OBJECTIVE:Postoperative recurrence is a common complication of percutaneous endoscopic lumbar discectomy for lumbar disc herniation,which can significantly increase the risk of reoperation.A well-performing risk prediction model can help identify high-risk groups early and prevent postoperative recurrence.This study systematically evaluated the risk prediction model for postoperative recurrence after percutaneous endoscopic lumbar discectomy to provide a reference for surgical decision-making.METHODS:The PubMed,Embase,Web of Science,CNKI,WanFang Data,VIP,and CBM were electronically searched to collect studies on the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy from inception to July 1,2024.Two reviewers independently screened the literature and extracted data.The models' risk of bias,applicability,and report quality were assessed using prediction model risk of bias assessment tool(PROBAST)and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis(TRIPOD)tools,respectively.Meta-analysis of postoperative recurrence rate of percutaneous endoscopic lumbar discectomy and related predictors was performed using Revman 5.4 software.RESULTS:(1)A total of 15 studies were included,all of which were retrospective studies,including 24 models for predicting the risk of recurrence after percutaneous endoscopic lumbar discectomy.(2)The PROBAST evaluation results indicated that all 15 studies exhibited a high risk of bias.Regarding applicability,two studies demonstrated a low risk,while 13 presented a high risk.(3)Regarding the TRIPOD reporting quality,the overall quality across the 15 studies was low.The primary reasons for this low compliance included the failure to report blinding,a lack of explanation for the sample size calculation method,lack of detailed description of missing data processing methods,and lack of information such as introduction to the model used.(4)Furthermore,the area under the receiver operating characteristic curve for the model ranged from 0.684 to 0.972,with the number of potential predictor variables varying from 15 to 28.(5)The results of meta-analysis showed that the postoperative recurrence rate of lumbar disc herniation patients treated with percutaneous endoscopic lumbar discectomy was 12％(95％CI=9.0％-15.0％),Modic changes(OR=6.72,95％CI=3.90-11.59),body mass index(OR=1.28,95％CI=1.10-1.49),work intensity(OR=3.22,95％CI=1.85-5.59),age(OR=2.28,95％CI=1.50-3.48),and smoking history(OR=2.65,95％CI=1.75-4.00)were independent influencing factors for postoperative recurrence of percutaneous endoscopic lumbar discectomy(all P＜0.05).CONCLUSION:The overall predictive performance of the recurrence risk prediction models after percutaneous endoscopic lumbar discectomy is satisfactory;however,the model exhibits a high overall risk of bias and applicability,coupled with low reporting quality.Additionally,there is a lack of prospective research and external validation.Future,risk prediction models should consider factors such as Modic changes,body mass index,work intensity,age,and smoking history as potential predictors.

Objective To systematically evaluate the therapeutic effects of video-assisted thoracoscopic surgery (VATS) and robot-assisted thoracic surgery (RATS) in treating mediastinal tumors. Methods A computer search was conducted on PubMed, Embase, Cochrane Library, Web of Science, Wanfang, CNKI, CBM, VIP databases for literature comparing the clinical efficacy of VATS and RATS in treating mediastinal tumors, with the search time from inception to March 31, 2024. The Newcastle-Ottawa Scale (NOS) was used to evaluate the quality of the included cohort studies, and Review Manager 5.4 software was used to perform a meta-analysis. Results A total of 32 articles were included, with 7868 patients. The NOS scores of the included cohort studies were all≥7 points. Meta-analysis results showed that compared with the VATS group, the RATS group had less intraoperative blood loss [MD=−16.71, 95%CI (−23.88, −9.54), P<0.001], lower conversion rate to open thoracotomy [OR=0.41, 95%CI (0.26, 0.67), P=0.003], lower overall postoperative complication rate [OR=0.66, 95%CI (0.48, 0.92), P=0.01], shorter postoperative drainage time [MD=−0.64, 95%CI (−0.92, −0.36), P<0.001], and shorter postoperative hospital stay [MD=−1.03, 95%CI (−1.28, −0.78), P<0.001]. There was no statistical difference between the two groups in terms of tumor size [MD=−0.06, 95%CI (−0.31, 0.19), P=0.64] or operation time [MD=5.52, 95%CI (−2.35, 13.40), P=0.17]. The RATS group had higher hospitalization costs than the VATS group [MD=1.69, 95%CI (1.26, 2.13), P<0.001]. Conclusion In mediastinal tumors resection, RATS is superior to VATS in terms of intraoperative blood loss, conversion rate to open thoracotomy, overall postoperative complication rate, postoperative drainage time, and postoperative hospital stay, but it increases hospitalization costs.

