The relationship between urinary excretion rate of glucose (UEGL) and uric acid (UA) metabolism in adults with type 2 diabetes (T2D) remains unclear to date. This study aimed to investigate the relationships of UEGL with serum UA (SUA), urinary excretion rate of uric acid (UEUA), and renal clearance of uric acid (CLUA) in adults with T2D. We hypothesised that high UEGL increases UA excretion, which in turn leads to lower SUA.This was a cross-sectional study of 635 inpatients with T2D recruited between 2018 and 2019. The relationships of UEGL with UEUA, CLUA, and hyperuricaemia were assessed using analysis of covariance and multivariate regression analysis.p for trend < 0.0001), and a similar trend was observed for UEUA. In adjusted multivariable linear regression model, UEGL was negatively correlated with SUA . However, positive correlations of UEGL with UEUA  and CLUA  were found. Furthermore, consistent significant inverse associations were observed between quartiles of UEGL and hyperuricaemia in the adjusted multivariate logistic regression model.Patients in the higher quartile of UEGL tended to have lower SUA levels than those in the lower quartile. In contrast, patients in the higher quartile of UEGL tended to have higher CLUA (A high UEGL level was positively correlated with UEUA and CLUA. Moreover, it was inversely associated with SUA level, and a consistently increased UEGL level reduced the risk of hyperuricaemia in patients with T2D. Elevated serum uric acid (SUA) is associated with a higher risk of hypertension, cardiovascular disease, and diabetic kidney disease in patients with type 2 diabetes (T2D) –3. In thThis single-centre cross-sectional study was reviewed and approved by the Medical Ethics Committee of Tianjin Medical University Chu Hsien-I Memorial Hospital  and was conducted in accordance with the tenets of the Declaration of Helsinki. All patients provided written informed consent.2 in accordance with the Kidney Disease: Improving Global Outcomes guideline in 2012 [We evaluated 635 patients with T2D who were admitted to Tianjin Medical University Chu Hsien-I Memorial Hospital between 2018 and 2019. T2D was diagnosed according to the World Health Organization 2009 criteria. To rule out the effects of renal insufficiency on uric acid excretion, we included the participants with estimated glomerular filtration rate (eGFR) > 90 ml/min/1.73 m in 2012 . PatientGeneral information, including sex, age, body weight, height, diabetic duration, medication history, and history of previous diseases, was recorded. Body mass index was calculated as body weight divided by height squared, and body surface area (BSA) was calculated using the Stevenson formula (BSA = 0.0061 × height + 0.0128 × weight – 0.1529)[Hyperuricaemia was defined as SUA levels > 416 μmol/L (1 mg/dl = 59.5 μmol/L) in men and 357 μmol/L in women , 13. UEUchi-square test for categorical variables.Given that all the continuous variables were skewed, data analysis were conducted after natural logarithmic transformation. Descriptive data were presented as geometric means  for continuous variables or as percentages (%) for categorical variables. For the analysis of participant characteristics, the differences between sexes were tested using analysis of covariance for continuous variables and β coefficients and 95% confidence intervals were reported. Finally, multivariate logistic regression was performed to evaluate the association between hyperuricaemia and quartiles of UEGL with adjustment for covariates as described previously. Multiple comparisons across different groups were corrected using the Bonferroni method.Analysis of covariance was applied to compare the indicators of UA metabolism  across the UEGL quartile groups, with adjustment for age, sex, body mass index, diabetes mellitus duration, smoking, hypertension, HbA1c, TC, triglyceride, high-density lipoprotein cholesterol, and eGFR. Furthermore, multivariable linear regression models with UEGL as the independent variable and SUA, UEUA, and CLUA as the dependent variables were used to assess their relationships, with adjustment for the above covariates. P < 0.05 was considered statistically significant.We tested for multicollinearity using the variance inflation factors before performing multivariate analysis. Because the covariates of TC and LDL-C were colinear (variance inflation factor for LDL-C > 10) in the present study, LDL-C was excluded in the multivariate models. All the variance inflation factors of the covariates included in the final multivariate models were < 2.93, indicating that no collinearity was acceptable. Moreover, we tested the interaction of sex with UEGL by including the interaction terms in the final linear regression and logistic models (sex × UEGL) . All staThe mean patient age was 51.7 (range 50.8–52.7) years, and there were 398 (62.7%) and 237 (37.3%) male and female patients, respectively. The patient characteristics are detailed in Table P for trend = 0.0001). With Q1 as the reference group, comparisons showed significant differences for each group  . In contrast, participants in the higher quartile of UEGL were more likely to have higher CLUA (P for trend < 0.0001), and a similar trend was observed for UEUA. Although the P value for trend of UEUA was 0.26 (P > 0.05), the UEUA of Q4 was significantly higher compared with that of Q1 (P = 0.01).The comparison of UA metabolism indicators, including SUA, UEUA, and CLUA, across the different UEGL quartile groups are presented in Table β = − 0.023, 95% CI − 0.034 to − 0.013, p < 0.0001). However, UEGL was positively correlated with UEUA  and CLUA  in the adjusted model.Table P for trend < 0.001).The results of multivariate logistic regression for the correlation of UEGL with hyperuricaemia are shown in Table P for interaction = 0.15 in the multivariable linear model and P for interaction = 0.78 in the multivariable logistic model).There were no statistically significant interactions between sex and UEGL , cardiovascular events, and death –29, suggThis study has some limitations. First, it was a single-centre cross-sectional study and did not prove causality. Second, to reduce the influence of renal insufficiency on uric acid excretion, only patients with basically normal renal function were included. Considering that some drugs can affect UA metabolism, we had to exclude a considerable number of individuals during screening, and this might have led to selection bias. Our participants only included those without taking drugs. However, this homogeneity can help reduce unmeasured confounding related to these drugs. Third, inconsistent glycaemic control may have an impact on urinary glucose excretion, although urine samples were collected after achieving stable glycaemic control. Despite these limitations, we believe that the present study remains valuable because it provides additional evidence to clarify the relationship between UEGL and UA metabolism in T2D.In conclusion, our study confirmed that high UEGL was positively correlated with UEUA and CLUA. Moreover, high UEGL was inversely associated with SUA level, and consistently increased UEGL lowered the risk of hyperuricaemia in patients with T2D.


N = 272), that fMRI participants differ from behaviour-only participants on one fundamental individual difference variable: trait anxiety. Analysing trait anxiety scores and possible confounding variables from healthy volunteers across multiple institutions (N = 3317), we found robust support for lower trait anxiety in fMRI study participants, consistent with a sampling or self-selection bias. The bias was larger in studies that relied on phone screening (compared with full in-person psychiatric screening), recruited at least partly from convenience samples (compared with community samples), and in pharmacology studies. Our findings highlight the need for surveying trait anxiety at recruitment and for appropriate screening procedures or sampling strategies to mitigate this bias.Over the past three decades, functional magnetic resonance imaging (fMRI) has become crucial to study how cognitive processes are implemented in the human brain. However, the question of whether participants recruited into fMRI studies differ from participants recruited into other study contexts has received little to no attention. This is particularly pertinent when effects fail to generalize across study contexts: for example, a behavioural effect discovered in a non-imaging context not replicating in a neuroimaging environment. Here, we tested the hypothesis, motivated by preliminary findings ( Neuroimaging methods, such as functional magnetic resonance imaging (fMRI), have been fundamental to the emergence of cognitive neuroscience as a research field. These methods provide a unique window into the function of the human brain and into the implementation of cognitive processes at the computational, neural and network levels. However, a key question that has not been examined in the field is whether individuals who participate in fMRI studies differ from those who participate in behaviour-only studies in terms of their psychological or psychiatric profiles. Given that many studies in cognitive neuroscience involve a behavioural piloting phase to assess behavioural effects, followed by an fMRI scanning phase to assess neural mechanisms, it is important to ensure that individuals who volunteer to participate in each study context exhibit similar profiles and can be characterized by similar population distributions. This is especially relevant for studies in which effects that are present (and replicate) outside the scanner  fail to Specifically, anxiety is likely to be a key factor influencing individuals’ decisions to select themselves into specific studies, situations or environments. Here, we formally test the hypothesis that, because of this selection bias or because of variability in screening procedures, individuals who participate in fMRI studies exhibit lower trait anxiety than individuals who participate in behavioural studies. Within populations of healthy volunteers, it is likely that anxious individuals are more nervous about going into the MRI scanner and are discouraged or excluded from participating if claustrophobic . While pper se. While anxiety disorders constitute a major global health burden . There was no gender or age difference between study contexts, meaning those factors were unlikely to drive the observed difference in trait anxiety. However, the sample size (N = 272) was small , and one factor that could be driving the difference in trait anxiety is whether participants were appropriately screened for psychiatric/affective disorders. In this preliminary sample, all fMRI subjects were screened, while a large proportion of the behaviour subjects (N = 145 out of 208) were not. In addition, all these data were collected by one experimenter at one institution, making it difficult to generalize.Initial support for our hypothesis of lower trait anxiety in fMRI study participants arose from preliminary pilot and published data from three studies . ResultsTherefore, we set out to gather a large data set of existing trait anxiety scores from behavioural and fMRI studies involving healthy volunteers across multiple institutions. In order to account for possible confounds and examine interaction effects, we additionally collected the following variables: gender, age, whether and how participants were screened for affective/psychiatric disorders, whether the study involved the presence of a stressor and/or pharmacological manipulation, whether the study was part of anxiety research, the type of sample recruited, study duration, compensation rate and whether the data were provided before or after participant exclusion.Trait anxiety total scores, from the STAI (lme4 package in R (vs fMRI) while competing for variance with the other variables (Model 1) and (ii) to assess interaction between group and other variables (Model 2). Model 1 included fixed effects of study context, gender, age, psychiatric screening, stressor, drug administration, sample type, study duration, pay rate, whether the study was part of anxiety research, and whether data were provided after participant exclusion, as well as a fixed intercept and a random intercept (grouped by study site). Model 2 included the same effects as Model 1, with the addition of a random effect of study context (grouped by study site) and the following fixed interaction effects: context × gender, context × age, context × psychiatric screening, context × stressor, context × drug administration, context * sample type, context * study duration, and context * pay rate. Study site was included as a random factor in all analyses, given the variability in mean trait anxiety across study sites (N = 103) were excluded, and for Model 2, subjects from study sites that only provided data for one study context (N = 173) were excluded to allow for the estimation of a random effect of condition for each study site. Model 1 thus included data from 3214 subjects, and Model 2 data included data from 3041 subjects. To determine the significance of individual effects, nested model comparison was performed, using chi-square test in R to compare the full model with the corresponding model lacking the one effect of interest. The ‘anova’ function was used to compute analysis of variance tables for model comparisons. Effect sizes were obtained