or best supportive care (0.82 months; 95% CI: 0.72-0.92; log-rank p-value < 0.001). Among patients who received first-line systemic therapy, the 1-year, 2-year and 5-year survival was 29.1% (95% CI: 26.3-32.3), 7.3% (95% CI: 5.7-9.2) and 2.9% (95% CI: 1.8-4.5), respectively and the average time spent in hospital was 17, 11, and 10 days per patient within years 1, 2, and 3, respectively. Conclusions: In a Canadian real-world setting, the initiation of first-line treatment in ES-SCLC was low with significant attrition in subsequent lines. It was evident that patients who received treatment had greater survival compared to those who do not. Collectively, these results underscore the need for effective front-line therapeutic options and highlight the potential for novel therapies to improve patient outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".