Xuanfuhua Decoction （旋覆花汤） is considered as the theoretical prototype of the method of unbloc-king collaterals with acrid and moistened medicinals. Guided by the theories of "chronic disease entering the collaterals" and "collaterals performing their functions when there is free flow"， YE Gui further developed this approach into a systematic method. The core of this approach lies in dispersing and opening constraint with acrid medicinals， nourishing and harmonizing collaterals with moistened medicinals， eliminating pathogens and unblocking collaterals with insect medicinals. The disease course of idiopathic pulmonary fibrosis （IPF） is prolonged， with a complex of deficiency and excess， and chronic disease entering the collaterals. The core pathogenesis involves lung collaterals obstruction， fluid depletion with blood stasis， and chronic disease entering the collaterals. Treatment can be guided by the method of unblocking collaterals with acrid and moistened medicinals based on Xuanfuhua Decoction， following a strategy of "dispersing and unblocking， moistening and nourishing， penetrating and venting". Specifically， for lung collaterals obstruction， acrid medicinals can be used to disperse lung qi and open bi （痹）. In case of fluid depletion and blood stasis， moistened medicinals for nourishing lung collaterals are suggested to restore vitality. For chronic disease ente-ring collaterals， it is advised to search and eliminate collateral pathogens in order to dissipate masses.

BackgroundAnxiety symptoms have become a public health issue affecting the physical and mental health of the elderly population. Mental health literacy is a predictor of anxiety symptoms in the elderly. Currently， there are limited studies on the pathogenic mechanism between the two. Exploring the relationship and mechanism between mental health literacy and anxiety symptoms among the elderly is of great significance for improving the mental health level of the elderly. ObjectiveTo investigate the impact of mental health literacy on anxiety symptoms in the elderly， and to analyze the role of insomnia in this process， in order to provide references for the formulation of prevention and intervention strategies for anxiety symptoms in the elderly. MethodsFrom August 2021 to December 2022， a total of 10 650 older adults aged 60 years old and above were selected from a city in Sichuan Province using a multistage stratified sampling method. Participants completed the self-compiled demographic questionnaire， the Insomnia Severity Index （ISI）， the Generalized Anxiety Disorder Scale-7 item （GAD-7）， and the National Mental Health Literacy Questionnaire （NMHLQ）. Spearman correlation analysis was adopted to examine the correlation between the scores of the scales. Model 4 in SPSS 27.0 plugin Process 4.1 was employed to test the pathway of insomnia between mental health literacy （and its various dimensions） and anxiety symptoms. ResultsAmong the participants， 9 609 cases （90.23%） completed the valid questionnaire survey， and 1 680 cases （17.48%） were found to have anxiety symptoms. The total score of the NMHLQ for the elderly， as well as the scores of the knowledge， awareness， and skills dimensions， were negatively correlated with the GAD-7 score and the ISI score （r_s=-0.506–-0.054， P<0.01）， and the ISI score was positively correlated with the GAD-7 score （r_s=0.666， P<0.01）. Insomnia served as the mediating pathway between the mental health literacy and anxiety symptoms， with an indirect effect value of -0.210 （95% CI： -0.227–-0.193）， accounting for 54.97% of the total effect. Insomnia was the mediating pathway between the mental health literacy knowledge and anxiety symptoms of the elderly， with an indirect effect value of -0.161 （95% CI： -0.178–-0.144）， accounting for 52.61% of the total effect. Insomnia played a mediating role in the relationship between the awareness of mental health literacy and anxiety symptoms， with an indirect effect value of -0.323 （95% CI： -0.342–-0.302）， accounting for 76.36% of the total effect. Insomnia was the mediating pathway between the mental health literacy skills and anxiety symptoms of the elderly， with an indirect effect value of -0.172 （95% CI： -0.187–-0.159）， accounting for 53.75% of the total effect. ConclusionThe dimensions of mental health literacy， knowledge， awareness and skills of the elderly not only directly affect anxiety symptoms， but also indirectly influence anxiety symptoms through the pathway of insomnia.［Funded by Medical Research Project Plan of Sichuan Province （number， S23049）］

