Additional file 1 of Associations of thiazide use with skin cancers: a systematic review and meta-analysis
Bibliographic record
Abstract
Additional file 1: Supplementary Material. Figure S1. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Basal Cell Carcinoma in Case-Control Studies. Figure S2. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Basal Cell Carcinoma in Cohort Studies. Figure S3. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Squamous Cell Carcinoma in Case-Control Studies. Figure S4. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Squamous Cell Carcinoma in Cohort Studies. Figure S5. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Merkel Cell Carcinoma in Case-Control Studies. Figure S6. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Unspecified Non-melanoma Skin Cancer in Cohort Studies. Figure S7. Forest Plot for the Subgroup Analysis According to Geographic Regions of Nonmelanoma Skin Cancer in Case-Control Studies of Hydrochlorothiazide (A) Non-Asian countries (B) Asian countries. Figure S8. Forest Plot for the Subgroup Analysis According to Geographic Regions of Nonmelanoma Skin Cancer in Cohort Studies of Hydrochlorothiazide (A) Non-Asian countries (B) Asian countries. Figure S9. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Melanoma in Case-Control studies. Figure S10. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Hydrochlorothiazide and Melanoma in Cohort studies. Figure S11. Forest Plot for the Subgroup Analysis According to Geographic Regions of Melanoma in Case-Control Studies of Hydrochlorothiazide. Figure S12. Forest Plot for the Subgroup Analysis According to Geographic Regions of Melanoma in Cohort Studies of Hydrochlorothiazide. Figure S13. Forest Plot for the Subgroup Analysis According to Melanoma Subtypes in Case-Control Studies of Hydrochlorothiazide. Figure S14. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Bendroflumethiazide and Basal Cell Carcinoma in Case-Control Studies. Figure S15. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Bendroflumethiazide and Squamous Cell Carcinoma in Case-Control Studies. Figure S16. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Bendroflumethiazide and Merkel Cell Carcinoma in Case-Control Studies. Figure S17. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Indapamide and Basal Cell Carcinoma in Case-Control Studies. Figure S18. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Indapamide and Squamous Cell Carcinoma in Case-Control Studies. Figure S19. Forest Plot for the Subgroup Analysis of the Association between Cumulative Doses of Indapamide and Melanoma in Case-Control Studies. Table S1. Search Strategy. Table S2. Studies with Overlapping Populations. Table S3. Exposures for Thiazide Use in the Included Studies. Table S4. Other Characteristics of Included Studies. Table S5. The Relationship Between Cumulative Duration of Individual Thiazide Uses and Skin Cancer Risk. Table S6. Risk-of-bias Assessment of Included Case-Control Studies Based on Newcastle Ottawa Quality Assessment Scale. Table S7. Risk-of-bias Assessment of Included Cohort Studies Based on Newcastle Ottawa Quality Assessment Scale. Table S8. Comparisons of the Results between the Main and Sensitivity Analyses. Table S9. Sensitivity Analysis By Including Only Low Risk-of-bias Case-Control Studies.
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.
How this classification was reachedexpand
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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.987 | 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 teacher head, 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".