Evidence-based interventions to improve sleep quality after thoracic surgery:A retrospective analysis of clinical studies.

OBJECTIVE: To investigate and rank the evidence for the efficacy of interventions in improving sleep quality after cardiac surgery using comprehensive comparisons. BACKGROUND: Clinical evidence suggests that over 80 % of adult cardiac surgery patients experience sleep disturbances during the first week postoperatively. While certain interventions have been shown to improve post-thoracic surgery sleep quality, a systematic description of the effects of these varied interventions is lacking. METHODS: This systematic search was conducted across PubMed, Web of Science, Cochrane, Embase, and CINAHL databases to collate all published randomized clinical trials as evidence. Two researchers independently extracted pertinent information from eligible trials and assessed the quality of included studies. Based on statistical heterogeneity, traditional meta-analysis using fixed or random-effects models was employed to assess the efficacy of interventions, and a Frequentist network meta-analysis using a consistency model was conducted to rank the effectiveness of intervention protocols. RESULTS: Our review incorporated 37 articles (n = 3569), encompassing 46 interventions, including 9 reports on pharmacological interventions (24.3 %), 28 on non-pharmacological interventions (75.7 %), and 5 on anesthetic management interventions (13.5 %). The analysis indicated the efficacy of Benson's relaxation technique, Progressive muscle relaxation, Education, Aromatherapy, Acupressure, Massage, and Eye masks in enhancing postoperative sleep quality. Specifically, Benson's relaxation technique (cumulative ranking curve area: 0.80; probability: 98.3 %) and Acupressure (cumulative ranking curve area: 0.96; probability: 58.3 %) were associated with the highest probability of successfully improving postoperative sleep quality, while Progressive muscle relaxation (cumulative ranking curve area: 0.70; probability: 35.2 %) and Eye masks (cumulative ranking curve area: 0.81; probability: 78.8 %) were considered secondary options. Eye masks and Massage significantly reduced postoperative sleep latency, with Eye masks (cumulative ranking curve area: 0.82; probability: 51.0 %) being most likely to enhance sleep quality postoperatively, followed by Massage (cumulative ranking curve area: 0.60; probability: 27.2 %). Education, Music, Massage, Eye masks, and Handholding were effective in alleviating pain intensity, with Education being most likely to successfully reduce postoperative pain (cumulative ranking curve area: 0.92; probability: 54.3 %), followed by Music (cumulative ranking curve area: 0.91; probability: 54 %). CONCLUSIONS: Our findings can be utilized to optimize strategies for managing post-thoracic surgery sleep disturbances and to develop evidence-based approaches for this purpose. Benson's relaxation technique, Progressive muscle relaxation, Education, Aromatherapy, Acupressure, Massage, and Eye masks significantly improve sleep quality in postoperative patients. KEY: disorders of initiating and maintaining sleep, sleep wake disorders, thoracic surgical procedures, cardiac surgical procedures, sleep quality, pain, network meta-analysis.

Three methods to optimise polymyxin B dosing using estimated AUC after first dose: validation with the data generated by Monte Carlo simulation.

To achieve the AUC-guided dosing, we proposed three methods to estimate polymyxin B AUC across 24 h at steady state (AUCSS,24h) using limited concentrations after its first dose.Monte Carlo simulation based on a well-established population PK model was performed to generate the PK profiles of 1000 patients with normal or abnormal renal function. Polymyxin B AUCSS,24h was estimated for each subject using three methods (two-point PK approach, three-point PK approach, and four-point PK approach) based on limited concentration data in its first dose and compared with the actual AUC at steady state calculated using the linear-trapezoidal formula.In patients with normal renal function, the mean bias of two-point PK approach, three-point PK approach, and four-point PK approach was -8.73%, 1.37%, and -0.48%, respectively. The corresponding value was -11.15%, 1.99%, and -0.28% in patients with renal impairment, respectively. The largest mean bias of two-point PK approach, three-point PK approach, and four-point PK approach was -12.63%, -6.47%, and -0.54% when the sampling time shifted.The Excel calculators designed based on the three methods can be potentially used to optimise the dosing regimen of polymyxin B in the clinic.

Comparison of whole-blood sirolimus concentrations measured by EMIT-based Siemens Viva-ProE® System and LC-MS/MS in Chinese transplant patients.

