Diabetes mellitus (DM) is a major chronic disease with ever‐increasing prevalence and a variety of serious complications for persons with DM, such as cardiovascular and/or renal complications. New glucose‐lowering therapies like DPP‐4 inhibitors, GLP‐1 receptor agonists, and SGLT‐2 inhibitors have undergone cardiovascular outcome trials (CVOTs) for type 2 diabetes (T2DM), as by the guidance of the FDA. However, CVOTs for type 1 diabetes (T1DM) are generally lacking. Both, persons with T1DM and T2DM, are burdened with a high incidence of cardiovascular and renal disease such as atherosclerotic cardiovascular disease (ASCVD) and diabetic kidney disease (DKD). Although pathologies of the two types of diabetes cannot be compared, similar mechanisms and risk factors like sex, hyperglycaemia, hypertension, endothelial damage and (background) inflammation have been identified in the development of CVD and DKD in T1DM and T2DM. Recent CVOTs in T2DM demonstrated that SGLT‐2 inhibitors, besides exerting a glucose‐lowering effect, have beneficial effects on cardiovascular and renal mechanisms. These mechanisms are reviewed in detail in this manuscript and evaluated for possible transferability to, and thus efficacy in, T1DM. Our review of current literature suggests that SGLT‐2 inhibitors have cardioprotective benefits beyond their glucose‐lowering effects. As this mainly has been observed in CVOTs in T2DM, further investigation in the adjunctive therapy for type 1 diabetes is suggested. Both, persons with T1DM and T2DM, are burdened with a high incidence of cardiovascular and renal disease such as atherosclerotic cardiovascular disease (ASCVD) and diabetic kidney disease (DKD). Although pathologies of the two types of diabetes cannot be compared, similar mechanisms and risk factors like sex, hyperglycaemia, hypertension, endothelial damage and inflammation have been identified in the development of ASCVD and DKD in T1DM and T2DM. Recent CVOTs in T2DM demonstrated that SGLT‐2 inhibitors, besides exerting a glucose‐lowering effect, have beneficial effects on cardiovascular and renal mechanisms. These mechanisms are reviewed in detail in this manuscript and evaluated for possible transferability to, and thus efficacy in, T1DM. T1DM usually develops early in patients’ lives (childhood or adolescence) and is classified as autoimmune disease with yet uncertain origin, resulting in systemic insulin deprivation, hyperglycaemia and a bias for the development of ketoacidosis. In T2DM, the body's cells develop an insulin resistance (IR) and beta‐cell dysfunction over time and systemic hyperglycaemia occurs. A variety of treatment options aside from insulin have been developed especially for T2DM, including sodium/glucose co‐transporter 2 inhibitors (SGLT‐2is). SGLT‐2is aim at reducing hyperglycaemia by removal of excess glucose through the kidneys by increasing glycosuria. Different SGLT‐2is have undergone extensive evaluation in various cardiovascular outcome trials (CVOTs); however, as these studies only address patients with T2DM, the late‐breaking question has been if SGLT‐2is will confer equal or varying benefits when used as an adjunct treatment to insulin in T1DM. While first efficacy and safety studies in T1DMThis review aims at highlighting and comparing mechanisms in the genesis of the two prominent diabetic comorbidities CVD and DKD between T1DM and T2DM. Common features of CV and renal disease in T1DM and T2DM include risk factors like hyperglycaemia, blood pressure (BP), body weight and associated effects. In addition, other mechanisms affected by SGLT‐2is like the renal tubuloglomerular feedback and its implications, cardiac substrate utilization in diabetes, the impact of inflammation, and direct effects on cardiac function are discussed. The review aims at comparing the learnings from SGLT‐2i CVOTs in T2DM to T1DM on a mechanistic basis and, to best current knowledge, elaborate why and when it could be particularly advantageous to consider SGLT‐2i use as an adjunct therapy to insulin in patients with T1DM, especially with respect to concomitant CVD and renal outcomes.2Sodium/glucose co‐transporters (SGLTs) are located at the apical membrane of the renal tubules and reabsorb filtered glucose by actively transporting glucose together with sodium against a concentration gradient, while the basolaterally located glucose transporters (GLUTs) mediate the transport of glucose back into the circulation along an existing concentration gradient.Inhibition of SGLT‐2 efficiently decreases the amount of glucose and sodium reabsorbed and fed back into systemic circulation. However, with SGLT‐2 inhibition alone, it has been shown that only around 50%‐60% of filtered glucose are excreted in normoglycaemic individuals, as significant downstream compensation is achieved by an increase in the expression or activity of renal SGLT‐1 in response to blockage of SGLT‐2.The major risk associated with administration of SGLT‐2is, particularly in T1DM, has been shown to be augmented rates of diabetic ketoacidosis (DKA)—also in euglycaemic range.2 or a baseline urine albumin‐to‐creatinine ratio (UACR) >1000 mg/g benefit from SGLT‐2i treatment.As SGLT‐2–dependent glycaemic control is directly linked to the renal glomerular filtration rate (GFR), an attenuation of the glycaemic lowering effect with decreasing kidney function is implied.3Even though management of micro‐ and macrovascular comorbidities in T1DM has improved over the last 15 years, patients with T1DM still face a substantially increased risk of all‐cause mortality and of developing CVD like coronary heart disease (CHD)These developments become particularly critical in the light of known complications of inadequate glycaemic control: the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) [DCCT‐EDIC] study demonstrated that intensive glycaemic control reduces the long‐term risk of developing macrovascular disease in T1DM.Along this line, it is important to be aware of renal (dys‐)function in T1DM: it has been demonstrated that an increase in HbA1c ,2 are limited as the DECLARE‐TIMI 58 and EMPA‐REG OUTCOME trials included only 7.4% and 26% of patients with an eGFR < 60 ml/min/1.72m2, respectively,22 at baseline.All SGLT‐2i CVOTs either met their primary end‐point 3‐point major adverse cardiovascular events  or showed a significant reduction in CV outcomes in co‐primary (DECLARE‐TIMI 58), secondary and exploratory end‐points. A meta‐analysis of the outcomes of CANVAS, EMPA‐REG OUTCOME and DECLARE‐TIMI 58 demonstrated an overall significant improvement of 3P‐MACE in patients with previous CVD (secondary prevention), yet not in patients with multiple risk factors (primary prevention).The CREDENCE trial confirmed the secondary/exploratory renal outcomes reported in SGLT‐2i CVOTs, fortifying the idea of a class effect of SGLT‐2is, particularly in relation to renal benefits.So far, there are no trials reporting CV or renal outcomes of SGLT‐2is as an adjunct therapy in T1DM. In contrast to CVOTs in T2DM, SGLT‐2i trials conducted in T1DM were considerably shorter, focused on efficacy and safety rather than CV or renal outcomes and had considerably smaller trial populations making them underpowered compared to CVOTs. However, these trials gave a first insight into the effects of SGLT‐2is on risk factor management in T1DM. So far, a phase II trial for canagliflozin5Clinically, DKD is defined as persisting, severely elevated albuminuria of > 300 mg/24 h or an albumin‐to‐creatinine ratio (ACR) of > 300 mg/g, usually accompanied by a progressive loss of GFR, concomitant diabetic retinopathy and characterized by lack of other forms of kidney disease.Pathophysiology of DKD in both T1DM and T2DM has been associated with a variety of processes: major structural changes during the progression of DKD include endothelial fenestrations, mesangial expansion, loss of podocytes with effacement of foot processes and glomerular sclerosis.5.1The major commonality of T1DM and T2DM—hyperglycaemia—was shown to likely be the biggest risk factor in the initiation and