Breast Cancer and HIV in Sub-Saharan Africa: A Complex Relationship
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
INTRODUCTION: The number and lifespan of individuals living with HIV have increased significantly with the scale-up of antiretroviral therapy. Furthermore, the incidence of breast cancer in women with HIV is growing, especially in sub-Saharan Africa (SSA). However, the association between HIV infection and breast cancer is not well understood. METHODS: A literature search was performed to identify articles published in journals pertaining to breast cancer and HIV, with an emphasis on SSA. Selected US-based studies were also identified for comparison. RESULTS: Among the 56 studies reviewed, the largest study examined 314 patients with breast cancer and HIV in the United States. There is no consensus on whether HIV infection acts as a pro-oncogenic or antioncogenic factor in breast cancer, and it may have no relation to breast cancer. A higher incidence of breast cancer is reported in high-income countries than in SSA, although breast cancer in SSA presents at a younger age and at a more advanced stage. Some studies show that patients with breast cancer and HIV experience worse chemotherapy toxicity than do patients without HIV. Data on treatment outcomes are limited. The largest study showed worse treatment outcomes in patients with HIV, compared with their counterparts without HIV. CONCLUSION: HIV infection has not been associated with different clinical presentation of breast cancer. However, some evidence suggests that concurrent diagnosis of HIV with breast cancer is associated with increased therapy-related toxicity and worse outcomes. Systematic prospective studies are needed to establish whether there is a specific association between breast cancer and HIV.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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