Impact of Chemotherapy Treatments on Dietary Intakes of Macro and Micronutrients among Jordanian Women with Breast Cancer
Bibliographic record
Abstract
Background: Breast cancer (BC) is the leading cause of cancer related deaths among women worldwide. Nutritional factors may account for the large variation in BC incidence around the world. Most studies have shown no link between dietary intakes and increased risk of BC.Objective: To evaluate the dietary intake of macro and some micronutrients among BC patients with respect to chemotherapy treatment.Methods: A total of 168 BC patients aged 20-70 years attending BC clinics at the Jordanian Royal Medical Services, Jordan were evaluated for dietary intake. The study design permitted to include 60 newly-diagnosed BC patients who were not exposed to any type of interventions and 108 recently-diagnosed BC patients (up to three months). Recently group member were sub-divided in two sub-groups to control exposure to chemotherapy. The Chemo group (have exposed to chemotherapy) and the non-chemo group (have exposed to other types of treatments interventions). Calculations were based on the computerized nutrient analysis program (the food processor nutrition and fitness analysis software (ESHA), version 10.6/.3, Salem, USA).Results: Energy, macronutrients and micronutrients intakes were not significantly different considering exposure to chemotherapy. However, they were less than recommended in all BC patients.Conclusion: The possible risk of dietary undernutrition among BC patients that need a careful monitoring, evaluation and managements care plan.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".