A propensity score-integrated approach for leveraging external data in a randomized controlled trial with time-to-event endpoints.

In a randomized controlled trial with time-to-event endpoint, some commonly used statistical tests to test for various aspects of survival differences, such as survival probability at a fixed time point, survival function up to a specific time point, and restricted mean survival time, may not be directly applicable when external data are leveraged to augment an arm (or both arms) of an RCT. In this paper, we propose a propensity score-integrated approach to extend such tests when external data are leveraged. Simulation studies are conducted to evaluate the operating characteristics of three propensity score-integrated statistical tests, and an illustrative example is given to demonstrate how these proposed procedures can be implemented.

Network Pharmacology Study on the Underlying Mechanism of Danggui-Kushen Herb Pair in Adjuvant Chemotherapeutics against Breast Cancer.

BACKGROUND: The Danggui-Kushen herb pair (DKHP) is a classic prescription that has long been used in combination with chemotherapeutic drugs to improve the immune status of patients with breast cancer (BC), however, the active components and the underlying pharmacological mechanisms remain unclear. Therefore, this study aimed to elucidate the possible mechanism of action of DKHP against BC-based comprehensive strategy combining network pharmacology, molecular docking, and cellular experiments. METHODS: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform was used to obtain the relevant compounds in DKHP. Genecards and the National Center for Biotechnology Information databases were used to predict BC targets. Then, drug-compound- target, andprotein-protein interaction networks were constructed to forecast the promising protein targets of DKHP and identify the primary interactions that occur between the protein targets and compounds. Finally, the predicted candidate targets were validated using docking techniques and in vitro experiments. RESULTS: A total of 30 potential active compounds and 173 intersecting pharmacological targets were identified in DKHP. Gene Ontology enrichment analysis revealed that the inflammatory response, positive regulation of protein phosphorylation, and cellular response to lipopolysaccharide were closely related to DKHP treatment in BC. Kyoto Encyclopedia of Genes and Genomes pathway analysis suggested that the PI3K/AKT pathway may be crucial for DKHP intervention in BC. Therefore, key targets could be AKT1, TP53, VEGR, CASP3, TNF, and IL6. Molecular docking analysis suggested that hyperforin, kushenin, and kushenol T had good binding ability to Akt, p53, and Caspase 3. The in vitro experiment showed that the DKHP extract promoted the apoptosis of MCF-7 cells via the PI3K/Akt signaling pathway. These results corresponded to the predictions produced using the network pharmacology approach. CONCLUSION: Hyperforin, kushenin, kushenol T, and other active compounds in DKHP can regulate multiple signaling pathways and targets, such as AKT1, TP53, and CASP3, thereby playing preventive and therapeutic roles in BC.

Propensity score-incorporated adaptive design approaches when incorporating real-world data.

The propensity score-integrated composite likelihood (PSCL) method is one method that can be utilized to design and analyze an application when real-world data (RWD) are leveraged to augment a prospectively designed clinical study. In the PSCL, strata are formed based on propensity scores (PS) such that similar subjects in terms of the baseline covariates from both the current study and RWD sources are placed in the same stratum, and then composite likelihood method is applied to down-weight the information from the RWD. While PSCL was originally proposed for a fixed design, it can be extended to be applied under an adaptive design framework with the purpose to either potentially claim an early success or to re-estimate the sample size. In this paper, a general strategy is proposed due to the feature of PSCL. For the possibility of claiming early success, Fisher's combination test is utilized. When the purpose is to re-estimate the sample size, the proposed procedure is based on the test proposed by Cui, Hung, and Wang. The implementation of these two procedures is demonstrated via an example.

CCL21-CCR7 signaling promotes microglia/macrophage recruitment and chemotherapy resistance in glioblastoma.

