Animal experimentation constitutes a critical link between basic research and clinical application, making its research quality and translational efficiency paramount. Although considerable progress has been made in standardizing operational procedures and ethical guidelines, the standardization of outcome evaluation systems has significantly lagged, creating a key bottleneck that constrains the quality of biomedical research and evidence synthesis. This deficiency is manifested by pronounced heterogeneity in outcome selection across similar studies, incomplete methodological reporting, and disparate criteria for result interpretation, which severely impairs the comparability of findings and the evidence integration. To cope with this challenge, this paper systematically introduces a mature methodological tool from clinical research–the core outcome set (COS)–and explores its construction strategies and application potential in the field of animal experimentation. Given the extensive diversity of animal experiments, a pragmatic strategy of "focusing on key areas, implementing phased pilots, and promoting gradual expansion" should be adopted. This approach prioritizes the development of domain-specific COS for disease areas characterized by high research volume, urgent translational needs, and well-established animal models. A multi-source integration pathway for COS development is detailed, comprising systematic literature searches, methodological appraisals, and expert consensus, with the feasibility of leveraging artificial intelligence (AI) to enhance efficiency also being examined. The development and promotion of such COS are not intended to restrict scientific exploration; rather, they aim to establish a new, tiered evaluation paradigm consisting of "core outcomes" (mandatory), "recommended outcomes" (encouraged), and "exploratory outcomes" (optional). This framework is expected not only to enhance research quality through standardization and to adhere to the "3R" principles but also to accelerate the accumulation of high-quality evidence. This, in turn, provides a solid foundation for higher-level evidence synthesis, ultimately facilitating the effective translation of basic research findings into clinical practice and providing an essential methodological framework for scientific advancement in relevant disciplines.

OBJECTIVE To further standardize the technical operations and management processes throughout therapeutic drug monitoring （TDM）， clarify the clinical value of TDM implementation， improve the scientific validity and reliability of monitoring results， and provide a solid reference basis for the formulation and optimization of clinical individualized precision dosing regimens. METHODS The Guidelines for the Management of Therapeutic Drug Monitoring were formulated in accordance with the latest definition of guidelines by the Institute of Medicine of the National Academies and the standard guideline development methodology of the World Health Organization， and in compliance with the requirements of the appraisal of guidelines for research and evaluation. A modified Delphi method was adopted to establish the research question system； evidence-based medicine research methods were applied to systematically search multiple databases to screen the latest and most comprehensive evidence. Evidence was graded and evaluated based on the evidence grading system of the Chinese Evidence-Based Medicine Center， and the grading criteria for recommendation strength from the Oxford Centre for Evidence-Based Medicine were used to determine the recommendation strength. The recommendation opinions were formed through multidisciplinary expert consensus. RESULTS The Guidelines for the Management of Therapeutic Drug Monitoring cover four core modules， including TDM application indications， technical procedures， result interpretation and clinical application， and quality control， involving 18 primary research questions， 34 secondary research questions， and yield 82 recommendations. CONCLUSIONS The guidelines systematically standardize the key technical links and management requirements of the whole TDM process， provide scientific and operable standardized tools， help improve the standardization level of TDM work， promote the translation of monitoring results into clinical decision-making， and provide strong support for precision personalized medicine and ensuring the safety and rationality of medication use.

Animal experiments are essential tools in biomedical research, serving as a bridge between basic research and clinical trials. Systematic reviews and meta-analyses (SRs/MAs) of animal experiments are crucial methods for integrating evidence from animal experiment, which can facilitate the translation of findings into clinical research, reduce translational risks, and promote resource integration in basic research. With the continuous development of the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) methodology, its application in SRs/MAs of animal experiments has gained increasing attention. This article first outlines the principles and specific applications of the GRADE methodology in SRs/MAs of animal experiments, including qualitative descriptive systematic reviews, meta-analyses, and network meta-analyses. It then deeply analyzes the misuse of the GRADE methodology in practice, including incorrect evidence grading, improper classification of evidence, misapplication in qualitative systematic reviews, inconsistencies between the documentation of the upgrading and downgrading process and results, and inappropriate use for making recommendations. Furthermore, this article comprehensively discusses the factors influencing the grading of evidence certainty in SRs/MAs of animal experiments, including the impact of bias risk, indirectness, inconsistency, imprecision, and publication bias on evidence downgrading, as well as the role of large effect sizes and cross-species consistency in evidence upgrading. Finally, in response to the issues discussed, improvement strategies are proposed, including further research and optimization of the GRADE methodology for SRs/MAs of animal experiments, the development of reporting guidelines tailored to the characteristics of SRs/MAs in animal experiment research, and enhanced professional training for researchers in the GRADE methodology. This article aims to improve the quality of evidence in SRs/MAs of animal experiments, strengthen their reliability in clinical decision-making, and promote the more efficient translation of findings from animal experiment research into clinical practice.

