Analysis Of Treatment Effects Research Articles

Innovative Applications and Perspectives of Surface-Enhanced Raman Spectroscopy Technology in Biomedicine.

Surface-enhanced Raman spectroscopy (SERS) has become a revolutionary technique in the biomedical field, providing unparalleled sensitivity for the detection and characterization of biological samples. In this review, recent SERS innovations are comprehensively discussed, including advanced substrate materials, different SERS detection strategies, and multimodal approaches that combine SERS with other biotechnologies. Among them, the role of SERS in the accurate diagnosis of tumors is highlighted, which has promoted accurate molecular analysis and real-time monitoring of treatment effects. In addition, the growing potential of SERS in the treatment of chronic diseases such as cardiovascular disease, diabetes, and neurodegenerative diseases is discussed. Moreover, the integration with microfluidic chip systems for precise single-cell analysis is presented. To give a forward-looking view, the key challenges faced by SERS technology are also proposed, and possible solutions to overcome these obstacles are provided.

Social media’s impact on environmental awareness: a marginal treatment effect analysis of WeChat usage in China

Environmental awareness serves as an intrinsic motivator for individuals’ engagement in environmental protection behaviors, and social media platforms can foster such awareness. Drawing on the 2018 China General Social Survey data (CGSS 2018), this study employs non-parametric and semi-parametric approaches within the framework of marginal treatment effect (MTE) to examine the influence of WeChat usage on the environmental awareness of Chinese residents. The findings unveil significant heterogeneity in the impact of frequent WeChat usage on individuals’ levels of environmental awareness. Through estimation of the average treatment effect, treatment group average treatment effect, and non-treatment group average treatment effect, the study reveals that WeChat exerts a stronger positive influence on the environmental awareness of residents with a high propensity for using the platform, while it has no discernible effect on the environmental awareness of residents with a low inclination to engage with WeChat. The growth of environmental knowledge facilitated by WeChat plays a crucial role in shaping environmental awareness. Furthermore, this research underscores the influence of real-life social network structures on information exchange within the WeChat platform in China. This observation suggests that WeChat transcends its role as a mere information transmission tool and becomes intricately woven into the social network fabric of its users, thus mirroring certain characteristics of information dissemination within offline social networks. These insights imply that targeted strategies can be devised to bolster residents’ environmental awareness by capitalizing on the interconnectedness of real-life social networks and leveraging the information exchange potential of WeChat. By doing so, it is possible to enhance environmental protection endeavors and encourage more sustainable behaviors among individuals.

Gambling Behavior and Cryptocurrency Investment: A Treatment-Effect Analysis

Gambling Behavior and Cryptocurrency Investment: A Treatment-Effect Analysis

Treatment Effect Heterogeneity in Acute Kidney Injury Incidence Following Intravenous Antihypertensive Administration for Severe Blood Pressure Elevation During Hospitalization

Severe hypertension (sHTN) that develops after hospital admission is prevalent in 10% of patients admitted for reasons other than HTN. sHTN is commonly treated with intravenous (IV) antihypertensives and is associated with a greater risk of acute kidney injury (AKI). Our goal was to explore whether there is heterogeneity in IV antihypertensives' effect on AKI incidence among patients who develop sHTN during hospitalization. Heterogeneity of treatment effect analysis. Patients who developed sHTN, systolic blood pressure (BP) >180, or diastolic BP >110 mmHg during hospitalization and did not have kidney failure. Treatment with IV antihypertensives within 3 hours of BP elevation. Time to develop AKI. An accelerated failure time Bayesian Additive Regression Trees (BART) model to capture the association between the time to develop AKI and predictors. Individual treatment effects estimated for each participant using a counterfactual outcome framework and these estimates were used to identify patient characteristics associated with treatment effect heterogeneity in response to IV antihypertensives. We included 11,951 patients who developed sHTN, 741 were treated with IV antihypertensives, and 11,210 were not, of which 18% and 13% developed AKI, respectively. Most patients would have been harmed from IV antihypertensive treatment except for a small subset of 317 patients who were White, had an SBP on admission ≥156 mmHg, an eGFR ≥70.7 ml/min/1.73m2, and a serum bicarbonate <21.7 mmol/L. Data-driven, hypothesis-generating approach. Findings were not validated with external data sources. These exploratory findings suggest that most patients who develop sHTN will not benefit from IV antihypertensive treatment. Future studies should assess for heterogeneity when identifying treatment options, if any are needed, for sHTN.