Sirolimus (SRL) is commonly used in transplant patients to prevent organ transplant rejection. The current guidelines recommend to perform SRL therapeutic drug monitoring regularly to improve treatment outcomes and avoid adverse effects. Consequently, a precise and accurate method for determining SRL is crucial in clinical practice. Currently, liquid chromatography-tandem mass spectrometry (LC-MS/MS) and immunoassays have been widely adopted for determining SRL concentrations. However, previous studies have shown that immunoassays exhibit a positive bias compared to LC-MS/MS. As the new updated version of the EMIT-based Viva-E® System (SVPS), this study aims to compare SRL blood concentrations measured by the SVPS and LC-MS/MS. The residual whole-blood samples obtained from transplant patients were simultaneously analyzed using the SVPS and LC-MS/MS, respectively. The correlation between the two assays was analyzed using the linear regression analysis and Deming linear regression. The Pearson correlation coefficient and Intraclass correlation coefficient (ICC) analysis were executed. The Paired Wilcoxon test and Bland-Altman analysis were performed to assess the concordance between the two methods. The SVPS considerably increased SRL concentration value by 46.62 % as compared to the LC-MS/MS method. When SRL concentrations measured by the SVPS were above 4.0 ng/mL, there was no significant difference between the corrected SVPS concentrations after using the Deming linear regression equation, indicating their interchangeability. Given the significant disparities observed between EMIT and LC-MS/MS, it is crucial to indicate the methodology and instruments in both TDM reports and future clinical guidelines. Our study also provides the conversion formulas between the SVPS and LC-MS/MS, which can be applied as a reference for different clinical centers.

Exploring the Link Between Exogenous Thyroid Hormones and Dementia Symptoms: A Real-World Disproportionality Analysis of FDA Adverse Event Reporting System.

BACKGROUND: A growing body of evidence indicates a strong association between exogenous thyroid hormone (ETH) and brain health. Establishing the potential relationship between ETH therapy and dementia symptoms is crucial for patients with thyroid disorders. OBJECTIVE: In this study, we investigate the potential association between ETH therapy and dementia symptoms by exploring the Food and Drug Administration Adverse Event Reporting System (FAERS) database. METHODS: Disproportionality analysis (DPA) was conducted using postmarketing data from the FAERS repository (Q1 2004 to Q4 2023). Cases of dementia symptoms associated with ETH therapy were identified and analyzed through DPA using reporting odds ratios and information component methods. Dose and time-to-onset analyses were performed to assess the association between ETH therapy and dementia symptoms. RESULTS: A total of 9889 cases of ETH-associated symptoms were identified in the FAERS database. Dementia accounted for a consistent proportion of adverse drug reactions each year (3.4%-6.3%). The DPA indicated an association between ETH therapy and dementia symptoms, which remained significant even across sex, age, and indications. The median time-to-onset of dementia symptoms was 7.5 days, and the median treatment time was 40.5 days. No significant dose-response relationship was observed. CONCLUSION AND RELEVANCE: This study provides evidence for a link between ETH therapy and dementia. Clinicians are therefore advised to exercise vigilance, conduct comprehensive monitoring, and consider individualized dosing to mitigate potential reactions to ETH drug administration.

A systematic evaluation of population pharmacokinetic models for polymyxin B in patients with liver and/or kidney dysfunction.

Polymyxin B (PMB) is considered a last-line treatment for multidrug-resistant (MDR) gram-negative bacterial infections. Model-informed precision dosing with population pharmacokinetics (PopPK) models could help to individualize PMB dosing regimens and improve therapy. However, the external prediction ability of the established PopPK models has not been fully elaborated. This study aimed to systemically evaluate eleven PMB PopPK models from ten published literature based on a new independent population, which was divided into four different populations, patients with liver dysfunction, kidney dysfunction, liver and kidney dysfunction, and normal liver and kidney function. The whole data set consisted of 146 patients with 391 PMB concentrations. The prediction- and simulation-based diagnostics and Bayesian forecasting were conducted to evaluate model predictability. In the overall evaluation process, none of the models exhibited satisfactory predictive ability in both prediction- and simulation-based diagnostic simultaneously. However, the evaluation of the models in the subgroup of patients with normal liver and kidney function revealed improved predictive performance compared to those with liver and/or kidney dysfunction. Bayesian forecasting demonstrated enhanced predictability with the incorporation of two to three prior observations. The external evaluation highlighted a lack of consistency between the prediction results of published models and the external validation dataset. Nonetheless, Bayesian forecasting holds promise in improving the predictive performance of the models, and feedback from therapeutic drug monitoring is crucial in optimizing individual dosing regimens.

