Extrapulmonary small cell cancer
Bibliographic record
Abstract
BACKGROUND: The objective of this study was to determine variables that correlate with the survival of patients with extrapulmonary small cell carcinoma (EPSCC). METHODS: Medical records of 101 eligible patients with EPSCC who were diagnosed in Saskatchewan from 1971 to 2002 were reviewed. Survival was calculated by using the Kaplan-Meier method. A logistic regression analysis with a backward elimination was carried out to determine prognostic variables that predicted mortality. RESULTS: The median patient age was 72 years (range, 24-100 years), and the male-to-female ratio was 1.4:1. The primary disease sites were as follows: breast, 9%; gastrointestinal, 20%; genitourinary, 18%; gynecologic, 11%; head and neck, 10%; thymus, 2%; and unknown primary site, 31%. Fifty-one patients had limited disease (LD), and 50 patients had extensive disease (ED). Patients with LD had a median overall survival of 34 months (range, 0.2-276 months) compared with 2 months (range, 0.1-108 months) in patients with ED (P < .0001). Among different primary sites, patients with gynecologic small cell cancer (SCC) had a median survival of 54.4 months, whereas patients with SCC of an unknown primary site had a survival of 2.5 months. Among various variables that were examined with respect to their prognostic importance, an abnormal white blood cell count (odds ratio [OR], 6.9; 95% confidence interval [95% CI], 3.4-14.1), an Eastern Cooperative Oncology Group performance status >2 (OR, 4.5; 95% CI, 2.1-9.9), and ED (OR, 2.7; 95% CI, 1.4-5.0) were found to be correlated significantly with mortality. CONCLUSIONS: The gastrointestinal and genitourinary tracts were the 2 major sites involved by EPSCC in the current series. Survival varied according to the primary sites, and patients with gynecologic tumors had the best prognosis. An abnormal white blood cell count, a poor performance status, and disease extent were important factors in predicting survival.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".