What makes a devoted local-food-buying club customer?

Local food-buying clubs (LFBCs) are special types of consumer-driven grassroots groups that are particularly well suited to enhancing the transition to a post-growth economy, given the finite growth potential of individual communities, the tendency of groups to distribute rather than accumulate capital, and the prospects of the movement for expansion. This paper analyses consumers of LFBCs and analyses how the different constructs proposed by the theory of planned behaviour are applicable according to engagement with LFBCs. A representative survey was run in May 2020 in Hungary. Respondents who were classified as devoted (regular) LFBC customers, occasional LFBC customers, and consumers not interested in local food were compared pairwise through matching-based treatment effect analysis approaches. Consumers of LFBCs comprised a heterogeneous group based on their pre-existing beliefs and attitudes. Occasional LFBC customers emphasised the broad quality-related features of local food and the potential for supporting local farmers. For more devoted customers, environmental aspects were very important. As belonging to a group has been shown to shape attitudes, targeted messages applied by LFBC managers may increase the level of engagement, contributing to the more efficient scaling up of local food systems.

Estimands and Cumulative Incidence Function Regression in Clinical Trials: Some New Results on Interpretability and Robustness.

Regression analyses based on transformations of cumulative incidence functions are often adopted when modeling and testing for treatment effects in clinical trial settings involving competing and semi-competing risks. Common frameworks include the Fine-Gray model and models based on direct binomial regression. Using large sample theory we derive the limiting values of treatment effect estimators based on such models when the data are generated according to multiplicative intensity-based models, and show that the estimand is sensitive to several process features. The rejection rates of hypothesis tests based on cumulative incidence function regression models are also examined for null hypotheses of different types, based on which a robustness property is established. In such settings supportive secondary analyses of treatment effects are essential to ensure a full understanding of the nature of treatment effects. An application to a palliative study of individuals with breast cancer metastatic to bone is provided for illustration.

Routine use of ultrasound-assisted catheter-directed thrombolysis for the management of intermediate-high risk pulmonary embolism: a service evaluation project

Abstract Background Intermediate-high risk Pulmonary Embolism (PE) has considerable morbidity. Conservative management could be sub-optimal. Ultrasound-Assisted Catheter-Directed Thrombolysis (UACDT) is used in our centre for the routine management of this presentation. Purpose We assessed the procedure safety and short-term outcomes by reviewing locally performed procedures. Methods This is an observational retrospective cohort study, with a historic control group. Our centre is a District General Hospital (DGH) in the United Kingdom, and we receive referrals from local acute hospitals. Since the introduction of this service in June 2018 until November 2023, 129 patients (2 patients/month) received routine management with UACDT for intermediate-high risk PE. The controls are 75 acute PE patients of comparable risk classes, managed from January to December 2016. We assessed procedural and in-hospital outcomes including minor, major bleeding/complications and death. We also assessed Length of Stay (LoS) in hospital, recurrent Venous Thrombo-Embolism (VTE) and re-admission rates for recurrent PE at 30 days. Reduction of oxygen requirements and improved estimated systolic Pulmonary Artery Pressure (sPAP) post-procedure were assessed as surrogate measures. Continuous variables were analysed with a Mann-Whitney U test, and categorical variables with a Chi-square Test. Results Baseline demographics are listed in Table 1. Mean duration between CT Pulmonary Angiography (CTPA) and the UACDT procedure was 1.6 (±SD 1.4) days, including inter-hospital transfer. Only 6% (8/129) of UACDT cohort received ≤12 mg standard alteplase dose. In the control group, 4% (3/75) of patients received standard 100mg systemic thrombolysis. There was no significant difference in the rates of minor (p= 0.9), major bleeding/complications (p= 0.8), or death (p= 1.0) between both groups. There was also no significant difference in rates of recurrent VTE (p= 1.0) or re-admission within 30 days for PE (p=0.1) (Table 2). LoS in hospital data were ratified, to exclude inappropriate delays (e.g. physiotherapy requirements, etc). We used the date when the patient was declared medically fit for discharge, and no significant difference was noted (p= 0.2). This was confirmed with a regression analysis of UACDT treatment effect (p= 0.9, CI= -3.5 to 3.1). Nonetheless, there was a 25% reduction of median LoS in hospital from 8 days in the controls to 6 days with UACDT. The proportion of patients requiring O2 was also reduced from 69% (89/129) to 41% (54/129) on day 1 post-procedure. A significant reduction of the estimated sPAP by TTE post-procedure was detected by a mean of 10.4 (±SD 13.9) mmHg (p= &amp;lt;0.01). Conclusion UACDT is generally safe with low complications rate. Compared to the control group, there was a reduction in absolute deaths and median LoS in hospital. This can be secondary to the significant acute reduction of systolic pulmonary artery pressure identified.