Randomized controlled trial of an app for cancer pain management.

PURPOSE: The primary objective of this investigation was to devise a mobile application for self-management of cancer-related discomfort, with the overarching goal of enhancing patients' overall well-being. Would the utilization of the self-management application result in an amelioration of life quality compared to conventional follow-up procedures? METHODS: Modules were meticulously devised with the collaborative expertise of oncology pain specialists employing the Delphi technique. Reliability of the consultation was assessed using Cronbach's α. After developing the app, a prospective randomized controlled study was conducted to evaluate the app's effect on participants' quality of life. The trial group used the app; the control group received a follow-up telephone consultation. Assessments of quality of life were conducted both at baseline and following a 4-week intervention period. RESULTS: After two rounds of Delphi expert consultation, the functional modules of Pain Guardian were determined to include five functional modules, including pain self-measurement (real-time dynamic recording of pain by patients), patient reminders (reminders of outbreaks of pain disposal, medication, and review), uploading of examination reports, online consultation, health education, and other functional modules. Cronbach's α was 0.81. Overall, 96 patients (including esophageal, gastric, colorectal, nasopharyngeal, pulmonary, pancreatic, breast, ovarian, uterine, bone, thoracic, bladder, cervical, soft tissue sarcoma, mediastinal, and lymphoma) with cancer pain were divided into the trial and control groups. There were no significant differences in basic information and quality of life at baseline between groups. After 4 weeks of intervention, quality of life was significantly higher in the trial group than in the control group. Patients' satisfaction with the app was high (93.7%). CONCLUSIONS: The primary obstacle encountered in the development of applications for managing cancer-related discomfort lies in the sensitive nature of the subject matter, potentially leading to patient apprehension regarding application usage for pain management. Consequently, meticulous attention to user preferences and anticipations is imperative, necessitating the creation of an application characterized by user-friendliness and medical efficacy. TRIAL REGISTRATION: Chinese Clinical Trials Registry ChiCTR1800016066; http://www.chictr.org.cn/showproj.aspx?proj=27153 . Date of Registration: 2018-05-09.

Population pharmacokinetic analyses of methotrexate in pediatric patients: a systematic review.

BACKGROUND AND OBJECTIVES: Methotrexate is widely utilized in the chemotherapy of malignant tumors and autoimmune diseases in the pediatric population, but dosing can be challenging. Several population pharmacokinetic models were developed to characterize factors influencing variability and improve individualization of dosing regimens. However, significant covariates included varied across studies. The primary objective of this review was to summarize and discuss population pharmacokinetic models of methotrexate and covariates that influence pharmacokinetic variability in pediatric patients. METHODS: Systematic searches were conducted in the PubMed and EMBASE databases from inception to 7 July 2023. Reporting Quality was evaluated based on a checklist with 31 items. The characteristics of studies and information for model construction and validation were extracted, summarized, and discussed. RESULTS: Eighteen studies (four prospective studies and fourteen retrospective studies with sample sizes of 14 to 772 patients and 2.7 to 93.1 samples per patient) were included in this study. Two-compartment models were the commonly used structural models for methotrexate, and the clearance range of methotrexate ranged from 2.32 to 19.03 L/h (median: 6.86 L/h). Body size and renal function were found to significantly affect the clearance of methotrexate for pediatric patients. There were limited reports on the role of other covariates, such as gene polymorphisms and co-medications, in the pharmacokinetic parameters of methotrexate pediatric patients. Internal and external evaluations were used to assess the performance of the population pharmacokinetic models. CONCLUSION: A more rigorous external evaluation needs to be performed before routine clinical use to select the appropriate PopPK model. Further research is necessary to incorporate larger cohorts or pool analyses in specific susceptible pediatric populations to improve the understanding of predicted exposure profiles and covariate identification.

