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.

Objective To explore the value of deep learning(DL)model based on grayscale ultrasound for predicting asymptomatic advanced chronic liver disease(cACLD).Methods Totally 258 patients with asymptomatic compensatory chronic liver diseases were retrospectively included,among them 117 with F3 or F4 stage liver fibrosis were classified into cACLD group,while 141 with F1 or F2 stage liver fibrosis were taken as non-cACLD group.The patients were divided into training set(n=180,including 82 cases of cACLD and 98 cases of non-cACLD)and validation set(n=78,including 35 cases of cACLD and 43 cases of non-cACLD)at the ratio of 7∶3.Univariate and multivariate logistic regression were used to screen independent clinical predictors of cACLD and construct a clinical model.Based on liver grayscale ultrasound,optimal DL features were extracted and screened,and Resnet50 network was adopted as framework,na?ve Bayes classifier was used to construct DL model,and a combined model was constructed based on clinical model and DL model.The efficacy and clinical value of each model for predicting asymptomatic cACLD were evaluated.Results Age,gamma-glutamyl transferase and platelet count were all independent clinical predictors of cACLD,and a clinical model was constructed.Totally 38 optimal DL features were screened to build a DL model.The AUC of combined model in training set and validation set was 0.950 and 0.740,of DL model was 0.944 and 0.737,respectively,being not significantly different(both P＞0.05)but all higher than that of clinical model(0.667 and 0.573,all P＜0.05).Taken 0.59-0.90 as the threshold,the net benefits of combined model in both training and validation sets were higher than that of other models.Conclusion DL model based on grayscale ultrasound could be used to effectively predict asymptomatic cACLD.Combining with clinical characteristics might improve clinical net benefit of this model.

Cesarean scar pregnancy refers to the formation of ectopic pregnancy after embryo implantation to the scar location of cesarean section. We report 2 cases of scar pregnancy after in vitro fertilization-embryo transfer (IVF-ET) in the First Hospital of Lanzhou University. Based on literature review, we explore the risk factors, clinical characteristics, and treatment options of scar pregnancy after in vitro fertilization embryo transfer (IVF-ET), in order to provide a basis for clinical physicians to understand and treat scar pregnancy after in vitro fertilization embryo transfer (IVF-ET).

Bruton's tyrosine kinase inhibitors (BTKi) are a class of novel small-molecule targeted antitumor drugs used to treat B-cell malignancies. However, safety issues associated with BTKi may lead to treatment interruption, compromising their efficacy. To promote the standardized management of safety in BTKi treatment, Evidence-Based Pharmacy Professional Committee of the Chinese Pharmaceutical Association, Hospital Pharmacy Professional Committee of the Chinese Pharmaceutical Association, Division of Therapeutic Drug Monitoring of Chinese Pharmacological Society, Expert Committee on Lymphoma of Chinese Society of Clinical Oncology, Expert Committee on Leukemia of Chinese Society of Clinical Oncology, Integrated Cancer Cardiology Branch of China Anti-Cancer Association, Hematology Branch of the Chinese Medical Association, and Hospital Pharmacy Professional Committee of the Cross-Straits Medicine Exchange Association formulated the Evidence-based Expert Consensus on the Clinical Management of Safety of Bruton′s Tyrosine Kinase Inhibitors (2024), which was published in the Chinese Journal of Cancer Research in June 2024. It covered 9 clinical issues in the following 3 domains: (1) the management of common adverse reactions of BTKi such as bleeding, cardiovascular events, hematological toxicity, infections, rashes, diarrhea, and arthralgia; (2) the management of drug-drug interactions; (3) management guidance for special populations. This consensus provides evidence-based recommendations for the safety management of BTKi medication in clinical practice. This article provides an interpretation and evidence summary of the consensus in Chinese, aiming to facilitate its implementation in China, enhance the safety management of BTKi treatment, and improve patient outcomes.

