Lymphopenia is linked to an increased incidence of cancer in smokers without COPD
Bibliographic record
Abstract
Background: Cigarette smoke is a major risk factor for the development of cancer and COPD. These two diseases are linked by the pathogenetic role of adaptive immunity and tissue lymphocytes. However, little is known about the possible role of blood lymphocytes (BL) as a biomarker of cancer development in smokers with or without COPD. Aim: To study the 5-year incidence of all types of cancer in smokers and its relationship to blood lymphocyte count. Methods: A cohort of smokers (302 with and 209 without COPD), free of cancer at study entry, were followed for 5 years clinically and with blood cell counts. Results: During 5-year follow-up, 115 of 511 smokers (22.5%) developed all types of cancer, of which 33 were lung cancers (6%). When smokers with low BL (<1800 cells/µL) (n=178) where compared to those with high BL (>1800 cells/µL) (n=333), a higher incidence of all cancers was seen in the low BL group (55/178, 31% vs 60/333, 18%; p=0.001). A similar trend was observed for lung cancer (16/178, 9% vs 17/333, 5%; p=0.06). However, the higher incidence of all cancers and lung cancer in subjects with low BL was only present in smokers without COPD (15/48, 31% vs 20/161, 12%; p=0.003 and 5/48, 10% vs 0/161, 0%; p=0.001 respectively) and not in those with COPD. The observation that none of the 161 smokers without COPD and high BL developed lung cancer, is of interest considering that smoking history was similar in high and low BL groups. Conclusions: Lymphopenia is associated to a higher 5-year incidence of all types of cancer and of lung cancer especially in smokers without COPD. This may be related to the role of lymphocytes in suppressing tumor development.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".