progression of hyperfiltration. Hyperfiltration as first step of DKD is experienced by 10%‐67% of patients with T1DM and 6%‐73% of patients with T2DM.Concomitant to an increase in glucose reabsorption by SGLT‐2 is a decrease in the delivery of sodium chloride (NaCl) to the macula densa.A recent study investigated the effects of dapagliflozin on renal function in a small cohort of patients with T2DM (n = 24), compared to the sulfonylurea gliclazide.2 and 60 to < 90 ml/min/1.73m2 and close to significant positive effects in patients with an eGFR < 60 ml/min/1.73m2 . Similarly, dapagliflozin significantly reduced the risk for the renal‐specific outcome across all ranges of UACR (<30 mg/g to > 300 mg/g).Recent studies demonstrated that SGLT‐2is may not only have a positive impact on the development and progression of hyperfiltration, but may also exert positive effects in patients already presenting with albuminuria and declining GFR. For example, an analysis of the DECLARE‐TIMI 58 trial (T2DM) demonstrated that dapagliflozin had significant positive effects on the renal‐specific outcome in patients with an eGFR ≥ 90 ml/min/1.73m5.2It has been demonstrated that particularly an early decline in the eGFR slope is correlated with subsequent risk of ESRD, for which reason maintaining GFR is the primary focus for prevention and slowing the progression of DKD to ESRD.Thus, current first‐line treatment for hypertension and DKD in DM are RAS blockers. Lowering systemic BP was shown to slow the initiation and progression of DKD in T1DM 2; ESDR, or renal death), while patients without baseline use of ACE inhibitors or ARBs showed a 23% reduction in the composite renal‐specific outcome (not significant).2 were excludedMore studies for primary prevention of DKD with SGLT‐2is are needed in T1DM and T2DM as reliable data are lacking so far. A recent study demonstrated a promotion of global RAS activation upon SGLT‐2i treatment in T1DM.5.3Compared to placebo, all SGLT‐2 is  have demonstrated a modest increase in haematocrit which cannot be explained solely by their diuretic effect.6DM significantly increases the risk for CVD and CVD is the leading cause of mortality and morbidity in T1DM and T2DM.One of the most important risk factor linking both diseases is chronic hyperglycaemia which serves as both initiation and progression factor, affecting several downstream mechanisms.6.1Hyperglycaemia has been proposed to play a role in chronic low‐grade inflammatory processes, thereby damaging endothelial integrity, to affect BP by various mechanisms like promoting oxidative stress by increasing advanced glycosylation end‐products (AGEs) and reactive oxygen species (ROS) production, to influence vasoactive substances, and many other mechanisms ultimately promoting CVD. While glycaemic control may play an important role in lifelong risk reduction, it has been argued for the setting of CVOTs in T2DM that cardioprotective effects are independent of glycaemic improvements for two reasons: first, the changes observed in the placebo subtracted difference in glycaemic control in SGLT‐2i CVOTs were modest and in similar ranges as in dipeptidyl‐peptidase‐4 inhibitor (DPP‐4i) CVOTs which all showed neutral effects on CV outcomes.6.22 to > 90 ml/min/1.73 m2.All SGLT‐2 inhibitors showed remarkable and similar improvements of HHF in their corresponding CVOTs in T2DM, ranging from 33%+)/hydrogen (H+) exchange in cardiomyocytes  Arterial stiffness and sodium retention, resulting in volume expansion, are other proposed mechanisms of hypertension in DM,6.5Particularly T2DM, overweight, and obesity are tightly interwoven. However, the proportion of overweight/obese patients has increased dramatically also in T1DM,SGLT‐2is caused a loss of mean total body weight of up to ≈2kg in T2DM CVOTs CVD development in DM and obesity is linked by the presence of low‐grade inflammation among other factors.In summary, the hypothesis of reduced inflammation is based on several observations: (1.) reduction in body weight, known to contribute to the decline of low‐grade inflammation in obese individuals; (2.) reduction in hyperglycaemia, shown to reduce inflammatory markers; (3) reduction in serum uric acid, a known activator of the NALP3 inflammasome; (4.) increase in ketone bodies conveying anti‐inflammatory signalling; (5.) reduction in oxidative stress; and (6.) the suppression of the pro‐inflammatory AGE‐RAGE‐axis, as reviewed elsewhere.6.6+/K+ ATPase of the proximal tubular cells of the kidneys upon an increase in glucose uptake and the concomitant increase in sodium uptake in the diabetic state, which results in a tissue‐specific local decrease in oxygen partial pressure, ultimately promoting a progress of interstitial fibrosis.Studies suggest that CV benefits of SGLT‐2is in T2DM are not solely mediated by direct effects , but also through modulation of the sympathetic nervous system (SNS).7Despite medical and technological advancements, there still is a major unmet need in the treatment of T1DM. Patients with T1DM are faced with increased rates of CV and all‐cause mortality, CVD and renal disease. SGLT‐2is have shown to be a promising treatment option in T2DM, demonstrating strong CV and renal benefits in designated CVOTs. As SGLT‐2is have insulin‐independent mechanisms of action, the question of transferability of these effects from T2DM to T1DM is debated heatedly. First results from trials with SGLT‐2is as adjunct therapy in T1DM  have demonstrated effects on CV risk factors like HbA1c, BP, and body weight in T1DM, comparable to results obtained in CVOTs in T2DM. However, these studies were designated application safety trials and not designed for CV or renal outcomes.2).While many pathological mechanisms have similar initiation factors, like hyperglycaemia, others result in substantial differences between the two diseases, e.g. IR or obesity. For example, there is a strong association of the presence of IR and CKD.Current data on SGLT‐2i–mediated protective mechanisms range from systemic effects, like increased glycosuria and natriuresis resulting in decreased glucotoxicity, body weight, plasma volume, BP, and arterial stiffness, to direct cardiac and renal protective mechanisms like reduction in inflammation, oxidative stress, and many more, ultimately hypothesized to improve cardiac, vascular, and renal structure by decreasing incidence of cardiac and renal hypertrophy, thickening, stiffness and fibrosis.It remains to be elucidated, however, if described effects of SGLT‐2is are of comparable magnitude in the primary and/or secondary prevention of the comorbidities of the two different diseases. It may well be possible that due to longer exposure times or metabolic effects, SGLT‐2is may exert a stronger or weaker effect in T1DM. Either way, whether this is desirable has yet to be confirmed by observational studies in the long run.OS has acted as a member of advisory boards and given lectures for companies; and is CEO and founder of Sciarc GmbH. PV discloses the potential following conflict of interest: participation in expert committees for Astra Zeneca, Boehringer Ingelheim, Novo Nordisk, Daiichi‐Sankyo and Sanofi; lectures for Abbott, AstraZeneca, Bayer, Eli Lilly, Hikma, Merck‐Sharp‐Dohme, Novo Nordisk, Novartis, Pfizer and Sanofi; and research grants from Abbott, Bristol‐Myers‐Squibb‐AstraZeneca and Novo Nordisk. ES reports personal fees from Oxford Diabetes Trials Unit, AstraZeneca, Bayer, Berlin Chemie, Boehringer Ingelheim, Menarini, Merck Serono, Excemed, Novartis, Novo Nordisk and Sanofi. AC discloses the potential following conflict of interest: advisory board membership: Abbott, Astra Zeneca, Boehringer Ingelheim, DOC Generici, Eli Lilly, Janssen, Mundipharma, Novo Nordisk and OM Pharma; lectures for Astra Zeneca, Berlin Chemie, Boehringer Ingelheim, Eli Lilly, Mundipharma, Novo Nordisk and Roche Diagnostics; and research grants from Astra Zeneca, Eli Lilly, Mitsubishi and Novartis.OS, ES, PV and AC supported the content and writing of the white paper. All authors read and approved the final manuscript.