Objective To explore the longitudinal changes of symptoms after discharge in patients with daytime lung cancer surgery by factor analysis,in order to strengthen nursing countermeasures and improve the quality of life of patients.Methods Patients who underwent day surgery in the thoracic surgery department of a tertiary general hospital in Zhejiang Province from October 2023 to January 2024 were selected using convenience sampling.On the 1st,3rd,14th and 30th day after discharge,the general information questionnaire and the postoperative symptom inventory for patients with lung cancer were used for investigation.Exploratory factor analysis was performed to extract the symptom clusters.Results A total of 227 patients were followed up in this study,including 19 shed cases and 2 excluded cases,and 206 patients were finally included.The percentage of the 9 major symptoms of patients with daytime lung cancer surgery after discharge showed dynamic changes.The highest percentage symptom on the 1st day after discharge was pain in 197 cases(95.63％).The highest percentage on the 30th day after discharge was cough in 129 cases(62.62％).The results of exploratory factor analysis were P＜0.001 and KMO＞0.500 for Bartlett's test of sphericity on days 1,3,and 14 after discharge,except for P=0.874 and KMO=0.495 on day 30,with digestive and respiratory symptom clusters on day 1;respiratory,digestive,and fatigue symptom clusters on day 3;fatigue and respiratory symptom clusters on day 14.Conclusion The single symptom and symptom clusters of patients with daytime lung cancer surgery after discharge showed dynamic changes at different time points.Therefore,in clinical work,targeted intervention strategies should be adopted,and precise symptom management should be implemented according to the characteristics of symptom clusters in different periods of discharge of patients undergoing daytime lung cancer surgery,so as to reduce the symptom burden of patients.

Objective To explore the longitudinal changes of symptoms after discharge in patients with daytime lung cancer surgery by factor analysis,in order to strengthen nursing countermeasures and improve the quality of life of patients.Methods Patients who underwent day surgery in the thoracic surgery department of a tertiary general hospital in Zhejiang Province from October 2023 to January 2024 were selected using convenience sampling.On the 1st,3rd,14th and 30th day after discharge,the general information questionnaire and the postoperative symptom inventory for patients with lung cancer were used for investigation.Exploratory factor analysis was performed to extract the symptom clusters.Results A total of 227 patients were followed up in this study,including 19 shed cases and 2 excluded cases,and 206 patients were finally included.The percentage of the 9 major symptoms of patients with daytime lung cancer surgery after discharge showed dynamic changes.The highest percentage symptom on the 1st day after discharge was pain in 197 cases(95.63％).The highest percentage on the 30th day after discharge was cough in 129 cases(62.62％).The results of exploratory factor analysis were P＜0.001 and KMO＞0.500 for Bartlett's test of sphericity on days 1,3,and 14 after discharge,except for P=0.874 and KMO=0.495 on day 30,with digestive and respiratory symptom clusters on day 1;respiratory,digestive,and fatigue symptom clusters on day 3;fatigue and respiratory symptom clusters on day 14.Conclusion The single symptom and symptom clusters of patients with daytime lung cancer surgery after discharge showed dynamic changes at different time points.Therefore,in clinical work,targeted intervention strategies should be adopted,and precise symptom management should be implemented according to the characteristics of symptom clusters in different periods of discharge of patients undergoing daytime lung cancer surgery,so as to reduce the symptom burden of patients.

Objective To explore the value of deep learning(DL)model based on grayscale ultrasound for predicting asymptomatic advanced chronic liver disease(cACLD).Methods Totally 258 patients with asymptomatic compensatory chronic liver diseases were retrospectively included,among them 117 with F3 or F4 stage liver fibrosis were classified into cACLD group,while 141 with F1 or F2 stage liver fibrosis were taken as non-cACLD group.The patients were divided into training set(n=180,including 82 cases of cACLD and 98 cases of non-cACLD)and validation set(n=78,including 35 cases of cACLD and 43 cases of non-cACLD)at the ratio of 7∶3.Univariate and multivariate logistic regression were used to screen independent clinical predictors of cACLD and construct a clinical model.Based on liver grayscale ultrasound,optimal DL features were extracted and screened,and Resnet50 network was adopted as framework,na?ve Bayes classifier was used to construct DL model,and a combined model was constructed based on clinical model and DL model.The efficacy and clinical value of each model for predicting asymptomatic cACLD were evaluated.Results Age,gamma-glutamyl transferase and platelet count were all independent clinical predictors of cACLD,and a clinical model was constructed.Totally 38 optimal DL features were screened to build a DL model.The AUC of combined model in training set and validation set was 0.950 and 0.740,of DL model was 0.944 and 0.737,respectively,being not significantly different(both P＞0.05)but all higher than that of clinical model(0.667 and 0.573,all P＜0.05).Taken 0.59-0.90 as the threshold,the net benefits of combined model in both training and validation sets were higher than that of other models.Conclusion DL model based on grayscale ultrasound could be used to effectively predict asymptomatic cACLD.Combining with clinical characteristics might improve clinical net benefit of this model.

