Methods Applied to Assess Real-World Effectiveness of Drugs: A Scoping Review.

BackgroundDespite the interest in machine learning (ML) algorithms for analyzing real-world data (RWD) in healthcare, the use of ML in predicting time-to-event data, a common scenario in clinical practice, is less explored. ML models are capable of algorithmically learning from large, complex datasets and can offer advantages in predicting time-to-event data. We reviewed the recent applications of ML for survival analysis using RWD in healthcare.MethodsPUBMED and EMBASE were searched from database inception through March 2023 to identify peer-reviewed English-language studies of ML models for predicting time-to-event outcomes using the RWD. Two reviewers extracted information on the data source, patient population, survival outcome, ML algorithms, and the Area Under the Curve (AUC).ResultsOf 257 citations, 28 publications were included. Random survival forests (N = 16, 57%) and neural networks (N = 11, 39%) were the most popular ML algorithms. There was variability across AUC for these ML models (median 0.789, range 0.6–0.950). ML algorithms were predominately considered for predicting overall survival in oncology (N = 12, 43%). ML survival models were often used to predict disease prognosis or clinical events (N = 27, 96%) in the oncology, while less were used for treatment outcomes (N = 1, 4%).ConclusionsThe ML algorithms, random survival forests and neural networks, are mainly used for RWD to predict survival outcomes such as disease prognosis or clinical events in the oncology. This review shows that more opportunities remain to apply these ML algorithms to inform treatment decision-making in clinical practice. More methodological work is also needed to ensure the utility and applicability of ML models in survival outcomes.

Real-world data on herb-drug interactions in oncology: A scoping review of pharmacoepidemiological studies

Emerging evidence links metabolic dysfunction-associated fatty liver disease (MAFLD) with increased all-cause and circulatory system disease (CSD) mortality in adults, yet survival machine learning studies are limited. This study analyzed 4415 NHANES participants with MAFLD to predict mortality using five survival models, and further, the optimal models were selected to identify the most significant predictors of mortality. Machine learning models proved highly effective in prediction. The Gradient Boosted Survival (GBS) model performed best for all-cause mortality, while Extra Survival Trees (EST) excelled for CSD mortality. The Shapley Additive Explanations (SHAP) analyses revealed that the five clinical factors most strongly associated with all-cause mortality were age, gender, platelet count, high-density lipoprotein cholesterol, and smoking status. For CSD mortality, the key factors associated with increased risk were age, blood urea nitrogen, systolic blood pressure, history of heart attack, and gender. Subgroup analyses confirmed GBS and Cox proportional hazard (CoxPH) were optimal for middle-aged and older all-cause mortality, whereas Elastic Net-regularized Cox proportional hazard (CoxNet) was best for older CSD mortality. The findings demonstrate that survival machine learning models effectively predict mortality risk in MAFLD patients. Integrating these models with permutation importance and SHAP provides transparent insights into individual risk profiles, enabling clinicians to clearly interpret how key variables contribute to predictions and improve risk stratification.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-26729-z.

650 Background: Randomized controlled trials (RCTs) are the basis of approval for medical interventions, but may not fully reflect populations seen in clinical practice. Sunitinib is a widely used 1st-line treatment for patients (pts) with metastatic renal cell carcinoma (mRCC). This is the first large-scale meta-analysis to evaluate the efficacy of sunitinib using the novel approach of combining RCTs and real-world data (RWD). Methods: PubMed, Ovid, MEDLINE and EMBASE were searched from 2000-2017 for RCTs and RWD studies of sunitinib as 1st-line treatment in pts with mRCC. Eligible studies contained a cohort of ≥50 adult pts per study arm. The meta-analysis combined RWD and RCT study arms, adjusting for data type (RCT or RWD). Recorded outcomes were: median progression-free survival (mPFS), median overall survival (mOS) and objective response rate (ORR). A random effects model to account for study heterogeneity was applied to each endpoint. Sensitivity analyses evaluated the robustness of the overall estimate. Results: Of the studies that met eligibility criteria, mPFS, mOS and ORR were reported by 18, 19 and 15 studies, respectively. Combined RWD and RCT analyses are presented in the Table. Reported mPFS (RWD, 7.5–11.0; RCTs, 5.6–15.1 months) and ORR data (RWD, 14.0–34.6%; RCTs, 18.8–46.9%) were consistent with the overall estimates. Reported mOS showed greater variation in RWD (6.8–33.2 months) compared with RCTs (21.8–31.5 months). Sensitivity analyses showed no evidence of lack of robustness for mPFS, mOS or ORR. Interpretation of these results is limited by differences in trial design and cohort characteristics. Conclusions: This novel, large-scale meta-analysis validates sunitinib as an effective 1st-line treatment for pts with mRCC in both RCTs and everyday clinical practice. [Table: see text]

Reconciling and Closing the Loop Between Evidence-Based and Practice-Based Medicine: The Case for Hemodiafiltration.

