Intake of red and processed meat and risk of renal cell carcinoma: a meta-analysis of observational studies
Bibliographic record
Abstract
// Shaojing Zhang 1 , Qingwei Wang 1 and Juanjuan He 2 1 Department of Urology Surgery, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan Province, China 2 Department of Breast Surgery, The First Affiliated Hospital, Zhengzhou University, Zhengzhou, Henan Province, China Correspondence to: Juanjuan He, email: hejj1350@126.com Keywords: red and processed meat, renal cell carcinoma, meta-analysis, relative risk Received: November 01, 2016 Accepted: June 02, 2017 Published: June 16, 2017 ABSTRACT Background: Findings on the association between intake of red and processed meat with renal cell carcinoma (RCC) risk are mixed. We conducted a meta-analysis to investigate this association. Materials and Methods: Eligible studies up to August 31, 2016, were identified and retrieved by searching the MEDLINE and Embase databases along with manual review of the reference lists from the retrieved studies. The quality of the included studies was evaluated using the Newcastle-Ottawa Quality Assessment Scale. The summary relative risk (SRR) and corresponding 95% confidence interval (CI) were calculated using a random-effects model. Results : Twenty-three publications were included in this meta-analysis: four cohort studies, one pooled study, and 18 case-control studies. The SRR (95% CI) for the highest vs. lowest intake of red meat was 1.36 (1.16–1.58, Pheterogeneity < 0.001); that for processed meat was 1.13 (95% CI, 1.03–1.24, Pheterogeneity = 0.014). Linear dose-response analysis yielded similar results, i.e., the SRR for per 100 g/day increment of red meat and per 50 g/day increment of processed meat was 1.21 (95% CI, 1.08–1.36) and 1.16 (95% CI, 0.99–1.36), respectively. A non-linear association was observed only for red meat (Pnonlinearity = 0.002), and not for processed meat (Pnonlinearity = 0.231). Statistically significant positive associations were observed for intake of beef, salami/ham/bacon/sausage, and hamburger. Conclusions: This meta-analysis indicates a significant positive association between red and processed meat intake and RCC risk.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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) | 0.000 | 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; a candidate call from one teacher head, 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".