Retrospective Assessment of Translational Pharmacokinetic-Pharmacodynamic Modeling Performance: A Case Study with Apitolisib, a Dual PI3K/mTOR Inhibitor.

BACKGROUND AND OBJECTIVES: Despite significant progress in biomedical research, the rate of success in oncology drug development remains inferior to that of other therapeutic fields. Mechanistic models provide comprehensive understanding of the therapeutic effects of drugs, which is crucial for designing effective clinical trials. This study was performed to acquire a better understanding of PI3K-AKT-TOR pathway modulation and preclinical to clinical translational bridging for a specific compound, apitolisib (PI3K/mTOR inhibitor), by developing integrated mechanistic models. METHODS: Integrated pharmacokinetic (PK)-pharmacodynamic (PD)-efficacy models were developed for xenografts bearing human renal cell adenocarcinoma and for patients with solid tumors (phase 1 studies) to characterize relationships between exposure of apitolisib, modulation of the phosphorylated Akt (pAkt) biomarker triggered by inhibition of the PI3K-AKT-mTOR pathway, and tumor response. RESULTS: Both clinical and preclinical integrated models show a steep sigmoid curve linking pAkt inhibition to tumor growth inhibition and quantified that a minimum of 35-45% pAkt modulation is required for tumor shrinkage in patients, based on platelet-rich plasma surrogate matrix and in xenografts based on tumor tissue matrix. Based on this relationship between targeted pAkt modulation and tumor shrinkage rate, it appeared that a constant pAkt inhibition of 61% and 65%, respectively, would be necessary to achieve tumor stasis in xenografts and patients. CONCLUSIONS: These results help when it comes to evaluating the translatability of the preclinical analysis to the clinical target, and provide information that will enhance the value of future preclinical translational dose-finding and dose-optimization studies to accelerate clinical drug development. TRIAL REGISTRY: ClinicalTrials.gov NCT00854152 and NCT00854126.

Quantitative Assessment of Drug Efficacy and Emergence of Resistance in Patients with Metastatic Renal Cell Carcinoma Using a Longitudinal Exposure-Tumor Growth Inhibition Model: Apitolisib (Dual PI3K/mTORC1/2 Inhibitor) Versus Everolimus (mTORC1 Inhibitor).

Cancer remains a significant global health challenge, and despite remarkable advancements in therapeutic strategies, poor tolerability of drugs (causing dose reduction/interruptions) and/or the emergence of drug resistance are major obstacles to successful treatment outcomes. Metastatic renal cell carcinoma (mRCC) accounts for 2% of global cancer diagnoses and deaths. Despite the initial success of targeted therapies in mRCC, challenges remain to overcome drug resistance that limits the long-term efficacy of these treatments. Our analysis aim was to develop a semi-mechanistic longitudinal exposure-tumor growth inhibition model for patients with mRCC to characterize and compare everolimus (mTORC1) and apitolisib's (dual PI3K/mTORC1/2) ability to inhibit tumor growth, and quantitate each drug's efficacy decay caused by emergence of tumor resistance over time. Model-estimated on-treatment tumor growth rate constant was 1.7-fold higher for apitolisib compared to everolimus. Estimated half-life for loss of treatment effect over time for everolimus was 16.1 weeks compared to 7.72 weeks for apitolisib, suggesting a faster rate of tumor re-growth for apitolisib patients likely due to the emergence of resistance. Goodness-of-fit plots including visual predictive check indicated a good model fit and the model was able to capture individual tumor size-time profiles. Based on our knowledge, this is the first clinical report to quantitatively assess everolimus (mTORC1) and apitolisib (PI3K/mTORC1/2) efficacy decay in patients with mRCC. These results highlight the difference in overall efficacy of 2 drugs due to the quantified efficacy decay caused by emergence of resistance, and emphasize the importance of model-informed drug development for targeted cancer therapy.

Analysis of Factors Influencing Prognosis and Assessment of 60 Cases of Decompensated Cirrhotic Patients with Portal Hypertension.