Comparison of immune checkpoint inhibitors related to pulmonary adverse events: a retrospective analysis of clinical studies and network meta-analysis.

BACKGROUND: Immune checkpoint inhibitors (ICIs) have transformed tumor treatment. However, the risk of pulmonary adverse events (PAEs) associated with ICI combination therapy is still unclear. We aimed to provide a PAE overview and risk ordering of ICIs used in tumor treatment. METHODS: We searched the databases of PubMed, PsycINFO, Embase, Cochrane Library, CINAHL, Web of Science, Scopus, and clinical trial websites during January 2011-April 2023 to identify phase II and III randomized clinical trials (RCTs) and single-arm clinical trials wherein at least one treatment arm received ICIs (e.g., ICI monotherapy, a combination of two ICIs, or ICIs in combination with conventional cancer therapy). We reported the results of PAEs. Additionally, we compared risks of PAEs between different drug classes using a Bayesian network meta-analysis. RESULTS: Among 143 RCTs and 24 single-arm trials, the incidence of all-grade and grade 3-4 PAEs were highest with programmed death L1 (PD-L1) plus cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4) and plus chemotherapy and anti-PD1 plus anti-CTLA4, the lowest with targeted therapy drug plus chemotherapy and anti-PD1 plus anti-PDL1. Anti-PD1 plus anti-CTLA4 and plus chemotherapy was the intervention with the highest risk for all-grade and 3-4 grade PAEs, and the intervention with the lowest risk was chemotherapy and anti-PD1 plus anti-PDL1. In terms of all-grade PAEs, chemotherapy was safer than ICI monotherapy. Except for the anti-PD1 plus anti-PDL1 regimen, no significant difference in the risk of grade 3-4 PAEs was detected between dual-ICIs and single-ICIs. Furthermore, the risk of PAEs associated with nivolumab, pembrolizumab, and atezolizumab may be dose dependent. CONCLUSIONS: In the single-drug regimen, anti-PD1 caused the greatest incidence of PAEs. The risk of PAEs was higher with all single-ICIs than with chemotherapy. However, no significant difference in the risk of PAEs was detected between single-ICIs. In the combined regimen, anti-PD1 plus anti-CTLA4 and plus chemotherapy showed the greatest risk of PAEs, but there were no significant differences in risk between dual-ICIs and single-ICIs.

Exploration of the potential association between GLP-1 receptor agonists and suicidal or self-injurious behaviors: a pharmacovigilance study based on the FDA Adverse Event Reporting System database.

BACKGROUND: Establishing whether there is a potential relationship between glucagon-like peptide 1 receptor agonists (GLP-1RAs) and suicidal or self-injurious behaviors (SSIBs) is crucial for public safety. This study investigated the potential association between GLP-1RAs and SSIBs by exploring the FDA Adverse Event Reporting System (FAERS) database. METHODS: A disproportionality analysis was conducted using post-marketing data from the FAERS repository (2018 Q1 to 2022 Q4). SSIB cases associated with GLP-1RAs were identified and analyzed through disproportionality analysis using the information component. The parametric distribution with a goodness-of-fit test was employed to analyze the time-to-onset, and the Ω shrinkage was used to evaluate the potential effect of co-medication on the occurrence of SSIBs. RESULTS: In total, 204 cases of SSIBs associated with GLP-1RAs, including semaglutide, liraglutide, dulaglutide, exenatide, and albiglutide, were identified in the FAERS database. Time-of-onset analysis revealed no consistent mechanism for the latency of SSIBs in patients receiving GLP-1RAs. The disproportionality analysis did not indicate an association between GLP-1RAs and SSIBs. Co-medication analysis revealed 81 cases with antidepressants, antipsychotics, and benzodiazepines, which may be proxies of mental health comorbidities. CONCLUSIONS: We found no signal of disproportionate reporting of an association between GLP-1RA use and SSIBs. Clinicians need to maintain heightened vigilance on patients premedicated with neuropsychotropic drugs. This contributes to the greater acceptance of GLP-1RAs in patients with type 2 diabetes mellitus or obesity.

Development and validation of a nomogram for predicting immune-related pneumonitis after sintilimab treatment.

