The effect of estrogen <i>vs.</i> combined estrogen‐progestogen therapy on the risk of colorectal cancer
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
Studies suggest that estrogen therapy (ET) and combined estrogen-progestogen therapy (EPT) may have different associations with colorectal cancer (CRC) risk, but data are conflicting. Prior meta-analyses did not distinguish between ET and EPT. We conducted a meta-analysis to summarize the relative risks (RR) of CRC due to ET versus EPT among peri- or postmenopausal women. From a total of 2,661 articles, four randomized controlled trials, eight cohort and eight case-control studies were included. Variables assessed included study characteristics, duration and recency of menopausal hormone therapy (HT) use, method of assessment of HT use, outcome definition and its ascertainment method. RRs were synthesized by random-effects models. We found that EPT ever use was associated with a decreased risk of CRC (RR 0.74, 95% CI 0.68-0.81), and so was ET ever use (RR 0.79, 95% CI 0.69-0.91). While current use of ET was associated with a significantly reduced risk of CRC (RR 0.70, 95% CI 0.57-0.85), former use was not (RR 0.86, 95%CI 0.67-1.11). Recency did not significantly modify the association between EPT and CRC risk. EPT former use was associated with a lower RR of CRC compared to ET former use (p = 0.008) but no such difference was observed between EPT and ET current use (p = 0.12). Overall, we found consistent evidence supporting the association between EPT and CRC risk reduction, regardless of recency. While literature for the association between ET and CRC risk is heterogeneous, our analyses suggest only current use of ET is associated with a decreased CRC risk.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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