Direct Estimation for Commonly Used Pattern-Mixture Models in Clinical Trials

Pattern-mixture models have received increasing attention as they are commonly used to assess treatment effects in primary or sensitivity analyses for clinical trials with nonignorable missing data. Pattern-mixture models have traditionally been implemented using multiple imputation, where the variance estimation may be a challenge because the Rubin’s approach of combining between- and within-imputation variance may not provide consistent variance estimation while bootstrap methods may be time-consuming. Direct likelihood-based approaches have been proposed in the literature and implemented for some pattern-mixture models, but the assumptions are sometimes restrictive and the theoretical framework is fragile. In this article, we propose an analytical framework for an efficient direct likelihood estimation method for commonly used pattern-mixture models corresponding to return-to-baseline, jump-to-reference, placebo washout, and retrieved dropout imputations. A parsimonious tipping point analysis is also discussed and implemented. Results from simulation studies demonstrate that the proposed methods provide consistent estimators. We further illustrate the utility of the proposed methods using data from a clinical trial evaluating a treatment for type 2 diabetes.

The effect of grandparental involvement on grandchildren's school grades: Heterogeneity by the extended family characteristics

As the early years are crucial for individuals' lifelong socioeconomic success, extensive research has examined the impact of non-maternal childcare on children's development. This study aims to enhance the understanding of the relationship between grandparental involvement (defined as grandparent childcare, frequency of contact, and financial support) and grandchildren's school grades, exploring a mechanism of positive selection: children from extended families with specific socioeconomic characteristics are more likely to spend time with grandparents and benefit the most from this involvement.We utilize data from the German Pairfam survey, which uniquely provides rich information on three family generations. By conducting a heterogeneous treatment effect analysis, we account for confounding factors associated with grandparental involvement and school performance that could bias our findings. For example, children from advantaged families could be more likely to spend time with grandparents and achieve better school grades. Additionally, this approach examines whether the effect of grandparental involvement systematically varies across children based on the extended family's characteristics. For example, children from advantaged families may benefit the most from spending time with grandparents who possess social, cultural, and cognitive resources conducive to their development.After accounting for confounding factors and heterogeneity, our analyses do not reveal a statistically significant effect of grandparental investment on children's school grades. The study concludes by discussing possible reasons for this result and highlighting the implications for the intergenerational transmission of inequality.

Impact of heterogenous capabilities on export performance amid the digital transformation