Udgivelsesdato: 2010-Nov

Aims This study aims to investigate associations between attendance in religious service at least once during the past year and all-cause and cause-specific mortality. Study design: Prospective cohort study design. Methods A public health survey conducted by Region Skåne in southern Sweden in the autumn of 2008 was sent to a stratified random sample of the adult 18-80 year population with a participation rate of 54.1%. A total of 24,855 participants were included in the present study. The baseline survey was connected to prospective mortality data with 8.3-year follow-up. Analyses were conducted in survival (Cox regression) models. Results A total 14% had attended religious service at least once during the past year, while 86% were non-attenders. The religious service attenders were women, high and medium position non-manual employees, born outside Sweden, never alcohol consumers and participants with high generalized trust to a higher extent than non-attenders. They also displayed lower proportions with daily smoking and low physical activity compared to non-attenders. The group of religious service attenders had significantly lower hazard rate ratios (HRRs) of all-cause mortality compared to non-attenders in all multiple models. Cardiovascular (CVD) mortality was significantly lower for religious service attenders in the multiple models until BMI, physical activity, daily smoking and alcohol consumption were entered in the survival model. No significant results for cancer and other cause mortality were found. Conclusions Religious service attendance in Sweden, a highly secularized and individualized high-income country, is significantly associated with lower all-cause mortality. This may to some extent be by explained lower CVD mortality partly mediated by protective health-related behaviors. Key messages • Religious service attendance and health has mostly been investigated in the USA, and much less in more secularized countries like Sweden. • Religious service attendance was associated with lower all-cause and CVD mortality, partly mediated by protective health-behaviors.

BackgroundRandomized controlled trials (RCTs) have stringent inclusion criteria and may not fully represent patients seen in everyday clinical practice. Real-world data (RWD) can provide supportive evidence for the effectiveness of medical interventions in more heterogeneous populations than RCTs. Sunitinib is a widely used first-line treatment for patients with metastatic renal cell carcinoma (mRCC).ObjectiveThis is the first comprehensive meta-analysis to evaluate the efficacy of sunitinib using the novel approach of combining RCTs and RWD.MethodsRCTs and RWD studies published between 2000 and 2017 were identified from PubMed, Ovid, MEDLINE, and EMBASE. Eligible studies contained a cohort of ≥ 50 adult patients with mRCC receiving first-line sunitinib treatment. The meta-analysis combined RWD and RCT treatment groups, adjusting for data type (RCT or RWD). Recorded outcomes were median progression-free survival (mPFS), median overall survival (mOS), and objective response rate (ORR). Publication bias was assessed via review of funnel plots for each outcome measure. A random effects model to account for study heterogeneity was applied to each endpoint. Sensitivity analyses evaluated the robustness of the overall estimates.ResultsOf the 3611 studies identified through medical database searches, 22 (15 RWD studies, 7 RCTs) met eligibility criteria and were analyzed. mPFS (18 studies), mOS (19 studies), and ORR (15 studies) were reported for aggregate measures based on 4815, 5321, and 4183 patients, respectively. Reported mPFS (RWD, 7.5–11.0 months; RCTs, 5.6–15.1 months) and ORR data (RWD, 14.0–34.6%; RCTs, 18.8–46.9%) were consistent with the overall confidence estimates (95% confidence interval [CI]) of 9.3 (8.6–10.2) months and 27.9% (24.2–32.0), respectively. Reported mOS showed greater variation in RWD (6.8–33.2 months) compared with RCTs (21.8–31.5 months), with an overall confidence estimate (95% CI) of 23.0 (19.2–27.6) months. Inspection of funnel plots and sensitivity analyses indicated that there was no publication bias for any efficacy endpoint. Sensitivity analyses showed no evidence of lack of robustness for mPFS, mOS, or ORR. Interpretation of these results is limited by differences in trial design, cohort characteristics, and missing data.ConclusionsThis novel, comprehensive meta-analysis validates sunitinib as an effective first-line treatment for patients with mRCC in both RCTs and everyday clinical practice. The methodology provides a framework for future analyses combining data from RCTs and RWD.Electronic supplementary materialThe online version of this article (10.1007/s11523-019-00653-5) contains supplementary material, which is available to authorized users.