Bruton's tyrosine kinase inhibitors (BTKi) are a class of novel small-molecule targeted antitumor drugs used to treat B-cell malignancies. However, safety issues associated with BTKi may lead to treatment interruption, compromising their efficacy. To promote the standardized management of safety in BTKi treatment, Evidence-Based Pharmacy Professional Committee of the Chinese Pharmaceutical Association, Hospital Pharmacy Professional Committee of the Chinese Pharmaceutical Association, Division of Therapeutic Drug Monitoring of Chinese Pharmacological Society, Expert Committee on Lymphoma of Chinese Society of Clinical Oncology, Expert Committee on Leukemia of Chinese Society of Clinical Oncology, Integrated Cancer Cardiology Branch of China Anti-Cancer Association, Hematology Branch of the Chinese Medical Association, and Hospital Pharmacy Professional Committee of the Cross-Straits Medicine Exchange Association formulated the Evidence-based Expert Consensus on the Clinical Management of Safety of Bruton′s Tyrosine Kinase Inhibitors (2024), which was published in the Chinese Journal of Cancer Research in June 2024. It covered 9 clinical issues in the following 3 domains: (1) the management of common adverse reactions of BTKi such as bleeding, cardiovascular events, hematological toxicity, infections, rashes, diarrhea, and arthralgia; (2) the management of drug-drug interactions; (3) management guidance for special populations. This consensus provides evidence-based recommendations for the safety management of BTKi medication in clinical practice. This article provides an interpretation and evidence summary of the consensus in Chinese, aiming to facilitate its implementation in China, enhance the safety management of BTKi treatment, and improve patient outcomes.

Cesarean scar pregnancy refers to the formation of ectopic pregnancy after embryo implantation to the scar location of cesarean section. We report 2 cases of scar pregnancy after in vitro fertilization-embryo transfer (IVF-ET) in the First Hospital of Lanzhou University. Based on literature review, we explore the risk factors, clinical characteristics, and treatment options of scar pregnancy after in vitro fertilization embryo transfer (IVF-ET), in order to provide a basis for clinical physicians to understand and treat scar pregnancy after in vitro fertilization embryo transfer (IVF-ET).

Objective To study the effect of silica in soil on the extraction of biological evidence DNA at the crime scene using the silica bead method.Methods Mud suspension and diluted blood were mixed to prepare biological samples mixed with dust and soil,which is to simulate biological evidence at the crime scene.Cell lysis was performed using heating lysis and guanidine salt chemical lysis,respectively.DNA was extracted using the silica bead method,amplified by PCR using Identifiler Plus kit and detected by capillary electrophoresis.The electrophoresis results were compared.Using mud suspension instead of silica beads to extract diluted blood DNA to validate the effect of silica in soil on the extraction of biological evidence DNA at crime scene using silica beads method.Results The complete STR loci were obtained after the extraction and amplification of 4 μL,20 μL dilute blood mixed with mud and lysed with heating cracking,whoes average peak heights arel 969.7±376.9 RFU and 9 706.7±349.8 RFU.For the 4 μL dilute blood mixed with mud guanidine salt chemical lysis,it cannot obtain complete STR loci after extraction and amplification.20 μL dilute blood mixed with mud guanidine salt was chemically cleaved and amplified to obtain complete STR loci with an average peak height of 1 899.8±801.3 RFU.After extraction and amplification by mud suspension instead of silica beads to extract 20 μL diluted blood DNA,complete STR loci were obtained.Conclusion Silicon dioxide in soil can bind to DNA in the presence of guanidine salts,leading to a decrease in the efficiency of recovering on-site biological evidence DNA using the silicon bead method.