Neurocognitive and psychiatric disorders have significant consequences for quality of life in patients with Parkinson's disease (PD). In the current study, we evaluated microstructural white matter (WM) alterations associated with neurocognitive and psychiatric disorders in PD using neurite orientation dispersion and density imaging (NODDI) and linked independent component analysis (LICA). The indices of NODDI were compared between 20 and 19 patients with PD with and without neurocognitive and psychiatric disorders, respectively, and 25 healthy controls using tract‐based spatial statistics and tract‐of‐interest analyses. LICA was applied to model inter‐subject variability across measures. A widespread reduction in axonal density (indexed by intracellular volume fraction [ICVF]) was demonstrated in PD patients with and without neurocognitive and psychiatric disorders, as compared with healthy controls. Compared with patients without neurocognitive and psychiatric disorders, patients with neurocognitive and psychiatric disorders exhibited more extensive (posterior predominant) decreases in axonal density. Using LICA, ICVF demonstrated the highest contribution (59% weight) to the main effects of diagnosis that reflected widespread decreases in axonal density. These findings suggest that axonal loss is a major factor underlying WM pathology related to neurocognitive and psychiatric disorders in PD, whereas patients with neurocognitive and psychiatric disorders had broader axonal pathology, as compared with those without. LICA suggested that the ICVF can be used as a useful biomarker of microstructural changes in the WM related to neurocognitive and psychiatric disorders in PD. This study demonstrates that axonal loss, indicated by a reduction in the intracellular volume fraction, is a major factor underlying white matter pathology related to neurocognitive and psychiatric disorders in Parkinson's disease. Furthermore, patients with neurocognitive and psychiatric disorders had broader axonal pathology (posterior predominant) compared with those without such disorders. Using neurite orientation dispersion and density imaging, this study demonstrates that axonal loss, indicated by a reduction in the intracellular volume fraction (ICVF), is a major factor underlying white matter (WM) pathology related to neurocognitive and psychiatric disorders in Parkinson's disease (PD). However, patients with neurocognitive and psychiatric disorders had broader axonal pathology (posterior predominant) compared with those without such disorders. Linked independent component analysis suggested that ICVF had the highest contribution to the diagnosis, thus representing a useful biomarker to detect microstructural changes in the WM related to neurocognitive and psychiatric disorders in PD.1Parkinson's disease (PD) is primarily considered to be a neurodegenerative movement disorder that is characterized by bradykinesia, rigidity, resting tremor, and postural abnormalities, with the pathological hallmarks of the loss of dopaminergic neurons in the substantia nigra  are associated with many disorders affecting cognition and physiological states Fields, . DiffusiOn the contrary, neurite orientation dispersion and density imaging (NODDI) can be used to address the limitations of DTI. NODDI was developed on the basis of a multicompartment  diffusion model with the particular advantage of providing useful microstructural indices from multishell diffusion magnetic resonance imaging (MRI) data that can be acquired in a clinically feasible amount of time  and tract‐of‐interest (TOI) analyses we evaluated differences in NODDI metrics between healthy controls and PD patients with and without NCPs in addition to DTI metrics. Also, recent studies of PD patients  based on the clinical diagnostic criteria for PD of the Movement Disorder Society  or 0 , respectively. Twenty‐five age‐ and sex‐matched healthy controls  with no history of neurologic or psychiatric diseases and no abnormal signals on structural MRI were recruited as a control group. The demographic and clinical characteristics of all participants are shown in Table The NCPs of PD patients might be caused by overlapping pathophysiology, whereas some symptoms might be similar Fields, . Thus, P2.2b values  along 64 isotropic diffusion gradients for each shell. The sequence parameters were as follows: repetition time (TR), 3,300 ms; echo time (TE), 70 ms; field of view (FOV), 229 × 229 mm; matrix size, 130 × 130; resolution, 1.8 × 1.8 mm; slice thickness, 1.8 mm; and acquisition time, 7.29 min. Acquisition of each diffusion‐weighted image was completed with a gradient‐free image (b = 0). Standard and reverse phase‐encoded blipped images with no diffusion weighting (Blip Up and Blip Down) were also acquired to correct for magnetic susceptibility‐induced distortions related to the echo‐planar imaging acquisitions  with a 64‐channel head coil was used for all imaging. Diffusion‐weighted imaging (DWI) was performed by spin‐echo echo‐planar imaging in the anterior‐to‐posterior phase‐encoding direction. Multishell DWI was performed using two 2.3The diffusion‐weighted data were corrected for susceptibility‐induced geometric distortions, eddy current distortions, and inter‐volume subject motion using the EDDY and TOPUP toolboxes . Maps of ICVF, ODI, and isotropic volume fraction  were generated using Accelerated Microstructure Imaging via Convex Optimization , and radial diffusivity (RD) maps  were then generated for all subjects using the DTIFIT tool of the FMRIB Software Library 5.0.9  to fit the tensor model to each voxel of the DWI data  common space  using the FMRIB's nonlinear registration tool   run on a Matlab 2014a platform  12 , which models inter‐subject variability across measures, as described in detail in earlier articles , where the number of components should be less than the number of subjects/4.Data‐driven decomposition of the imaging features obtained from all subjects was classified into independent components using FMRIB's linked independent component analysis , except for general linear model (GLM) analysis, which was performed using the FSL and SPM. A t‐test for two groups and one‐way analysis of variance (ANOVA) for three groups for continuous variables and the chi‐squared test for categorical variables.The Shapiro–Wilk test was used to assess the normality of the data. The demographic and clinical data were analyzed using the Mann–Whitney U test or unpaired For TBSS analyses, a voxel‐wise GLM framework with one‐way ANOVA followed by pairwise post hoc comparisons, which included age and sex as covariates, was applied to compare all diffusion metrics among groups  using the FSL randomize tool with 5,000 permutations. The results were then corrected for multiple comparisons by controlling family‐wise error (FWE) and applying threshold‐free cluster enhancement. The same method was applied for voxel‐wise correlation analysis among all diffusion metrics with disease duration or MDS‐UPDRS part III of the whole PD group and with MDS‐UPDRS part I.1–I.6 scores of the PD‐wNCPs group.p values by conducting nonparametric Mann–Whitney U tests. The mean diffusion metric values of each TOI were then correlated with the disease duration or MDS‐UPDRS part III of the whole PD group and with MDS‐UPDRS part I.1–I.6 scores in PD‐wNCPs using Spearman's rank correlation coefficient. Considering the exploratory nature of this analysis, Bonferroni correction was not applied.For TOI analyses, the mean diffusion metric values in the WM tracts were compared among groups with the Kruskal–Wallis test. Then, the Benjamini–Hochberg false discovery rate (FDR) correction was applied to correct multiple testing (11 TOIs). Pairwise comparisons were then performed to detect significant main effects on any area with significant FDR‐corrected For VBM analysis, WM volumes were compared between groups using GLM analysis of covariance, with age, sex, and total intracranial volume as covariates. Comparisons of WM volumes were corrected for multiple comparisons using the FWE rate.d  lower FA and ICVF values and higher MD, RD, and AD values were observed in the PD‐wNCPs group than in the healthy controls, and lower ICVF values and higher MD, RD, and AD values were observed in the PD‐wNCPs group than in the PD‐woNCPs group. Changes in all indices were observed across the broad areas of the WM compared with the healthy controls. Changes in ICVF and MD values predominantly occurred in the posterior portion of the WM, whereas changes in the RD and AD values were observed in the circumscribed areas of the WM compared with the PD‐woNCPs group. Compared with the healthy controls, the PD‐woNCPs group had significantly (pFWE < 0.05) lower FA and ICVF values and higher MD and RD values. Changes in the FA and RD values were observed across the broad areas of the WM, whereas changes in the ICVF and MD values predominantly occurred in the anterior portion of the WM. Details regarding the anatomical regions, peak t‐values, and peak MNI coordinates of significant clusters are shown in Table Figure 3.3p < .05) lower FA  and ICVF  values and higher MD  and RD  values. Furthermore, the PD‐wNCPs group had lower FA and ICVF values and higher MD and RD  values, as compared with the healthy controls. As compared with the PD‐woNCPs group, the MD , RD (SLF), and ICVF (SLF) values were lower in the PD‐wNCPs group.Figure 3.4There was no significant difference in total and focal WM volumes among the three groups.3.5F = 12.03; corrected p < .05) main effects on the diagnosis . IC1 is a multimodal component mainly driven by ICVF (59% weight) followed by FA (23%), RD (7%), MD (5%), AD (2%), ODI (2%), and WM volume (2%)  and PD‐woNCPs  group. The PD‐woNCPs group also had significantly weaker subject loadings than those of the healthy controls   had significant  compared to DTI, NODDI gave a pattern of results that was more regionally specific, (b) both TBSS and TOI analyses showed axonal loss in the WM of PD patients with and without NCPs, whereas the PD‐wNCPs group had more extensive axonal pathology , as compared with the PD‐woNCPs group, and (c) in LICA, ICVF, the measure of neurite density had the highest contributions to the main effect of diagnosis.Lower ICVF in the WM areas of PD patients with and without NCPs, which indicated an axonal density reduction  in the PD‐wNCPs group, as compared with that of the healthy controls and PD‐woNCPs group, respectively. Our results are in agreement with those of previous DTI studies showing a lower FA value in the anterior cingulate fiber tracts of PD patients without dementia and in the anterior and posterior cingulate fiber tracts of PD patients with dementia, as compared with that of healthy controls, and in the posterior cingulate fiber tracts of PD patients with dementia, as compared with those without  using LICA . Because the NCPSs of PD patients might occur earlier than motor symptoms  in the PD‐wNCPs group than in the PD‐woNCPs group. Furthermore, the LICA results showed that ICVF can be used as a useful measure for the evaluation of microstructural changes in the WM related to the NCPs of patients with PD. Taken together, these results suggest the potential of NODDI as an imaging biomarker for NCPs‐related microstructural changes in the WM of PD patients.Journal of Neuroscience Research this manuscript presents an accurate and transparent account of the study being reported and that all critical details describing the methods and results are present.The authors, reviewers, and editors affirm that in accordance with the policies set by the The authors have no conflict of interest to declare.Conceptualization, C.A., K.K., T.H., T.O., H.T.‐A., N.H., and S.A.; Data Curation, C.A., Yu.S., W.U., S.M., G.O., Ya.S., A.U., and N.H.; Formal Analysis, C.A.; Investigation, C.A. and A.H.; Methodology, C.A., K.K., T.H., Yu.S., W.U., T.O., H.T.‐A., and S.A.; Writing – Original Draft, C.A.; Writing – Review & Editing, C.A., K.K., T.H., T.O., H.T.‐A., A.H., G.O., Ya.S., A.U., T.A., A.W., K.K.K., M.H., N.H., and S.A.; Funding Acquisition, K.K. and S.A.; Supervision, K.K., T.H., T.A., A.W., K.K.K., M.H., and S.A.; Validation, K.K., A.H., and M.H.; Software, Yu.S. and W.U.; Visualization, Yu.S., W.U., and S.M.Figure S1 DTI  and NODDI  maps of one healthy control and one patient with Parkinson's disease. Abbreviations: AD, axial diffusivity; FA, fractional anisotropy; ICVF, intracellular volume fraction; ISO, isotropic volume fraction; MD, mean diffusivity; ODI, orientation, dispersion index; RD, radial diffusivityFigure S2 Relative weights indicating the contribution of each modality within each componentClick here for additional data file.Transparent Science Questionnaire for AuthorsClick here for additional data file.Transparent Peer Review ReportClick here for additional data file.


