Real-world predictors of survival in patients with extensive-stage small-cell lung cancer in Manitoba, Canada: a retrospective cohort study
Bibliographic record
Abstract
Background: Extensive-stage small-cell lung cancer (ES-SCLC) is an incurable cancer with poor prognosis in which characteristics predictive of long-term survival are debated. The utility of agents such as immune checkpoint inhibitors highlights the importance of identifying key characteristics and treatment strategies that contribute to long-term survival and could help guide therapeutic decisions. Objective: This real-world analysis examines the characteristics, treatment patterns, and clinical outcomes of patients receiving chemotherapy without immunotherapy for ES-SCLC in Manitoba, Canada. Methods: A retrospective cohort study assessed patient characteristics, treatment, and survival duration (short: <6 months; medium: 6-24 months; long: >24 months) using the Manitoba Cancer Registry and CancerCare Manitoba records. Eligible patients were aged >18 years with cytologically confirmed ES-SCLC diagnosed between January 1, 2004, and December 31, 2018, and received cytotoxic chemotherapy (CT). The one-, two-, and five-year probabilities of overall survival (OS) were assessed relative to patient, disease, and treatment characteristics using Kaplan-Meier methods and Cox proportional hazards models. Results: This analysis included 537 patients. Cisplatin was used in 56.1% of patients, 45.6% received thoracic radiotherapy (RT), and few received prophylactic cranial irradiation (PCI). In the overall cohort, one-, two- and five-year OS rates were 26%, 8%, and 3%, respectively. For patients with Eastern Cooperative Oncology Group Performance Status (ECOG PS) 0, OS rates at one, two, and five years were 43%, 17%, and 10%, respectively, vs. 27%, 8%, and 2% for those with ECOG PS 1-2, and 16%, 3%, and 3% for those with ECOG PS 3-4. In long-term survivors, ECOG PS scores were lower and abnormal laboratory test results were less frequent. Overall, 74.4% of long-term survivors received thoracic RT and 53.5% received PCI. Known poor prognostic factors - including brain/liver metastases, high lactate dehydrogenase (LDH), abnormal sodium, and low hemoglobin levels - were less common but still seen in long-term survivors. Conclusion: Although rare, patients with ES-SCLC may experience long-term survival with CT ± thoracic RT ± PCI. Factors predicting long-term survival include traditional prognostic factors such as ECOG PS, LDH level, and receipt of thoracic RT or PCI. These findings support current treatment algorithms for ES-SCLC and provide baseline survival estimates to assess the real-world impact of adding immune checkpoint inhibitors in the future.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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".