<scp>BMI</scp> Association With Treatment Outcomes in Head and Neck Cancer Patients Receiving Immunotherapy: A Comprehensive Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: In recent years, immunotherapy using immune checkpoint inhibitors (ICIs) has revolutionized the treatment of advanced malignancies. As such, numerous ICIs are establishing themselves as prospective therapy alternatives for individuals with head and neck cancer (HNC). Evidence suggests a potential correlation between body mass index (BMI) and the efficacy of ICIs in cancer patients. However, this association in HNC patients subjected to immunotherapy is still unclear. AIMS: To investigate the effect of BMI on the survival outcomes of HNC patients treated with immunotherapy. METHODS: PubMed, Web of Science, and Google Scholar databases were searched extensively for records published until January 2024. Full-text articles aligned with the research objective were included, while records published in English, case reports, reviews, editorials, and studies reporting immunotherapy combined with other cancer therapies were excluded. The data required for review and analysis was abstracted in Excel files by two independent reviewers. Additionally, data synthesis was carried out using the Review Manager program, and evaluation of methodological quality was done with the Newcastle Ottawa scale. The statistical analyses were stratified according to the BMI values, of which patients were categorized as follows: Obese (BMI ≥ 27.5), non-obese (BMI < 27.5), overweight (BMI: 23.5-27.5), underweight (BMI < 18.5), normal (BMI: 18.5-23.5), low (BMI < 20), and high (BMI ≥ 20). RESULTS: Only six studies were reviewed and analyzed. A subgroup analysis of data from these studies showed that obese HNC patients on immunotherapy had significantly better overall survival (OS) rates than non-obese patients (HR: 0.51; 95% CI: 0.29-0.93; p = 0.03). However, the progression-free survival (PFS) was statistically similar between obese and non-obese patients (HR: 0.72; 95% CI: 0.39-1.33; p = 0.30). In addition, when BMI was stratified as either low or high, no significant difference was observed in the OS and PFS of HNC patients (HR: 0.99; 95% CI: 0.59-1.66; p = 0.97 and HR: 0.93; 95% CI: 0.61-1.41; p = 0.42, respectively). Similarly, the statistical analyses showed that overweight patients have similar OS and PFS as patients with normal BMI (HR: 0.53; 95% CI: 0.15-1.92; p = 0.33 and HR: 0.55; 95% CI: 0.20-1.52; p = 0.25, respectively). In contrast, underweight patients demonstrated poor OS and PFS (HR: 2.56; 95% CI: 1.29-5.12; p = 0.008 and HR: 2.76; 95% CI: 1.17-6.52; p = 0.02, respectively). DISCUSSION AND CONCLUSION: Obese HNC patients on immunotherapy tend to have improved OS than non-obese patients, while underweight patients have worse clinical prognoses than those with normal or above BMI.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.028 |
| Bibliometrics | 0.006 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".