for pairwise comparisons of the marginal means using the eff_size function from the emmeans package in R.Using the 10), which represents the evidence for the full model relative to the null model (which here simply lacks one effect of interest). The magnitude of BF10 was used to interpret the strength of evidence in favour of either model (10 < 3), substantial (3 < BF10 < 10), strong (10 < BF10 < 30), very strong (30 < BF10 < 100) or decisive (BF10 > 100). Similarly, evidence in favour of the null model could also be qualified as anecdotal (0.33 < BF10 < 1), substantial (0.1 < BF10 < 0.33), strong (0.033 < BF10 < 0.1), very strong (0.01 < BF10 < 0.033) or decisive (BF10 < 0.01).Bayesian analyses were conducted using JASP , taking into account whether screening was performed by phone or in-person structured interview. The detailed screening procedures for each study site and study context are reported in N = 2324) from the main data set. We ran a mixed level model on this subset of the data examining the effect of both study context and state anxiety (competing for variance) on trait anxiety. The model contained fixed effects of study context and state anxiety, as well as a random intercept for study site, and was compared with the same model excluding the fixed effect of the study context.To assess whether the difference in trait anxiety observed between fMRI and behavioural studies could in fact be explained by a difference in state anxiety, we obtained state anxiety scores (STAI-S) for a subset of participants . Only results reaching threshold for both methods were considered robust enough to support our conclusions.2 = 71.29, P < 0.0001; d = 0.418 . This indicates that lower trait anxiety in individuals participating in fMRI over behavioural studies is a robust effect in our large sample, present even when competing for variance with multiple other factors such as gender, age, study details and recruitment strategy. In fact, accounting for the variance explained by these variables yielded a 90% larger effect size. Bayesian analyses supported this finding, with the model including all main effects outperforming the same model lacking only the effect of the study context (BF10 > 1014). This is indicative of decisive evidence for this effect. While the size of the effect is variable across the specific study sites that provided data for both contexts , we included fixed effects of all factors , as well as a fixed and random intercept for study site. We found a significant main effect of study context [estimate = −3.677 ± 0.43 (SE), χ2 = 21.56, P < 0.0001; 2 = 38.54, P < 0.001; 10 = 4528; anxiety research: BF10 > 107). We note that the negative correlation between age and trait anxiety is robust to outliers .We then set out to analyse the effect of other variables on trait anxiety to determine which effects are robust to the other variables in the model. The mixed effects model (Model 1) revealed significant effect of age [lower trait anxiety in older individuals: estimate = −0.117 ± 0.025 (SE), χ2 = 7.773, P = 0.0053, 2 = 5.283, P = 0.022, 2 = 4.212, P = 0.04, 10 = 1.83; stressor: BF10 = 0.645, drug administration: BF10 = 0.392).Evidence for effects of gender, stressor and drug administration was mixed, as the mixed effects model suggested significant fixed effects [higher trait anxiety in females: estimate = −0.907 ± 0.32 (SE), χ2 = 2.082, P = 0.149; 2 = 0.009, P = 0.92, vs both estimates = −0.535 ± 0.69 (SE), convenience vs both estimates = 2.843 ± 1.73 (SE), χ2 = 3.327, P = 0.190; 2 = 1.785, P = 0.182, 2 = 1.435, P = 0.231, 10 = 0.075, sample type: BF10 = 0.18, screening: BF10 = 0.21, study duration: BF10 = 0.30, pay rate: BF10 = 0.51).Finally, both analyses showed no significant effect of psychiatric screening [estimate = −0.747 ± 0.51 (SE), χWe then examined whether the difference in trait anxiety between behavioural and fMRI studies was moderated by any of the other variables. To test this, we built a second mixed effects model (Model 2) which, in addition to Model 1 effects, included the following two-way interactions with study context as fixed effects: context × gender, context × age, context × screening, context × stressor, context × drug, context × sample type, context × study duration and context × pay rate. A random effect of study context (with study site as random variable) was also included, allowing to model the interaction between context and site. Note that (i) this model only included the seven study sites that had data from both behavioural and fMRI study contexts, thus leading to a slightly reduced sample size of 3041, and (ii) given the small proportion of studies  that were classified as anxiety research and provided data after participant exclusions, we were unable to include the interaction between study context and these variables. Finally, because the difference between behavioural and fMRI studies was our main question of interest, we did not investigate interactions between the other factors (i.e. not including study context).2 = 7.860, P = 0.005; 2 = 6.730, P = 0.035; 2 = 4.933, P = 0.026; 10 = 13.07; context × sample type: BF10 = 3.282; context × drug: BF10 = 4.742). The context × screening interaction was such that higher trait anxiety in behaviour compared with fMRI study contexts was only present when subjects were screened  compared with when they were not screened (d = −0.042). The context × sample type interaction was such that the behaviour–fMRI difference in anxiety was present in studies using convenience samples (d = 0.558) or a mix of convenience and community samples (d = 0.898) but not in studies relying on community samples only (d = −0.199). Finally, the context × drug interaction was such that the behaviour–fMRI difference in trait anxiety was larger in studies involving a drug administration procedure (d = 0.62) than in those without (d = 0.22). All other interactions were not significant , as supported by the Bayesian tests (BF10 < 0.45). Given that some categories had no data (e.g. combined stress and drug administration study without screening), we refrained from investigating higher-level interactions than the ones reported above.We found significant interactions between the study context and screening [estimate = −8.008 ± 2.71 (SE), χ2 = 2.21, P = 0.33).In the analyses reported above, participants were considered screened for affective/psychiatric disorders if either a phone screening or in-person structured interview was conducted and not screened if absence of psychiatric condition was based purely on self-report of meeting the eligibility criteria specified in the recruitment material or if no such eligibility criteria were specified. However, it is likely that the exact type of screening procedure . Mean trait anxiety scores collapsed across all sites  but not for studies with no screening  or studies with full in-person screening .Re-running linear mixed effect Model 1, but distinguishing between phone and full screening procedures, showed that the difference in trait anxiety across study contexts remained significant [estimate = −3.388 ± 0.43 (SE), χll sites  showed tvs 37.64), while the 80th percentile is lower for fMRI studies (45 vs 48), confirming the narrower distribution of trait anxiety scores in fMRI studies when no psychiatric screening is performed at recruitment. For individuals screened by phone (vs 36.15) and 80th percentile (40.2 vs 48) were lower in fMRI study contexts, driven by a smaller proportion of individuals scoring above 42. When individuals were fully screened using an in-person structured clinical interview , making the comparison for this particular site very underpowered and difficult to interpret. Overall, this heterogeneity between sites seems reduced in the case of full screening, for which trait anxiety scores are consistent across study contexts in all three sites that provided data for this arm .We also note that specific sites could be driving some of the differences between no screening and phone screening . SpecifiN = 2324) across five sites with both behavioural and fMRI studies  and other study details . In addition, the trait anxiety difference remained significant when state anxiety scores were included in the model. Both mixed modelling approaches and Bayesian analyses supported this effect. Interestingly, while the mean difference in trait anxiety scores was relatively small , we note that the effect size nearly doubled  or components assessing anxiety, worry, sadness, self-deprecation as well as general negative affect. Whether a subset of these components is more likely to weigh in on the decision to take part in an fMRI or behavioural study remains an open question for future investigation. We note this analysis was beyond the scope of the present study, given that individual item scores from the trait anxiety questionnaires were not obtained in the data.Procedures in place to screen participants for psychiatric and/or affective disorders were found to modulate the distribution of trait anxiety scores in different ways for fMRI and behavioural study contexts. Specifically, when no or minimal (i.e. phone) screening was performed, the range of trait anxiety scores was narrower in fMRI compared with behavioural studies, while the two distributions matched when full in-person clinical interviews were used. Several possible factors could explain the observed differences. For studies using phone or online screening procedures, participants with higher anxiety might be screened out of fMRI studies more often than behavioural studies, because of inherent differences in screening questions. For example, during recruitment of fMRI studies, participants are likely asked additional screening questions, such as history of claustrophobia, which would usually not be asked for behavioural studies. It is also possible that participants are more likely to not reveal, or not be aware of, their history of psychiatric disorders when participating in a behavioural study for which screening does not occur in person. Finally, a self-selection bias during recruitment is also possible, whereby individuals with high trait anxiety are less likely to volunteer to participate in fMRI studies, even if they meet all eligibility criteria. When full in-person clinical screening is performed, however, we believe that participants with higher anxiety are more likely to be excluded from the study, given the high comorbidity between elevated anxiety and many disorders from the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), for which meeting criteria will usually result in exclusion from a healthy control sample. This is irrespective of whether the study involves neuroimaging or not. Undergoing MRI scanning has been found to be anxiogenic, because of claustrophobia, discomfort and/or fear of learning about potential incidental findings ; therefoExamining the distributions of trait anxiety scores across sites, screening procedures and study context  indicateOur results also revealed that the type of sample or participant pool subjects are recruited from seems to matter, consistent with previous evidence suggesting an effect of sample composition on neuroimaging findings  are of course not exhaustive, and one could imagine that other mediators are likely to explain additional variance in trait anxiety scores and/or in the willingness to participate in fMRI studies  anxiety, evidenced in a behavioural study, fails to replicate in a follow-up fMRI study  or running pharmacology studies, both of which were associated with larger trait anxiety differences between behavioural and fMRI contexts. However, while screening can ensure better matching of trait anxiety across study contexts, it may still lead to samples that are not representative of the general population, as anxious individuals may be excluded from all study contexts at a higher rate. This could result in a loss of power to examine individual differences and undermine relevance for psychopathology.A solution would then be to rely on methods that help recruit participants with higher anxiety into fMRI studies, such as the use of a mock scanner, virtual reality or psychological interventions. These methods have been successful in alleviating MRI anxiety in paediatric populations (In conclusion, our recommendations in the light of the present findings are as follows. First, regardless of the specific causes behind this bias, this study sheds light on the possibility that fMRI samples are less representative of the general population than behavioural samples, or at the very least that behavioural and fMRI samples are different from each other, when it comes to trait anxiety. This is likely to be problematic for mechanistic or experimental research, irrespective of generalizability. Second, researchers should adopt recruitment and/or screening strategies that can help them mitigate this bias if it is likely to impact the validity or interpretation of their results. Finally, future research should further explore possible causes of this bias and mitigation strategies, particularly through controlled experiments. Probing more deeply into individual reasons for participating in fMRI studies and differences in screening procedures seems necessary to ensure researchers can enforce a distribution of psychological and psychiatric profiles that is representative of the general population.nsab057_SuppClick here for additional data file.


