Hormone replacement use, age, and prognosis for women with non-small cell lung cancer
Bibliographic record
Abstract
18099 Background: Lung cancer is the leading cancer cause of mortality in women. A recent report by Ganti et al, presented at ASCO, suggested that women who had been taking hormone replacement therapy (HRT) had significantly decreased survival after a lung cancer diagnosis. In addition, in women fit enough to be enrolled on randomized controlled trials in advanced lung cancer, younger women (under age 60) may have a worse prognosis than older women. The purpose of this current study was to do an institutional review on women diagnosed with lung cancer to determine whether these novel prognostic factor results could be duplicated. Methods: All female patients who were diagnosed with lung cancer between January 1999 and December 2003 were reviewed for age at diagnosis, stage, treatment, smoking history, hormonal therapy, performance status, weight loss, age at menopause, and overall survival. Patients were excluded if they had small cell lung cancer, were unknown primary, or had previous or synchronous non-lung, non-skin, cancers. Statistics were performed using Chi- Squared tests for categorical variables, while the Kaplan-Meier method and Cox-Regression models were used for univariate and multivariate analysis of overall survival. Results: Of 397 patients, the majority (68%) were stage 3 or 4. There were very few never smokers (5%). Twenty-nine percent of patients had prior HRT, with no effect on overall survival, with median survivals of 13 months in the non- HRT group and 14 months in the HRT group. The most powerful predictors of overall survival were: Stage, Performance Status, and Weight Loss. Patients aged 60–75 did as poorly as younger patients (median survival 10 months for stage 4 disease). Conclusions: Stage, performance status, and weight loss, are the most powerful predictors of survival for women with lung cancer. Patients with prior HRT use do not have inferior outcomes compared to non-HRT users. In a non-clinical trial population, patients under age 60 have similar outcomes as women aged 60 to 75. No significant financial relationships to disclose.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".