ObjectiveTo explore the diagnostic value of resting-state functional magnetic resonance imaging (rs-fMRI) for mild cognitive impairment (MCI) stage of Alzheimer's disease (AD), and to investigate the changes in brain functional connectivity in default mode network (DMN) and medial temporal lobe (MTL) regions. MethodsLiteratures were retrieved from multiple databases including CNKI, PubMed, Medline, and Embase, etc. from January, 2020 to October, 2025, investigating the changes in functional connectivity of DMN and MTL in patients with MCI compared to health control (HC) using rs-fMRI. Two researchers independently screened and extracted the literatures and methodological quality was assessed using QUADAS-2. Review Manager 5.4 was used to perform a meta-analysis of neuroimaging indicators in MCI patients and HC subjects. Stata and SDM were utilized to summarize diagnostic efficacy and brain functional connectivity, calculating the over all sensitivity, specificity and summary receiver operating characteristic-area under the curve (SROC-AUC). Deeks funnel plots were drawn, literature weights were analyzed, and subgroup analyses were conducted. ResultsA total of ten literatures were ultimately included, involving 1 010 patients with MCI and 1 714 HC subjects. MCI patients showed decreased or abnormal blood oxygen level dependence signals in DMN, focusing on bilateral medial prefrontal cortex (mPFC) and posterior cingulate cortex. The SROC-AUC was 0.91. In MTL, there was a characteristic decrease of spontaneous neural functional connectivities between the hippocampus and other regions, reflecting the obstruction of information transmission from episodic memory to the central nodes. Abnormal functional connectivity in DMN and MTL resulted in compensatory resting-state functional connectivity enhancement in other subnetworks or local functional connections, such as frontoparietal network and the hippocampal-parietal network. Abnormal activation of mPFC suggested atrophy of the hippocampus or abnormal brain function. The decline in functional connectivity between DMN and MTL indicated impairment of memory and information processing in the early stage. ConclusionThe early functional decoupling between DMN and MTL is a crucial neural mechanism at the MCI stage of AD, providing important neuroimaging evidence for the early diagnosis of AD.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

ObjectiveTo clarify whether METTL14 mediates the core role of acupuncture at Neiguan (PC6) in promoting myelination and improving behavior in young autistic rats through gene intervention technology. MethodsThe ASD model was established by intraperitoneal injection of valproic acid (VPA) in pregnant rats. Male offspring were intracerebroventricularly injected with adenovirus-packaged METTL14 shRNA (sh-METTL14) or its control (sh-NC) on postnatal day 1, with a model group set as well. Subsequently, the juvenile rats were divided into model group, acupuncture group, acupuncture+sh-NC group, and acupuncture+sh-METTL14 group. The acupuncture group received acupuncture at Neiguan (PC6) from postnatal day 7, once daily for 21 consecutive days. Neurobehavioral changes were evaluated by behavioral tests; METTL14 knockdown efficiency and the expression of METTL14, METTL3, and PTEN were detected by quantitative real-time PCR (qRT-PCR) and Western blot (WB); PTEN m⁶A levels were measured by RNA immunoprecipitation-qPCR (RIP-qPCR); myelin ultrastructure, expression of myelin basic protein (MBP) and neurofascin 155 (NF155), and dendritic spine density were observed using transmission electron microscopy (TEM), enzyme-linked immunosorbent assay (ELISA), immunofluorescence, qRT-PCR, and primary neuron culture. ResultsBehaviorally, knockdown of METTL14 significantly counteracted