We investigate the effects of adopting digital technology on export performance of Korean manufacturing firms amidst the digital transformation. We recognize firm-level capabilities should be closely associated with adoption of rapidly progressing digital technology but also with export performance. And our data indicates that the most common purpose of digital technology adoption is to launch new products to the market. Hence, we consider that technology adoption is a strategic and purposeful decision to gain competitive edge mostly by producing new product, and treating technology adoption exogenous can be misleading. Due to the endogeneity and selection issues in technology adoption, the endogenous switching regression is applied to this study as Coad et al. (2020). On technology adoption decision, we find external innovative resources from strategic alliance in addition to internal innovative capabilities stand out. Given technology adoption decision, internal capabilities like patent rights and international affiliation are complementary factors to export growth. The treatment effect analysis has implications as follows: the result on contribution of technology adoption to export growth for actually adopting firms is rather small, and shows heterogenous innovation, organizational, and external capabilities are still critical factors as much as new products embedding high-end digital technology; the result on non-adopting firms indicates potential of advanced digital technology to improve export performance by helping to produce such new products if they were actually capable to do it. In sum, our findings provide another evidence that structurally positive interaction between innovative activities and export performance as Aw et al. (2011), since adoption of digital technology to products itself is innovative in the digital transformation. Furthermore, the result is consistent with the capability theory in that heterogenous innovative and complementary capabilities determine strategic technology adoption and export performance simultaneously. Finally, our findings indicate that the digital transformation might be still at the early stage. The fact that Korean firms have adopted advanced digital technology mainly for new products can be interpreted as an indicator of early development stage of transformation, since firms concentrate on product innovation than process innovation to gain competitive edge at the early stage (Utterback and Abernathy, 1975). Thus, we expect that further evolution of digital transformation can facilitate process innovation, then contribute to firm performance by improving cost efficiency that should be tackled in the upcoming study.

Design of explosively welded Fe–Al multilayer laminated composite pipes: A critical microscopy analysis of stand-off distance and post-weld heat treatment effects on interface properties

This study examined the microstructure and mechanical properties of explosively welded (EXW) Fe–Al multilayer laminated composite pipes, specifically SS321/AA1050/AA5083, with varying stand-off distances (SD) and post-weld heat treatments (PWHT). Findings revealed that higher collision forces at higher-SD produced a wavy interface with finer grains at the AA1050/AA5083 interface. In contrast, lower-SD yielded a smooth, flat interface. At the SS321/AA1050 interface, collision energy resulted in the formation of an uneven composite reaction layer comprising multiple intermetallics. Analysis of the SS321/AA1050 interface revealed that an increase in the PWHT temperature results in diffusion toward the reaction layer, transforming the unevenly Al-rich and Fe-rich phases into a uniform Al85(Fe,Cr,Ni)15 solid solution. The increase in the fraction of this phase made the reaction layer more brittle. At the AA1050/AA5083 interface, PWHT at higher temperatures caused a significant hardness decline extending further from the interface in samples with higher-SD. On the SS321 side of the laminated composite, higher SD resulted in higher kernel average misorientation (KAM) and increased hardness. Despite a decrease in hardness after PWHT at 350 °C, the hardness gradient from the matrix to the interface in laminates with higher SD remained relatively unaffected, whereas the lower SD counterparts experienced a noticeable stress relief.

Safety and Effectiveness Analysis of Endovascular Treatment versus Standard Medication Treatment in Patients with Progressive Acute Ischemic Stroke with Large Vessel Occlusion Stroke in the Ultra-Late Time Window: A Propensity Score Matched Cohort Study

The time from onset to symptom deterioration in ischemic stroke often exceeds 24hours, and this ultra-late time window is excluded from the endovascular treatment (EVT) guideline. This study aimed to explore the safety and efficacy of EVT in progressive acute ischemic stroke with large vessel occlusion stroke patients with onset to symptom deterioration times of 24 hours-7days. Progressive stroke patients with time window of 24 hours-7days treated at our hospital over the past 6years were retrospectively collected. Patients were categorized into EVT and standard medication treatment (SMT) groups based on the treatment approach. Patients were matched using propensity score matching. Safety outcomes primarily included 3-month mortality and symptomatic intracranial hemorrhage; efficacy outcome primarily included functional independence (3-month modified Rankin scale≤2). A total of 396 patients were included in the study, with 86 (21.7%) in EVT and 310 (78.3%) in SMT group. There were 140 remaining after propensity score matching, with 70 in each group (50%). Compared to SMT group, EVT group had higher functional independence (52.9% vs. 15.7%, odds ratio [OR]=7.504, 95% confidence interval [CI] 2.141-14.093, P < 0.001) and lower 3-month mortality (14.3% vs. 40.0%, OR=0.412, 95% CI 0.099-0.856, P < 0.001). EVT was also associated with higher symptomatic intracranial hemorrhage (25.7% vs. 5.7%, OR=9.926, 95% CI 1.874-36.547, P < 0.001). For patients with progressive acute ischemic stroke with large vessel occlusion in the ultra-late time window, EVT remains a viable treatment approach.