Changes in endothelial function may contribute to the positive and negative effects of alcohol consumption on cardiovascular conditions, such as hypertension and coronary artery disease. Numerous studies have used brachial artery flow‐mediated dilation (FMD) to examine the effects of alcohol consumption on endothelial function in humans. However, the findings are inconsistent and may be due to multiple factors such as heterogeneity in subject characteristics, the alcohol use pattern, and amount/dose of alcohol consumed. Therefore, the aim of this systematic review was to investigate the effect of alcohol consumption on brachial artery FMD in humans considering the above‐mentioned factors. This review found that while light to moderate alcohol consumption may have minimal effects on FMD, heavy alcohol consumption was associated with a decrease in FMD. However, most of the published studies included healthy, younger, and male individuals, limiting generalizability to other populations. Future studies should include more women, older subjects, and those from diverse and underrepresented backgrounds. Numerous studies have used brachial FMD to examine the effects of alcohol consumption on endothelial function, but the findings are inconsistent. This may be due to multiple factors such as heterogeneity in subject characteristics , alcohol type and amount, and measurement timing (acute vs. chronic consumption). Therefore, the purpose of this systematic review was to investigate the effect of alcohol consumption on FMD in human. Endothelial cells play a critical role in maintaining vascular health by releasing endothelial cell‐derived substances such as nitric oxide, a potent vasodilator  is a non‐invasive method used to assess endothelial function in peripheral conduit vessels , alcohol type , alcohol amount , and acute versus short‐ and long‐term alcohol consumption. Overall, this systematic review will provide a better understanding of the benefit or harm of alcohol consumption on brachial FMD and provide directions for future research.22.1A systematic literature search was conducted using electronic medical databases . The search was conducted independently by a medical librarian in accordance with PRISMA guidelines and in consultation with authors C.‐L.H. and M.R.P. using Mesh terms related to alcohol use and endothelial function (see Table Studies were eligible for inclusion in this systematic review if the following inclusion criteria were met: (1) studies conducted in human adult (age ≥18 years) subjects following: an acute (one time), short‐term , or long‐term  period of alcohol consumption, (2) studies reported the amount of alcohol consumed and duration of consumption, and (3) studies used FMD measurements of the brachial artery with ultrasound and presented the FMD response to hyperemia either in absolute (mm) or relative (%) change. The screening process included the initial review of titles and abstracts and the full‐text review was performed independently by authors C.‐L.H. and M.R.P. Articles were excluded if the article did not meet the inclusion criteria. Articles included in the final review were done so by consensus, with final inclusion decisions being made by author S.A.P.2.2Primary outcomes of the included studies were alcohol consumption and brachial artery FMD. Depending on study design and purpose, FMD data were extracted at the following time points: (1) at baseline, (2) following acute alcohol consumption, (3) following short‐term alcohol consumption, and/or (4) following a history of long‐term, repeated alcohol consumption. For studies investigating the acute effect of alcohol, we noted the timing of the FMD measurement after drinking. In order to evaluate the contribution of endothelial function to FMD, endothelium‐independent vasodilation data (if tested) were noted from the included studies. We recorded, alcohol drink type, amount , and drinking duration/history length. When calculating the alcohol content in grams for studies which did not specify alcohol content, we estimated that the alcohol content was 13% v/v for red wine with an alcohol density of 0.785 g/ml. For studies conducted in the European Union, unless otherwise noted, we assumed one standard drink contained 12 g of alcohol. If the amount of alcohol consumption was normalized to body weight, we assumed a body weight of 75 kg for an adult subject. Subject characteristics were assessed by extracting health status and other quantitative characteristics such as age, sex, race, body mass index and systolic blood pressure. Data were extracted independently by C.‐L.H and M.R.P and then confirmed by S.A.P.2.3To evaluate the quality of the included studies, we used the National Institute for Health and Clinical Excellence (NICE) quality assessment tool. This tool consists of the following eight questions: (1) Was the case series collected in more than one center ? (2) Is the hypothesis, aim, or objective of the study clearly described? (3) Are the inclusion and exclusion criteria (case definition) clearly reported? (4) Is there a clear definition of the outcomes reported? (5) Were data collected prospectively? (6) Is there an explicit statement that patients were recruited consecutively? (7) Are the main findings of the study clearly described? (8) Are outcomes stratified ?To evaluate the quality of brachial artery FMD measurements, we used the 2019 guideline published by Thijssen et al. . For ana33.1The search produced 155 records from Pubmed, 75 records from CINHAL, and 456 records from EMBASE. After cross‐checking the repeated records, a total of 539 articles were reviewed for possible inclusion Figure  was iden3.23.2.1n, ranging from 7 to 100; total n = 224), while the other three studies enrolled patients with coronary artery disease  on FMD Table . Among t3.2.2n = 173), and subjects had no history of cardiovascular disease and were predominantly male and young and middle‐aged. With regard to race/ethnicity, two studies included only White participants  on FMD Table , four st3.2.3Eleven studies examined the effects of repeated, long‐term (at least 1 year) alcohol consumption on FMD, using a cross‐sectional design and a control or abstinent group Table . Six out3.33.3.1N; N = 6), the alcohol consumption protocol included consuming the alcoholic beverage with a meal (Table N = 9), followed by vodka (N = 4) or pure alcohol (N = 4) combined with other ingredients, such as water or juice. De‐alcoholized red wine (N = 5), pure water (N = 5), and juice (N = 3) were often served as the non‐alcoholic or low‐alcoholic beverage to the control group. Overall, alcohol content ranged from 20 to 68 g, drinking volume ranged from 110 to 800 ml, and drinking duration ranged from 5 to 45 min. Two studies testing red wine consumption did not report alcohol content , while the other study reported an increase in FMD 6 h following red wine consumption  reported no difference in endothelial‐independent dilation versus non‐drinkers or healthy controls  The acute effects of alcohol consumption have primarily been evaluated in healthy, younger individuals in which there appears to be no significant effect of light to moderate amounts of acute alcohol consumption (<3 standard drinks) on FMD, whereas a higher amount of alcohol (3–5 standard drinks) acutely and transiently decreases FMD; (2) in healthy individuals, short‐term alcohol consumption  may not have an effect on FMD; and (3) in young and middle‐aged individuals, a history of long‐term heavy alcohol consumption (daily or binge pattern) is associated with a reduced FMD.4.1Despite the variation in experimental designs, such as type of alcoholic beverage, alcohol content, and timing of FMD measurements following acute alcohol consumption, the alcohol content or dose of alcoholic beverages appears to influence the acute FMD response to alcohol: light to moderate amounts of acute alcohol consumption (<3 standard drinks) may not influence FMD, while higher amounts of alcohol (3–5 standard drinks) may acutely decrease FMD in healthy, young and middle‐aged individuals. The reduced FMD following one‐time alcohol consumption of 3–5 drinks may be associated with several factors. One of the potential mechanisms is alcohol‐induced oxidative stress  alcohol consumption at moderate levels (2–3 drinks/day) may have no appreciable effect on FMD or endothelial‐independent vasodilation in healthy individuals. In contrast, in subjects with hyperlipidemia , duration of alcohol consumption , and age range (23–71 years). Despite these variations, results from most of the included studies suggest that long‐term high levels of alcohol consumption (>3–4 drinks/day) or unhealthy drinking patterns  were associated with a decrease in brachial artery FMD. In addition, many of the studies included confounding variables  that may influence FMD or endothelial function in the statistical models. Along with the findings of acute studies which indicate that alcohol consumption of 3–5 standard drinks acutely decreases FMD, these findings suggest that the repeated exposure to high amounts of alcohol can lead to impairments in FMD, which is associated with an increased risk for future cardiovascular disease events  was associated with an improvement in FMD (Di Gennaro et al., Ethnic/racial differences may influence the effects of long‐term alcohol consumption on FMD. Among the five population‐based cohort cross‐sectional studies, three studies were conducted in East Asian populations (Oda et al., 4.4The overall quality of studies reviewed in this systematic review were fair. Most of the studies were conducted before 2015 and FMD measurements did not meet the current measurement guidelines (Thijssen et al., Individuals from underrepresented minority populations are at increased risk for the development of cardiovascular disease, compared to White populations (Kurian & Cardarelli, 4.5Overall, this review found that while light to moderate alcohol consumption may not influence FMD, heavy alcohol consumption was associated with a decrease in FMD. Adults should avoid drinking three drinks or more on any single occasion to prevent FMD from decreasing acutely or permanently, which may increase future risk for cardiovascular disease. However, current evidence is based primarily on data from healthy, younger, and male individuals, with limited information on individuals from underrepresented minority populations. Alcohol consumption is projected to increase in the United States, South‐East Asia, and the Western Pacific (World Health Organization, None.All authors contributed to study design, selection of studies, data extraction, synthesis of study, manuscript drafting, and critical discussion.Table S1‐3Click here for additional data file.