Managing critically ill patients requires specific skills, yet little is known about how teaching occurs during real-time resuscitations. This scoping review aimed to summarize and map how teaching during real-time resuscitation has been described and conceptualized in the literature, to inform emergency physician clinician-educators and to identify gaps in this area. We searched 6 databases from inception to April 2025 and hand-searched abstracts from 10 conferences held in the past 7years. Backward and forward citation searches were performed. Eligible studies described a teaching interaction involving a medical learner (any level) and an actual critically ill patient in a hospital-based setting. No restrictions were applied based on publication type. Included eligible empirical studies were appraised using the Mixed Methods Assessment Tool. Using descriptive qualitative content analysis, we inductively and iteratively developed categories through team discussion to organize how teaching during resuscitation has been reported in the literature. A total of 25,530 titles and abstracts were screened. Full-text review of 242 articles yielded 13 included records, with 8 additional identified through reference screening, forward searching, and conference material review. Resuscitations most commonly occurred in the emergency department (n = 8) or the intensive care unit (n = 4). Learners were primarily residents (n = 17) or fellows (n = 7). Appraisal of 10 empirical studies showed heterogeneous quality. Twenty-three teaching strategies were described. Three categories emerged from the analysis: (1) teaching adapted to learners' level of involvement during the resuscitation, (2) supervisor practices, and (3) ethical considerations shaping teaching during resuscitation. This scoping review summarizes and maps how teaching during real-time resuscitation has been described and conceptualized in the literature. It highlights reported strategies that emergency physicians may consider adapting in clinical practice while also underscoring the paucity of empirical work in this underexplored area.

Relation of Thoracic Aortic Distensibility to Left Ventricular Area (from the Multi-Ethnic Study of Atherosclerosis [MESA

FRI0037 ALL-CAUSE MORTALITY IN EARLY RHEUMATOID ARTHRITIS PREDICTED BY HEALTH ASSESSMENT QUESTIONNAIRE AT ONE YEAR

The internet has become an everyday tool to communicate and network with people around the globe, but its perceived anonymity, availability, and instant access have made it an environment conducive to spreading hateful content and connecting to like-minded individuals with similar hateful ideologies. Hate speech and other prejudice-motivated behavior, however, need to be considered on a continuum of victimization, and "like other social processes, [be seen as] dynamic and in a state of constant movement and change, rather than static and fixed" (Bowling, 1993, p. 238). It is a social process that is marked by multiple, repeat, and constant victimization (Bowling, 1993), with victims no longer distinguishing between specific hateful events, and rather normalizing experiences of hateful conduct "as an everyday, unwanted but routine reality of being 'different'" (Chakraborti, 2016, p. 581). Understanding hateful behavior and victimization as a process allows us to connect "low-level" incidents of hateful behavior to the more serious and life-threatening incidents at the more extreme end of the spectrum (Bowling & Phillips, 2002). The Christchurch attacks in New Zealand and their link to hateful communication on the online platform 8chan is only one such example of how online hate speech and cyberhate can escalate to "in real life" attacks, leaving the online sphere and spilling into the offline world. As per Allport's (1954) scale of prejudice, more extreme forms of prejudice-motivated violence are founded on "lower level" acts of prejudice and bias, therefore, hateful content online should not be ignored. Intervening online to interrupt or counter hateful behavior already at the lower end of the scale of prejudice becomes important; online interventions which are to be identified and synthesized through this systematic review. Allport's (1954) scale of prejudice will be the basis for this systematic review. Early on, Allport (1954) asserted that individuals with negative attitudes toward groups are likely to act out on these prejudices "somehow, somewhere" (p. 14), and that the more intense such negative attitudes are, the more hostile the action will be. Allport (1954) put forward a scale of acts of prejudice to illustrate different degrees of acting out negative attitudes, a scale that starts with antilocution (or what we call hate speech), described as explicitly expressing prejudices through negative verbal remarks to either friends or strangers (Allport, 1954). Avoidance is the next level on the scale of prejudice, with people avoiding members of certain groups, followed by discrimination, where distinctions are made between people based on prejudices, which leads to the active exclusion of members from certain groups (Allport, 1954). This level of acting on prejudices is routed in institutional or systemic prejudices, for example, in the differential treatment of people within employment or education practices, but also within the criminal justice system, or through social exclusion of certain minority group members. Physical attack is the