To develop a guideline terminology system and promote its standardization, thereby enhancing medical staff's accurate understanding and correct application of guidelines.

Objective To sort,summarize,and introduce key terms related to guideline reporting,evaluation,dissemination,implementation,and updating.Methods We systematically searched guideline de-velopment manuals and methodological literature from database inception to October 25,2024.Terms related to guideline reporting,updating,evaluation,and implementation were extracted,standardized,and finalized through a structured consensus process.Results A total of 13 guideline manuals and 32 methodological articles were included,yielding 14 core terms with standardized definitions.Conclusions This article introduces key terms such as reporting standards,external review,and research gaps across guideline development phases to promote concept application and deepen readers'understanding of guideline development.

Methodological quality assessment is a pivotal link between primary studies and reliable evidence-based practice,and an essential pathway for operationalizing the core principles of the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition).A prevalent challenge in practice,however,is the conflation of appraising methodological robustness(risk of bias assessment)with verifying reporting transparency(adherence to reporting guidelines).This paper systematically addresses this fundamental challenge,beginning with a clear distinction between the essence and boundaries of these two concepts.On this basis,the article provides a comprehensive review of mainstream quality assessment tools,covering the methodological features and evolutionary trajectory of numerous instruments for interventional(e.g.,RoB 2,ROBINS-I),observational(e.g.,NOS,the JBI/SIGN/NIH series),secondary(e.g.,AMSTAR 2),and other specific types of studies such as health economic evaluations.Furthermore,a complete case study is used to illustrate the practical application of the ROBINS-I tool.The paper's central thesis advocates for an"appraisal-informed design"philosophy,urging a conceptual shift from the retrospective critique of existing literature to the prospective quality control of new research by internalizing appraisal standards as design principles,while also exploring the emerging paradigm of artificial intelligence in assisting assessment.This paper provides a comprehensive methodological reference for researchers and practitioners to prudently select appropriate assessment tools and to conduct rigorous critical appraisals of pharmacoepidemiological evidence.

Robotic surgery, as an increasingly widespread application in the treatment of gastric and colorectal cancer, still faces obvious discrepancies in recommendations, indications, and evidence strength across existing guidelines. This study systematically analyzed 31 relevant guidelines and consensus statements (retrieved from Chinese and English databases from January 2010 to May 2025) from two dimensions: feasibility (effectiveness, safety, etc.) and training quality control.The results showed that colorectal cancer guidelines had a higher proportion (4 guidelines) of "clear recommendations" for robotic surgery, while gastric cancer guidelines predominantly presented "conditional recommendations" or no recommendations. In the training and quality control dimension, although structured suggestions received positive recommendations, more than half were based on low or very low-quality evidence. Evidence mapping indicated insufficient matching between "case-specific recommendations" and evidence grades in the feasibility dimension, while training processes emphasized the importance of standardized systems and team collaboration.The study highlights the existing heterogeneity in evidence-based guidelines for robotic gastrointestinal surgery, with colorectal cancer demonstrating a more mature evidence base and gastric cancer showing notable evidence gaps. It is recommended that future guideline development should strengthen the consistency between recommendation grades and evidence levels, promote high-quality research in upper gastrointestinal surgery, and improve surgeon training and certification systems to facilitate standardized clinical translation of robotic gastrointestinal surgery.