BACKGROUND: Immune-related pneumonitis is a rare and potentially fatal adverse event associated with sintilimab. We aimed to develop and validate a nomogram for predicting the risk of immune-related pneumonitis in patients treated with sintilimab. METHODS: The least absolute shrinkage and selection operator (LASSO) regression was used to determine risk factors. Multivariable logistic regression was used to establish a prediction model. Its clinical validity was evaluated using calibration, discrimination, decision, and clinical impact curves. Internal validation was performed against the validation set and complete dataset. RESULTS: The study included 632 patients; 59 were diagnosed with immune-related pneumonitis. LASSO regression analysis identified that the risk factors for immune-related pneumonitis were pulmonary metastases (odds ratio [OR], 4.015; 95% confidence interval [CI]: 1.725-9.340) and metastases at >3 sites (OR, 2.687; 95% CI: 1.151-6.269). The use of combined antibiotics (OR, 0.247; 95% CI: 0.083-0.738) and proton pump inhibitors (OR, 0.420; 95% CI: 0.211-0.837) were protective factors. The decision and clinical impact curves showed that the nomogram had clinical value for patients treated with sintilimab. CONCLUSIONS: We have developed and validated a practical nomogram model of sintilimab-associated immune-related pneumonitis, which provides clinical value for determining the risk of immune-related pneumonitis and facilitating the safe administration of sintilimab therapy.

Limited Sampling Strategies for Estimating Busulfan Area Under the Concentration-Time Curve: Based on Peak and Trough Concentrations in Saliva.

Therapeutic drug monitoring for busulfan is currently performed by multiple plasma sampling. Saliva is considered a noninvasive therapeutic drug monitoring matrix. This study aimed to investigate intravenous busulfan pharmacokinetics (PK) in plasma and saliva, and establish a limited sampling strategy (LSS) for predicting the area under the concentration-time curve from time zero to infinity in plasma (AUC0-∞,p) by using saliva samples. Therefore, the PK of busulfan was studied in 37 Chinese patients. Pearson correlation analysis was used to evaluate the correlation between the AUC of busulfan in plasma and saliva. LSS models were established by the multiple linear regression analysis. The prediction error, the mean prediction error, and the root mean square error were used to evaluate the predictive accuracy. The agreement between the predicted and observed AUC0-∞ in saliva was investigated by the intraclass correlation coefficient and Bland-Altman analysis. The accuracy and robustness of the models were evaluated by using the bootstrap procedure. The result of PK analysis 62.2% of patients (23/37) was within the target range of AUC0-∞,p . A good correlation between saliva and plasma busulfan AUC0-∞ was observed (r = 0.63, p < .01). The bias and precision of the models 7 and 13 were less than 15%. The intraclass correlation coefficient exceeded 0.9, and the limits of agreement were within ±15%. The 2-point LSS model in saliva is a convenient and desirable approach to predict the AUC0-∞ of 4 times daily intravenous busulfan in plasma, which can be used to design personalized dosing for busulfan.

External Evaluation of Population Pharmacokinetic Models for High-Dose Methotrexate in Adult Patients with Hematological Tumors.

Currently, numerous population pharmacokinetic (popPK) models for methotrexate (MTX) have been published for estimating PK parameters and variability. However, it is unclear whether the accuracy of these models is sufficient for clinical application. The aim of this study is to evaluate published models and assess their predictive performance according to the standards of scientific research. A total of 237 samples from 74 adult patients who underwent high-dose MTX (HDMTX) treatment at Shanghai Changzheng Hospital were collected. The software package NONMEM was used to perform an external evaluation for each model, including prediction-based diagnosis, simulation-based diagnosis, and Bayesian forecasting. The simulation-based diagnosis includes normalized prediction distribution error (NPDE) and visual predictive check (VPC). Following screening, 7 candidate models suitable for external validation were identified for comparison. However, none of these models exhibited excellent predictive performance. Bayesian simulation results indicated that the prediction precision and accuracy of all models significantly improved when incorporating prior concentration information. The published popPK models for MTX exhibit significant differences in their predictive performance, and none of the models were able to accurately predict MTX concentrations in our data set. Therefore, before adopting any model in clinical practice, extensive evaluation should be conducted.

Managing delayed or missed pregabalin doses in patients with focal epilepsy: a Monte Carlo simulation study.

