Incidence of Breast Cancer and Enterococcus Infection: A Retrospective Analysis
Bibliographic record
Abstract
Background: Enterococci role in the microbiome remains controversial, and researches regarding enterococcal infection (EI) and its sequelae are limited. The gut microbiome has shown to play an important role in immunology and cancer. Recent data have suggested a relationship between the gut microbiome and breast cancer (BC). Methods: Patients in a Health Insurance Portability and Accountability Act (HIPAA) compliant national database (2010 - 2020) were used for this retrospective study. International Classification of Disease (ICD) Ninth and Tenth Codes, Current Procedural Terminology (CPT), and National Drug Codes were used to identify BC diagnosis and EI. Patients were matched for age, sex, Charlson comorbidity index (CCI), antibiotic treatment, obesity, and region of residence. Statistical analyses were implemented to assess significance and estimate odds ratio (OR). Results: EI was associated with a decreased incidence of BC (OR = 0.60, 95% confidence interval (CI): 0.57 - 0.63) and the difference was statistically significant (P < 2.2 × 10 -16 ). Treatment for EI was controlled for in both EI and noninfected populations. Patients with a prior EI and treated with antibiotics were compared to patients with no history of EI and received antibiotics. Both populations subsequently developed BC. Results remained statistically significant (P < 2.2 × 10 -16 ) with an OR of 0.57 (95% CI: 0.54 - 0.60). In addition to standard matching protocol, obesity was controlled for in both groups by exclusively containing obese patients, but one group with prior EI and the other without. In obese patients, a lower incidence of BC was shown in the infected group compared to the noninfected group. Results were statistically significant (P < 2.2 × 10 -16 ) with an OR of 0.56 (95% CI: 0.53 - 0.58). Age of BC diagnosis with and without a prior EI was analyzed and demonstrated increased BC incidence with increasing age in both groups, but less in the EI group. Incidence of BC based on region was analyzed, which showed lower BC incidence across all regions in the EI group. Conclusion: This study shows a statistically significant correlation between EI and decreased incidence of BC. Further exploration is needed to identify and understand not only the role of enterococcus in the microbiome, but also the protective mechanism(s) and impact of EI on BC development. World J Oncol. 2023;14(1):32-39 doi: https://doi.org/10.14740/wjon1551
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.000 | 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 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".