To re‐evaluate the suitability of calf circumference as a surrogate marker of low muscle mass measured by both bioelectrical impedance analysis (BIA) and dual‐energy X‐ray absorptiometry (DXA). We also examined the effects of obesity and age on low muscle mass screening using calf circumference.In total, 1239 adults participated in this cross‐sectional study. We measured the maximum calf circumference in a standing position and appendicular skeletal muscle mass (ASM) using BIA and DXA. We defined low muscle mass based on the Asian Working Group for Sarcopenia 2019 consensus.2  and DXA‐measured ASM/height2 . In the subgroup analyses by obesity and age, calf circumference was also positively correlated with ASM/height2. The optimal calf circumference cut‐offs for low muscle mass screening measured by BIA and DXA were 35 cm  and 36 cm  for men, and 33 cm  and 34 cm  for women, respectively.Calf circumference was positively correlated with BIA‐measured ASM/heightGeriatr Gerontol Int 2020; 20: 943–950.Calf circumference is positively correlated with BIA‐ and DXA‐measured muscle mass regardless of obesity and age and is a simple and accurate surrogate marker of muscle mass for diagnosing sarcopenia.  Sarcopenia,Dual‐energy X‐ray absorptiometry (DXA) is most widely used for assessing muscle mass in the diagnosis of sarcopenia.2 measured by DXA,2 for determining LMM using bioelectrical impedance analysis (BIA) and DXA are separately proposed by the AWGS 2019 consensus.Calf circumference is positively correlated with appendicular skeletal muscle mass (ASM) and ASM/height2 measured by both BIA and DXA and to re‐evaluate the validity of the optimal calf circumference cut‐offs for LMM screening. Furthermore, we examined the effect of obesity and age on LMM screening measured by calf circumference.Therefore, we aimed to investigate the relationship between calf circumference and ASM/heightn = 6), those with metal implants or fragments in their bodies and those unable to remove metal items they were wearing at the time of measurement (n = 51), leaving 1239 participants (827 men and 412 women) for analysis.This cross‐sectional study used baseline measurements from the Waseda Alumni's Sports, Exercise, Daily Activity, Sedentariness and Health Study , a prospective cohort study whose participants included Waseda University alumni and their spouses aged ≥40 years. The participants selected one of four cohorts (cohorts A–D) with different measurement items. The study participants comprised 1296 middle‐aged and elderly adults who received calf circumference, muscle strength, BIA and DXA measurements in cohort D of the WASEDA'S Health Study between March 2015 and January 2020. Of the 1296 participants, we excluded foreign nationals . All participants received an explanation of the study before measurement and provided their written informed consent.Trained researchers measured all participants in the morning after the participants had fasted for ≥12 h, and recorded height and weight in 0.1‐cm and 0.1‐kg increments, respectively, and calf circumference in 0.1‐cm increments using a steel measuring tape . Calf circumference was measured according to the protocol of the International Society for the Advancement of Kinanthropometry. Care was taken not to compress the subcutaneous tissue when placing the measuring tape around the calf and when measuring the calf circumference twice on each side where the circumference was the largest in the standing position; the average was calculated Fig. .R2 = 0.92).et al.We used multifrequency BIA analyzer  to measure bioimpedance according to the manufacturer's protocol, with participants wearing light clothing and barefoot. The device uses six electric frequencies  and employs the manufacturer's proprietary formula to estimate ASM. A previous study showed a strong correlation between the ASM measured using this device and that measured by DXA  R2 = 0.92.2).We employed a DXA system  to measure body fat percentage and lean soft tissue mass. Inter‐instrument reliability of ASM between the two devices was excellent (intraclass correlation coefficient = 0.97). Participants were placed in a supine position on the DXA table for a whole‐body scan according to the manufacturer's protocol. The lean soft tissue mass of the entire body was divided into several areas, including the arms, legs and trunk. We calculated the ASM by adding up the lean soft tissue mass for the arms and legs. To adjust for build, we divided ASM (kg) by the square of the height  twice for each hand. The average of the maximum values for each hand was calculated.t‐test. We calculated Pearson's correlation coefficients to evaluate the correlations between calf circumference and the BIA or DXA‐measured ASM/height2. We performed receiver operating characteristic (ROC) analysis to identify the optimal cut‐off for calf circumference in screening LMM measured by BIA and DXA. We calculated the areas under the ROC curve, 95% confidence intervals (95% CI), and the optimal cut‐off point, calculated by determining the shortest distance between the ROC curve and upper left corner of the graph. To examine the effect of obesity and age on the LMM screening measured by calf circumference, we divided the participants into two groups based on body fat percentage (non‐obese and obese) and age (middle‐aged: <60 years and older: ≥60 years) to perform subgroup analyses. Obesity was defined as a body fat percentage of ≥25% for men and ≥30% for women.We compared the mean values of the participants' characteristics between the non‐LMM and LMM groups measured by DXA using Student's P < 0.05 in two‐tailed tests. All statistical analyses were performed using SPSS Statistics version 26 for Windows .Statistical significance was set at The mean ages for men and women were 57 (range 40–87) and 52 (40–84) years, respectively. The prevalence rates for LMM measured by BIA and DXA were 4.1% and 8.6% for men and 6.6% and 12.9% for women, respectively.2 and hand‐grip strength than those with non‐LMM, for both men and women. No significant differences were found in age, height and body fat percentage in the LMM and non‐LMM groups, for both men and women.Table 2 was positively correlated with DXA‐measured ASM/height2 . We performed ROC analysis for screening LMM measured by DXA using BIA‐measured ASM/height2 . The areas under the ROC curve for LMM measured by DXA were 0.92 (95% CI 0.90–0.95) for men and 0.90 (0.86–0.94) for women. The optimal cut‐offs for BIA‐measured ASM/height2 for screening LMM measured by DXA were 7.7 kg/m2  for men and 5.9 kg/m2  for women.BIA‐measured ASM/heightr = 0.33, women: r = 0.31; Fig. S4). Figure 2. Calf circumference was positively correlated with BIA‐measured ASM/height2  and DXA‐measured ASM/height2 . Table Calf circumference was positively but weakly correlated with hand‐grip strength . The areas under the ROC curve and optimal calf circumference cut‐offs for LMM were similar to the results of the main analysis .We also performed a subanalysis using the publicly available ASM estimation formula for BIA (for results see Supporting Information). Although the correlation between calf circumference and BIA‐measured ASM/height2 regardless of obesity and age  and DXA‐measured ASM/height2 . In the subgroup analyses by obesity and age, calf circumference was also positively correlated with DXA‐measured ASM/height2.We investigated the association of calf circumference with ASM/heightn = 12) in Brusselsn = 23),r = 0.84, or men: r = 0.90 and women: r = 0.77). Furthermore, maximal calf circumference was strongly correlated with calf muscle mass measured by magnetic resonance imaging .r = 0.68, BIA‐measured ASM/height2: r = 0.56–0.78, DXA‐measured ASM: r = 0.55–0.81, DXA‐measured ASM/height2: r = 0.42–0.84). Moreover, the National Health and Nutrition Examination Survey that examined 15 293 participants reported a moderate correlation between calf circumference and DXA‐measured ASM across all BMI subgroups  or age subgroups .Previous studies that examined human cadavers, such as the study involving male cadavers  for men and 30–33 cm  for women, similar to those reported in studies that examined Asian individuals, except for one study where calf circumference was measured in the supine position.Our study calculated the optimal calf circumference cut‐offs for LMM screening measured by BIA and DXA: 35 cm  and 36 cm  for men and 33 cm  and 34 cm  for women. The cut‐offs were similar between BIA and DXA. We also performed the subgroup analyses based on obesity and age to calculate optimal cut‐offs, which were roughly similar to the main results. A study on hospitalized patients found no difference in calf circumference between those with normal weight and those who were overweight or obese, as assessed by BMI.To date, several studies have determined the cut‐offs for LMM screening measured by calf circumference Table . However2 regardless of obesity and age, and is a simple and accurate surrogate marker of muscle mass for diagnosing sarcopenia measured by both BIA and DXA.In conclusion, calf circumference is positively correlated with BIA‐ and DXA‐measured ASM/heightThe authors declare no conflict of interest.Figure S1. Method of calf circumference measurement.Figure S2. Correlation between BIA‐measured ASM/height2 and DXA‐measured ASM/height2 in men and women.Figure S3. Receiver operating characteristic curves for screening low muscle mass measured by DXA using BIA‐measured ASM/height2 in men and women.Figure S4. Correlation between calf circumference and hand‐grip strength in men and women.Figure S5. Correlation between calf circumference and BIA‐measured ASM/height2 estimated by Yamada et al. formula in men and women.Figure S6. Receiver operating characteristic curves for screening low muscle mass measured by BIA estimated by Yamada et al. formula using calf circumference in men and women.Table S1. Previous studies examining the calf circumference cut‐offs for screening low muscle mass measured by multifrequency BIA and DXA.Click here for additional data file.