the beneficial effects of acupuncture in improving self-grooming, open field exploration, three-chamber social interaction, and Morris water maze learning and memory (P<0.05, P<0.01). Compared with the acupuncture+sh-NC group, the acupuncture+sh-METTL14 group showed significantly decreased mRNA and protein expression of hippocampal METTL14 (P<0.01), and the upregulating effects of acupuncture on METTL3 and PTEN expression were reversed (P<0.01). Meanwhile, knockdown of METTL14 significantly inhibited the acupuncture-induced increase in PTEN m⁶A levels (P<0.01). Morphologically, knockdown of METTL14 attenuated the improvement of myelin structure by acupuncture, reversed the downregulation of MBP and upregulation of NF155 induced by acupuncture, and blocked the increase in dendritic spine density (P<0.05, P<0.01). ConclusionMETTL14 is a key molecule mediating the therapeutic effect of acupuncture at Neiguan. Acupuncture at Neiguan upregulates METTL14, thereby enhancing m⁶A methylation modification of PTEN mRNA to stabilize its expression, ultimately promoting myelin development and improving behavioral symptoms in ASD juvenile rats. This preliminarily reveals the modern biological connotation of “opening Xuanfu and dredging myelin”.

The initiation of adaptive immune responses relies on the precise recognition and interpretation of antigenic information. In this process, the specific binding of T cell receptors (TCRs) to peptide-major histocompatibility complex (pMHC) molecules represents one of the key molecular events in the initiation of adaptive immune responses. Accordingly, the structural features of TCR-pMHC complexes provide a fundamental basis for dissecting antigen recognition mechanisms and support rational vaccine design, therapeutic target discovery in TCR-based immunotherapy, and TCR identification and optimization. However, experimental determination of TCR-pMHC structures remains costly, time-consuming, and limited in coverage, making computational approaches essential for rapidly obtaining reliable structural information. Computational methods for predicting the structures of TCR-pMHC complexes have advanced rapidly in recent years, driven by progress in deep learning-based modeling frameworks and the increasing availability of structural and sequence resources. Despite these developments, most existing tools do not adequately distinguish the key structural and biophysical differences between MHC class I (MHC-I) and MHC class II (MHC-II) complexes during model construction. As a consequence, their predictive performance differs substantially between class I and class II complexes. In general, structural predictions for class I complexes outperform those for class II complexes. This discrepancy may be related to several fundamental differences between the two systems, including the architecture of the peptide-binding groove, the distribution of peptide lengths, and the properties of peptide flanking residues (PFRs). Compared with MHC-I molecules, MHC-II molecules usually bind longer antigenic peptides, which typically range from 13 to 25 amino acids in length. PFRs at both termini of these peptides participate in regulating the overall conformation of TCR-pMHC class II complexes and exert a pronounced effect on the geometric and physicochemical characteristics of the TCR-pMHC binding interface. Furthermore, within the TCR recognition interface, the complementarity-determining regions (CDRs) consist of segments that differ markedly in conformational behavior. They commonly include regions that are relatively rigid and structurally stable, together with highly flexible segments exhibiting substantial conformational plasticity. These rigidity-flexibility features constitute an essential structural basis enabling TCRs to recognize diverse peptide-MHC ligands and to accommodate conformational heterogeneity at the interface. However, many current modeling tools, in an effort to enforce global conformational stability or reduce structural noise, tend to over-constrain intrinsically flexible regions. Such oversimplification may lead to inappropriate rigidification of flexible CDR loops, resulting in local structural