next level on the scale of prejudice, which includes violence against members of certain groups by physically acting on negative attitudes or prejudices. The last level is extermination, which is the ultimate act of violence against members of specific groups, an expression of prejudice that systematically eradicates an entire group of people (e.g., genocide or lynchings; Allport, 1954). Allport's (1954) scale of prejudice makes it clear how hate speech/cyberhate is connected to more extreme forms of violence motivated by specific prejudices and biases, with hate speech (or antilocutions) being only the starting point on a 5-point continuum (Bilewicz & Soral, 2020). The importance of this scale of prejudice is not only that it clearly illustrates a range of different ways and intensity levels to act out prejudices, but also the "progression from verbal aggression to physical violence or, in other words, the performative potential of hate speech" (Allport, 1954; Kopytowska & Baider, 2017, p. 138). This is where interventions at the lower level of the scale of prejudices, interventions targeting hate speech/cyberhate, become important. There is no universal definition of hateful conduct online, but there is some consensus that hate speech targets disadvantaged social groups (Jacobs & Potter, 1998). Bakalis (2018) more narrowly defines cyberhate as "any use of technology to express hatred towards a person or persons because of a protected characteristic—namely race, religion, gender, sexual orientation, disability and transgender identity" (p. 87). Another definition that also points out the ambiguity and challenges involved with identifying more subtle forms of hate speech, and also making reference to the potential threat of hate speech escalating to offline violence, is that put forward by Fortuna and Nunes (2018), who analyzed various definitions of hate speech "Hate speech is language that attacks or diminishes, that incites violence or hate against groups, based on specific characteristics such as physical appearance, religion, descent, national or ethnic origin, sexual orientation, gender identity or other, and it can occur with different linguistic styles, even in subtle forms or when humour is used" (p. 5). In this systematic review, we also distinguish hate speech/cyberhate specifically from other forms of harmful online activity, such as cyber-bullying, harassment, trolling or flaming, as perpetrators of such online behavior repeatedly and systematically target specific individuals to cause upset, to seek out negative reactions, or to create discord on the internet. In contrast, hate speech/cyberhate is more general and does not necessarily target a specific individual (Al-Hassan & Al-Dossari, 2019), instead hate speech/cyberhate heavily features prejudice, bias and intolerance toward certain groups within society. With the majority of hate speech happening online, interventions that take place online are an important way to challenge prejudice and bias, potentially reaching masses of people across the globe. The unique feature of the internet is that such individual negative attitudes toward minority groups and more extreme hateful ideology can find its way onto certain platforms and can instantly connect people sharing similar prejudices. By closing the social and spatial distance, the internet creates a form of collective identity (Perry, 2000, p. 123) and can convince individuals with even the most extreme ideologies that others out there share their views (Gerstenfeld et al., 2003). In addition, the enormous frequency of hate speech/cyberhate within online environments creates a sense of normativity to hatred and the potential for acts of intergroup violence or political radicalization (Bilewicz & Soral, 2020, p. 9). It is, therefore, important to challenge this hate speech epidemic (Bilewicz & Soral, 2020), especially since hate movements have increasingly crossed into the mainstream (Perry, 2000). With hate speech/cyberhate posing a threat to the social order by violating social norms (Soral et al., 2018), perceptions of social norms as either supporting or opposing prejudice has been found to have an influence on how individuals react online (Hsueh et al., 2015). Seeing other people post prejudiced (opposed to antiprejudiced) comments online can lead to the adoption of an online group's biases and can influence an individual's own perceptions and feelings toward the targeted stigmatized group (Hsueh et al., 2015). In addition, research around desensitization also suggests that being exposed to hate speech leads to desensitization, which further leads to an increase in outgroup prejudice toward groups targeted by such speech (Soral et al., 2018). With society increasingly recognizing that it is inappropriate to express prejudices in public settings, many interventions will include some form of social norms nudging to reduce such prejudices; interventions that "nudge behavior in the desired direction" (Titley et al., 2014, p. 60). Therefore, hate speech not only affects minority group members, but also has an influence on opinions of majority group members (Soral et al., 2018), which makes strategies that can elicit change in people's prejudice-related attitudes crucial (see, e.g., Zitek & Hebl, 2007). Governments around the world face increased demand for understanding and countering hateful ideology and violent extremism both online and offline (e.g., the Christchurch Call in New Zealand). The U.S. Government's 2011 CVE Strategy highlights the importance of ongoing research and analysis, the sharing of knowledge and best practices internationally, and the countering of hateful ideologies and propaganda (see also Department of Homeland Security, 2016, 2019). The goal of this systematic review is to use an integrated and interdisciplinary approach to examine the effectiveness of online campaigns and strategies for reducing hate speech and cyberhate. The internet also provides an opportunity to reach masses of people who have been exposed to hateful content and ideology online, therefore, this systematic review will focus on online interventions addressing online hate speech and cyberhate. The specific settings where we would expect to see the online interventions deployed will be on websites, text messaging applications, and online and social media platforms including, but not limited to, Facebook, Instagram, TikTok, WhatsApp, Google, YouTube, and Snapchat. As mentioned previously, many online interventions will be based on social norm nudges to reduce online hate. These interventions aim to change people's online behavior and encourage individuals or groups to conform to established social norms. The communication of social norms can happen through establishing community standards on online platforms themselves (e.g., Facebook, Twitter, etc.), through more formal online training courses, or through anti-hate speech/anti-cyberhate campaigns teaching people to recognize hate, embrace diversity, and stand up to bias. Such prevention campaigns are designed to challenge bias and build ally behaviors by supplying people with constructive responses to combat, for example, antisemitism racism, and homophobia, as well as provide resources to help people explore and critically reflect on current events. Other interventions may add messages to hateful online comments, counter hateful content or extremist ideology, or redirect people to more credible sources. Both peers and parents have been found to foster racial consciousness and identity development, define interracial relationships and cultivate ethnic heritage and culture (Hagerman, 2016). Socialization influences how children understand their group's social position and their membership within that group by providing an understanding of racial, religious, and sexual privilege (Bowman & Howard, 1985). Socialization often reflects peers' and parents' experiences with racism, discrimination, and their ideological perspectives about race, religion, or sexuality (Umaña-Taylor & Fine, 2004). This is important because peers and parents who feel discriminated against or believe that the "other" is a threat may impart their prejudices to their children or friends, which could lead them to interpret the social world with similar discriminatory views and/or behavior. Individuals who feel socially alienated or rejected are especially vulnerable to such socialization practices as they feel that adopting these views will provide them with a sense of acceptance and belonging (Leiken, 2012). Regardless of how an individual develops certain racial, religious, or sexual biases, the online interventions under review are expected to target and reduce the production of original hateful content such as antisemitic Tweets and/or homophobic blog posts as well as the consumption of hate speech material (e.g., watching or reading hate speech videos or blogs). For example, some interventions take a rather broad messaging approach by implementing racial sensitivity and diversity training through Public Service Announcements, peer-to-peer dialogue workshops, or films that provide opportunities for youth and adults to self-reflect and learn about historical oppression, people of color, women, and the LGBTQIA+ community from credible sources. The factual understanding of diverse groups is often supplemented by experiences with people within the group. These educational programs often identify a cultural guide who is willing to introduce youth to new experiences and who can aid in processing thoughts, feelings, and behaviors. These interventions intend to dispute and contradict negative stereotypes associated with specific cultures, people, and institutions by sharing different points of view based on human rights values such as openness, respect for difference, freedom, and equality (Gomes, 2017). Moreover, such interventions tend to involve blanket bans on specific behaviors enforced through the public promotion of norms or individual sanctions enforced by moderators. Other interventions, such as the "Redirect Method," are narrower in their messaging. These interventions generate curated playlists and collections of authentic content that challenge hate speech/cyberhate narratives and propaganda (Helmus & Klein, 2018). For instance, people who are directly searching for extremist content online may be linked to videos and written content that confronts such claims. These videos are designed to be objective in appearance instead of containing material that explicitly counters extremist propaganda. The underlying goal of this type of interventions is to provide credible content that effectively undermines extremist messaging but does not overtly attack the source of propaganda. In addition to confronting hate speech narratives, these interventions provide users with links to numerous