Glioblastoma (GBM) is the most common and fatal primary tumor of the central nervous system (CNS) and current treatments have limited success. Chemokine signaling regulates both malignant cells and stromal cells of the tumor microenvironment (TME), constituting a potential therapeutic target against brain cancers. Here, we investigated the C-C chemokine receptor type 7 (CCR7) and the chemokine (C-C-motif) ligand 21 (CCL21) for their expression and function in human GBM and then assessed their therapeutic potential in preclinical mouse GBM models. In GBM patients, CCR7 expression positively associated with a poor survival. CCL21-CCR7 signaling was shown to regulate tumor cell migration and proliferation while also controlling tumor associated microglia/macrophage recruitment and VEGF-A production, thereby controlling vascular dysmorphia. Inhibition of CCL21-CCR7 signaling led to an increased sensitivity to temozolomide-induced tumor cell death. Collectively, our data indicate that drug targeting of CCL21-CCR7 signaling in tumor and TME cells is a therapeutic option against GBM.

Principled leveraging of external data in the evaluation of diagnostic devices via the propensity score-integrated composite likelihood approach.

In the area of diagnostics, it is common practice to leverage external data to augment a traditional study of diagnostic accuracy consisting of prospectively enrolled subjects to potentially reduce the time and/or cost needed for the performance evaluation of an investigational diagnostic device. However, the statistical methods currently being used for such leveraging may not clearly separate study design and outcome data analysis, and they may not adequately address possible bias due to differences in clinically relevant characteristics between the subjects constituting the traditional study and those constituting the external data. This paper is intended to draw attention in the field of diagnostics to the recently developed propensity score-integrated composite likelihood approach, which originally focused on therapeutic medical products. This approach applies the outcome-free principle to separate study design and outcome data analysis and can mitigate bias due to imbalance in covariates, thereby increasing the interpretability of study results. While this approach was conceived as a statistical tool for the design and analysis of clinical studies for therapeutic medical products, here, we will show how it can also be applied to the evaluation of sensitivity and specificity of an investigational diagnostic device leveraging external data. We consider two common scenarios for the design of a traditional diagnostic device study consisting of prospectively enrolled subjects, which is to be augmented by external data. The reader will be taken through the process of implementing this approach step-by-step following the outcome-free principle that preserves study integrity.

Some Thoughts on the Use of Predictive Probability in Clinical Trials.

In this short note, we express our viewpoint regarding declaring study success based on Bayesian predictive probability of study success.

Improving precision and power in randomized trials with a two-stage study design: Stratification using clustering method.

In a randomized controlled trial (RCT), it is possible to improve precision and power and reduce sample size by appropriately adjusting for baseline covariates. There are multiple statistical methods to adjust for prognostic baseline covariates, such as an ANCOVA method. In this paper, we propose a clustering-based stratification method for adjusting for the prognostic baseline covariates. Clusters (strata) are formed only based on prognostic baseline covariates, not outcome data nor treatment assignment. Therefore, the clustering procedure can be completed prior to the availability of outcome data. The treatment effect is estimated in each cluster, and the overall treatment effect is derived by combining all cluster-specific treatment effect estimates. The proposed implementation of the procedure is described. Simulations studies and an example are presented.

Research and application of herbal medicine in the treatment of chronic kidney disease since the 21st century: A visualized bibliometric analysis.

Background: Here, a bibliometric and knowledge-map analysis was used to analyze the research status and application of herbal medicine for the treatment of chronic kidney disease (CKD). By looking for research hotspots and key topics, we provide new clues and research directions for future research. Methods: Articles and reviews regarding herbal medicine in the treatment of CKD were retrieved from the Web of Science Core Collection on 23 May 2022. The R-bibliometrix, VOSviewer, and CiteSpace software were used to conduct the bibliometric and knowledge-map analysis. Results: In total, 5,920 authors at 1,330 institutions from 68 countries published 1,602 papers in 355 academic journals. China is the leader and pioneer in the research and application of herbal medicine in the field of CKD treatment. Beijing University of Chinese Medicine contributed the most publications. Ping Li (China-Japan Friendship Hospital) published the most articles, while Yingyong Zhao (Northwest University) had the most cocitations. However, cooperation among countries and the research institutions is not sufficient. Journal of Ethnopharmacology published the most research and application of herbal medicine in the treatment of CKD and was the most commonly co-cited journal. The most influential research hotspots about herbal medicine in the treatment of CKD focused on diabetic nephropathy-related research, Balkan endemic nephropathy, and pharmacokinetic study. Conclusion: Herbal medicine has a wide range of pharmacological activities and therapeutic value. The research and application of herbal medicine for the treatment of CKD, especially diabetic nephropathy, will remain a hot topic in the future.