Objective: To investigate the risk factors for the development of portal hypertension in patients with decompensated cirrhosis and analyze their prognosis. Methods: Patients with decompensated cirrhosis who were admitted to our hospital and Qu fu People's Hospital from June 2022 to June 2023 were included in this study. Among them, there were 45 male and 15 female patients, with a median age of 56 (range: 35-77) years. A comparative analysis was performed between Group A (hepatic venous pressure gradient, HVPG <16 mmHg) and Group B (HVPG ≥16 mmHg) patients, along with various clinical outcomes. Multivariate analysis was conducted to explore the risk factors influencing the occurrence of portal hypertension and adverse prognosis in patients with cirrhosis. Results: In Group A patients with portal hypertension, we observed lower levels of aspartate aminotransferase, laminin, serum hyaluronic acid, type III procollagen N-terminal peptide, total bile acids, and cholylglycine acid compared to Group B. On the other hand, levels of alanine aminotransferase, white blood cells, and serum albumin were higher in Group A than in Group B. These differences between the groups were statistically significant (P < 0.05). Multivariate analysis of the aforementioned risk factors indicated that low white blood cell count, high cholylglycine acid levels, and high serum hyaluronic acid levels were identified as independent risk factors for the occurrence of difficult-to-control complications in decompensated portal hypertension among patients with liver cirrhosis (P < 0.05). Conclusion: Liver cirrhosis patients with portal hypertension and multiple risk factors like low white blood cell count and high liver transaminase levels should be cautious regarding the progression of portal hypertension when combined with splenomegaly, liver fibrosis, and bile stasis, as it often indicates a poor prognosis.

The global distribution and the risk prediction of relapsing fever group Borrelia: a data review with modelling analysis.

BACKGROUND: The recent discovery of emerging relapsing fever group Borrelia (RFGB) species, such as Borrelia miyamotoi, poses a growing threat to public health. However, the global distribution and associated risk burden of these species remain uncertain. We aimed to map the diversity, distribution, and potential infection risk of RFGB. METHODS: We searched PubMed, Web of Science, GenBank, CNKI, and eLibrary from Jan 1, 1874, to Dec 31, 2022, for published articles without language restriction to extract distribution data for RFGB detection in vectors, animals, and humans, and clinical information about human patients. Only articles documenting RFGB infection events were included in this study, and data for RFGB detection in vectors, animals, or humans were composed into a dataset. We used three machine learning algorithms (boosted regression trees, random forest, and least absolute shrinkage and selection operator logistic regression) to assess the environmental, ecoclimatic, biological, and socioeconomic factors associated with the occurrence of four major RFGB species: Borrelia miyamotoi, Borrelia lonestari, Borrelia crocidurae, and Borrelia hermsii; and mapped their worldwide risk level. FINDINGS: We retrieved 13 959 unique studies, among which 697 met the selection criteria and were used for data extraction. 29 RFGB species have been recorded worldwide, of which 27 have been identified from 63 tick species, 12 from 61 wild animals, and ten from domestic animals. 16 RFGB species caused human infection, with a cumulative count of 26 583 cases reported from Jan 1, 1874, to Dec 31, 2022. Borrelia recurrentis (17 084 cases) and Borrelia persica (2045 cases) accounted for the highest proportion of human infection. B miyamotoi showed the widest distribution among all RFGB, with a predicted environmentally suitable area of 6·92 million km2, followed by B lonestari (1·69 million km2), B crocidurae (1·67 million km2), and B hermsii (1·48 million km2). The habitat suitability index of vector ticks and climatic factors, such as the annual mean temperature, have the most significant effect among all predictive models for the geographical distribution of the four major RFGB species. INTERPRETATION: The predicted high-risk regions are considerably larger than in previous reports. Identification, surveillance, and diagnosis of RFGB infections should be prioritised in high-risk areas, especially within low-income regions. FUNDING: National Key Research and Development Program of China.

Assessment of arterial pulsatility of cerebral perforating arteries using 7T high-resolution dual-VENC phase-contrast MRI.