social services such as anger management training, drug and alcohol treatment, and mental health resources. Online platforms, such as Twitter and Facebook, have also started to employ a similar method, redirecting people who comment on or share "fake news" or conspiracy theories, which often are fraught with prejudicial undertones and are harmful to minority groups, to more credible content and news sources. The aforementioned interventions are designed to counter-balance these biased perceptions (e.g., unsupported claims of the Black community as criminal or the LGBTQIA+ community as pathologized) Blacks as criminals, LGBTQIA+ as pathologized) by blunting the occurrence of racist discourse and reducing the likelihood these individuals will internalize and normalize racial, religious, and/or sexual prejudices (Qian et al., 2019). Being in new situations is uncomfortable and often awakens fears and apprehensions that can block our experiential development. Acquiring information or being exposed to minority-run businesses, poverty, and writings from minority authors allows a person to understand the thoughts, hopes, fears, and aspirations of the people outside their racial perspective rather than from the perspective of the majority society (Dunham et al., 2013; Lee et al., 2017). Doing so, counters racist programming by challenging hegemonic beliefs, which can lead to the acceptance of tolerant attitudes and the reduction of hateful expressions online. Findings from the proposed review will enhance our understanding of the effectiveness of online anti-hate speech/anti-hate interventions, will help ensure that programming funds are dedicated to the most-effective efforts, and will play a critical role in helping individual programs improve the quality of service provisions. It will inform governments and policymakers of the current state of such online efforts, what works and which modes of interventions to implement, and help guide economically viable investments in nation-state security. Our search of the scholarly literature identified one review, Blaya (2019), as similar to the proposed topic. Blaya's (2019) review, however, focused on the prevalence, type, and characteristics of existing interventions for counteracting cyberhate and did not include a meta-analysis. Two other similar reviews focused on exposure to extremist online content (Hassan et al., 2018) and communication channels associated with cyber-racism (Bliuc et al., 2018). A search of the Campbell Library using key terms (hate OR radical*) returned two protocols and one review identified for further inspection to assess potential overlap. The protocols include "Psychosocial processes and intervention strategies behind Islamist deradicalization: A scoping review" by de Carvalho et al. (2019) and "Police programs that seek to increase community connectedness for reducing violent extremism behavior, attitudes and beliefs" by Mazerolle et al. (2020). A further review on a similar topic is a recently completed Campbell review (January 2020), "Counter-narratives for the prevention of violent radicalization: A systematic review of targeted interventions" by Carthy et al. (2018) at the National University of Ireland, Galway. Our proposed review is distinguished from the de Carvalho et al. (2019) review in that we are focusing on hate speech and cyberhate generally without delimiting our approach to a specific type of radicalization (e.g., Islamist). Furthermore, we are electing to complete a systematic review and meta-analysis. Likewise, the protocol by Mazerolle et al. (2020) focuses on interventions involving police officers either as initiators, recipients, or implementers of community connectedness interventions. Our review will focus specifically on any online intervention, which may or may not involve police, but police will not be the focus nor be the basis of the online intervention strategy. Judging from Carthy et al. (2018) protocol, we anticipate our review will also capture counter-narrative interventions, but will differ based on setting, timing, and scope of interventions. Specifically, we are interested in online interventions that extend beyond counter-messaging campaigns to include a broad array of interventions outlined above and extend beyond radicalization to include everyday hate and prejudice. In addition to conducting a meta-analysis, the proposed review would build on Blaya's (2019) work by expanding the population parameters to include both adolescents as well as adults. Blaya (2019) limited her search to include interventions aimed toward youth, young people, children, young adults, adolescents, children, and teenagers and did not focus on extremism. The main objective of this review is to synthesize the available evidence on the effectiveness of online interventions aimed at reducing the creation and/or consumption of online hate speech/cyberhate material. To what extent are online interventions effective in reducing online hate speech/cyberhate? How is effectiveness related to the type of online hate speech/cyberhate intervention used? How is effectiveness related to the characteristics of individuals experiencing the online hate speech/cyberhate intervention (e.g., age, gender, race/ethnicity, offense history, childhood trauma)? Both experimental and quasi-experimental quantitative studies will be included. These study designs will address research questions #1 to #3. Eligible