distortions, compromised interface geometry, or even complete modeling failure for specific complexes. Against this background, the review approaches the field from the perspective of computational differences between MHC-I and MHC-II complexes. We first systematically organize and summarize available resources related to TCRs and pMHCs, including structural datasets, sequence databases, prediction tools, and benchmarking studies. We then focus on five representative tools capable of predicting both class I and class II complexes—AlphaFold2, AlphaFold3, TCRmodel2, tFold-TCR, and TCR-pHLA_ModellerS. After excluding structures present in the training sets of these tools, we constructed a benchmark dataset comprising 25 class I and 10 class II TCR-pMHC complexes in the bound state and conducted a systematic evaluation using this dataset. We first employ widely used general evaluation metrics, including All-Atom Root Mean Square Deviation (All-Atom RMSD), Backbone RMSD, Template Modeling score (TM-score), and DockQ, to assess the global conformational accuracy and interface modeling quality of class I and class II complexes. For class II complexes, we propose for the first time a peptide flanking residue deviation index, including the PFRs-Deviation Index (PFRs-DI), N-PFR-Deviation Index (N-PFR-DI), and C-PFR-Deviation Index (C-PFR-DI), to quantitatively characterize conformational deviations in PFRs. In addition, we propose the CDR conformational consistency index (CCC) designed to qualitatively evaluate the ability of prediction tools to capture TCR CDR conformational flexibility. These metrics collectively assess a tool’s ability to model both overall conformation and critical functional regions, thereby addressing the limitations of existing evaluation criteria that overemphasize global structure while inadequately capturing modeling quality in key functional areas. This establishes a unified analytical framework for MHC-I and MHC-II complexes to guide data resource selection, modeling strategy formulation, and evaluation system development. The framework further advances computational modeling and provides crucial support for multi-scale analysis of TCR-pMHC recognition mechanisms and their biological functions.

OBJECTIVE To compare the risk of pneumonitis and interstitial lung disease （ILD） associated with different antibody-drug conjugates （ADC） in the treatment of breast cancer. METHODS CNKI， VIP， PubMed， Embase and other Chinese and English databases， and ClinicalTrials.gov were searched from the inception to June 15， 2025. Randomized controlled trials （RCT） about pneumonitis and ILD associated with ADC （T-DM1， T-DXd， SG， Dato-DXd， SHR-A1811，ARX788， and T-Duo） in the treatment of breast cancer were included. After literature screening， data extraction， and quality assessment， a network meta-analysis was conducted using Stata 17.0 software， and the surface under the cumulative ranking curve（SUCRA） of all interventions were ranked. RESULTS A total of 19 RCTs involving 10 556 patients were included. The overall incidence of pneumonitis with ARX788 and T-DXd was significantly higher than that with T-DM1， T-DM1 plus TPC（T-DM1combined with pertuzumab or atezolizumab）， TPC（treatment of primary care）， and SG （ P ＜0.05）， for grade 1-2 pneumonitis， ARX788 and T-DXd showed significantly higher incidence than T-DM1， T-DM1 plus TPC， and TPC （ P ＜0.05）. For both indicators， ARX788 and T-Duo were ranked as the top two by SUCRA. For the incidence of grade ≥3 pneumonitis， T-DXd and T-DM1 were significantly higher than SG （ P ＜0.05）， T-Duo and Dato-DXd were ranked as the top two by SUCRA. For overall incidence of ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， TPC， and SG （ P ＜0.05）， for the incidence of grade 1-2 ILD， ARX788 was significantly higher than T-DM1， SHR-A1811， and TPC （ P ＜0.05）， for the incidence of grade ≥3 ILD， ARX788 was significantly higher than TPC （ P ＜0.05）. For three indicators above， ARX788 and T-DXd combined with pertuzumab were ranked as the top two by SUCRA. CONCLUSIONS Compared with other ADCs， ARX788 and T-Duo are associated with a higher risk of pneumonitis and ILD in patients with breast cancer.