As the leading sexually transmitted infection worldwide, human papillomavirus (HPV) may disproportionately affect transwomen. We aimed to estimate anal HPV prevalence, especially focusing on high‐risk (hr)‐HPV types and evaluate their associated factors among transwomen living in Rio de Janeiro, Brazil.Transwomen enrolled in a respondent‐driven sampling (RDS)‐based survey conducted between August 2015 and January 2016 self‐collected anal samples, which were promptly stored at minus 80°C. After DNA extraction, HPV detection and genotyping were performed using the PapilloCheck test. We estimated HPV prevalences and evaluated the correlates of anal hr‐HPV infection using a regression logistic model.Out of 345 transwomen, 272 (78.8%) were included in this analysis (122 [44.9%] HIV‐positive). No participant had ever received HPV vaccination. Among participants enrolled, 212 (77.9%) were positive for any anal HPV type and 165 (60.7%) for hr‐HPV. Most common hr‐HPV were as follows: HPV16 (17.6%), HPV68 (14.7%), HPV39 (14.3%), HPV56 (12.5%), HPV51 (11.4%) and HPV52 (11.0%). HIV‐positive transwomen had three times the odds of having an hr‐HPV compared to HIV‐negative transwomen. Participants who had a current rectal Neisseria gonorrhoeae infection had 3.7 times the odds of being coinfected with hr‐HPV. Among HIV‐positive transwomen, neither antiretroviral therapy use, undetectable viral load, current and nadir CD4 counts were associated with anal hr‐HPV infection.Brazilian transwomen in our study exhibit some of the highest population‐specific rates of HPV and hr‐HPV. There is an urgent need to elucidate the burden of HPV infection, prevalence of HPV‐related diseases and access to and uptake of HPV vaccination among transwomen, especially from low‐ and middle‐income settings. Most sexually active people become infected with HPV at some point in their lives , 2, 3. HBesides a necessary factor to cervical oncogenesis , hr‐HPV Transgender women (henceforth “transwomen”) experience numerous socio‐economic factors that increase their vulnerability to HIV/STIs . However2Transcender, a cross‐sectional study that enrolled 345 transwomen using respondent‐driven sampling (RDS) at the Evandro Chagas National Institute of Infectious Diseases (INI)‐FIOCRUZ, Rio de Janeiro, Brazil, between August 2015 and January 2016. RDS has been used to obtain robust and diverse samples of hard‐to‐reach populations [This is a secondary analysis of ulations . ProceduInstituto de Medicina Tropical da Universidade de São Paulo. Analysis methods have been described elsewhere [We offered HIV/STIs testing to all participants. A trained staff member provided anal self‐collection materials and explained how to perform the procedure using illustrated instructions . In a prlsewhere . In summTreponema pallidum. We detected rectal Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infection by using the Abbott Real Time platform and the Amplification Reagent Kit  in INI‐FIOCRUZ Laboratory. Indeterminate results were repeated with the same tests on the same samples. All participants living with HIV collected CD4+ count (Becton Dickinson FACScan) and HIV viral load (VL). Previous CD4+ counts were retrieved from the Brazilian National Registry, which records most measures performed in the country. Participants self‐reported antiretroviral therapy (ART) use.Syphilis screening used Venereal Disease Research Laboratory (VDRL) tests, and positive results were confirmed by a microhaemagglutination assay for We estimated prevalence of any anal HPV, at least one HPV type in the 2‐valent , 4‐valent  and 9‐valent  vaccines, hr‐HPV (positive for 1+ hour‐HPV detected by the test) and individual HPV types.T. pallidum. The nadir CD4+ count was defined as the participant’s lowest level ever recorded.Continuous variables were reclassified as categorical. We defined active or recent syphilis as VDRL titers of at least 1/8 plus a positive microhaemagglutination assay for p < 0.2 in the univariable logistic regression analysis and potential confounders were included in the initial multivariable model. A backward elimination procedure guided the removal of non‐significant variables until we reached a final multivariable model where all variables had a p ≤ 0.05 or modified the effect of other variables. Statistical analysis was performed using R software version 3.4.3.We used RDS‐unadjusted data. Descriptive analysis used median and interquartile range (IQR) and absolute and relative frequencies. We compared participants according to HIV status using chi‐square tests. We used a regression logistic model to evaluate the correlates of anal hr‐HPV infection. Variables with This study was approved by the INI‐FIOCRUZ Institutional Review Board. All participants provided an informed consent form. This study received grants of the Brazilian Research Council (CNPq) and the National Institute of Allergy and Infectious Diseases (NIAID‐NIH).3Transcender study, 341 (98.8%) agreed to and conducted anal specimen collection, 69 (20.0%) had invalid anal samples due to insufficient material and 272 (78.8%) had samples with valid results and were included in the present analysis. HIV‐negative status was more common among participants with invalid samples than those with valid samples (72.9% vs. 55.1% respectively). Overall, participants were aged 30 years (IQR 24 to 37), 76.8% were non‐white, and 48.9% were currently on hormones. Only 16 (5.9%) participants had gender‐affirming surgery. Ever and currently doing sex work were reported by 79.0% and 48.9% respectively. No participant had received HPV vaccine. HIV‐infection was present in 122 individuals (44.9%). Among those living with HIV, 83 were on ART, 43.7% were virologically suppressed, and median current and nadir CD4 count were, respectively, 631 cells/mm3 (IQR 384 to 833) and 380 cells/mm3 (IQR 196 to 576).Among 345 transwomen enrolled in the Out of 272 participants tested for anal HPV, 212 (77.9%) and 165 (60.7%) were positive for any HPV and hr‐HPV respectively (Table The most common hr‐HPV was HPV16 (17.6%). Only three people had both HPV16 and 18 (1.1%), and none were positive for all 4‐ and 9‐valent vaccine types. Transwomen living with HIV had a significantly higher prevalence of most types of anal HPV than those HIV negative. HPV6 and HPV43 had decreasing prevalences according to age Table . TranswoYounger participants had significantly higher odds of anal hr‐HPV infection Table . TranswoThese data add to the limited research on anal HPV infection among transwomen. In the United States, unvaccinated transwomen had a significantly higher anal HPV prevalence than unvaccinated MSM (88.6% vs. 70.9%), even after stratifying by HIV status . ArgentiRates of anal HPV and hr‐HPV in our sample of transwomen are higher than previously described among individuals with diverse gender identities and sexual orientations. A meta‐analysis found that anal HPV prevalences varied widely between cisgender men (mostly MSM) and women . Their dAnal hr‐HPV detection was significantly higher among younger transwomen. There is a strong relationship between age and cervical HPV prevalence . NeverthTranswomen living with HIV had a higher HPV and hr‐HPV prevalences compared to HIV‐negative participants, consistent with previous findings. MSM have the highest population‐specific HPV rates reported to date, especially among those living with HIV , 33, 34.The 4‐valent HPV vaccine, available at no cost in Brazil since 2014, is currently offered to girls aged 9 to 14 years, boys aged 9 to 14 years and people living with HIV aged 9 to 26 years (regardless of gender identity) . NeverthThis study has several limitations. First, although RDS survey is commonly used for hard‐to‐reach populations, its results may not be generalizable. In addition, the cross‐sectional design does not allow us to establish causal inference. We also did not evaluate anal cytology or histopathology data, which could ultimately reinforce the burden of anal HPV infection among transwomen. Syphilis definition only included laboratory results and did not consider clinical data. Finally, the high proportion of invalid samples may be due to user error. Two rectal samples had to be collected (for HPV and CT/NG), which may create burden on participants and interfered with the process. Although self‐collection has been described as an acceptable tool, including for anal samples, the proportion of invalid samples varied from 5% up to 37% across studies , 42, 43.4Our extremely high rates of HPV and hr‐HPV among transwomen show that this group is disproportionately affected by HPV and may be at a high risk for cancer. HPV16 was the most prevalent anal hr‐HPV type. Prevalence of hr‐HPV was higher among younger participants, those living with HIV and concomitant rectal NG infection. There is an urgent need to elucidate the burden of HPV infection and to increase access to and uptake of HPV vaccination among transwomen, especially from low‐ and middle‐income settings.The authors declare no conflict of interests.BG, EMJ, ECW and VGV conceived the analysis and interpreted the findings. BG, EMJ, ECW and VGV drafted the manuscript. LSV and EMJ performed the statistical analyses. JEL supervised the biological analysis, interpreted the results and provided biological inputs. EMJ, LM, LSV and ACFG helped with data acquisition, interpretation of the results and drafting the manuscript. All authors read and approved the final manuscript.


