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.

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

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 introduce and analyze guideline terminology related to clinical question formulation, evidence retrieval and appraisal, and recommendation development.

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.

OBJECTIVE To standardize the main processes and related technical links of the clinical comprehensive evaluation of drugs， and provide guidance and reference for improving the quality of comprehensive evaluation evidence and its transformation and application value. METHODS The construction of Guideline for the Workflow of Clinical Comprehensive Evaluation of Drugs was based on the standard guideline formulation method of the World Health Organization （WHO）， strictly followed the latest definition of guidelines by the Institute of Medicine of the National Academy of Sciences of the United States， and conformed to the six major areas of the Guideline Research and Evaluation Tool Ⅱ. Delphi method was adopted to construct the research questions； research evidence was established by applying the research methods of evidence-based medicine. The evidence quality classification system of the Chinese Evidence-Based Medicine Center was adopted for evidence classification and evaluation. The recommendation strength was determined by the recommendation strength classification standard formulated by the Oxford University Evidence-Based Medicine Center， and the recommendation opinions were formed through the expert consensus method. RESULTS & CONCLUSIONS The Guideline for the Workflow of Clinical Comprehensive Evaluation of Drugs covers 4 major categories of research questions， including topic selection， evaluation implementation， evidence evaluation， and application and transformation of results. The formulation of this guideline has standardized the technical links of the entire process of clinical comprehensive evaluation of drugs， which can effectively guide the high-quality and high-efficient development of this work， enhance the standardized output and transformation application value of evaluation evidence， and provide high-quality evidence support for the scientific decision-making of health and the rationalization of clinical medication.

To explore the role of the "Clinical Practice Guidelines" column and others in the Medical Joumnal of Peking Union Medical College Hospital (Med J PUMCH) in promoting diseiplinary development.

BACKGROUND: Neoadjuvant chemoradiotherapy followed by radical surgery has been a common practice for patients with locally advanced rectal cancer, but the response rate varies among patients. This study aimed to develop a ResNet-Vision Transformer based magnetic resonance imaging (MRI)-endoscopy fusion model to precisely predict treatment response and provide personalized treatment. METHODS: In this multicenter study, 366 eligible patients who had undergone neoadjuvant chemoradiotherapy followed by radical surgery at eight Chinese tertiary hospitals between January 2017 and June 2024 were recruited, with 2928 pretreatment colonic endoscopic images and 366 pelvic MRI images. An MRI-endoscopy fusion model was constructed based on the ResNet backbone and Transformer network using pretreatment MRI and endoscopic images. Treatment response was defined as good response or non-good response based on the tumor regression grade. The Delong test and the Hanley-McNeil test were utilized to compare prediction performance among different models and different subgroups, respectively. The predictive performance of the MRI-endoscopy fusion model was comprehensively validated in the test sets and was further compared to that of the single-modal MRI model and single-modal endoscopy model. RESULTS: The MRI-endoscopy fusion model demonstrated favorable prediction performance. In the internal validation set, the area under the curve (AUC) and accuracy were 0.852 (95% confidence interval [CI]: 0.744-0.940) and 0.737 (95% CI: 0.712-0.844), respectively. Moreover, the AUC and accuracy reached 0.769 (95% CI: 0.678-0.861) and 0.729 (95% CI: 0.628-0.821), respectively, in the external test set. In addition, the MRI-endoscopy fusion model outperformed the single-modal MRI model (AUC: 0.692 [95% CI: 0.609-0.783], accuracy: 0.659 [95% CI: 0.565-0.775]) and the single-modal endoscopy model (AUC: 0.720 [95% CI: 0.617-0.823], accuracy: 0.713 [95% CI: 0.612-0.809]) in the external test set. CONCLUSION The MRI-endoscopy fusion model based on ResNet-Vision Transformer achieved favorable performance in predicting treatment response to neoadjuvant chemoradiotherapy and holds tremendous potential for enabling personalized treatment regimens for locally advanced rectal cancer patients.
Humans ; Rectal Neoplasms/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Neoadjuvant Therapy/methods* ; Aged ; Adult ; Chemoradiotherapy/methods* ; Endoscopy/methods* ; Treatment Outcome

The aims of developing rapid and living guidelines is to keep the recommendations in the guideline up-to-date. Compared with the conventional guideline, the rapid and living guideline can make better use of the existing evidence and apply and transform the evidence in a timely manner. This paper introduces the advantages and usage of rapid and living guidelines, the development process and existing challenges, and offers some insights, in order to provide reference for domestic organizations and scholars engaged in guideline development.

With the development of the Scientific, Transparent and Applicable Rankings tool for clinical practice guidelines(STAR), the publication of evaluation and ranking for scientificity, transparency and applicability of Chinese guidelines and consensus published in the medical journals in 2021and 2022, as well as the publication of the STAR evaluation and ranking for some specialities, the STAR evaluation and ranking has received widespread attention in the medical community. In order to further enhance its scientificity and transparency, Methodology and Technology Specialization Committee of the STAR Working Group presents this article to introduce sample identification and speciality assignment in the evaluation and ranking process.