BACKGROUND: Delayed or missed doses are inevitable in epilepsy pharmacotherapy. The current remedial measures recommended by the United States Food and Drug Administration (FDA) for non-adherence are generic and lack clinical evidence. AIM: To assess remedial strategies for delayed or missed pregabalin doses in patients with epilepsy using Monte Carlo simulations. METHOD: Monte Carlo simulations were performed using a published population pharmacokinetic model for pregabalin. The applicability of five proposed remedial regimens as well as FDA recommendations was evaluated by simulating various poor adherence scenarios in eight populations, including those with renal dysfunction. RESULTS: All proposed remedial strategies were associated with delay duration and renal function. When delays are relatively short, an immediate regular dose is advised. The cut-off time points for taking the regular dose as a remedial regimen were 1, 2, 4, and 12 h for patients with mild renal impairment and normal renal function, moderate renal impairment, severe renal impairment, and end-stage renal disease, respectively. However, when delay aligns closely with a dosing interval, a regular dose combined with a partial dose proves effective. Generally, supplementing 1.3-fold the regular dose at the next scheduled time adequately compensates for the missed dose. CONCLUSION: Model-based simulations provided quantitative evidence for the effectiveness and feasibility of remedial strategies for missed or delayed pregabalin doses.

Metabolomic profiling reveals the mechanisms underlying the nephrotoxicity of methotrexate in children with acute lymphoblastic leukemia.

BACKGROUND: Methotrexate is widely recommended as a first-line treatment for the intensive systemic and consolidation phases of childhood acute lymphoblastic leukemia. However, methotrexate-induced nephrotoxicity is a severe adverse reaction, of which the mechanisms remain unclear. METHODS: An untargeted metabolomics analysis of serum from childhood acute lymphoblastic leukemia patients with delayed methotrexate excretion, with or without acute kidney injury, was performed to identify altered metabolites and metabolic pathways. An independent external validation cohort and in vitro HK-2 cell assays further verified the candidate metabolites, and explored the mechanisms underlying the nephrotoxicity of methotrexate. RESULTS: Four metabolites showed significant differences between normal excretion and delayed excretion, seven metabolites reflected the differences between groups with or without acute kidney injury, and six pathways were finally enriched. In particular, oxidized glutathione was confirmed as a candidate metabolite involved in the toxicity of methotrexate. We further explored the role of glutathione deprivation-induced ferroptosis on methotrexate cytotoxicity, and it was found that methotrexate overload significantly reduced cell viability, triggered reactive oxygen species and intracellular Fe2+ accumulation, and altered the expression of ferroptosis-related proteins in HK-2 cells. These methotrexate-induced changes were alleviated or reversed by the administration of a ferroptosis inhibitor, further suggesting that ferroptosis promoted methotrexate-induced cytotoxicity in HK-2 cells. CONCLUSIONS: Our findings revealed complex metabolomic profiles and provided novel insights into the mechanism by which ferroptosis contributes to the nephrotoxic effects of methotrexate.

Population pharmacokinetics of polymyxin B in patients with liver dysfunction.

AIMS: Polymyxin B (PMB) is widely used to treat infections caused by multidrug-resistant Gram-negative pathogens. Currently, the pharmacokinetic data of PMB in patients with liver dysfunction are limited. This study aimed to develop a population pharmacokinetic (PopPK) model of PMB in patients with liver dysfunction and identify the factors affecting PMB pharmacokinetics. METHODS: We conducted a retrospective pharmacokinetic study involving 136 adults with different levels of liver function. Nonlinear mixed effects modelling was used to develop a PopPK model of PMB. Monte Carlo simulation was used to design PMB dosage schedules across various liver and renal functions. RESULTS: PMB pharmacokinetic analyses included 401 steady-state concentrations in 136 adult patients. A one-compartment pharmacokinetic model with first-order absorption and elimination was used to describe the data. The typical population value of PMB clearance was 2.43 L/h and the volume of distribution was 23.11 L. This study revealed that creatinine clearance (CrCL) and Child-Pugh class were significantly associated with PMB pharmacokinetic parameters; however, clinically relevant variations of dose-normalized drug exposure were not significant. For patients with a minimum inhibitory concentration of ≤0.5 mg/L, the appropriate dose was 40-75 mg/12-h. When the dose exceeded 100 mg/12-h, the risk of nephrotoxicity increased significantly. CONCLUSIONS: This study provided PMB pharmacokinetic information for patients with liver dysfunction. Patients with renal and liver dysfunctions may not require an initial dose adjustment. Rather than PopPK-guided dose adjustment, therapeutic drug monitoring of PMB plays a more direct role in optimizing dosing regimens based on its therapeutic window.