Primary care payment models and avoidable hospitalizations in Ontario, Canada: A multivalued treatment effects analysis.

Improving access to primary care physicians' services may help reduce hospitalizations due to Ambulatory Care Sensitive Conditions (ACSCs). Ontario, Canada's most populous province, introduced blended payment models for primary care physicians in the early- to mid-2000s to increase access to primary care, preventive care, and better chronic disease management. We study the impact of payment models on avoidable hospitalizations due to two incentivized ACSCs (diabetes and congestive heart failure) and two non-incentivized ACSCs (angina and asthma). The data for our study came from health administrative data on practicing primary care physicians in Ontario between 2006 and 2015. We employ a two-stage estimation strategy on a balanced panel of 3710 primary care physicians (1158 blended-fee-for-service (FFS), 1388 blended-capitation models, and 1164 interprofessional team-based practices). First, we account for the differences in physician practices using a generalized propensity score based on a multinomial logit regression model, corresponding to three primary care payment models. Second, we use fractional regression models to estimate the average treatment effects on the treated outcome (i.e., avoidable hospitalizations). The capitation-based model sometimes increases avoidable hospitalizations due to angina (by 7 per 100,000 patients) and congestive heart failure (40 per 100,000) relative to the blended-FFS-based model. Switching capitation physicians into interprofessional teams mitigates this effect, reducing avoidable hospitalizations from congestive heart failure by 30 per 100,000 patients and suggesting better access to primary care and chronic disease management in team-based practices.

Effectiveness, Utility, and Economic Analysis of Three-drug Treatment vs Two-drug Treatment in Chronic Obstructive Pulmonary Disease Patients

Effectiveness, Utility, and Economic Analysis of Three-drug Treatment vs Two-drug Treatment in Chronic Obstructive Pulmonary Disease Patients

A Longitudinal Treatment Effect Analysis of Antipsychotics on Behavior of Residents in Long-Term Care

ObjectiveThe proportion of long-term care (LTC) residents being treated with antipsychotic medication is high, and these medications may exacerbate behavioral symptoms. We used propensity scores to investigate the effect of antipsychotic use on the worsening of behavioral symptoms among residents in LTC facilities. DesignA retrospective study. Setting and participantsResidents in LTC in 8 provinces and 1 territory in Canada, without severe aggressive behavior at baseline and reassessed at follow-up, between March 2000 and March 2022. MethodsWe used propensity score matching and weighting to balance baseline covariates and logistic regression to estimate the effect of antipsychotics on the worsening of behavioral symptoms in the original, matched, and weighted cohorts. The treatment variable was use of antipsychotic medication at baseline and the outcome was worsening of behavior at follow-up. ResultsA total of 494,215 participants were included [318,234 women and 175,981 men; mean age 82.8 years (SD 10.1; range 18–112)].130 558 (26.4%) used antipsychotics at baseline and 88,632 (17.9%) had worsening behavior in follow-up. In the matched cohort, there were 249,698 participants, and 124,849 were matched (1:1) in each treatment group. There was a significant association between antipsychotic use at baseline and worsening in behavior at follow-up in the adjusted regression models [OR 1.27 (95% CI 1.25–1.29), <0.0001] as well as in matched [OR 1.20 (95% CI 1.17–1.21), <0.0001] and weighted [OR 1.26 (95% CI 1.24–1.28), <0.0001] cohorts. Conclusions and implicationsThis study further evidence to support the cautious use of antipsychotics in LTC facilities. Future research in LTC facilities could include a more granular analyses of behavior change, including bidirectional analyses between different symptom severity classifications.