PURPOSE: Directly imaging the function of cerebral perforating arteries could provide valuable insight into the pathology of cerebral small vessel diseases (cSVD). Arterial pulsatility has been identified as a useful biomarker for assessing vascular dysfunction. In this study, we investigate the feasibility and reliability of using dual velocity encoding (VENC) phase-contrast MRI (PC-MRI) to measure the pulsatility of cerebral perforating arteries at 7 T. METHODS: Twenty participants, including 12 young volunteers and 8 elder adults, underwent high-resolution 2D PC-MRI scans with VENCs of 20 cm/s and 40 cm/s at 7T. The sensitivity of perforator detection and the reliability of pulsatility measurement of cerebral perforating arteries using dual-VENC PC-MRI were evaluated by comparison with the single-VENC data. The effects of temporal resolution in the PC-MRI acquisition and aging on the pulsatility measurements were investigated. RESULTS: Compared to the single VENCs, dual-VENC PC-MRI provided improved sensitivity of perforator detection and more reliable pulsatility measurements. Temporal resolution impacted the pulsatility measurements, as decreasing temporal resolution led to an underestimation of pulsatility. Elderly adults had elevated pulsatility in cerebral perforating arteries compared to young adults, but there was no difference in the number of detected perforators between the two age groups. CONCLUSION: Dual-VENC PC-MRI is a reliable imaging method for the assessment of pulsatility of cerebral perforating arteries, which could be useful as a potential imaging biomarker of aging and cSVD.

Assessment and predictive ability of the absolute neutrophil count in peripheral blood for in vivo CAR T cells expansion and CRS.

BACKGROUND: Chimeric antigen receptor (CAR) T cell therapy is an advanced and effective immunotherapy for relapsed or refractory B-cell malignancies. High expansion of CAR T cells in vivo and durable antitumor activity indicate a persistent therapeutic response. However, this treatment is linked to a high frequency of adverse events, such as cytokine release syndrome (CRS), which affects its efficacy and can even be life-threatening. At present, a variety of markers associated with clinical response and treatment toxicity after CAR T cells infusion have been reported. Although these biomarkers can act as effective indicators reflecting CAR T cells expansion as well as CRS, they fail to predict the expansion rate of CAR T cells. Hence, further investigation is urgent to find a new biomarker to fill this void. METHODS: We analyzed the association between the absolute neutrophil count (ANC) and CAR expansion and CRS in 45 patients with B-cell malignancies from two clinical trials. We proposed that ANC could be a practical biomarker for CAR T cells expansion and CRS, and conducted a feasibility analysis on its predictive ability. RESULTS: In this study, 17 B-cell hematological malignancy patients with anti-B-cell maturation antigen CAR-treated and 28 with CAR19/22 T-cell-treated were enrolled and divided into an ANC-absence group and an ANC-presence group. The results showed that ANC absence correlated positively with CAR expansion and the expansion rate. The ANC can be used as a predictive marker for CAR T cells expansion. Moreover, the patients with ANC absence experienced a more severe CRS, and ANC performed a predictive ability for CRS. In addition, the peak serum concentration of several cytokines involved in CRS was higher in patients with ANC absence. CONCLUSION: Thus, we suggest ANC as an evaluative and predictive biomarker for CAR expansion and CRS during CAR T cell therapy, which can help to maximize clinical efficacy, reduce treatment-related toxicity and prolong survival.

A new method for multiancestry polygenic prediction improves performance across diverse populations.

Polygenic risk scores (PRSs) increasingly predict complex traits; however, suboptimal performance in non-European populations raise concerns about clinical applications and health inequities. We developed CT-SLEB, a powerful and scalable method to calculate PRSs, using ancestry-specific genome-wide association study summary statistics from multiancestry training samples, integrating clumping and thresholding, empirical Bayes and superlearning. We evaluated CT-SLEB and nine alternative methods with large-scale simulated genome-wide association studies (~19 million common variants) and datasets from 23andMe, Inc., the Global Lipids Genetics Consortium, All of Us and UK Biobank, involving 5.1 million individuals of diverse ancestry, with 1.18 million individuals from four non-European populations across 13 complex traits. Results demonstrated that CT-SLEB significantly improves PRS performance in non-European populations compared with simple alternatives, with comparable or superior performance to a recent, computationally intensive method. Moreover, our simulation studies offered insights into sample size requirements and SNP density effects on multiancestry risk prediction.

Leaching characteristics and pollution risk assessment of potentially harmful elements from coal gangue exposed to weathering for different periods of time.