Saliva as a noninvasive sampling matrix for therapeutic drug monitoring of intravenous busulfan in Chinese patients undergoing hematopoietic stem cell transplantation: A prospective population pharmacokinetic and simulation study.

Therapeutic drug monitoring (TDM) of busulfan (BU) is currently performed by plasma sampling in patients undergoing hematopoietic stem cell transplantation (HSCT). Saliva samples are considered a noninvasive TDM matrix. Currently, no salivary population pharmacokinetics (PopPKs) model for BU available. This study aimed to develop a PopPK model that can describe the relationship between plasma and saliva kinetics in patients receiving intravenous BU. The performance of the model in predicting the area under the concentration-time curve at steady state (AUCss ) based on saliva samples is evaluated. Sixty-six patients with HSCT were recruited and administered 0.8 mg/kg BU intravenously. A PopPK model for saliva and plasma was developed using the nonlinear mixed effects model. Bayesian maximum a posteriori (MAP) optimization was used to estimate the model's predictive performance. Plasma and saliva PKs were adequately described with a one-compartment model and a scaled central compartment. Body surface area correlated positively with both clearance and apparent volume of distribution (Vd), whereas alkaline phosphatase correlated negatively with Vd. Simulations demonstrated that the percentage root mean squared prediction error and lower and upper limits of agreements reduced to 10.02% and -16.96% to 22.86% based on five saliva samples. Saliva can be used as an alternative matrix to plasma in TDM of BU. The AUCss can be predicted from saliva concentration by Bayesian MAP optimization, which can be used to design personalized dosing for BU.

Predicting busulfan exposure in patients undergoing hematopoietic stem cell transplantation using machine learning techniques.

PURPOSE: This study aimed to establish an optimal model to predict the busulfan (BU) area under the curve at steady state (AUCss) by using machine learning (ML). PATIENTS AND METHODS: Seventy-nine adult patients (age ≥18 years) who received BU intravenously and underwent therapeutic drug monitoring from 2013 to 2021 at Fujian Medical University Union Hospital were enrolled in this retrospective study. The whole dataset was divided into a training group and test group at the ratio of 8:2. BU AUCss were considered as the target variable. Nine different ML algorithms and one population pharmacokinetic (pop PK) model were developed and validated, and their predictive performance was compared. RESULTS: All ML models were superior to the pop PK model (R2 = 0.751, MSE = 0.722, 14 and RMSE = 0.830) in model fitting and had better predictive accuracy. The ML model of BU AUCss established through support vector regression (SVR) and gradient boosted regression trees (GBRT) had the best predictive ability (R2 = 0.953 and 0.953, MSE = 0.323 and 0.326, and RMSE = 0.423 and 0.425). CONCLUSION: All the ML models can potentially be used to estimate BU AUCss with the aim of facilitating rational use of BU on the individualized level, especially models built by SVR and GBRT algorithms.

Movement disorders associated with antiseizure medications: A real-world disproportionality analysis of the Food and Drug Administration Adverse Event Reporting System.

AIMS: Patients with epilepsy often require long-term use of antiseizure medications (ASMs) to control their seizures. However, movement disorders (MDs) related to ASMs can significantly impact their quality of life. This study aims to analyse MDs related to ASMs in the Food and Drug Administration Adverse Event Reporting System database to provide recommendations for safe medication. METHODS: All adverse drug reactions associated with 26 marketed ASMs in Food and Drug Administration Adverse Event Reporting System were extracted for analysis. Disproportionality analyses were used to assess the association between ASMs and MDs, and signal colour scale maps were created to identify potential ASM-MD safety signals. RESULTS: A total of 1921 cases experienced MDs while taking ASMs were included. A higher prevalence of MDs was observed in females compared to males. The association between specific MDs with ASMs was revealed, including known and unknown MDs such as tremors, Parkinson and paralysis. Lamotrigine and carbamazepine exhibited multiple significant MDs, while levetiracetam and pregabalin were linked to the earlier onset of MDs. Generally, higher doses were linked to a higher incidence of MDs. CONCLUSION: MDs were the most obvious adverse drug reactions in the nervous system triggered by using ASMs. Fourteen drugs exhibited positive signals for MDs, including some not previously reported. Conversely, 12 ASMs were deemed to have a lower possibility of inducing MDs. The incidence of MDs can be mitigated by selecting appropriate ASMs for epileptic patients. These findings enhance our understanding of the relationship between ASMs and MDs.