Treatment effect analysis of the Frailty Care Bundle (FCB) in a cohort of patients in acute care settings

PurposeThe aim of this study is to explore the feasibility of using machine learning approaches to objectively differentiate the mobilization patterns, measured via accelerometer sensors, of patients pre- and post-intervention.MethodsThe intervention tested the implementation of a Frailty Care Bundle to improve mobilization, nutrition and cognition in older orthopedic patients. The study recruited 120 participants, a sub-group analysis was undertaken on 113 patients with accelerometer data (57 pre-intervention and 56 post-intervention), the median age was 78 years and the majority were female. Physical activity data from an ankle-worn accelerometer (StepWatch 4) was collected for each patient during their hospital stay. These data contained daily aggregated gait variables. Data preprocessing included the standardization of step counts and feature computation. Subsequently, a binary classification model was trained. A systematic hyperparameter optimization approach was applied, and feature selection was performed. Two classifier models, logistic regression and Random Forest, were investigated and Shapley values were used to explain model predictions.ResultsThe Random Forest classifier demonstrated an average balanced accuracy of 82.3% (± 1.7%) during training and 74.7% (± 8.2%) for the test set. In comparison, the logistic regression classifier achieved a training accuracy of 79.7% (± 1.9%) and a test accuracy of 77.6% (± 5.5%). The logistic regression model demonstrated less overfitting compared to the Random Forest model and better performance on the hold-out test set. Stride length was consistently chosen as a key feature in all iterations for both models, along with features related to stride velocity, gait speed, and Lyapunov exponent, indicating their significance in the classification.ConclusionThe best performing classifier was able to distinguish between patients pre- and post-intervention with greater than 75% accuracy. The intervention showed a correlation with higher gait speed and reduced stride length. However, the question of whether these alterations are part of an adaptive process that leads to improved outcomes over time remains.

Radiomic Analysis of Treatment Effect for Patients with Radiation Necrosis Treated with Pentoxifylline and Vitamin E.

The combination of oral pentoxifylline (Ptx) and vitamin E (VitE) has been used to treat radiation-induced fibrosis and soft tissue injury. Here, we review outcomes and perform a radiomic analysis of treatment effects in patients prescribed Ptx + VitE at our institution for the treatment of radiation necrosis (RN). A total of 48 patients treated with stereotactic radiosurgery (SRS) had evidence of RN and had MRI before and after starting Ptx + VitE. The radiation oncologist's impression of the imaging in the electronic medical record was used to score response to treatment. Support Vector Machine (SVM) was used to train a model of radiomics features derived from radiation necrosis on pre- and 1st post-treatment T1 post-contrast MRIs that can classify the ultimate response to treatment with Ptx + VitE. A total of 43.8% of patients showed evidence of improvement, 18.8% showed no change, and 25% showed worsening RN upon imaging after starting Ptx + VitE. The median time-to-response assessment was 3.17 months. Nine patients progressed significantly and required Bevacizumab, hyperbaric oxygen therapy, or surgery. Patients who had multiple lesions treated with SRS were less likely to show improvement (p = 0.037). A total of 34 patients were also prescribed dexamethasone, either before (7), with (16), or after starting (11) treatment. The use of dexamethasone was not associated with an improved response to Ptx + VitE (p = 0.471). Three patients stopped treatment due to side effects. Finally, we were able to develop a machine learning (SVM) model of radiomic features derived from pre- and 1st post-treatment MRIs that was able to predict the ultimate treatment response to Ptx + VitE with receiver operating characteristic (ROC) area under curve (AUC) of 0.69. Ptx + VitE appears safe for the treatment of RN, but randomized data are needed to assess efficacy and validate radiomic models, which may assist with prognostication.

Comparison of perioperative bleeding risk between direct oral anticoagulants in transurethral resection of prostate.