To explore the leaching behavior and potential degree of pollution that can result from the backfilling of goafs with different types of coal gangue (CG), fresh CG from the Hongqi Coal Mine goaf and surface CG (weathered for 1 year) were selected as the research objects in this study. A series of leaching experiments were carried out using the Ordovician limestone karst waters of the mining areas as the soaking solution. A comparative study on the dissolution characteristics of Fe3+, Mn2+, and SO42- and on the traditional water quality parameters of the two types of CG was conducted. The results showed that the soaked, weathered CG displayed a higher ion dissolution value than fresh CG. The ratio of each ion was as follows: Fe3+ was 1, Mn2+ was 2.86 ~ 68.18, and SO42- was 1.34 ~ 2.09. Over time, the ion concentration of water samples that initially contained high ion concentration values showed a decreasing trend after CG was soaked in these waters, but the values were still in the range of high ion release concentrations. The pH and oxidation‒reduction potential (ORP) values of the leachate of both CG types indicated that the leachates were weakly alkaline and weakly oxidizing, and the overall change in total dissolved solids (TDS) was small and consistent with the SO42- trend. SO42- in the leachate of the weathered CG showed a more significant correlation with the pH and TDS of the soaking solution, and it was the major pollutant. According to the geoaccumulation index evaluation, weathered CG had higher pollution potential than fresh CG. Fe3+ presented a slight and moderate risk for contamination.

Tumor Dynamic Model-Based Decision Support for Phase Ib/II Combination Studies: A Retrospective Assessment Based on Resampling of the Phase III Study IMpower150.

PURPOSE: Model-based tumor growth inhibition (TGI) metrics are increasingly incorporated into go/no-go decisions in early clinical studies. To apply this methodology to new investigational combinations requires independent evaluation of TGI metrics in recently completed Phase III trials of effective immunotherapy. PATIENTS AND METHODS: Data were extracted from IMpower150, a positive, randomized, Phase III study of first-line therapy in 1,202 patients with non-small cell lung cancer. We resampled baseline characteristics and longitudinal sum of longest diameters of tumor lesions of patients from both arms, atezolizumab+ bevacizumab+chemotherapy (ABCP) versus BCP, to mimic Phase Ib/II studies of 15 to 40 patients/arm with 6 to 24 weeks follow-up. TGI metrics were estimated using a bi-exponential TGI model. Effect sizes were calculated as TGI metrics geometric mean ratio (GMR), objective response rate (ORR) difference (d), and progression-free survival (PFS), hazard ratio (HR) between arms. Correct and incorrect go decisions were evaluated as the probability to achieve desired effect sizes in ABCP versus BCP and BCP versus BCP, respectively, across 500 replicated subsamples for each design. RESULTS: For 40 patients/24 weeks follow-up, correct go decisions based on probability tumor growth rate (KG) GMR <0.90, dORR >0.10, and PFS HR <0.70 were 83%, 69%, and 58% with incorrect go decision rates of 4%, 12%, and 11%, respectively. For other designs, the ranking did not change with TGI metrics consistently overperforming RECIST endpoints. The predicted overall survival (OS) HR was around 0.80 in most of the scenarios investigated. CONCLUSIONS: Model-based estimate of KG GMR is an exploratory endpoint that informs early clinical decisions for combination studies.

Bioaccessibility of microplastic-associated heavy metals using an in vitro digestion model and its implications for human health risk assessment.

Microplastics can act as carriers of heavy metals and may enter humans through ingestion and threaten human health. However, the bioaccessibility of heavy metals associated with microplastics and its implications for human health risk assessments are poorly understood. Therefore, in this study, four typical heavy metals (As(V), Cr(VI), Cd(II), and Pb(II)) and one typical microplastic (polyvinyl chloride, PVC) were chosen to estimate the human health risk of microplastic-associated heavy metals by incorporating bioaccessibility. Significant adsorption of heavy metals was observed with the following order for adsorption capacity: Pb(II) > Cr(VI) > Cd(II) > As(V); the efficiencies for desorption of these four heavy metals from PVC microplastics were all below 10%. The Fourier transform infrared spectroscopy results indicated that the functional groups on the surface of the virgin PVC microplastics did not play an important role in the capture process. Heavy metals in both gastric and small intestinal phases were prone to release from PVC microplastics when bioaccessibility was evaluated with the in vitro SBRC (Soluble Bioavailability Research Consortium) digestion model. In addition, Pb(II) bioaccessibility in the gastric phase was significantly higher than those in the other phases, while As(V), Cr(VI), and Cd(II) bioaccessibilities showed the opposite trend. After incorporating bioaccessibility adjustments, the noncarcinogenic hazards and carcinogenic risks determined were lower than those based on total metal contents. The individual hazard quotients (HQ) and carcinogenic risks (CR) for ingestion of these four heavy metals from PVC microplastics were all lower than the threshold values for adults and children. In summary, this study will provide a new view of the human health risks of heavy metals associated with microplastics.

