Obesity as a Risk Factor and Prognostic Indicator for B-cell Lymphoma: An Umbrella Review
Bibliographic record
Abstract
Introduction: Obesity constitutes an important risk factor for numerous chronic diseases, including various types of cancer. Epidemiological evidence shows that individuals with elevated body mass index (BMI) present a higher incidence of malignant tumors, including hematological neoplasms like B-cell lymphomas. Objective: To synthesize and evaluate the available evidence regarding the dual role of obesity both as a risk factor for developing B-cell lymphoma and as a prognostic indicator in patients already diagnosed with this malignancy. Methodology: This umbrella review followed PRISMA guidelines. A comprehensive search was conducted in PubMed/MEDLINE, Scopus, Embase, Web of Science, and Cochrane databases. Studies were included if they were systematic reviews or meta-analyses examining obesity/BMI as a risk factor or prognostic indicator for B-cell lymphoma, particularly DLBCL. The ROBIS tool was used to assess methodological quality. Results: Systematic reviews consistently demonstrate that elevated BMI increases the risk of developing DLBCL, with relative risk estimates between 1.11-1.31. Obese individuals have approximately 11-31% greater risk compared to those of normal weight, with stronger associations observed for BMI during early adulthood. For prognosis, while underweight consistently shows negative effects on survival, the impact of overweight and obesity varies. One review identified a protective effect of overweight (BMI 25-29.9 kg/m²) on overall survival (HR=0.86), suggesting an "obesity paradox," while others found neutral effects. Conclusions: The obesity-lymphoma relationship involves chronic inflammation, adipokine dysregulation, insulin resistance, and altered tumor microenvironment. Clinical recommendations include detailed body composition assessments, personalized nutritional interventions, and adapted physical exercise programs.
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 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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".