Considering the increasing prevalence of non‐alcoholic fatty liver disease and non‐alcoholic steatohepatitis (NASH), the development of an effective screening and follow‐up system that enables the recognition of etiological changes by primary physicians in clinics and specialists in hospitals is required.n = 272) and underwent magnetic resonance elastography (MRE) (n = 119) were enrolled. Patients who underwent MRE were also tested by ultrasound elastography (USE) (n = 80) and for M2BPGi (n = 97), autotaxin (ATX) (n = 62), and platelet count (n = 119), and their fibrosis‐4 (FIB‐4) index was calculated (n = 119).Chronic hepatitis B (HBV) and C (HCV), NASH, and alcoholic steatohepatitis (ASH) patients who were assayed for Mac‐2‐binding protein glycosylation isomer (M2BPGi)  in the clinic. During specialty care in the hospital, MRE exhibited high diagnostic ability for fibrosis stages >F3 or F4; it could efficiently predict collateral circulation with high sensitivity, which can replace USE. We also identified etiological features and found that collateral circulation in NASH/ASH patients tended to exceed high‐risk levels; moreover, these patients exhibited more variation in HCC‐associated liver stiffness than the HBV and HCV patients.FIB‐4 index >2, excluding HBV‐infected patients, M2BPGi >0.5, ATX >0.5, and platelet count <20 × 10Using appropriate markers and tools, we can establish a stepwise, practical, noninvasive, and etiology‐based screening and follow‐up system in primary and specialty care. Using appropriate markers and tools, we can establish a stepwise, practical, noninvasive, and etiology‐based screening and follow‐up system in primary and specialty care. A recently developed treatment for hepatitis C that uses direct‐acting antivirals (DAAs) has achieved nearly 100% sustained virologic response (SVR).Recent large‐scale cohort studies showed that fibrosis determines the outcomes in non‐alcoholic fatty liver disease (NAFLD),The most critical, game‐changing intervention for the HCC course remains the improvement of detection rates at an early stage. To achieve this goal, the most useful approach may be to optimize screening strategies to better identify higher‐risk patients who require a more intense survey.Wisteria floribunda agglutinin+—Mac‐2 binding protein ,In this study, we first focused on serum markers that had recently become available, namely, n = 272; hepatitis B virus [HBV], n = 82; hepatitis C virus [HCV], n = 88; NASH, n = 45; ASH, n = 59) and ATX  and underwent magnetic resonance elastography (MRE)  were enrolled. The patients who underwent MRE were also subjected to USE, using acoustic radiation force impulse (ARFI) (n = 80), and assayed for M2BPGi (n = 97), ATX (n = 62), and platelet count (n = 119); in addition, their FIB‐4 index was also calculated (n = 119). For studies on noninvasive markers for HCC detection, the data for M2BPGi (n = 272), ATX (n = 122), platelet count (n = 119), and FIB‐4 index (n = 119) were used. For studies on the correlation of the other parameters with MRE, the data for MRE (n = 119) and their corresponding platelet count (n = 119), FIB‐4 (n = 119), ATX (n = 62), M2BPGi (n = 97), and USE (n = 80) data were used. For studies on the correlation of MRE with USE for specialist use, MRE (n = 119) and USE (n = 80) data were used (Table n = 23) or echo‐guided liver biopsy (n = 8) using a fine biopsy needle (Majima needle) for the diagnosis of the etiology of the liver disease were enrolled in the study to verify the relationship between liver stiffness, as calculated by MRE, and the fibrosis stage of the liver tissue. This retrospective study was approved by the Institutional Review Board (IRB) of Niigata University. Written informed consent was obtained from each patient, and the study protocol conformed to the ethical guidelines of the 1975 Declaration of Helsinki.Inpatients and outpatients at the Niigata University Hospital, from 2016 to 2018, who were tested for M2BPGi , suggesting that HBV patients must be followed up regardless of the levels of these fibrosis markers. For all other etiologies, HCC was found in all patients with FIB‐4 index >2 , except for three patients . Therefore, we propose that an FIB‐4 index >2 might be sufficient to predict HCC. With regard to the other markers, platelet count <20 × 104/μL , M2BPGi >1 , and ATX >1  might be used in addition to regular follow‐up with ultrasonography and/or tumor markers. In addition, the frequency of HCC patients presenting with 1 > M2BPGi > 0.5 or 1 > ATX > 0.5 was very low; however, this range must be considered by keeping in mind the differences in the etiologies. In HCV patients, a small‐sized HCC was detected in patients with 1 > M2BPGi > 0.5 or 1 > ATX > 0.5  during regular follow‐up. In NASH and ASH patients with 1 > M2BPGi > 0.5 or 1 > ATX > 0.5, the HCCs were not followed up regularly, and the detected tumors were of a larger size . NASH and ASH HCC patients with 1 > M2BPGi > 0.5 or 1 > ATX > 0.5 were characterized by diabetes mellitus (DM) and/or relatively old age (>75 years old).To evaluate which markers are effective for identifying HCC patients in the clinic, we assessed common fibrosis markers, such as M2BPGi, ATX, FIB‐4 index, and platelet count , in patients with or without HCC. As shown in Figure Specialists in hospitals perform detailed follow‐up to manage the risk of HCC and collateral circulation. Here, we evaluated the validity of MRE in effectively evaluating advanced fibrosis in patients. First, we compared the relationship between the available tissue fibrosis stages and MRE data and found that MRE levels increased with increasing fibrosis stages  Fig. . Next, wP < 0.0001), which was much higher than that of other parameters, such as USE , M2BPGi , ATX , FIB‐4 index , and platelet count   Fig. . These r01) Fig. .r = 0.723 (P < 0.0001) for USE, r = 0.530 (P < 0.0001) for M2BPGi, r = 0.505 (P < 0.0001) for ATX, r = 0.456 (P < 0.0001) for FIB‐4 index, and r = −0.418 (P < 0.0001) for platelet count. These results indicated a high correlation between MRE and USE ; 0.882, P < 0.0001 (USE); 0.837, P < 0.0001 (M2BPGi); 0.788, P = 0.0012 (ATX); 0.825, P < 0.0001 (FIB‐4 index); and 0.861, P < 0.0001 (platelet count)  Fig. . Althougnt) Fig. .P = 0.0018 and 0.6292, P = 0.0381, respectively , whereas for other patients, M2BPGi >0.5, ATX >0.5, and FIB‐4 index >2 may be important screening benchmark indices for recommending further examinations, such as US, depending on the local conditions. Furthermore, depending on a patient's HCC risk, tumor marker calculation may be necessary. Patients with 1 > M2BPGi > 0.5 and 1 > ATX > 0.5 had a relatively lower risk of HCC compared to those with M2BPGi >1 and ATX >1. However, when patients of older age >75 years) and with DM were included in the analysis, we found that patients with 1 > M2BPGi > 0.5 and 1 > ATX > 0.5 might require more attention with regard to HCC risk. The MRE and USE data showed that the liver stiffness associated with HCC varied depending on the etiology. NASH/ASH patients tended to have a wide variation in HCC‐associated liver stiffness. USE or MRE  helped predict collateral circulation and HCC occurrence. MRE (>4000 Pa) could efficiently predict collateral circulation with high sensitivity, and patients with NASH/ASH tended to exceed high‐risk collateral circulation levels  to lysophosphatidic acid (LPA), a pleiotropic growth factor‐like phospholipid, and has been reported to promote liver fibrosis and cancer.et al. reported that the prevalence of NAFLD and NASH in patients with type 2 (T2) DM is over 60%, and the presence of T2DM seems to accelerate the course of NAFLD and is a predictor of advanced fibrosis and mortality.et al. reported that, when patients were divided based on the FIB‐4 index into <2.67 and ≥ 2.67 groups, the FIB‐4 index ≥2.67 group displayed significantly lower overall survival rates and higher incidence of HCC and LC‐related complications than the FIB‐4 index <2.67 group.Age and DM seem to be very important factors in the context of carcinogenesis