Prognostic factors and trends in outcome for small cell lung cancer over 20 years.
Bibliographic record
Abstract
e17518 Background: There has been little change in the chemotherapeutic treatment of small cell lung cancer (SCLC) over the last 30 years but changes in radiotherapy have demonstrated a survival benefit in clinical trails. There is substantial disagreement in the literature on whether or not there has been an improvement in survival for SCLC patients and which patient characteristics serve as important prognostic factors. The majority of the data comes from the selective population of patients included in clinical trials, which do not necessarily reflect real world therapeutic effectiveness. Methods: Using the Manitoba Cancer Registry and Manitoba’s physician billing database, we extracted information on all patients receiving a pathologic diagnosis of SCLC in the Canadian province of Manitoba between Jan 1, 1985 and Dec 31, 2004. Linear regression and Cox proportional hazard regression were then used to determine trends in SCLC incidence, survival, sex distribution, treatment, and prognostic factors. Results: Over the course of the study, the number of cases of SCLC diagnosed each year decreased by 1.41 cases/year (p=0.007), due entirely to a decrease in male cases. The proportion of females increased by 1%/year (p<0.001, 95% CI [0.007, 0.013]). In the whole study population, the proportion of patients receiving no antineoplastic treatment increased dramatically with age, from 11.7% in those ≤50 to 50.6% in patients >80 years old (p<0.001). There has been no change in 2 or 5-year survival (p>0.05 at both time points), which is true for both males and females. Two-year survival was 12.7% for females vs 8% for males (p<0.001), and at 5 years 5.3% of females vs 2.6% of males survive (p=0.002). Male sex was a negative prognostic factor with an adjusted hazard ratio of 1.27 (95% CI [1.16, 1.39]). Conclusions: Female sex is a positive prognostic factor in SCLC. In this population based trial, evolution of therapy over 20 years did not translate into improved survival. A further decline solely in the number of male cases may independently improve survival 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".