Immune Effects of Macrophages in Rheumatoid Arthritis: A Bibliometric Analysis From 2000 to 2021.

Rheumatoid arthritis (RA) is a chronic autoimmune inflammatory disease characterized by macrophage activation. The current characteristics, hotspots, and research frontiers of macrophage-related RA were analyzed using bibliometric analysis. Relatedpapers published from 2000 to 2021 in the Web of Science database were retrieved. The diagrams were generated and analyzed using the bibliometric software package. VOSviewer and CiteSpace were used to evaluate and visualize the research trends and hotspots in macrophage-related RA. A total of 7253 original articles were obtained. Global research on macrophage-related RA is in an advanced stage of development, with core authors, teams and research institutions emerging. United States has published the most papers, received the most citations, and had the highest H-index over the last 22 years. The University of Amsterdam and the journal of Arthritis and Rheumatism are the most productive research institutions and journals. Tak PP's (St Vincent's Hospital) paper has the highest publication and citation scores. The keywords "bone loss" and "polarization" have the highest frequency. Additionally, the study of macrophage polarization in RA has been research focus in recent years. This study demonstrates that research on macrophages in RA will continue. China is a significant producer, whereas the United States is an influential nation in this regard. In the last decade, most studies have concentrated on fundamental research. Recent studies have shown how macrophages play a role in controlling and weakening inflammation, and drug delivery and mechanism have come to the fore.

Antibacterial properties of lactoferrin: A bibliometric analysis from 2000 to early 2022.

Background: Here, a bibliometric and knowledge map analysis are used to analyze the research hot spots and development trends regarding the antibacterial effect of lactoferrin (LF). By looking for research hot spots and new topics, we provide new clues and research directions for future research. Methods: Articles and reviews regarding the antibacterial effect of LF were retrieved and from the Web of Science Core Collection (WoSCC) on 25 June 2022. CiteSpace and VOSviewer were used to conduct the bibliometric and knowledge map analysis. Results: In total, 8,292 authors at 2,151 institutions from 86 countries published 1,923 articles in 770 academic journals. The United States was the leader regarding research on the antibacterial effects of LF, while the Netherlands was a pioneer in conducting research in this field. The University of California system contributed the most publications. Bolscher JGM published most articles, while Wayne Bellamy had most cocitations. However, there was insufficient cooperation among the various institutions and authors. BioMetals published most LF-antibacterial activity-related articles, whereas Infection and Immunity was most commonly cocited journal. The most influential research hot spots about the antibacterial effect of LF focused on antimicrobial peptides, casein, human milk, expression, and Escherichia coli-related research. The latest hot spots and research frontier included COVID-19, antibiofilm activity, and immune defense. Conclusions: LF is a multifunctional protein with a broad spectrum of antimicrobial activities. The related field of antibacterial properties of LF will remain a research hot spot in future.

Conserved meningeal lymphatic drainage circuits in mice and humans.

Meningeal lymphatic vessels (MLVs) were identified in the dorsal and caudobasal regions of the dura mater, where they ensure waste product elimination and immune surveillance of brain tissues. Whether MLVs exist in the anterior part of the murine and human skull and how they connect with the glymphatic system and extracranial lymphatics remained unclear. Here, we used light-sheet fluorescence microscopy (LSFM) imaging of mouse whole-head preparations after OVA-A555 tracer injection into the cerebrospinal fluid (CSF) and performed real-time vessel-wall (VW) magnetic resonance imaging (VW-MRI) after systemic injection of gadobutrol in patients with neurological pathologies. We observed a conserved three-dimensional anatomy of MLVs in mice and humans that aligned with dural venous sinuses but not with nasal CSF outflow, and we discovered an extended anterior MLV network around the cavernous sinus, with exit routes through the foramina of emissary veins. VW-MRI may provide a diagnostic tool for patients with CSF drainage defects and neurological diseases.

Simultaneous screening, identification, quantitation, and activity evaluation of six acetylcholinesterase (AChE) inhibitors in Coptidis Rhizoma by online UPLC-DAD coupled with AChE biochemical detection.