Real‐world data from large administrative claims databases in Japan have recently become available, but limited evidence exists to support their validity. VALIDATE‐J validated claims‐based algorithms for selected cancers in Japan.VALIDATE‐J was a multicenter, cross‐sectional, retrospective study. Disease‐identifying algorithms were used to identify cancers diagnosed between January or March 2012 and December 2016 using claims data from two hospitals in Japan. Positive predictive values (PPVs), specificity, and sensitivity were calculated for prevalent (regardless of baseline cancer‐free period) and incident  cases, using hospital cancer registry data as gold standard.22 108 cancers were identified in the hospital claims databases. PPVs (number of registry cases) for prevalent/incident cases were: any malignancy 79.0% (25 934)/73.1% (18 119); colorectal 84.4% (3519)/65.6% (2340); gastric 87.4% (3534)/76.8% (2279); lung 88.1% (2066)/79.9% (1636); breast 86.4% (4959)/59.9% (3185); pancreatic 87.1% (582)/80.4% (508); melanoma 48.7% (46)/42.9% (36); and lymphoma 83.6% (1457)/77.8% (1035). Specificity ranged from 98.3% to 100% /99.5% to 100% (incident); sensitivity ranged from 39.1% to 67.6% /12.5% to 31.4% (incident). PPVs of claims‐based algorithms for several cancers in patients ≥66 years of age were slightly higher than those in a US Medicare population.VALIDATE‐J demonstrated high specificity and modest‐to‐moderate sensitivity for claims‐based algorithms of most malignancies using Japanese claims data. Use of claims‐based algorithms will enable identification of patient populations from claims databases, while avoiding direct patient identification. Further research is needed to confirm the generalizability of our results and applicability to specific subgroups of patient populations. Real‐world data from healthcare claims databases are available in Japan, but few validation studies exist to support the validity of these data.In VALIDATE‐J, a multicenter validation study in Japan, algorithms were developed from institutional claims data and validated against hospital‐based cancer registry data.Positive predictive value (PPV), specificity, and sensitivity were computed for incident and prevalent cancers; PPVs for several cancers were higher than those reported in the USA.One of the first and largest validation studies in Japan, VALIDATE‐J will inform future claims‐based research and serve as a model for validation studies for claims‐based post‐marketing studies in Japan.1The incidence of many primary cancers is increasing in Japan, with colorectal, lung, and gastric cancers as the most frequently reported cancer types in 2018.Real‐world data are essential for understanding cancer epidemiology, both in the general population and as part of drug safety surveillance. Administrative healthcare claims databases provide a valuable source of longitudinal, real‐world data for pharmacoepidemiology, comparative effectiveness research, and health services/outcome research. Claims‐based definitions for cancers have been developed and validated in the USA and EU for the identification of incident cases of breast, lung, gastric, colorectal, and hematologic cancers in hospital or commercial administrative databasesMultiple claims databases, such as the National Database of Health Insurance Claims and Specific Health Checkups of Japan, the Japan Medical Data Center, and the Medical Data Vision, are now available to academic and industry researchers in Japan. The Pharmaceuticals and Medical Devices Agency encourages the use of claims‐based pharmacoepidemiology research for drug safety surveillance in Japan, and requires validation studies to support the credibility of claims database research for post‐marketing surveillance.The Validity of Algorithms in Large Databases: Infectious Diseases, Rheumatoid Arthritis, and Tumor Evaluation in Japan (VALIDATE‐J) study investigated the validity of several predefined disease‐identifying algorithms using hospital claims data in Japan. Here, we report the positive predictive value (PPV), specificity, and sensitivity of claims‐based algorithms for selected malignancies  from VALIDATE‐J.22.1VALIDATE‐J was a cross‐sectional, retrospective study of claims data, medical records, and cancer registry data from two general acute‐care hospitals in Chiba, Japan – a large 917‐bed private teaching and cancer care hospital designated by the national government, located in a rural area , and a large 716‐bed community teaching and cancer care hospital designated by the local government, located in a city area  – conducted between December 2017 and February 2019. The overall study objectives were to validate claims‐based algorithms for rheumatoid arthritis (RA), infectious diseases, and malignancies. Data for RA and infectious disease will be reported elsewhere. An overview of the study is shown in Figure Prior to study initiation, claims‐based algorithms for any malignancy, colorectal, gastric, lung, breast, and pancreatic cancers, melanoma, and lymphoma, were developed and modified by a steering committee of experts in oncology, Japanese cancer registries, and epidemiology Table . The algAn Independent Ethics Committee and the Institutional Review Board at each participating hospital approved the study protocol. The study was conducted in accordance with accepted practices for pharmacoepidemiology studies issued by the International Society for Pharmacoepidemiology and the Council for International Organizations of Medical Sciences. Patients identified in the claims databases were not required to provide consent and could opt out from participating in the study.2.2The claims‐based cohort included patients treated as outpatients or inpatients at either hospital between January 01, 2012  or March 01, 2012  and December 31, 2016, who met the prespecified claims‐based criteria for each selected malignancy type Table  were con2.3PPV, specificity, and sensitivity of claims‐based algorithms for each malignancy type were calculated using the registry‐based gold‐standard diagnosis, based on prevalent and incident cases, with claim and registry periods within the same month.2.4Demographics and disease characteristics were summarized using descriptive statistics .PPV for each claims‐based algorithm was calculated as the number of cases meeting the claims‐based algorithm that were confirmed in the cancer registry  divided by the total number of cases meeting the claims‐based algorithm  Table . SpecifiCalculations of specificity and sensitivity were based on the following assumptions: case identification in the cancer registry was close to 100%, and all the data from the hospital cancer registries could be linked to hospital claims data. 95% confidence intervals (CI) for PPV, specificity, and sensitivity were calculated using the normal approximation of the binomial distribution. Deidentified data were analyzed using Python version 3.6.0 (2016).33.1During the ascertainment period (2012–2016), a total of 25 934 cases of malignancies specified in this study were recorded in the hospital cancer registries.In situ cancer was the most common type of breast cancer (21%) identified, and localized cancer was most common among gastric cancer, accounting for 66% of cases. A numerically higher proportion of patients with lung and pancreatic cancers, or lymphoma had Stage IV disease compared with other cancer types. Approximately one‐third of all cases  had been treated with surgery or chemotherapy.Demographics and disease characteristics for cases identified in the hospital cancer registries are shown in Table 3.2n = 14 257; Hospital B, n = 7851). The number of cases by cancer type was: any malignancy (n = 22 108), colorectal (n = 1717), gastric (n = 1784), lung (n = 1135), breast (n = 3880), pancreas (n = 303), melanoma (n = 37), and lymphoma (n = 965)  and the least common was melanoma .A total of 22 108 prevalent cases of malignancies were identified in the hospital claims databases using the prespecified claims‐based algorithms . Compared with the PPVs for identical cancers in a US Medicare population ≥65 years of age, the PPVs for claims‐based incident cases of gastric and lung cancers, and lymphoma, in patients ≥66 years of age, were higher in Japan Table . In cont4Claims databases have been a critical component of real‐world data for decades in the USA, Europe, and other geographic regions for post‐marketing safety surveillance. The use of such data in Japan is in its early stages, but is quickly evolving. A key component in the use of claims data is the demonstration of high validity of the algorithms used to identify study populations and outcomes of interest.in situ through metastatic), with high specificity and modest‐to‐moderate sensitivity across claims data from two hospitals.VALIDATE‐J is one of the first and largest multicenter studies conducted in Japan to validate claims‐based algorithms for malignancies specifically developed for the Japanese clinical practice environment. The claims‐based algorithms based on diagnostic and procedural codes identified more than 22 000 cancers of various stages .Compared with data from a US validation study using US Medicare claims data,In one of the first validation studies of claims‐based definitions in Japan, Sato et al assessed the accuracy of 14 definitions for identifying prevalent breast cancer cases using hospital‐based claims at a large teaching hospital in Tokyo.n = 130),n = 1019) and 91%/95% for colorectal cancers (n = 2253) using definitions based on combinations of diagnosis and procedural codes.n = 665), colorectal (n = 796), and breast (n = 897) cancer was reported using definitions based on hospital discharge codes.n = 340),n = 22 413).The PPVs of the claims‐based algorithms reported here are comparable with those from studies conducted outside Japan, although between‐study comparisons may be limited by differences in the cancer definitions used. For example, validation studies conducted in Europe and Australia using administrative claims data have reported PPV from 58% to 79% and sensitivity from 97% to 99% for incident cases of lung cancer based on diagnostic codes only (Strengths of this study include the large sample size covering multiple tumor types and various disease stages, and the inclusion of data from two large hospitals, both of which had nearly complete cohorts of confirmed cancer cases in the registries. In addition, the claims‐based algorithms were developed by a multidisciplinary team of Japanese experts to ensure relevance to the Japanese clinical practice environment and the use of claims data unique to Japan. Other strengths include additional sensitivity analyses to evaluate incident cases, and the comparison of the Japanese data to similar validation studies conducted in the USA to identify important differences.A limitation of this study was that the study hospitals were not selected randomly and may not reflect broader Japanese healthcare practices or patient populations. Additionally, the claims data analyzed are derived solely from the study hospitals and, as such, do not represent complete claims data from broader Japanese healthcare systems. The lack of coverage for multiphasic health screening or annual health check‐ups under the Japanese universal health insurance system may have contributed to false negatives, thereby influencing the sensitivity of the analysis. The inclusion of payer‐based claims data would improve the sensitivity of the algorithm, but privacy laws in Japan prohibit the identification of patients directly from administrative healthcare databases, thus making a truly representative validation study not possible. Until privacy restrictions are eased to allow for validation studies to be conducted more easily, researchers must rely on hospital‐based patient sampling of claims data. Despite these existing restrictions, validation studies, such as this study, are steadily increasing and will expand our knowledge about the validity of Japanese claims data for research purposes.In conclusion, VALIDATE‐J demonstrates that validation of disease‐identifying algorithms for malignancies created specifically for the Japanese clinical practice environment and unique to Japanese claims data is feasible and has high specificity when applied to data from Japanese administrative databases. Data from VALIDATE‐J on disease‐identifying algorithms for RA and infectious diseases will provide additional information on the utility of claims‐based algorithms with Japanese databases. Studies such as VALIDATE‐J will provide researchers with much‐needed knowledge about the validity of Japanese claims data, and may serve as a model for future validation studies in situations where direct identification of patients from administrative healthcare databases is not possible. As with other geographic regions where claims database research is conducted, validation will continue to be a crucial activity to support the integrity of claims database research in Japan.C.D. and N.S. are employees of Pfizer Inc. T.M., T.H., K.K., S.N., R.H., S.J., M.K. and D.S. have received consultancy fees from Pfizer Inc in connection with this study. H.C. has received funding from Pfizer Inc in connection with this study through her University, and has received grants from the Cystic Fibrosis Foundation, National Institute of Health, and Pfizer Inc. E.N. has no potential conflict of interest to declare. Y.T. has received speaker fees and/or honoraria from AbbVie, Asahi Kasei, Astellas, Bristol‐Myers Squibb, Chugai Pharmaceutical Co., Ltd, Daiichi Sankyo, Eisai, Eli Lilly, Gilead, GSK, Janssen, Mitsubishi Tanabe Pharma, Novartis, Pfizer Inc, Sanofi, and YL Biologics Ltd, and has received research grants from AbbVie, Asahi Kasei, Chugai Pharmaceutical Co., Ltd, Daiichi Sankyo, Eisai, Mitsubishi Tanabe Pharma, and Takeda. S.S. has received consultancy fees from Pfizer Inc in connection with this study, and has received grants from Bristol‐Myers Squibb, Cystic Fibrosis Foundation, Daiichi Sankyo, Janssen, National Institute of Health, PCORI, and Pfizer Inc, and personal consulting fees from Janssen, Medtronic, Merck, and Pfizer Inc.All authors participated in the conception and development of this article. H.C., E.N., Y.T., and S.S. were involved in data collection and analysis. T.M., T.H., K.K., S.N., R.H., S.J., M.K., D.S., and Y.T. were involved in data interpretation. All authors critically reviewed the manuscript and approved the final draft prior to submission.An Independent Ethics Committee and the Institutional Review Board at each participating hospital approved the study protocol. The study was conducted in accordance with accepted practices for pharmacoepidemiology studies issued by the International Society for Pharmacoepidemiology and the Council for International Organizations of Medical Sciences. Patients identified in the claims databases were not required to provide consent and could opt out from participating in the study.Appendix S1 Supporting informationClick here for additional data file.


