Lung cancer in systemic lupus erythematosus
Bibliographic record
Abstract
An increased lung cancer risk in SLE has been suggested in the literature [ 1 ]. Our objective was to provide an updated analyses of the lung cancer cases from a multi-site international cohort study, including descriptive statistics of the demographics (age, sex, and race/ethnicity) of cases, as well the of histology. Data from an SLE sample of 15,980 SLE patients from 28 centers were analyzed (in Canada, the United States, the United Kingdom, Denmark, Sweden, Scotland, Korea and Iceland). Information on date of birth, sex and race was available, along with the date of SLE diagnosis. Cancer occurrence was ascertained through linkages with regional tumor registries. We assessed the demographic characteristics for all lung cancer cases in the SLE patients, and information on histology types was analyzed from the centers where this information was available. In the current analyses, 101 lung cancer cases that had occurred after SLE diagnosis were studied. The lung cancer cases were distributed across 21 centers. The average age of the SLE patients at lung cancer diagnosis was 60 years (median 40, standard deviation (SD) 10.9). The average SLE duration at the time of lung cancer diagnosis was 13 years (median 12, SD 10.6). Race/ethnicity was not provided by six centers (35 cases). Of the remaining 66 cases, the majority were Caucasian ( n = 54, 53.5%) followed by nine African-American, one Asian, one Pacific-Islander and one of unknown racial/ethnic origin. Histological lung cancer type was only provided by 12 centers (59 cases). The most common histological type reported within these 59 cases was squamous cell carcinoma ( n = 15, 25.4%; 95% CI = 16.1 to 37.8) followed by adenocarcinoma ( n = 13, 22%; 95% CI = 13.4 to 34.1) and nonsmall-cell carcinoma ( n = 5, 8.5%; 95% CI = 3.7 to 18.4). The remaining 44% were composed of carcinomas not otherwise specified and a variety of uncommon tumors: large cell, clear cell, solid, bronchoalveolar, adenosquamous, epithelial hemangioendothelioma, oat cell, carcinoid, small cell and mucinous histological types. In the general population, about 30 to 40% of lung cancer cases are adenocarcinoma, with 20 to 30% squamous cell carcinoma, and 10% large cell carcinoma [ 2 ]. Our results suggest a similar distribution, but with a possibly lower proportion of adenocarcinomas, and a higher number of uncommon lung cancer types. Further work is planned to assess other features of these cancers.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".