Citations

Introduction Increasing publication of fraudulent clinical trials poses a serious threat to evidence-based medicine. In the VITALITY Study I, we demonstrated that contamination by retracted trials significantly distorts evidence synthesis. The upcoming VITALITY Study II will take a step further and investigate how such problematic evidence undermines the credibility of guideline recommendations. Methods and analyses The VITALITY Study II will adopt a retrospective cohort design and will be structured as three work packages (WPs). To start with, a cohort of clinical practice guidelines (CPGs) that were contaminated by retracted trials and/or meta-analyses that included retracted trials will be established based on forward citation searching (WP1). Then, recommendations from these CPGs that used evidence from retracted trials and/or meta-analyses that synthesised these retracted trials will be re-evaluated after removing such problematic evidence, in terms of both the direction and strength of effect sizes (WP2). Finally, the subsequent impact on patient outcomes attributable to distorted recommendations will be estimated on a hypothetical population, measured by the number of expected benefit loss and the number of expected harm increment per 100 000 patients (WP3). Ethics and dissemination Formal ethical approval is not necessary for this study as it does not involve human or animal participants, nor does it involve the collection of primary data. We will disseminate the findings through publication in peer-reviewed journals and, whenever possible, presentations at academic conferences.

Abstract Although costimulatory molecules have been shown to boost antitumor immune responses, their significance in stomach adenocarcinoma (STAD) is unknown. The purpose of this study was to examine the gene expression patterns of costimulatory molecule genes in STAD and to develop a predictive signature to aid in therapy selection and outcome prediction. We used 60 costimulatory family genes from prior research to conduct the first complete costimulatory molecule analysis in STAD patients. For the two groups discovered, consensus clustering analysis based on these 60 genes indicated unique distribution patterns and prognostic differences. Then, using Lasso and Cox regression analysis, 9 costimulatory molecular gene pairs (CMGPs) of prognostic value were discovered. With these 9 CMGPs, we were able to develop a costimulatory molecule-related prognostic signature, which performed well in an external dataset. For STAD patients, the signature was proved to be a risk factor independent of clinical characteristics, indicating that this may be employed in conjunction with clinical considerations. An further connection between the signature and immunotherapy response was discovered. People who had high mutation rates, an abundance of infiltrating immune cells, and an immunosuppressive milieu were classed as high-risk. It is possible that patients classed as high-risk have a better prognosis for immunotherapy since these patients have greater cytolytic activity scores and immunophenoscores of CTLA4 and PD-L1/PD-L2 blocker As a consequence, clinicians might use our signature to better assess patient prognosis and develop treatment plans.