Liquid biopsy, a minimally invasive approach, is a highly powerful clinical tool for the real‐time follow‐up of cancer and overcomes many limitations of tissue biopsies. Epigenetic alterations have a high potential to provide a valuable source of innovative biomarkers for cancer, owing to their stability, frequency, and noninvasive accessibility in bodily fluids. Numerous DNA methylation markers are now tested in circulating tumor DNA (ctDNA) as potential biomarkers, in various types of cancer. DNA methylation in combination with liquid biopsy is very powerful in identifying circulating epigenetic biomarkers of clinical importance. Blood‐based epigenetic biomarkers have a high potential for early detection of cancer since DNA methylation in plasma can be detected early during cancer pathogenesis. In this review, we summarize the latest findings on DNA methylation markers in ctDNA for early detection, prognosis, minimal residual disease, risk of relapse, treatment selection, and resistance, for breast, prostate, lung, and colorectal cancer. Blood‐based epigenetic biomarkers present in circulating tumor DNA (ctDNA) have a high potential for early detection of cancer, since DNA methylation in plasma can be detected early during cancer pathogenesis. In this review, we summarize the latest findings on DNA methylation markers in ctDNA for early detection, prognosis, minimal residual disease, risk of relapse, treatment selection, and resistance in patients with breast, prostate, lung, and colorectal cancer. AAabiraterone acetateBPHbenign prostatic hyperplasiacfDNAcell‐free DNACRCcolorectal cancerCTCscirculating tumor cellsctDNAcirculating tumor DNAddMSPdroplet digital methylation‐specific PCRddPCRdroplet digital PCREMAEuropean Medicines AgencyFDAFood and Drug AdministrationmCRPCmetastatic castration‐resistant prostate cancerMRDminimal residual diseaseMS‐ddPCRmethylation‐specific droplet digital PCRMSPmethylation‐specific PCRNSCLCnon‐small‐cell lung cancerOSoverall survivalqMSPquantitative methylation‐specific PCRSBsodium bisulfiteTCGACancer Genome Atlas1Liquid biopsy is a highly powerful clinical tool for the real‐time follow‐up of cancer patients that overcomes many limitations of tissue biopsies , 2. LiquEpigenetic alterations have a high potential to provide a valuable source of innovative biomarkers for cancer, since they are stable, highly frequent for specific genes, and can also be detected in biological fluids in a minimally invasive way. A variety of studies on DNA methylation markers focus on the evaluation of their clinical significance as novel epigenetic biomarkers . Among ehttps://cancergenome.nih.gov) is an important source of information for DNA methylation biomarkers in many types of cancer. In a recent study, homogenous groups of secondary breast cancers to matched cohorts of primary breast cancers that were included in the TCGA were compared in order to identify specific gene expression and DNA methylation signatures [Analysis of DNA methylation markers in primary tumors has already shown impressive results. The Cancer Genome Atlas  tests [Despite all these advantages, up to now clinical tests are commercially available only for a very low number of DNA methylation‐based biomarkers (only 14 at present) , 17, andChanges in DNA methylation patterns in plasma are known to arise early during cancer pathogenesis . Blood‐bLarge‐scale targeted methylation sequencing of plasma cfDNA has a high potential for early cancer diagnosis. Recently, a novel assay targeting 9223 CpG sites that are consistently hypermethylated according to TCGA was developed and validated in plasma cfDNA from patients with advanced colorectal cancer (CRC), non‐small‐cell lung carcinoma (NSCLC), breast cancer, and melanoma [Another recent study has shown that cfDNA methylation analysis in plasma could provide some patterns that can detect and discriminate common primary intracranial tumors . In renaIn this review, we summarize the latest findings on DNA methylation markers in ctDNA for early detection, prognosis, minimal residual disease (MRD), risk of relapse, treatment selection, and resistance, for breast, prostate, lung, and CRC.2The main analytical methodologies used for the analysis of ctDNA methylation markers are based either (a) on PCR following sodium bisulfite (SB) treatment that converts all nonmethylated cytocines to uracils and subsequently through PCR to thymines, which include methylation‐specific PCR (MSP), real‐time MSP, and droplet digital MSP (ddMSP) or (b) on a large‐scale omic approaches that include genome‐wide DNA methylation analysis, pyrosequencing, methyl‐BEAMing, array‐based genome‐wide DNA methylation analysis, highly multiplexed targeted next‐generation sequencing, and bisulfite sequencing. ctDNA methylation markers can provide information on early detection, prognosis, MRD, and therapy response in various types of cancer Fig. .2.12.1.1SPAG6, NKX2‐6, ITIH5, and PER1 genes was detected early in serum of breast cancer patients [Detection of methylated ctDNA in the peripheral blood of cancer patients is highly promising for the discovery of highly sensitive and specific molecular biomarkers for screening and early detection. Recently, by using genome‐wide DNA methylation analysis, novel cfDNA biomarkers that could differentiate breast cancer patients from healthy individuals were identified for sporadic breast cancer . Accordipatients .APC, BRCA1, CCND2, FOXA1, PSAT1, RASSF1A, and SCGB3A1) in primary tissues and cfDNA of breast cancer patients [APC, FOXA1, RASSF1A, or SCGB3A1 could discriminate noncancerous from cancerous tissues with an accuracy of 95%. The same study has shown that high PSAT1 methylation levels were associated with longer disease‐free survival (DFS), and that high FOXA1 methylation levels were associated with shorter DFS, while a combination of APC, FOXA1, and RASSF1A methylation provided a sensitivity, specificity, and accuracy of over 70% [Toward the same direction, another study has evaluated the prognostic significance of promoter methylation of seven genes  was evaluated as a prognostic marker in a study that included 150 and 16 breast cancer patients under adjuvant and neoadjuvant therapy, respectively, 34 patients with metastatic disease and 35 healthy volunteers by quantitative MSP (QMSP) [GATA3 methylation was detected in all patient groups but not in the healthy control population. In the metastatic setting, WNT5A methylation was correlated with poor prognosis and a shorter overall survival (OS), SOX17 methylation to shorter PFS and OS, and KLK10 methylation to relapse. When at least 3 or 4 of these genes were methylated, a shorter OS and no response to therapy were documented in this group [CCND2 promoter hypermethylation was detected in 40.9% of breast tumors and 44.4% of plasma circulating cfDNA of patients, and could serve as a potential diagnostic and prognostic marker in breast cancer [ry tumor . DNA mett cancer .2.1.3In operable breast cancer, there is a high risk of recurrence and disease progression after surgery and therapeutic treatment. Early detection of MRD during a disease‐free follow‐up period would greatly improve patient outcomes. However, MRD monitoring in breast cancer through DNA methylation markers in ctDNA analysis is still not well established . In brea2.1.4ESR1 methylation in CTCs and corresponding plasma ctDNA was shown to be a potential biomarker for response to endocrine therapy; moreover, a high concordance of ESR1 methylation in CTCs and paired plasma ctDNA was shown in the metastatic setting [ESR1 epigenetic status, as evaluated by methylation‐specific ddPCR (MS‐ddPCR), is indicative of resistance to endocrine therapy [MGMT promoter methylation was not related to different chemotherapy response rates [In 25–30% of hormone‐positive metastatic breast cancer patients treated with endocrine therapy, adaptive mechanisms emerge through alterations in the estrogen receptor ligand‐binding domain , 40. Rec setting . Another therapy . In tripse rates .In Table 2.22.2.1de novo metastatic prostate cancer, three genes, DOCK2, HAPLN3, and FBXO30, were found to be specifically hypermethylated in prostate cancer tissues using MS‐ddPCR [MCAM, ERα, and ERβ genes in serum ctDNA could be utilized as a combined biomarker for the early detection of prostate cancer, with a sensitivity and specificity almost equal to and better than serum PSA, respectively [Numerous diagnostic tests based on prostate‐specific antigen (PSA) have been developed so far to improve early detection of prostate cancer; however, minimally invasive tests with better specificity and sensitivity are still needed to further improve diagnosis and risk stratification. Tests based on DNA methylation markers in cfDNA are highly promising for early detection since they are minimally invasive, highly specific, and can be detected at very early stages of the disease. These epigenetic alterations can be detected in both plasma and urine of prostate cancer patients . In locaMS‐ddPCR . In plasMS‐ddPCR . It was MS‐ddPCR . Anotherectively .APC, FOXA1, GSTP1, HOXD3, RARβ2, RASSF1A, SEPT9, and SOX17) in plasma, based on a multiplex QMSP, was evaluated for the early detection of lung, prostate, and CRC [SEPT9 and SOX17, were methylated in all three cancers; FOXA1, RARβ2, and RASSF1A methylation was detected in lung and prostate cancer with 64% sensitivity and 70% specificity; and methylation of GSTP1 and SOX17 could discriminate lung cancer from prostate cancer with 93% specificity [The quantification of DNA methylation levels of another set of eight genes  and additionally CCDC181 and HAPLN3 was evaluated in ctDNA of 27 patients with prostate cancer and 10 patients with benign prostate hyperplasia using MS‐ddPCR [ST6GALNAC3, CCDC181, and HAPLN3) could detect prostate cancer with 100% diagnostic specificity and 67% diagnostic sensitivity [Promoter methylation of two genes, namely 46–0.903 . In the 46–0.903 . In the MS‐ddPCR . ctDNA asitivity .2.2.4DNA methylation is highly important in prostate cancer initiation and progression. Epigenetic alterations that regulate prostate cancer progression could provide a source of biomarkers indicating resistance or response to specific therapies . AbirateIn Table 2.3et al. [During the last 20 years, numerous studies have shown the importance of epigenetic alterations in lung cancer. DNA methylation of specific genes has been shown to play an important role in lung