RETRACTED: Investigating the relationship between insulin use and all-cause mortality, breast cancer mortality, and recurrence risk in diabetic patients with breast cancer: A comprehensive systematic review and meta-analysis
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: The co-occurrence of breast cancer and diabetes presents complex clinical challenges, as each condition may influence the progression and management of the other, potentially worsening patient outcomes. This study aims to examine the association between insulin use and the risks of all-cause mortality, breast cancer-specific mortality, and recurrence in diabetic patients with breast cancer. METHODS: A systematic review and meta-analysis were conducted using studies identified from multiple databases, including Web of Science, Scopus, PubMed, Cochrane, Google Scholar, and Embase. The meta-analysis approach was used to estimate the relative risk (RR) of the relationship between insulin use and the risks of all-cause mortality, breast cancer-specific mortality, and recurrence in diabetic patients with breast cancer. Heterogeneity among studies was assessed using statistical tests such as the Chi-square test, I2, and forest plots. Meta-regression and sensitivity analyses were performed to explore sources of heterogeneity. The quality of the included studies was assessed using the Newcastle-Ottawa Scale checklist. Data were analyzed using Stata version 17 (Stata Corp, College Station, Texas). RESULTS: Data from 22 studies conducted between 2002 and 2023, with a total of 159,674 participants, were analyzed. Nineteen studies were rated as high quality, and three as moderate quality. Diabetic patients with breast cancer who received insulin had a 1.65 (95% CI: 1.36-2.02; P < 0.001; I2 = 89.7%) times higher risk of overall mortality compared to those who did not use insulin. Meta-regression revealed that sample size and study quality were significant contributors to heterogeneity (P ≤ 0.10). Furthermore, insulin use was associated with a 1.22 (95% CI: 1.05-1.42; P = 0.009; I2 = 37.9%) times higher risk of breast cancer-specific mortality. For breast cancer recurrence, insulin use was associated with a 1.45 (95% CI: 1.19-1.77; P < 0.001; I2 = 3.4%) times higher risk. Sensitivity analysis confirmed the stability of the results across all outcomes. CONCLUSION: This meta-analysis provides strong evidence that insulin use in diabetic patients with breast cancer is associated with increased risks of overall mortality, breast cancer-specific mortality, and recurrence. These findings underscore the need for careful consideration of insulin therapy in this patient population.
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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 | 0.068 | 0.216 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.009 | 0.014 |
| Bibliometrics | 0.008 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".