quantitative study designs include the following: Eligible experimental designs must involve random assignment of participants to distinct treatment and control group(s). Designs that involve quasi-random assignment of participants such as alternate case assignment are also eligible and will be coded as experimental designs. All eligible quasi-experimental designs must include a comparison group of participants compared to participants in the treatment condition. Eligible studies include those that report matching procedures (individual- or group-level) and statistical procedures employed to achieve equivalency between groups. Statistical procedures may but are not limited to, analysis, and Furthermore, in of a limited quantitative evidence we will also include quasi-experimental studies with comparison groups that provide of for both groups. will also be included. Eligible include designs with a control group and designs with or without a control group than quasi-experimental designs include studies that a comparison group of participants who either to in the study or who in a but out to the of a Eligible comparison include other online interventions or in which participants not or an online Both youth and participants of any gender sexual orientation, or will be eligible for this review. The eligible youth population will be study participants with a of through The eligible population will be study participants with a of and in which only a of the is eligible for example, a study in both online and offline hate speech be not anticipate studies based on as our will be and we will take to studies that only online interventions. will of the of a study for through and be we will elicit the of a the of and studies will be these studies will be they will be and be in the and any related Blaya's (2019) of intervention strategies to the potential of eligible interventions. The intervention is the of responses to hate speech/cyberhate, which includes the countering of violent extremism and to address online interventions that are eligible range from hateful content online specific (e.g., of social media to to online hate using targeted strategies (e.g., through hateful of studies focusing on online include the and of online and content online content and & 2018), hateful online comments to comments et al., 2018), and to users out of online are also interested in interventions such as the of 8chan this online platform linked to "in real life" attacks in New Zealand and the and interventions that further hateful online content and radicalization similar events. hateful content online such has up speech as well as around online users and hateful groups on to other online to hateful content online using targeted strategies therefore, been as an effective online include using the from & 2020), the use of to online responses to in online where hate speech has been (Qian et al., 2019), and redirecting online users to videos for example, Our systematic review will include a range of online interventions, many of which have only recently Two other strategies identified by Blaya (2019) are the and of hate speech/cyberhate using technology as well as the creation of online and These interventions include online counter-narrative the and/or use of online counter online interventions, online training, and online narrowly to address extremist ideologies and hate speech that incites targeted violence and In such interventions seek to or the occurrence of violent extremism or the of hate speech and extremist by channels and opportunities to such groups. The and intervention eligible for this systematic review educational programs for example, provide people with online and challenge 2019). will include online programs with an online (e.g., and and educational and online interventions. of these interventions may by individuals no longer in the creation and/or consumption of cyberhate and extremist material online. These online interventions may be by and internet service or or in the case of interventions. The comparison may be routine exposure and to hate speech/cyberhate or online The of is the creation and/or consumption of hateful content online. By we to the production and of original hateful content such as antisemitic racist and/or homophobic blog The consumption of hate speech material may include or being a of a hate watching or reading hate speech videos or being a target of online hate speech/cyberhate, or hate speech material. of include and of study participants such as and attitudes toward hate Eligible studies must report a or (or to be included. There will be no exclusion on the source of for the and can be from any institutional or completed by will include any of from strategies to increase the scale of of potentially effective anti-hate speech and interventions for These could include to or to the creation of and behaviors. can also include such as a of hate speech/cyberhate to other platforms instead of a reduction of hate All described in eligible studies will be in the will focus on the between and the current The starting with the when the internet to a and community et al., are for an approach in the lower end of our search to the may be it is hate speech/cyberhate online through or and some studies may capture Our population of studies will also be limited to studies in and but of studies completed in any as we are focused on online content that can be and across and nation-state The language parameters reflect the language of the review Our will where studies the of study in will be between the members of the review These will be and as a from the protocol in the review. 