cancer pathogenesis, and can provide novel biomarkers for early detection, prognosis, and prediction of response to specific treatments . In paraet al. . Since tet al. , 63. In et al. . Liquid et al. .2.3.1Plasma‐based detection of cancer‐specific DNA methylation markers may provide a simple cost‐effective method for the early detection of lung cancer and can be used for noninvasive diagnostics and monitoring. A very recent review on the main approaches to develop biomarkers for the early detection of lung cancer, with considerations of detection of rare tumor events, focused on DNA methylation‐based detection in plasma and sputum . In a re2.3.2APC, HOXA9, RARβ2, and RASSF1A was evaluated by QMSP in lung cancer, it was found that HOXA9 and RASSF1A had higher methylation levels in small‐cell lung cancer than in NSCLC, with HOXA9 methylation levels displaying a sensitivity of 63.8%, and RASSF1A displaying a specificity of 96.2% for small‐cell lung cancer detection in ctDNA [HOXA9 methylation levels were higher in squamous cell carcinoma than in adenocarcinoma [KMT2C (MLL3) promoter methylation was detected in plasma cfDNA of NSCLC patients at both early and advanced stages, but not in plasma of healthy individuals [BRMS1 and SOX17, in plasma ctDNA from NSCLC patients has also been shown to be of prognostic significance [When DNA methylation of in ctDNA . Additioarcinoma . Very reividuals . Promoteividuals . Promoteificance , 70.2.3.3Up to now, only a few studies have evaluated the potential of DNA methylation markers in ctDNA of lung cancer patients for therapy resistance. Recently, a combined detection of somatic mutations and DNA methylation markers in plasma cfDNA was used to evaluate response to osimertinib in NSCLC patients positive for the T790M EGFR mutation . AccordiIn Table 2.42.4.1In CRC, a blood‐based test based on real‐time MSP detection of methylated Septin9 in DNA obtained from peripheral blood samples has been FDA‐approved for early detection; however, a positive result should still be verified by colonoscopy or sigmoidoscopy . Methyla2.4.2RASSF1A promoter methylation was reported as a prognostic biomarker in patients with stage II and III CRC receiving oxaliplatin‐based chemotherapy, when investigated by MSP in 108 CRC patients before and after chemotherapy and 78 healthy controls [BCAT1 and IKZF1 was recently reported in ctDNA of CRC patients, and it was shown to be related to CRC stage; after surgery, these DNA methylation markers were not detected, indicating a possible role of these markers on the adequacy of surgical resection [controls . DNA met2.4.3NPY methylation along with tumor‐specific mutations in ctDNA could give similar results to radiographic evaluation, showing that this combined liquid biopsy approach can be used for the follow‐up of mCRC patients during treatment [EYA4, GRIA4, ITGA4, MAP3K14‐AS1, and MSC) in cfDNA using ddPCR can be used in cases where patient‐specific mutations cannot be detected for monitoring tumor burden dynamics in liquid biopsy under different therapeutic regimens [In a prospective study, a combined detection of reatment . Accordiregimens . The detregimens .In Table 3ACTB, SOX17, and BRMS1. According to this study, plasma and SB‐converted DNA samples are stable and can be used safely for MSP when kept at −80 °C [Pre‐analytical conditions could significantly affect the results of DNA methylation analyses in liquid biopsies. For this reason, standardization of pre‐analytical conditions and implementation of quality control steps is extremely important for reliable liquid biopsy analysis, and a prerequisite for routine applications in the clinic. In a recent systematic study, the stability of DNA methylation in plasma and SB‐converted DNA under different storage conditions was evaluated . In the t −80 °C .https://fnih.org/what‐we‐do/biomarkers‐consortium/programs/ilsa)—who recently provided a white paper focused on the independent liquid biopsy‐ and standardization‐based programs [https://www.uke.de/english/departments‐institutes/institutes/tumor‐biology/european‐liquid‐biopsy‐society‐elbs/index.html) and the International Society of Liquid Biopsy (https://www.isliquidbiopsy.org/).Different blood collection tubes and cfDNA isolation methods can influence the cfDNA amount and the detection of promoter methylation , 83. Recprograms —the Euro4ctDNA methylation analysis has the potential to improve early cancer detection, which could lead to a substantial reduction in cancer‐related mortality. Biomarkers based on DNA methylation in ctDNA have a huge potential to be used for screening, early diagnosis, and in predicting and monitoring the response to specific therapies . However


Reduction of myocardial MIBG uptake is a supportive feature in the latest PD diagnostic criteria.To explore the clinical contribution of myocardial scintigraphy in discriminating different forms of parkinsonisms, especially when atypical features are present.123I‐MIBG myocardial scintigraphy in our Movement Disorders Center. Disease evolution was reviewed by applying the latest disease criteria for PD, multiple system atrophy (MSA), progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), as appropriate. Three diagnostic times were defined: T1 (before scintigraphy execution), T2 (immediately after the exam) and T3 (two years later). Early and delayed heart/mediastinum (H/M) ratios and washout rate (WR) were analyzed.Forty‐one patients with parkinsonism underwent a 123I‐MIBG myocardial scintigraphy was abnormal in all PD patients with dysautonomia. After 123I‐MIBG myocardial scintigraphy (T2), in 9 patients (22%) an improvement of diagnostic accuracy was reached.Myocardial scintigraphy showed impaired MIBG uptake in 12 out of 15 patients with a definite PD diagnosis, while normal uptake was found in 20 of 26 patients with no‐PD. Early and delayed H/M ratios were significantly lower in PD compared to overall no‐PD patients and MSA patients. 123I‐MIBG myocardial scintigraphy for the discrimination of PD from atypical parkinsonism, especially when dysautonomic symptoms are present.Diagnostic accuracy of myocardial scintigraphy in distinguishing PD from atypical parkinsonism was suboptimal. Nevertheless, this study confirmed the relevance of  Over the past decade, our center incorporated this technique in the diagnostic algorithm of patients presenting with a parkinsonian syndrome showing mixed or ambiguous clinical features in the attempt to reach a prompt differential diagnosis. The present study, consisting of a clinical revision of all these cases, aimed to investigate the contribution of 123I‐MIBG myocardial scintigraphy in the differential diagnosis of parkinsonisms.Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder clinically characterized by bradykinesia, rigidity, tremor at rest, and postural abnormalities with gait impairment.123I‐MIBG myocardial scintigraphy. The reasons for the execution of the test were the presence of at least one of the following clinical features: suboptimal levodopa response, early falls, autonomic dysfunction at disease onset or rapid progression of symptoms. Patients were screened for medical conditions and medications potentially influencing MIBG scintigraphy results such as diabetes mellitus, various cardiomyopathies, atherosclerotic coronary artery disease, cardiac autonomic neuropathy and pharmacologic compounds including antidepressants, antihypertensive drugs, MAO‐B‐I, Ca2+ channel antagonists, sympathomimetics/sympatholytics. Patients presenting with these confounding medical conditions or incomplete clinical information, were excluded from the study.An observational, retrospective study was conducted on patients with a parkinsonian syndrome referred to the Movement Disorders Unit of the Neurology Department of Trieste, Italy, between 2008 and 2017, who underwent a 123I‐MIBG myocardial scintigraphy execution. When available, brain MRI, 123I‐Ioflupane SPECT, and autonomic tests were also reviewed. In order to assess the specific contribution of MIBG scan to the diagnostic process, we defined three independent diagnostic time points: time of the clinical evaluation (T1), time of MIBG scan execution (T2), and a 2 years follow‐up assessment (T3). Notably, T1 was defined as the time point in which patients were clinically assessed immediately before undergoing the 123I‐MIBG myocardial scintigraphy while T2 was defined immediately after checking 123I‐MIBG scintigraphy results. Thus, a very short period of time (no longer than 10 days) intervened between T1 and T2 evaluations. For each diagnostic time point, patients were retrospectively assigned to two mutually exclusive diagnostic categories: PD and no‐PD, the latter including all patients deemed to have MSA, PSP, or CBS. The diagnostic categorization was conducted by two neurologists with expertise on movement disorders (M.A. and L.A.) by applying the latest recommended criteria for PD,The following clinical data were collected for each subject: age at disease onset, clinical phenotype , and asymmetrical vs. symmetrical parkinsonism), initial suspected diagnosis, responsiveness to levodopa, levodopa equivalent dose (LED), probable REM behavior disorder (pRBD), presence of clinical features suggesting autonomic dysfunction  was injected intravenously. Early and delayed imaging was performed 15 minutes and 4 hours after injection, respectively. The planar imaging was performed with a double–head gamma camera (Siemens Symbya Intevo 2) equipped with a low‐energy, high‐resolution parallel‐hole collimator. The heart to mediastinum ratio (H/M) was calculated by dividing the average counts of the left ventricular ROI by that of the average counts of mediastinum ROI according to the standard method described previously.123I‐MIBG washout rate (WR) background correct (%) was calculated with the following formula: ⦋(early heart counts − early mediastinum counts) − (late heart counts − late mediastinum counts) × 1.21⦌ / early heart counts − early mediastinum counts × 100. According to our database, a delayed H/M ratio of 1.6 or higher and washout 30% or lower are considered normal. If the tracer's uptake was normal or mildly reduced a CT/SPECT was also performed.For T‐test or Mann–Whitney test, as appropriate. Pearson's chi square test or Fisher's exact test were applied for categorical variables, as appropriate. A two‐tail P value <0.05 was considered statistically significant. Statistical analysis was performed by means of IBM Statistical Package for the Social Sciences (SPSS), version 24.0.Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and likelihood ratios of positive and negative results were calculated using published formulas. These parameters were calculated considering only the clinical diagnosis on follow‐up (T3). In order to verify the normal distribution of continuous variables we applied Shapiro–Wilk test. Variables with normal distribution were described as mean ± standard deviation (SD), while non‐normally distributed variables as median (range). Continuous variables were compared between groups using independent samples 123I‐Ioflupane SPECT. In all cases a significant decrement of dopamine transporter (DAT) binding in the striatum was observed. Table 123I‐MIBG myocardial scintigraphy, were the only variables which differed significantly between PD and no‐PD patients. Mean values of early and delayed H/M ratio and WR were significantly different in PD compared to overall no‐PD patients (P < 0.05) and to MSA patients (P < 0.05). When comparing PD to PSP patients, only WR differed significantly (P < 0.05), while only a trend towards significance was found for delayed H/M ratio (P = 0.065) , 7 patients received a diagnosis of probable PD, 10 patients of MSA , and 8 patients of PSP . Three patients were considered uncertain, and 13 undefined. Within the latest group, 3 patients had a clinical course suggestive of MSA, but the lack of evidence for autonomic dysfunction did not allow to formally include them in the MSA group at this time point.Immediately before undergoing 123I‐MIBG myocardial scintigraphy, a different diagnosis was obtained in nine patients . This was more evident for PD: 5 undefined patients on T1 turned into probable PD on T2: in these cases, on T1 evaluation, the number of red flags was not higher than two, but still outweighed the number of supportive features. The finding of cardiac sympathetic denervation on MIBG scintigraphy on T2, increased the number of supportive features, thus counterbalancing the number of red flags. Hence, for these patients, in the absence of any absolute exclusion criteria, the diagnosis changed from undefined to probable PD.Following On final follow‐up (T3), the number of undefined patients further decreased (n = 3). Three undefined patients were diagnosed with possible MSA as autonomic dysfunction  became clinically evident. Only 1 patient, who was previously deemed uncertain on T1, then included in the PD group on T2, had his final diagnosis disconfirmed at T3, that is, from probable PD to possible MSA. This occurred because of the emergence of an absolute exclusion criteria, that is, otherwise unexplained cerebellar signs. For all the other patients, the follow‐up evaluation confirmed the diagnosis established on T2  of patients who were assigned to the PD category at T3, showed a significant impairment in the uptake of the radiotracer . Conversely, the exam resulted normal in 20/26 of subjects who were assigned to the no‐PD category at T3. This group included 12/15 patients with MSA, 6/8 patients with PSP, and 2/3 undefined patients  in patients without a definite diagnosis at baseline (uncertain and undefined groups). Intuitively, these patients are likely to benefit the most from receiving a proper diagnosis, which would have otherwise remained elusive. Interestingly, only one of these patients had a disconfirmation of the diagnosis on the follow‐up evaluation. Finally, one out of the three patients who, despite a normal MIBG uptake, met the diagnosis of PD at the end of the study, deceased in the following year with a final diagnosis of MSA. In this case, a clinical misdiagnosis, due to the relatively brief follow‐up period (2 years), is likely to have occurred.The main finding of our study is the relevant contribution of MIBG scintigraphy to provide a correct diagnosis in a subset of parkinsonian patients with atypical features and uncertain diagnosis. On this topic, the role of 123I‐MIBG myocardial scintigraphy accuracy in differentiating PD from atypical parkinsonisms improved when only patients with autonomic dysfunction were considered. However, in line with literatureIn the present study, patients with dysautonomia were identified by the presence of orthostatic hypotension, or symptoms suggesting bladder or sexual dysfunction . Only a minority of patients (14) underwent specific autonomic nervous system testing. For this reason, the incidence of autonomic dysfunction in our cohort may have been likely underestimated and this limit is due to the retrospective design of the study. Interestingly, all PD patients with dysautonomia on T1, had an abnormal scan: as a consequence, we found that Finally, specific considerations should be made regarding the different semi‐quantitative measures used to quantify MIBG myocardial uptake (early and delayed H/M and WR). Some authors demonstrated that WR has the highest accuracy in discriminating MSA from PD patients.123I‐MIBG myocardial scintigraphy data were analyzed according to all the available semi‐quantitative parameters, including early H/M ratio, delayed H/M ratio, and WR, thus improving the overall interpretation of our findings. Furthermore, the relatively long follow‐up evaluation (T3) of two years provided us with a reliable observational window on the natural evolution of the disease.We acknowledge different limitations, mostly inherent to the retrospective nature of this study, including the likelihood of selection biases. In particular the clinical characterization of patients is not extensive . Another limitation concerns the disease duration at the time of MIBG scintigraphy execution, which was longer than 3 years, while a prompt differential diagnosis should ideally be established earlier. Furthermore, the relatively small sample size and the lack of a pathological confirmed diagnosis may have further limited the generalizability of our findings. In the effort to partially overcome these limitations, we identified a very short period of time (in the order of a few days) between T1  and T2 (time of MIBG scan). This allowed us to consider as virtually negligible other potentially interfering variables on MIBG results between the two evaluations. 123I‐MIBG myocardial scintigraphy in patients with a parkinsonian syndrome of uncertain nature, this test led to a definite diagnosis in up to 50% of cases. Notably, all the diagnoses established after 123I‐MIBG myocardial scintigraphy execution were subsequently confirmed at 2 years follow‐up, except for only one case. Although our study methodology does not allow to draw conclusive recommendations regarding the diagnostic utility of this technique, our results suggest that 123I‐MIBG myocardial scintigraphy could be an important tool, especially for the differential diagnosis between PD and MSA in patients reporting dysautonomic complaints. We trust that our data will contribute to the ongoing debate surrounding the future role of 123I‐MIBG myocardial scintigraphy in the new diagnostic criteria for MSA. In this setting, large prospective studies, possibly incorporating multimodal biomarkers, are strongly needed.In the present study, diagnostic accuracy of myocardial scintigraphy in distinguishing PD from atypical parkinsonism was suboptimal. Nevertheless, when evaluating the specific diagnostic contribution of (1) Research project: A. Conception, B. Organization, C. Execution; (2) Statistical Analysis: A. Design, B. Execution, C. Review and Critique; (3) Manuscript: A. Writing of the first draft, B. Review and Critique.M.C.: 1A, 1B, 2A, 3AF.D.: 1A, 1B, 3BP.P.: 1C, 2B, 3AC.B.: 1C, 2A, 2BS.A.: 2A, 2C, 3AA.L.: 1B, 1CA.C.: 2C, 3BF.G.: 1CS.C.: 1BP.M.: 1A, 2C, 3CEthical Compliance Statement: The study was approved by the local ethics committee “Comitato Etico Unico Regionale – CEUR”. Informed consent for data collection was undersigned by all patients included in the present study. We confirm that we have read the Journal's position on issues involved in ethical publication and affirm that this work is consistent with those guidelines.Funding Sources and Conflict of Interest: No specific funding was received for this work. The authors declare that there are no conflicts of interest relevant to this work.Financial Disclosures for the Previous 12 Months: The authors declare that there are no additional disclosures to report.


Autism spectrum disorder (ASD) is neurodevelopmental disorder characterized by core deficits in social interaction and communication. ASD occurs in 0.8–2.0% of school‐aged children, some experiencing comorbid disruptive behaviors.t‐test to verify the effect of the whole PCIT treatment session, which included two phases: child‐directed interaction (CDI) and parent‐directed interaction (PDI) for all four cases , ranged in age from 3 to 5 years  and were diagnosed with ASD, based on the DSM‐5 criteria. While clinic‐based PCIT provides live parent coaching in a clinic, I‐PCIT uses a webcam to stream parent‐child interactions in real‐time from their home. PCIT is an evaluation‐oriented treatment. Assessments were conducted before and after treatment using observation and standardized questionnaires, mainly the Eyberg Child Behavior Inventory (ECBI). The ECBI was used to assess the children's problematic behaviors. The scale includes 36 items and comprises an intensity scale and a problem scale. The intensity scale measures the frequency of various behaviors on a 7‐point scale and the problem scale classifies behavior as either problematic or not (yes or no). The Japanese version of the ECBI was standardized by Kamo and the cutoff scores are 124 for the intensity scale and 13 for the problem scale in Japan.ses Fig. . Second,ses Fig. .n = 4, ECBI intensity scores: P = 0.0002, effect size(r) = 0.97; ECBI problem scores: P = 0.018, effect size(r) = 0.90; Fig. n = 3) and were 62.6 % and 100%, respectively for I‐PCIT (n = 1; Fig. Figure PCIT was effective in improving behavioral problems in all cases, regardless of the PCIT type. Using either type of PCIT effectively, seamless PCIT treatment is feasible in the COVID‐19 era. As our previous study,The authors declare no conflicts of interest.M.M. and Y.M. drafted the initial manuscript and approved the final manuscript. M.K. conceptualized the study and K.K. and T.K. supported the implementation of the PCIT therapy. All authors read and approved the final manuscript.