Acetylcholinesterase (AChE) inhibition is a common treatment in the early stages of dementia and neurodegenerative diseases, including Alzheimer's disease (AD). Coptidis Rhizoma (CR), a traditional Chinese medicine (TCM), contains numerous isoquinoline alkaloids that substantially inhibit AChE played neuroprotective effects in the treatment of cognitive diseases. We established a method using an ultra-high-performance liquid chromatography-diode array detector coupled with AChE biochemical detection (UPLC-DAD-AChEBCD) to screen and identify AChE inhibitors (AChEIs), measure AChEIs content and activity, and evaluate the quality of CR derived from different plant species and growth year. The chromatographic fingerprint and AChEIs activity profiles of CR were simultaneously obtained by UPLC-DAD-AChEBCD, and six alkaloids including groenlandicine, coptisine, epiberberine, jatrorrhizine, berberine, and palmatine, were identified by UPLC-electrospray ionization-tandem mass spectrometry. Data analysis based on AChEIs content and total activity of 12 batches of CR indicated differences among different species and growth year. Therefore, the online method could be used to rapidly identify AChEIs in complex matrixes and screen potential agents for neurodegenerative prevention and treatment, as well as provide information for the identification and quantitation of active markers directly associated with herbal medicine quality.

Propensity score-integrated approach to survival analysis: leveraging external evidence in single-arm studies.

External data, referred to as data external to the traditional clinical study being planned, include but are not limited to real-world data (RWD) and data collected from clinical studies being conducted in the past or in other countries. The external data are sometimes leveraged to augment a single-arm, prospectively designed study when appropriate. In such an application, recently developed propensity score-integrated approaches including PSPP and PSCL can be used for study design and data analysis when the clinical outcomes are binary or continuous. In this paper, the propensity score-integrated Kaplan-Meier (PSKM) method is proposed for a similar situation but the outcome of interest is time-to-event. The propensity score methodology is used to select external subjects that are similar to those in the current study in terms of baseline covariates and to stratify the selected subjects from both data sources into more homogeneous strata. The stratum-specific PSKM estimators are obtained based on all subjects in the stratum with the external data being down-weighted, and then these estimators are combined to obtain an overall PSKM estimator. A simulation study is conducted to assess the performance of the PSKM method, and an illustrative example is presented to demonstrate how to implement the proposed method.

Endothelial Unc5B controls blood-brain barrier integrity.

Blood-brain barrier (BBB) integrity is critical for proper function of the central nervous system (CNS). Here, we show that the endothelial Unc5B receptor controls BBB integrity by maintaining Wnt/ß-catenin signaling. Inducible endothelial-specific deletion of Unc5B in adult mice leads to BBB leak from brain capillaries that convert to a barrier-incompetent state with reduced Claudin-5 and increased PLVAP expression. Loss of Unc5B decreases BBB Wnt/ß-catenin signaling, and ß-catenin overexpression rescues Unc5B mutant BBB defects. Mechanistically, the Unc5B ligand Netrin-1 enhances Unc5B interaction with the Wnt co-receptor LRP6, induces its phosphorylation and activates Wnt/ß-catenin downstream signaling. Intravenous delivery of antibodies blocking Netrin-1 binding to Unc5B causes a transient BBB breakdown and disruption of Wnt signaling, followed by neurovascular barrier resealing. These data identify Netrin-1-Unc5B signaling as a ligand-receptor pathway that regulates BBB integrity, with implications for CNS diseases.

Estimands in observational studies: Some considerations beyond ICH E9 (R1).

The document ICH E9 (R1) has brought much attention to the concept of estimand in the clinical trials community. ICH stands for International Conference for Harmonization. In this article, we draw attention to one facet of estimand that is not discussed in that document but is crucial in the context of observational studies, namely weighting for covariate balance. How weighting schemes are connected to estimand, or more specifically to one of its five attributes identified in ICH E9 (R1), the attribute of population, is illustrated using the Rubin Causal Model. Three estimands are examined from both theoretical and practical perspectives. Factors that may be considered in choosing among these estimands are discussed.

Protective Effect of the Pearl Extract from Pinctada fucata martensii Dunker on UV-Induced Photoaging in Mice.