Methodological quality assessment is a pivotal link between primary studies and reliable evidence-based practice,and an essential pathway for operationalizing the core principles of the Guide on Methodological Standards in Pharmacoepidemiology(2nd edition).A prevalent challenge in practice,however,is the conflation of appraising methodological robustness(risk of bias assessment)with verifying reporting transparency(adherence to reporting guidelines).This paper systematically addresses this fundamental challenge,beginning with a clear distinction between the essence and boundaries of these two concepts.On this basis,the article provides a comprehensive review of mainstream quality assessment tools,covering the methodological features and evolutionary trajectory of numerous instruments for interventional(e.g.,RoB 2,ROBINS-I),observational(e.g.,NOS,the JBI/SIGN/NIH series),secondary(e.g.,AMSTAR 2),and other specific types of studies such as health economic evaluations.Furthermore,a complete case study is used to illustrate the practical application of the ROBINS-I tool.The paper's central thesis advocates for an"appraisal-informed design"philosophy,urging a conceptual shift from the retrospective critique of existing literature to the prospective quality control of new research by internalizing appraisal standards as design principles,while also exploring the emerging paradigm of artificial intelligence in assisting assessment.This paper provides a comprehensive methodological reference for researchers and practitioners to prudently select appropriate assessment tools and to conduct rigorous critical appraisals of pharmacoepidemiological evidence.

Robotic surgery, as an increasingly widespread application in the treatment of gastric and colorectal cancer, still faces obvious discrepancies in recommendations, indications, and evidence strength across existing guidelines. This study systematically analyzed 31 relevant guidelines and consensus statements (retrieved from Chinese and English databases from January 2010 to May 2025) from two dimensions: feasibility (effectiveness, safety, etc.) and training quality control.The results showed that colorectal cancer guidelines had a higher proportion (4 guidelines) of "clear recommendations" for robotic surgery, while gastric cancer guidelines predominantly presented "conditional recommendations" or no recommendations. In the training and quality control dimension, although structured suggestions received positive recommendations, more than half were based on low or very low-quality evidence. Evidence mapping indicated insufficient matching between "case-specific recommendations" and evidence grades in the feasibility dimension, while training processes emphasized the importance of standardized systems and team collaboration.The study highlights the existing heterogeneity in evidence-based guidelines for robotic gastrointestinal surgery, with colorectal cancer demonstrating a more mature evidence base and gastric cancer showing notable evidence gaps. It is recommended that future guideline development should strengthen the consistency between recommendation grades and evidence levels, promote high-quality research in upper gastrointestinal surgery, and improve surgeon training and certification systems to facilitate standardized clinical translation of robotic gastrointestinal surgery.

Animal experiments are an essential component of life sciences and medical research. However, the external validity and reliability of individual animal studies are frequently challenged by inherent limitations such as small sample sizes, high design heterogeneity, and poor reproducibility, which impede the effective translation of research findings into clinical practice. Systematic reviews and meta-analysis represent a key methodology for integrating existing evidence and enhancing the robustness of conclusions. Currently, however, the application of systematic reviews and meta-analysis in the field of animal experiments lacks standardized guidelines for their conduct and reporting, resulting in inconsistent quality and, to some extent, diminishing their evidence value. To address this issue, this paper aims to systematically delineate the reporting process for systematic reviews and meta-analysis of animal experiments and to propose a set of standardized recommendations that are both scientific and practical. The article's scope encompasses the entire process, from the preliminary preparatory phase [including formulating the population， intervention， comparison and outcome （PICO） question, assessing feasibility, and protocol pre-registration] to the key writing points for each section of the main report. In the core methods section, the paper elaborates on how to implement literature searches, establish eligibility criteria, perform data extraction, and assess the risk of bias, based on the Preferred Reporting Items for Systematic Reviews and Meta-analysis （PRISMA) statement, in conjunction with relevant guidelines and tools such as Animal Research： Reporting of in Vivo Experiments （ARRIVE) and a risk of bias assessment tool developed by the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE). For the presentation of results, strategies are proposed for clear and transparent display using flow diagrams and tables of characteristics. The discussion section places particular emphasis on how to scientifically interpret pooled effects, thoroughly analyze sources of heterogeneity, evaluate the impact of publication bias, and cautiously discuss the validity and limitations of extrapolating findings from animal studies to clinical settings. Furthermore, this paper recommends adopting the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to comprehensively grade the quality of evidence. Through a modular analysis of the entire reporting process, this paper aims to provide researchers in the field with a clear and practical guide, thereby promoting the standardized development of systematic reviews and meta-analysis of animal experiments and enhancing their application value in scientific decision-making and translational medicine.