Glutathione S-Transferase M1 (GSTM1) Polymorphisms and Lung Cancer: A Literature-based Systematic HuGE Review and Meta-Analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multiple genes have been studied for potential associations with lung cancer. The gene most frequently associated with increased risk has been glutathione S-transferase M1 (GSTM1). The glutathione S-transferase enzyme family is known to catalyze detoxification of electrophilic compounds, including carcinogens, therapeutic drugs, environmental toxins, and products of oxidative stress. In this review, the authors summarize the available evidence associating lung cancer with the GSTM1 gene. They describe results from an updated meta-analysis of 98 published genetic association studies investigating the relation between the GSTM1 null variant and lung cancer risk including 19,638 lung cancer cases and 25,266 controls (counting cases and controls in each study only once). All studies considered, the GSTM1 null variant was associated with an increased risk of lung cancer (odds ratio (OR) = 1.22, 95% confidence interval (CI): 1.14, 1.30), but no increase in risk was seen (OR = 1.01, 95% CI: 0.91, 1.12) when only the five largest studies (>500 cases each) were considered. Furthermore, while GSTM1 null status conferred a significantly increased risk of lung cancer to East Asians (OR = 1.38, 95% CI: 1.24, 1.55), such a genotype did not confer increased risk to Caucasians. More data regarding the predictive value of GSTM1 genetic testing are needed before population-based testing may be reasonably considered.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it