Although the effect of pearl powder has been recognized for more than a thousand years from healthcare to beauty care, there has yet to be an in-depth understanding of its anti-photoaging effect. In the present study, the protective effect of pearl extract (PE) on UV-induced photoaging in mice was evaluated. First, the amino acid analysis of PE was carried out. Then, different dosages of pearl extract gel (PEG) were applied topically on the shaved dorsal skins regions of mice before UV irradiation. Skin physiological and histological analysis, antioxidant enzymes and inflammatory factor test were used to evaluate the anti-photoaging effect of PEG. The results showed that PEG contained 14 amino acids, and could inhibit UV-irritated skin wrinkles, laxity, thickness, and dryness. Moreover, PEG upregulated the activities of CAT, GSH-Px, SOD and decreased MDA level, and suppressed the production of IL-1ß, IL-6, PGE2 , TNF-α, and COX-2 in UV-irradiated mice. The therapeutic effect in high dose PEG group was superior to those of positive control (Vitamin E). This study demonstrated the underlying mechanisms of PEG against UV-irritated photoaging. And PEG possesses a potential use in photoprotective medicines and cosmetics.

Leverage multiple real-world data sources in single-arm medical device clinical studies.

The interest in utilizing real-world data (RWD) has been considerably increasing in medical product development and evaluation. With proper usage and analysis of high-quality real-world data, real-world evidence (RWE) can be generated to inform regulatory and healthcare decision-making. This paper proposes a study design and data analysis approach for a prospective, single-arm clinical study that is supplemented with patients from multiple real-world data sources containing patient-level covariate and outcome data. After the amount of information to be borrowed from each real-world data source is determined, the propensity score-integrated composite likelihood method is applied to obtain an estimate of the parameter of interest based on data from the prospective clinical study and this real-world data source. This method is applied to each real-world data source. The final estimate of the parameter of interest is then obtained by taking a weighted average of all these estimates. The performance of the proposed approach is evaluated via a simulation study. A hypothetical example is presented to illustrate how to implement the proposed approach.

Augmenting Both Arms of a Randomized Controlled Trial Using External Data: An Application of the Propensity Score-Integrated Approaches.

Leveraging external data is a topic that have recently received much attention. The propensity score-integrated approaches are a methodological innovation for this purpose. In this paper we adapt these approaches, originally introduced to augment single-arm studies with external data, for the augmentation of both arms of a randomized controlled trial (RCT) with external data. After recapitulating the basic ideas, we provide a step-by-step tutorial of how to implement the propensity score-integrated approaches, from study design to outcome analysis, in the RCT setting in such a way that the study integrity and objectively are maintained. Both the Bayesian (power prior) approach and the frequentist (composite likelihood) approach are included. Some extensions and variations of these approaches are also outlined at the end of this paper.

Propensity score-integrated power prior approach for augmenting the control arm of a randomized controlled trial by incorporating multiple external data sources.

In this paper, a propensity score-integrated power prior approach is developed to augment the control arm of a two-arm randomized controlled trial (RCT) with subjects from multiple external data sources such as real-world data (RWD) and historical clinical studies containing subject-level outcomes and covariates. The propensity scores for the subjects in the external data sources versus the subjects in the RCT are first estimated, and then subjects are placed in different strata based on their estimated propensity scores. Within each propensity score stratum, a power prior is formulated with the information contributed by the external data sources, and Bayesian inference on the treatment effect is obtained. The proposed approach is implemented under the two-stage study design framework utilizing the outcome-free principle to ensure the integrity of a study. An illustrative example is provided to demonstrate the implementation of the proposed approach.

Leveraging real-world evidence for determining performance goals for medical device studies.

Performance goals are numerical target values pertaining to effectiveness or safety endpoints in single-arm medical device clinical studies. Typically, performance goals are determined at the planning stage of the investigational study under consideration based on summarized outcome information from existing relevant clinical trials. In recent years, there is a growing interest in leveraging real-world evidence in medical product development. In this article, we introduce a new method for proposing performance goals by leveraging real-world evidence. The method applies entropy balancing to address possible patient dissimilarities between the study's target patient population and existing real-world patients, and can take into account operation differences between clinical studies and real-world clinical practice. An illustrative example is provided to demonstrate how to implement the proposed method for performance goal determination while leveraging real-world evidence.