To evaluate the perioperative morbidity and mortality associated with direct oral anticoagulants (DOACs) and warfarin for patients receiving transurethral resection of prostate (TURP). This was a single-centre, retrospective cohort analysis of patients who underwent TURP for benign prostate hyperplasia from April 2019 to December 2023. The primary objective was to evaluate the perioperative bleeding and thromboembolic risk between anticoagulated (AC) vs no-AC patients. The secondary objective was to evaluate perioperative bleeding and thromboembolic risk between different formulations of DOACs. Patient demographics, prior treatment, prostate size, baseline bleeding risk, and operative details were collected. Bleeding and thromboembolic-related morbidity were captured within a 3-month postoperative period. Perioperative management of AC therapy was recorded, and all patients had their AC therapy withheld. Cohort characteristic between the AC vs no-AC, and DOAC groups were analysed with two-sided t-test, and chi-square test. Further logistic regression analyses were carried out to identified significant variables between the groups. These significant variables were used for adjustment in inverse probability-weighted treatment effect analysis to evaluate bleeding risk. There were 629 patients in the cohort, and 113 (18%) patients were receiving AC therapy. The AC patients were at 1.6 times statistically significant increased risk of acute bleeding, and 11 times increased risk of prolonged haematuria for >14 days. When compared to apixaban, patients on rivaroxaban conferred a statistically significant increased risk of acute bleeding by 2.21 times. Patients receiving AC therapy had a statistically significant increased risk of stroke in the perioperative setting (no-AC vs AC: 0.4% vs 2.7%, P = 0.01). This is the first study to evaluate risk of bleeding for TURP patients receiving DOACs. The AC patients are more likely to experience haematuria and stroke in the perioperative period despite withholding therapy. Apixaban appears to cause less bleeding-related complications than rivaroxaban.

Exploring the mechanism of path-creating strategy for latecomers: a combined approach of econometrics and causal machine learning

In this paper, the traditional econometrics method and causal machine-learning method are combined to study the mechanism of a path-creating strategy of latecomers to influence latecomers’ catch-up performance. A total of 283 high-tech manufacturing enterprises listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2019 were selected for the study. OLS linear regression model verifies that path-creating has a positive impact on latecomers’ technological catch-up performance, technological capability plays an intermediary role between path-creating and technology catch-up performance, technological innovation appropriability positively moderates the effect of path-creating on technological capability, and technological innovation cumulativeness negatively moderates the effect of path-creating on technological catch-up but positively moderate the effect of technological capability on catch-up performance. Through machine learning, on the one hand, a conclusion basically consistent with the linear regression model is obtained, but on the other hand, a more heterogeneous situation is presented. Through analyses of the individual treatment effect of a path-creating strategy of latecomers, the Shapley value graph shows the complex influence of different features on the treatment effect of the enterprise using the path-creating strategy. Through the decision tree, some more complex patterns are found. In addition, the decision tree model based on causal analysis can also assist enterprises in making strategic decisions.

Head-to-head studies on psoriasis and psoriatic arthritis

Given the ever-increasing number of approved therapies for the treatment of psoriasis (PsO) and psoriatic arthritis (PsA), head-to-head (H2H) comparative studies are essential. These are aimed primarily at acomparative analysis of treatment effectiveness. In both PsO and PsA, biological disease-modifying antirheumatic drugs (bDMARD) have been shown to be superior to conventional therapies in H2H studies. In PsO interleukin 17 (IL-17) and IL-23 inhibitors proved superiority compared to tumor necrosis factor (TNF) inhibitors (etanercept and adalimumab) in several studies. Ustekinumab was more effective than etanercept, but less effective than IL-17 and IL-23 inhibitors. Only afew H2H studies have been published on the treatment of PsA. In the Spirit H2H study ixekizumab was superior to adalimumab using acombined endpoint of arthritis and psoriasis response (ACR-50 and PASI-100). When looking at arthritic symptoms only (ACR-20), secukinumab was not significantly superior to adalimumab in the EXCEED study but was superior in terms of the effect on skin involvement (PASI90). Other H2H studies focused on the treatment of enthesitis (ECLIPSA study), the efficacy of Janus kinase (JAK) inhibition (SELECT-PSA-1) or the additional administration of methotrexate to bDMARD treatment (MUST study). The H2H data have been incorporated into the treatment guidelines and have led to IL-17 and IL-23 inhibition being preferred over TNF inhibition in cases of relevant skin involvement in PsA.