Assessment of cytochrome P450 3A4-mediated drug-drug interactions for ipatasertib using a fit-for-purpose physiologically based pharmacokinetic model.

PURPOSE: Ipatasertib, a potent and highly selective small-molecule inhibitor of AKT, is currently under investigation for treatment of cancer. Ipatasertib is a substrate and a time-dependent inhibitor of CYP3A4. It exhibits non-linear pharmacokinetics at subclinical doses in the clinical dose escalation study. To assess the DDI risk of ipatasertib at the intended clinical dose of 400 mg with CYP3A4 inhibitors, inducers, and substrates, a fit-for-purpose physiologically based pharmacokinetic (PBPK) model of ipatasertib was developed. METHODS: The PBPK model was constructed in Simcyp using in silico, in vitro, and clinical data and was optimized and verified using clinical data. RESULTS: The PBPK model described non-linear pharmacokinetics of ipatasertib and captured the magnitude of the observed clinical DDIs. Following repeated doses of 400 mg ipatasertib once daily (QD), the PBPK model predicted a 3.3-fold increase of ipatasertib exposure with itraconazole; a 2-2.5-fold increase with moderate CYP3A4 inhibitors, erythromycin and diltiazem; and no change with a weak CYP3A4 inhibitor, fluvoxamine. Additionally, in the presence of strong or moderate CYP3A4 inducers, rifampicin and efavirenz, ipatasertib exposures were predicted to decrease by 86% and 74%, respectively. As a perpetrator, the model predicted that ipatasertib (400 mg) caused a 1.7-fold increase in midazolam exposure. CONCLUSION: This study demonstrates the value of using a fit-for-purpose PBPK model to assess the clinical DDIs for ipatasertib and to provide dosing strategies for the concurrent use of other CYP3A4 perpetrators or victims.

Recognize and assessment of key host humic-reducing microorganisms of antibiotic resistance genes in different biowastes composts.

Humic-reducing microorganisms (HRMs) can utilize humic substance as terminal electron mediator promoting the bioremediation of contaminate, which is ubiquitous in composts. However, the impacts of HRMs on antibiotic resistance genes (ARGs) and mobile genetic elements (MGEs) in composts and different HRMs community composition following the types of biowastes effected the spread of ARGs have not been investigated. Herein, the dynamics and mobility of ARGs and HRMs during protein-, lignocellulose- and lignin-rich composting were investigated. Result show that ARGs change significantly at the thermophilic phase, and the relative abundance of most ARGs increase during composting. Seven groups of HRMs communities are classified as primary host HRMs of ARGs, and most host HRMs groups from protein-rich composts. Conclusively, regulating methods for inhibiting ARGs spread for different composts are proposed. HRMs show a higher ARGs dissemination capacity in protein-rich composts than lignocellulose- and lignin-rich composts, but the spread of ARGs can be inhibited by regulate physicochemical parameters in protein-rich composts. In contrary, most HRMs have inhibitory effects on ARGs spread in lignocellulose- and lignin-rich composts, and those HRMs can be used as a new agent that inhibits the spread of ARGs. Our results can help in understanding the potential risk spread of ARGs by inoculating functional bacteria derived from different biowastes composts for environmental remediation, given their expected importance to developing a classification-oriented approach for composting different biowastes.

Incorporating bioaccessibility and source apportionment into human health risk assessment of heavy metals in urban dust of Xiamen, China.