in NAFLD patients.et al. reported that patients with NAFLD who meet the MRE–liver stiffness measurement (LSM) criterion (<4.2 kPa) and the platelet count criterion (>18 × 104/μL) do not need to undergo screening esophagogastroduodenoscopy; however, these criteria should be rechecked annually. If the LSM increases or the platelet count decreases, a screening EGD should be performed.et al.In this report, we show that considering the etiology is very important for monitoring HCC. In patients rigorously treated for viral hepatitis, HCC tended to occur before collateral vein formation (before 4000 Pa); however, in NASH and ASH patients, HCC can occur at a very wide range of liver stiffness. Thus, in these patients, it is better to carefully follow both the HCC occurrence and collateral vein formation at the same time. USE for HCC screening is an easy approach in chronic liver disease patients. In this study, we used ARFI; however, FibroScan and Supersonic Shear Imaging are also widely used.As clinical evidence has revealed that liver function improves after balloon‐occluded retrograde transvenous obliteration, the prevention of a portosystemic shunt may be very important for liver regeneration and fibrosis regression.A limitation of this study was that data were collected from only one specialized institution that primarily treats patients with chronic liver disease. In addition, almost all of the high‐risk HCV and HBV patients were already being treated using nucleoside analogs or DAA. Future researchers should consider collecting data from multiple primary health facilities to confirm our results.In conclusion, we showed that, using appropriate markers and tools, we can establish stepwise, practical, noninvasive, and etiology‐based screening for improving prognosis at the level of primary and specialty care depending on the situation of the facility. It is very important for doctors in clinics and specialists in hospitals to understand the available methods and share the proper role for following chronic liver disease depending on the etiology.AppendixS1 Supplementary Information.Click here for additional data file.Figure S1 Flow chart of this study. The highlighted areas indicate the factors to be considered by primary physicians (blue), factors correlated with MRE (red), and factors to be considered by specialists (green).Click here for additional data file.Table S1 Characteristics of the patients with HBV, HCV, NASH, and ASH who underwent MRE.Click here for additional data file.


EGFR mutations. Uncommon mutations, excluding exon 19 deletions and exon 21 L858R, comprise 7%–23% of EGFR mutation‐positive NSCLC. The treatment of uncommon EGFR mutation‐positive NSCLCs is controversial. Here, we present the case of an 81‐year‐old man who was diagnosed with lung adenocarcinoma cStage IVA harboring the uncommon EGFR L861Q mutation. The patient received oral afatinib treatment (40 mg/day). One month after the initiation of afatinib treatment, Common Terminology Criteria for Adverse Events version 4.0 grade 2 stomatitis was observed. It improved upon afatinib withdrawal. After 10 days of withdrawal, afatinib treatment was resumed at a reduced dose of 20 mg/day. Subsequently, the patient continued treatment with afatinib. A partial response to afatinib treatment was maintained for 49 months until primary tumor regrowth. Afatinib treatment was continued after disease progression, but the patient died of bacterial pneumonia 59 months after initiation of afatinib treatment. Several studies have previously reported a large number of compound mutations with uncommon mutations, and that compound mutation‐induced cells are most susceptible to afatinib. This suggests the efficacy of afatinib in clinical practice and that afatinib may be safely administered to elderly patients with appropriate dose reductions.Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors are the standard treatment for patients with non‐small cell lung cancer (NSCLC) harboring  EGFR mutation‐positive NSCLC. Compound mutation‐induced cells are most susceptible to afatinib, suggesting the efficacy of afatinib in clinical practice. Afatinib may be administered to elderly patients with appropriate dose adjustmentsA large number of compound mutations have been observed in patients with uncommon  EGFR mutations.EGFR mutation‐positive NSCLC. However, 7%–23% of EGFR mutation‐positive NSCLC, except for exon 19 deletions and exon 21 L858R, are uncommon mutations.EGFR mutation‐positive NSCLC developed early resistance to first‐generation EGFR‐TKIs. Afatinib, a second‐generation EGFR‐TKI, was found to have a clinical benefit for patients with NSCLC harboring uncommon EGFR mutations.EGFR mutation‐positive NSCLC.EGFR mutation‐positive NSCLC is controversial. Moreover, the proportion of elderly participants in clinical trials is small, therefore the safety of EGFR‐TKIs, such as afatinib, in these patients remains unclear.Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) are the standard treatment for patients with non‐small cell lung cancer (NSCLC) harboring EGFR mutation‐positive lung adenocarcinoma.Here, we report a case of a long‐term response to afatinib in an elderly patient harboring uncommon An 81‐year‐old man was referred to our hospital following chest xray which revealed an abnormal shadow, and he was subsequently diagnosed with lung adenocarcinoma cT1bN0M1a (M: PLE) Stage IVA . One month later, Common Terminology Criteria for Adverse Events (CTCAE) version 4.0 grade 2 stomatitis was observed, which improved with afatinib withdrawal. After 10 days of withdrawal, afatanib treatment was resumed at a reduced dose of 20 mg/day. Subsequently, grade 1 skin toxicity was observed. However, the patient continued treatment with afatinib. A partial response to afatinib treatment was noted for 49 months until the primary tumor recurred (Figure Examination of the DNA sequence of the EGFR mutation, developed a long‐term response to afatinib with appropriate dose reduction.The elderly patient in our report, who presented with lung adenocarcinoma with an uncommon EGFR mutation‐positive NSCLC with uncommon mutations.EGFR mutations, namely G719X, L861Q, and S761I.EGFR mutation‐positive NSCLC with L861Q was 56.3%. Afatinib has previously been associated with an ORR of 59.6% in EGFR mutation‐positive NSCLC with L861Q.EGFR mutation‐positive NSCLC responded to afatinib for more than three years. In our case, the patient remained responsive for more than four years.EGFR mutation‐positive NSCLC patients with major uncommon EGFR mutations.EGFR mutations including L858R/del19, G719C/S/A, and L861Q mutations have been reported in 15.9%, 93.3%, and 36.4% of all cases, respectively.EGFR mutation and resistance, there was no difference between afatinib and osimertinib in terms of the susceptibility of uncommon mutation‐induced cells to them. However, compound mutation‐induced cells have been reported to be most susceptible to afatinib.An integrated analysis of LUX‐Lung 2, 3, and 6 reported the clinical benefits of afatinib, a second‐generation TKI, for treating EGFR mutations, which have shown promising clinical efficacy and good tolerability. A phase II study using low starting doses of afatinib reported that 22% of patients aged 75 years or older who started with afatinib at 20 mg/day were able to increase the dose up to 30 mg/day, and 17% were able to increase the dose to 40 mg/day, with the majority at 20 mg/day.Since the proportion of elderly participants in clinical trials is small, the safety of the administration of EGFR‐TKIs, including afatinib, in the elderly population remains unclear. In the LUX‐Lung 3 and 6 analysis, the rate at which patients required dose reduction was higher in the afatinib group. However, the trend was similar among younger and elderly patients.EGFR mutations, and may be administered safely to elderly patients with an appropriate dose reduction.In conclusion, afatinib is effective in treating NSCLC harboring uncommon All authors declare that they have no conflicts of interest.


