The Incidence of Breast Cancer in Iran: A Systematic 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
Background: Breast cancer is the most common invasive cancer among women globally. Its incidence greatly varies around the world the globe. There are several estimates of breast cancer incidence from different geographical areas in Iran. In addition, no systematic reviews are available pertaining to the incidence rate of breast cancer in Iran. Therefore, the present systematic review aimed to address this epidemiological gap. Method: This systematic review was carried out based on the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) in January 2016. In doing so, the researchers searched Medline/PubMed, Scopus, Sciencedirect, and Google scholar for international papers and four Iranian databases (Scientific Information Database, MagIran, Iran Medex, and Iran Doc) for Persian articles. Result: A total of 427 titles were retrieved in the initial search of the databases. Further refinement and screening of the retrieved studies produced a total of 18 researches. Based on the random effect model, the Age-Standardized Rate (ASR) of breast cancer was 26.4, 95% CI (20.1 to 31.7). However, the results of Cochran's test showed the heterogeneity of the studies (Q=1788.2, df=17, I2=99%, p<0.001). Conclusion: The incidence of breast cancer was lower in Iran compared to other parts of the world. However, establishing cancer registries covering a broader perspective of the population and carrying out further studies are needed to map out the exact incidence rate and trend of breast cancer in Iran.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.013 | 0.003 |
| 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 | 0.001 |
| 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