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Introduction: Circulating metabolites are associated with all-cause and cause-specific mortality. Cardiovascular disease (CVD) and cancer are two leading causes of mortality, providing complementary assessment of disease burden in addition to all-cause mortality. However, the role of urine markers in predicting the risk of mortality is understudied. Hypothesis: We hypothesize that urine metabolites are associated with all-cause, CVD, and cancer mortality. Methods: Using the Nightingale platform, urine metabolite profiling was performed at the Atherosclerosis Risk in Communities (ARIC) Study visit 5 (2011-13). Urine metabolite levels were probability quotient normalized. We conducted Cox proportional models on 42 urine metabolites with all-cause, CVD, and cancer mortality, adjusting for traditional risk factors and kidney function. A metabolite risk score (MRS) was constructed using weights obtained from least absolute shrinkage and selection operator regression. Harrell’s C statistics was calculated to estimate the models’ predictive performance. Results: Over an average of 5 years of follow-up, 372, 113, and 85 all-cause, CVD, and cancer mortality cases were developed among 1,350 participants (mean age: 75 years, 74% women, 35% Blacks). Seven and one urine metabolites were associated with all-cause and CVD mortality (FDR<0.05, Figure.1). 4-deoxythreonate, a carboxylic acid found in foods, was associated with a decreased risk of all-cause (HR per SD: 0.77, 95% CI: 0.68-0.87) and CVD (HR per SD: 0.63, 95% CI: 0.50-0.80) mortality. The highest quartile of MRS, consisting of 13 and 5 selected urine metabolites, had about a three-fold and four-fold risk of all-cause and CVD mortality compared to the lowest quartile, respectively, and a graded effect across quartiles was observed (p for trend: p<0.001, Figure.2). Adding seven significant urine metabolites improved all-cause mortality prediction by 4% over a traditional risk model (p<0.05). Conclusions: We identified urine metabolites associated with all-cause and CVD mortality, suggesting the potential of considering urine markers in clinical practice and for at-risk population identification.

Hospital-based registry data, including patients’ information collected by academic societies or government based research groups, were previously used for clinical research in Japan. Now, real-world data routinely obtained in healthcare settings are being used in clinical epidemiology and pharmacoepidemiology. Real-world data include a database of claims originating from health insurance associations for reimbursement of medical fees, diagnosis procedure combinations databases for acute inpatient care in hospitals, a drug prescription database, and electronic medical records, including patients’ medical information obtained by doctors, derived from electronic records of hospitals. In the past ten years, much evidence of clinical epidemiology and pharmacoepidemiology studies using real-world data has been accumulated. The purpose of this review was to introduce clinical epidemiology and pharmacoepidemiology approaches and studies using real-world data in Japan.

The rapid rise in the number of older adults, including frail and dependent individuals, has increased demand for medical and dental care. This study aimed to develop a competency-based framework for undergraduate and postgraduate geriatric dental education by identifying key themes and corresponding competencies through a scoping review. A scoping review was conducted using Ovid-MEDLINE, Ovid-EMBASE, and the Cochrane Library, including studies published from January 1, 2010 to June 13, 2025, and following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Scoping Reviews. Eligible studies were screened in two stages, consisting of title/abstract screening and full-text review, and were analyzed using thematic synthesis to identify curricular domains and derive a structured competency framework. The initial database search yielded 1403 articles, of which 42 met the inclusion criteria after full-text review. Thematic synthesis identified four main categories of geriatric dentistry curricula: (1) existing curricula worldwide; (2) educational themes and competencies; (3) teaching and learning methods; and (4) postgraduate and continuing education curricula. Across these areas, 8 major themes were identified, informing the development of a competency framework comprising 6 core competencies, 34 sub-competencies, and 72 enabling competencies. These competencies encompassed aging-related physical, cognitive, and psychosocial changes, oral health management, interdisciplinary communication, ethical and legal considerations, and clinical practice in outreach settings. This study proposes an integrated, staged competency-based framework for geriatric dental education that bridges foundational undergraduate learning and more advanced postgraduate training. By organizing the literature into major themes and corresponding competency domains, the framework provides a practical reference for curriculum planning and revision in response to population aging and the increasing complexity of geriatric oral healthcare.