The Estudio Vacuna de Influenza Peru (VIP) cohort aims to describe the frequency of influenza virus infection, identify predictors of vaccine acceptance, examine the effects of repeated influenza vaccination on immunogenicity, and evaluate influenza vaccine effectiveness among HCP.The VIP cohort prospectively followed HCP in Lima, Peru, during the 2016‐2018 influenza seasons; a fourth year is ongoing. Participants contribute blood samples before and after the influenza season and after influenza vaccination (for vaccinees). Weekly surveillance is conducted to identify acute respiratory or febrile illnesses (ARFI). When an ARFI is identified, participants self‐collect nasal swabs that are tested for influenza viruses by real‐time reverse transcriptase‐polymerase chain reaction. Influenza vaccination status and 5‐year vaccination history are ascertained. We analyzed recruitment and enrollment results for 2016‐2018 and surveillance participation for 2016‐2017.P‐values < .05).In the first 3 years of the cohort, VIP successfully contacted 92% of potential participants, enrolled 76% of eligible HCP, and retained >90% of participants across years. About half of participants are medical assistants (54%), and most provide “hands‐on” medical care (76%). Sixty‐nine percent and 52% of participants completed surveillance for >70% of weeks in years 1 and 2, respectively. Fewer weeks of completed surveillance was associated with older age (≥50 years), being a medical assistant, self‐rated health of fair or poor, and not receiving the influenza vaccine during the current season (The VIP cohort provides an opportunity to address knowledge gaps about influenza virus infection, vaccination uptake, effectiveness and immunogenicity among HCP. Here, we summarize the objectives and design, results of recruitment during the first 3 years of the study, and rates of participation in active surveillance during the first 2 years of the study.A meta‐analysis of studies of seasonal influenza estimated that 1/5 HCP are infected with influenza virus annually, based on serologic and clinical testing.Vaccination of HCP against influenza virus infection is an important component of infection control in healthcare settings,Studies of influenza vaccine immunogenicity among HCP have demonstrated that repeated vaccination can blunt the antibody response to hemagglutininAlthough recent reviews confirm that seasonal influenza vaccine is moderately effective in reducing the risk of illness among adults,22.1The VIP Cohort recruited HCP in Lima, Peru, at Dos de Mayo National Hospital, Cayetano Heredia National Hospital, and Daniel Alcides Carrión National Hospital in 2016 and expanded to include National Institute of Child Health (Del Niño) and Archbishop Loayza Hospital in 2017 Table .2.2Eligible participants are HCP aged ≥18 years, working ≥30 hours/week, with routine, direct patient contact and must have been employed by the hospital for ≥1 year. Similar to previous definitions for HCP,2.3To minimize potential selection biases, HCP are invited to join the cohort using a stratified sampling strategy. We categorize potential participants at each hospital into 18 strata by sex, three age groups, and three occupational categories. To ensure the cohort includes participants with all combinations of sex, age, and occupation, we set a goal of ≥50 participants in each strata. We set goals for total recruitment in year 1 of 1200, year 2 of 2800, and year 3 of 2400, and set minimum enrollment goals per study hospital Appendix .2.4Participants complete an enrollment survey when they enter the cohort and complete follow‐up surveys at the end of season and start of season for their remaining time in the cohort. The enrollment survey gathers information on sociodemographic characteristics, work responsibilities, health status, health behaviors, and KAP regarding influenza illness and vaccination Appendix . Influen2.5Based on previous surveillance for laboratory‐confirmed influenza virus infection in Lima,During the influenza season, participants receive twice‐weekly short‐message‐service (SMS) text messages to confirm whether they had an acute illness with one or more of the following symptoms within the past 7 days: cough, runny nose, body aches, or feverishness. Upon illness identification, staff conduct an acute illness survey and participants contribute a self‐collected nasal swab. Staff conduct a follow‐up survey at illness resolution. To verify surveillance completeness and mitigate information bias, the end‐of‐season survey asks participants whether any illness was missed during the season Appendix .2.6The primary study outcome is ARFI associated with influenza virus infection confirmed by rRT‐PCR. Specimens are tested by NAMRU‐6 Laboratory for influenza A and B viruses, subtypes and lineages using rRT‐PCR assays, with standard protocols, primers, probes, and reagents supplied by US CDC's International Reagent Resource (IRR) Appendix .2.7All participants contribute 10 mL of whole blood at enrollment and 5 mL at the start of session and end of season; vaccinees also provide 5 mL approximately 28 days (21‐42 days) after vaccination. A subset of participants provide an additional 10 mL of whole blood at start of season and end of season and approximately 7 days post‐vaccination (for vaccinees) for extraction of peripheral blood mononuclear cells (PBMCs). See Appendix 2.8Data collection and management were conducted using REDCap (Research Electronic Data Capture), a browser‐based metadata‐driven software system2.9α = 0.05, we are 80% powered to estimate a true VE of approximately 30% and to estimate a difference in cumulative incidence between vaccinated and unvaccinated HCP of approximately 2.3 cases per 100 HCP. A higher VE and/or greater difference in cumulative incidence by vaccination status would increase the statistical power. Models, such as a generalized estimating equation, that take into account repeated observations should improve statistical power. See Appendix We expect 1500‐2000 HCP participants to enroll each year with approximately 50% enrolling in multiple years. Thus, we assumed we would observe at least 5000 person‐seasons, approximately 30% HCP vaccination coverage and 7% influenza illness attack rate, with 2.10To assess the stratified recruitment approach, we evaluated the proportion of HCP who fully enrolled out of all eligible HCP. Full enrollment is defined as providing informed consent, completing the enrollment survey and contributing the enrollment blood sample. We compared full enrollment stratified by major recruitment categories in the 18 recruitment strata (sex by occupation by age) using chi‐square tests and used multivariable logistic regression to model full study enrollment as a function of these five factors.To describe performance of surveillance activities in years 1 and 2, we examined the proportion of participants who completed surveillance participation each week, defined as completion of surveillance questions. Participants known to have an ongoing illness and therefore ineligible for contact during a week were counted among completed surveillance events for that week. We used multivariable linear regression to predict the percentage of all surveillance weeks with completed contact as a function of the major recruitment variables . Surveillance data from year 1 and year 2 were evaluated separately. Variables with fewer than 10 missing responses are denoted on the tables; data were not imputed for these analyses.2.11The study protocol and procedures were reviewed and approved by seven institutional review boards including NAMRU‐6, each study hospital and by Abt Associates (coordinating institution for US CDC). All participants completed written informed consent. Small gifts were given to participants at study milestones. Given the research nature of the laboratory methods and time delays in batch testing, rRT‐PCR results were not available to participants and did not inform decisions regarding their medical care or approval to return‐to‐work.33.1The recruitment flow diagram for years 1‐3 is presented in Figure Information on study retention is currently available through the start of year 3 Table . Of year3.2Characteristics of the 3050 HCP enrolled during years 1‐3 are in Table 3.3Results on active surveillance participation are available for the 19 weeks of surveillance in year 1  and 20 weeks in year 2 . Figure F‐ratio[1] = 84.79, P < .001), though there was variability in surveillance completion across weeks in both years  than year 2 (61.5%)  and year 2 .In the end‐of‐season survey, a small percentage of participants reported that they had failed to report at least one possible ARFI as part of surveillance: 10% (112/1145) in year 1 and 7% (205/2831) in year 2. Participants who said they forgot to report an illness had fewer weeks of completed surveillance in year 1 versus those who did not forget ; Formal analysis (lead); Writing – original draft (lead); Writing – review & editing . Giselle Soto: Conceptualization ; Data curation ; Investigation (lead); Methodology ; Writing – review & editing . Carmen Arriola: Conceptualization ; Investigation ; Methodology ; Writing – review & editing . Miriam Gonzales: Data curation ; Investigation ; Project administration ; Writing – review & editing . Gabriella Newes‐Adeyi: Conceptualization ; Investigation ; Methodology ; Project administration ; Supervision ; Writing – review & editing . Candice Romero: Data curation ; Investigation ; Project administration ; Writing – review & editing . Vic Veguilla: Investigation ; Methodology ; Writing – review & editing . Min Levine: Investigation ; Methodology ; Writing – review & editing . Maria Silva: Investigation ; Methodology ; Writing – review & editing (supporting). Jill Ferdinands: Conceptualization ; Investigation ; Methodology ; Writing – review & editing . Fatimah Dawood: Conceptualization ; Investigation ; Methodology ; Writing – review & editing . Sue Reynolds: Formal analysis ; Methodology ; Writing – review & editing . Avital Hirsch: Methodology ; Writing – review & editing . Mark Katz: Methodology ; Writing – review & editing . Eduardo Matos: Investigation ; Project administration ; Writing – review & editing . Eduardo Ticona: Investigation ; Project administration ; Writing – review & editing . Juan Castro: Investigation ; Project administration ; Writing – review & editing . Maria Castillo: Investigation ; Project administration ; Writing – review & editing . Eduar Bravo: Investigation ; Project administration ; Writing – review & editing . Angela Cheung: Data curation ; Writing – review & editing . Rachael Phadnis: Data curation ; Writing – review & editing . Emily Martin: Investigation ; Methodology ; Writing – review & editing . Yeny Tinoco: Investigation ; Methodology ; Project administration ; Writing – review & editing . Joan Manuel Neyra Quijandria: Data curation ; Methodology ; Project administration ; Writing – review & editing . Eduardo Azziz‐Baumgartner: Conceptualization ; Investigation ; Methodology ; Writing – review & editing . Mark Thompson: Conceptualization (lead); Investigation (lead); Methodology (lead); Supervision (lead); Writing – original draft ; Writing‐review & editing (lead).The views expressed in this manuscript reflect the results of research conducted by the authors and do not necessarily reflect the official policy or position of the Centers for Disease Control and Prevention, the Department of the Navy, Department of Defense, nor the US Government.Some authors are employee of the US Government. This work was prepared as part of their official duties. Title 17, USC, §105 provides that copyright protection under this title is not available for any work of the US Government. Title 17, USC, §101 defines a US Government work as a work prepared by a military Service member or employee of the US Government as part of that person's official duties.Fig S1Click here for additional data file.Fig S2Click here for additional data file.Supplementary MaterialClick here for additional data file.