Heavy metals in urban dust could pose noticeable human health risks, but there are few studies focusing on comprehensive human health risk assessment with the incorporation of both bioaccessibility and source apportionment in urban dust. Thus, fifty-eight urban dust samples were collected from kindergartens in Xiamen to analyze the bioaccessibility-based, source-specific health risk of heavy metals (V, Co, Ni, As, Mo, Cr, Mn, Cu, Zn, and Pb). Most heavy metals, except for V and Mn, were significantly enriched in urban dust based on their values of geoaccumulation index (Igeo) and may be influenced by human activities. The oral bioaccessibility values of heavy metals, which were estimated by the Solubility/Bioaccessibility Research Consortium (SBRC) in vitro model, ranged from 1.563% to 76.51%. The source apportionment determined by applying the absolute principal component analysis-multiple linear regression (APCS-MLR) model indicated five main potential sources, coal combustion, traffic and industrial, natural, construction and furniture sources, and unidentified sources, with contributions of 34.09%, 20.72%, 18.72%, 7.597% and 18.87%, respectively, to the accumulation of heavy metals in urban dust. After incorporating bioaccessibility adjustments, lower non-carcinogenic and carcinogenic risks of heavy metals were observed than those based on total metal content, with the mean hazard index (HI) values being less than the threshold value (1) and the mean total carcinogenic risk (TCR) values exceeding the precautionary criterion (10-6) for both adults and children. By combining bioaccessibility-based health risk assessment and source apportionment, traffic and industrial emissions and coal combustion dominated the noncarcinogenic and carcinogenic risks induced by heavy metals in urban dust, respectively. This study is expected to promote the systematic integration of source apportionment and bioaccessibility into health risk estimation for heavy metal contamination in urban dust, thus providing useful implications for better human health protection.

Large-scale genomic analysis reveals the genetic cost of chicken domestication.

BACKGROUND: Species domestication is generally characterized by the exploitation of high-impact mutations through processes that involve complex shifting demographics of domesticated species. These include not only inbreeding and artificial selection that may lead to the emergence of evolutionary bottlenecks, but also post-divergence gene flow and introgression. Although domestication potentially affects the occurrence of both desired and undesired mutations, the way wild relatives of domesticated species evolve and how expensive the genetic cost underlying domestication is remain poorly understood. Here, we investigated the demographic history and genetic load of chicken domestication. RESULTS: We analyzed a dataset comprising over 800 whole genomes from both indigenous chickens and wild jungle fowls. We show that despite having a higher genetic diversity than their wild counterparts (average π, 0.00326 vs. 0.00316), the red jungle fowls, the present-day domestic chickens experienced a dramatic population size decline during their early domestication. Our analyses suggest that the concomitant bottleneck induced 2.95% more deleterious mutations across chicken genomes compared with red jungle fowls, supporting the "cost of domestication" hypothesis. Particularly, we find that 62.4% of deleterious SNPs in domestic chickens are maintained in heterozygous states and masked as recessive alleles, challenging the power of modern breeding programs to effectively eliminate these genetic loads. Finally, we suggest that positive selection decreases the incidence but increases the frequency of deleterious SNPs in domestic chicken genomes. CONCLUSION: This study reveals a new landscape of demographic history and genomic changes associated with chicken domestication and provides insight into the evolutionary genomic profiles of domesticated animals managed under modern human selection.

Online medical services utilization evaluated through the lens of socioecological theory and the information-motivation-behavioral skills model: evidence from China.

Online medical services (OMS) have become increasingly advantageous, but there are still several barriers to utilization among patients. This study aims to explore the factors influencing OMS utilization (OMSU) for patients in micro-, meso-, and macrosystems based on socioecological theory (SET) and from the perspective of the information-motivation-behavioral skills (IMB) model. We selected 1065 participants through multistage stratified cluster random sampling in Jiangsu, China. In microsystems, information and behavioral skills were positively associated with intention (ß = 0.84; ß = 3.21) and actual utilization (OR = 1.69; OR = 1.69). Education level (ß = 0.83) and personal motivation (ß = 1.68) were positively related to intention. Chronic diseases (OR = 2.03) had a positive relationship with actual use. In mesosystems, recommendations from people around the patients (ß = 1.14; OR = 1.99), provision of OMS in the nearest primary medical facility (ß = 0.98; OR = 3.60), and provision of instructional information by medical institutions (ß = 1.01; OR = 1.65) were related to OMSU. The average monthly household income (ß = 0.54) was related to intention. Patients who had information about the OMSU experiences of people around them (OR = 1.73) correlated with actual utilization. In macrosystems, the social medical insurance type (OR = 0.66) was associated with OMSU. This study supports the applicability of the SET and IMB model to interpret patients' OMSU.