Population Pharmacokinetic Modeling Using Polymyxin B Free Plasma Concentrations From Published Reports and Evaluation of Dosage Regimens Based on Monte Carlo Simulation in Critically Ill Patients.

A population pharmacokinetic (pop PK) model of polymyxin B was developed using nonlinear mixed-effects (NONMEM) modeling based on free plasma concentrations to determine whether dose adjustment is required in critically ill patients. One thousand pharmacokinetic profiles for virtual patients with a body weight of 70 kg were simulated using Monte Carlo simulation at different dose scenarios, and area under the concentration-time curve of free drug (fAUC) was computed. The probability of target attainment (PTA) at each minimum inhibitory concentration (MIC) was calculated using fAUC/MIC as a pharmacokinetic/pharmacodynamic (PK/PD) index. The final population PK model was a 2-compartment model. PTA showed that 3.5 mg/kg/day regimens of polymyxin B effectively achieved the fAUC/MIC target of 10 (one log10 kill) against Pseudomonas aeruginosa strains with MIC of 1 mg/L or less (PTA,  90.7% or greater), while the dose regimen were ineffective against strains with an MIC of 2 mg/L or greater (PTA, 56.9% or less). For Klebsiella pneumoniae, the fAUC/MIC target of 17.4 (one log10 kill) was achieved in more than 90.4% of cases for MIC of 0.5 mg/L or less with 3 mg/kg/day regimens. However, the PTA decreased dramatically as MICs increased above 1 mg/L (PTA, 56.1% or less). The polymyxin B dosage regimen of 3.5 mg/kg/day and 3 mg/kg/day are sufficient to treat P. aeruginosa infections with an MIC of 1 mg/L or less and K. pneumoniae infections with an MIC of 0.5 mg/L or less, respectively. The current recommended dose (1.5-3 mg/kg/day) of polymyxin B appears inadequate to attain the PK/PD target for therapeutic efficacy against infections caused by P. aeruginosa and K. pneumoniae isolates when MIC is above the values.

First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric cancer, gastroesophageal junction cancer, and esophageal adenocarcinoma: a cost-effectiveness analysis.

Background: The CheckMate-649 trial compared nivolumab plus chemotherapy (NC) with chemotherapy alone as first-line treatment for advanced gastric cancer (GC), gastroesophageal junction cancer (GEJC), and esophageal adenocarcinoma (EAC) and showed significant benefits to progression-free survival and overall survival. This study evaluated the lifetime cost-effectiveness of NC versus chemotherapy alone in patients with GC/GEJC/EAC from the perspective of the US payers. Methods: A 10-year partitioned survival model was constructed to evaluate the cost-effectiveness of NC and chemotherapy alone and measured the health achievements in quality-adjusted life-years (QALYs), incremental cost-effectiveness ratios (ICERs), and life-years. Health states and transition probabilities were modeled from the survival data from the CheckMate-649 clinical trial (NCT02872116). Only direct medical costs were considered. One-way and probabilistic sensitivity analyses were conducted to assess the robustness of the results. Results: On comparing the chemotherapy, we found that NC incurred substantial health costs, resulting in ICERs of $240,635.39/QALY, $434,182.32/QALY, and $386,715.63/QALY for the model of patients with programmed cell death-ligand 1 (PD-L1) combined positive score (CPS) ⩾5, PD-L1 CPS ⩾1, and all-treated patients, respectively. All ICERs were significantly higher than the willingness-to-pay threshold value of $150,000/QALY. The main influencing factors were the cost of nivolumab, the utility value of the progression-free disease, and the discount rate. Conclusion: Compared with chemotherapy alone, NC may not be a cost-effective option for treating advanced GC, GEJC, and EAC in the United States.