Trematura patavina , Oodinychus ovalis , and Olodiscus minima . Other nidicolous—i.e., nest-dwelling—species included: Nenteria oudemansi , Phaulodiaspis borealis , Phaulodiaspis rackei , Uroseius hunzikeri , Uropoda orbicularis , and Apionoseius infirmus . The most frequent species were: Oodinychus ovalis , N. oudemansi , and Olodiscus minima . Detrended correspondence analysis indicated that the Uropodina community from badger nests differed from that of mole nests, studied earlier. In setts, the Uropodina community included T. patavina and N. oudemansi, which were for the first time recorded from underground badger nests. This is the first record of N. oudemansi from Poland.Badgers can gather huge quantities of organic material to build their nests for winter time and to rear their cubs. Moreover, badger burrows (setts) are characterized by specific microclimate with quite stable temperature and humidity. Their fauna is poorly studied, especially in respect of saprobiontic Uropodina mites. In 2018–2019, we monitored 94 badger setts to search for nest material that had been thrown away during cleaning of the chambers after mating and winter sleep. In the collected material from 32 badger nests, we found 413 Uropodina mites of 16 species, in various stages of development . The community was dominated by three mite species:  Meles meles) burrows, also known as setts, play an important role in shaping species diversity in many habitats across Europe, e.g., in respect of vascular plants . However, badgers are known to be hosts for only few mite species: Demodex melesinus  fauna of mammal burrows and warrens were mostly focused on small mammals dwelling in underground nests Hackman . The nes Nowosad . Thus, mReports presenting some mites from burrows of medium-sized carnivores Howell  allowed 2, mostly a mosaic of forests and fields. Forests, forming 213 patches varying in size from 1 ha to more than 2000 ha, occupy 52% of the study area. Scots pine (Pinus sylvestris) on sandy soils is the dominant species. Four small rivers flow through the study area, and lakes cover about 1350 ha. The mild climate prevails, with an average annual temperature of 10.5 °C. The coldest month is February, with a mean temperature of −4.1 °C, and the warmest one is August, with a mean of 21.7 °C (meteomodel.pl).Field research was carried out in a lowland region of western Poland near Trzciel . The study area covered 389.5 kmIn 2018–2019 we monitored 94 badger setts, including those used as breeding sites, to collect nest material that has been thrown away during cleaning the chambers, i.e., after mating and winter sleep. The setts were controlled in the autumn of 2018 (17 nests found) as well as spring of 2019 (7 nests) and autumn of 2019 (12 nests), when badgers started to be active after winter (February–March) and when they began preparing for the coming winter (ca. late September). Only fresh, moist nest material was sampled. In 10 cases, nest material was sampled in the same sett: in three setts we found nest material during three surveys (3 × 3 = 9 nests) and in seven setts during two surveys (7 × 2 = 14 nests). In the other 13 setts, nests were sampled only once, so the total number of found nests was 36. However, to avoid data duplication in dominance and frequency computations, we excluded four nests sampled in the autumn of 2019 from analyses, as they were obtained from the same setts as four nests sampled in the spring of the same season. Consequently, the final number of nests analysed in this study was 32.Badgers throw away the nest material from the sett and leave it near the entrance—on top of the soil heaps or just below. The volume of nest material differed between setts and its dry mass varied (0.2–2.9 kg). Nest material consisted mostly of grass and Scots pine needles, and partially it was mixed with soil excavated from the burrow. All the organic material was sampled and transported to the laboratory. The mites were extracted with Tullgren funnels for 6 days, and preserved in 75% alcohol. Both permanent and temporary microscope slide preparations were made (using Hoyer’s medium), and the specimens were identified with the keys of  and frequency . The following classes of dominance were used: D5 = eudominants (> 30%); D4 = dominants (15.1–30.0%); D3 = subdominants (7.1–15.0%); D2 = residents (3.1–7.0%); and D1 = subresidents (≤3%). Frequency classes were: F5 = euconstants (> 50%); F4 = constants (30.1–50.0%); F3 = subconstants (15.1–30.0%); F2 = accessory species (5.1–15.0%); and F1 = accidentals (≤5%). The dominance and frequency characteristics were computed with data pooled for both seasons.In accordance with Błoszyk , the anat test was applied with R v.3.5.3 software (R Core Team Uropoda sp.) and improved the relation between the number of variables in comparison to the number of samples.To assess the significance of differences in numbers of Uropodina species and individuals in badger nests between years, Student’s Trematura patavina , Oodinychus ovalis , and Olodiscus minima  , Phaulodiaspis borealis , Phaulodiaspis rackei , Uroseius hunzikeri , Uropoda orbicularis , and Apionoseius infirmus . The other eurytopic species recorded in this research  were not associated with nests as their only habitat. The three most frequent species were: Oodinychus ovalis , Nenteria oudemansi , and Olodiscus minima   . Also, there were no significant differences in the number of individuals per nest between 2018  and 2019  . The DCA indicated that the Uropodina community from badger nests differed from that of mole nests . Badger nests were distinguished by two species: T. patavina and N. oudemansi. These species are on the one end of the marked gradient along the horizontal axis, which may reflect different microhabitat conditions offered by extensive badger setts in comparison to mole burrows. At the other end of the gradient are Nenteria breviunguiculata, Pseudouropoda calcarata, Discourella modesta, Dinychus carinatus, and D. perforates, which occurred only in mole nests.In total, 255 individuals of 14 species were recorded in 2019, in comparison to 158 individuals of 13 species in 2018, in spite of the lower number of analysed nests in 2019 (15) than in 2018 (17). There were no significant differences in the number of species per nest between 2018  and 2019   and sand martin (Riparia riparia)  nests, while others from litter or soil: Olodiscus minima, Oodinychus ovalis, Oodinychus karawaiewi  of harabasy  found ases Table . This brNenteria oudemansi, a very rare Uropodina mite species known from few locations across Europe, which was never found in Poland before  nests (Fain et al. N. oudemansi for microhabitats like underground nests built of plant material. The high frequency and dominance of this Uropodina mite, with the presence of both sexes and developmental stages in our results, confirms that badger nests are optimal and natural microhabitats for this species.The second, exclusive dweller of badger nests is T. patavina and N. oudemansi in the Uropodina assemblage from badger nests—in comparison to other microhabitats, such as mole nests—may result from the large size and volume of underground corridors and chambers dug by this medium-sized carnivore. Badger setts offer secluded and stable microhabitats that are characterized by specific and constant microclimate due to low temperature fluctuations between day and night all over the year (Moore and Roper 3 (Neal and Roper The high shares of Oodinychus karawaiewi, O. ovalis, Phaulodiaspis rackei, Ph. borealis and Urodiaspis tecta. However, our results revealed that—in contrast to moles—the Uropodina community of badger nests is distinguished by a high abundance of Trematura patavina and the first record of Nenteria oudemansi from underground mammal nests. In addition to previous studies of the impact of badgers on local fauna and flora (Sleeman et al. Mole nests are characterised by very diverse and rich Uropodina assemblages (Napierała et al.