Prognostic impact of obesity in cancer patients with COVID-19 infection: A systematic review and meta-analysis.
Bibliographic record
Abstract
e18578 Background: Obesity is a bona fide risk factor for ICU admission, mechanical ventilation, and mortality in patients (pts) with COVID-19 in the general population. However, whether obesity is a risk factor in cancer pts remains unknown. Herein, we have conducted a systematic review/meta-analysis of obesity and all-cause mortality in cancer pts with COVID-19. Methods: Following PRISMA guidelines,a systematic search of PubMed and Embase as well as major conference proceedings (ASCO/ESMO/AACR) was conducted for publications from inception to 14 January 2020. Observational studies that reported all-cause mortality in cancer pts with lab confirmation or clinical diagnosis of COVID-19 and BMI (obese (>30 kg/m 2 ) vs. non-obese) were included in the analysis. The pooled odds ratio (OR) and 95% confidence interval (CI) were calculated with the fixed-effects model based on low heterogeneity. Small sample publication bias was evaluated using the Begg’s Funnel Plot and Egger’s test. Results: After reviewing 3387 studies,3 retrospective cohort studies of 419 obese and 1694 non-obese cancer pts (N=2117) with COVID-19 in both inpatient/outpatient settings that reported outcomes based on obesity were found. The 3 studies were conducted multi-nationally in North America, in France, and in the Netherlands respectively. The median ages of the cohorts ranged 66-68. All studies included various cancers of various stages and were of high quality per Newcastle Ottawa scale (scores 7-9). Fixed effects meta-analysis showed no association between obesity and all-cause mortality (OR 0.95, 95% CI 0.74-1.23) in cancer pts with COVID-19. Heterogeneity was low (I 2 = 33%). No significant funnel plot asymmetry was detected per Egger’s test (P=0.2273). The reported OR of each study is outlined in the table. Conclusions: In contrast to the general population, our analysis reveals that obesity is not associated with increased all-cause mortality in cancer pts with COVID-19. Limitations of this study include a limited number of included studies, reliance on retrospective studies, non-use of ethnicity-specific WHO BMI criteria, and limited granularity of the study-reported BMI. Future prospective studies are warranted to assess the complex interplay among anthropomorphic measures, cachexia/sarcopenia, comorbidities associated with the metabolic syndrome, and COVID-19 outcomes in the cancer pt population.[Table: see text]
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.029 | 0.014 |
| 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".