A Frailty Assessment Tool to Predict In-Hospital Mortality in Patients with Acute Exacerbations of Chronic Obstructive Pulmonary Disease.

Background: The exacerbation of chronic obstructive pulmonary disease (AECOPD) is a chronic, frequent, and life-threatening lung disease. In 2014, a frailty index (FI) based on deficits in commonly used laboratory tests (FI-Lab) was suggested to identify older adults at increased risk of death. Objective: We aim to study the prognostic value of the FI-Lab in older Chinese patients who were admitted because of AECOPD. Methods: We screened 1932 older patients hospitalized with AECOPD from September 2016 to June 2019 at Zhenjiang First People's Hospital, China. A multivariate logistic regression analysis was used to identify prognostic factors for in-hospital mortality. Results: A total of 77 survivors and 77 non-survivors were finally included in the study. Both the mean DECAF (including dyspnea, eosinopenia, consolidation, acidemia, and atrial fibrillation) score and the mean FI-Lab value of non-survivors were statistically higher than those of survivors (4.45 ± 0.80 versus 3.03 ± 0.90, P=0.000; 0.51 ± 0.13 versus 0.29 ± 0.10, P=0.000, respectively). Logistic regression analysis suggested that DECAF Rank and FI-Lab Rank were strongly related factors of death in AECOPD patients. The areas under the receiver-operating characteristic (ROC) curves were 0.906 for FI-Lab and 0.870 for DECAF (P=0.2991). Conclusion: FI-Lab is a simple, efficient, and objective tool to stratify the risk of in-hospital mortality of AECOPD.

Analysis of Longitudinal-Ordered Categorical Data for Muscle Spasm Adverse Event of Vismodegib: Comparison Between Different Pharmacometric Models.

Longitudinal-ordered categorical data, common in clinical trials, can be effectively analyzed with nonlinear mixed effect models. In this article, we systematically evaluated the performance of three different models in longitudinal muscle spasm adverse event (AE) data obtained from a clinical trial for vismodegib: a proportional odds (PO) model, a discrete-time Markov model, and a continuous-time Markov model. All models developed based on weekly spaced data can reasonably capture the proportion of AE grade over time; however, the PO model overpredicted the transition frequency between grades and the cumulative probability of AEs. The influence of data frequency (daily, weekly, or unevenly spaced) was also investigated. The PO model performance reduced with increased data frequency, and the discrete-time Markov model failed to describe unevenly spaced data, but the continuous-time Markov model performed consistently well. Clinical trial simulations were conducted to illustrate the muscle spasm resolution time profile during the 8-week dose interruption period after 12 weeks of continuous treatment.

Alternative dosing regimens for atezolizumab: an example of model-informed drug development in the postmarketing setting.

PURPOSE: To determine the exposure-response (ER) relationships between atezolizumab exposure and efficacy or safety in patients with advanced non-small cell lung cancer (NSCLC) or urothelial carcinoma (UC) and to identify alternative dosing regimens. METHODS: ER analyses were conducted using pooled NSCLC and UC data from phase 1 and 3 studies (PCD4989g, OAK, IMvigor211; ClinicalTrials.gov IDs, NCT01375842, NCT02008227, and NCT02302807, respectively). Objective response rate, overall survival, and adverse events were evaluated vs pharmacokinetic (PK) metrics. Population PK-simulated exposures for regimens of 840 mg every 2 weeks (q2w) and 1680 mg every 4 weeks (q4w) were compared with the approved regimen of 1200 mg every 3 weeks (q3w) and the maximum assessed dose (MAD; 20 mg/kg q3w). Phase 3 IMpassion130 (NCT02425891) data were used to validate the PK simulations for 840 mg q2w. Observed safety data were evaluated by exposure and body weight subgroups. RESULTS: No significant ER relationships were observed for safety or efficacy. Predicted exposures for 840 mg q2w and 1680 mg q4w were comparable to 1200 mg q3w and the MAD and consistent with observed PK data from IMpassion130. Observed safety was similar between patients with a Cmax above and below the predicted Cmax for 1680 mg q4w and between patients in the lowest and upper 3 body weight quartiles. CONCLUSION: Atezolizumab regimens of 840 mg q2w and 1680 mg q4w are expected to have comparable efficacy and safety as the approved regimen of 1200 mg q3w, supporting their interchangeable use and offering patients greater flexibility.