Principal component analysis followed by exploratory linear discriminant analysis showed that increased R-SLF  AD, YMRS and family bipolarity distinguished BPII from UD  independent of episode number and frequency. Young, medication-naïve adults with BPII depression did not show the WM disruptions distinguishing more chronically ill BP patients from UD. These WM disruptions may therefore be partly attributable to illness chronicity. Longitudinal studies should examine the trajectory of WM changes in BPII and UD and predictive validity of these baseline clinical and imaging parameters.It is unknown if young medication-naïve bipolar II (BPII) depressed patients have increased white matter (WM) disruptions. 27 each of young (average 23 years) and treatment-naïve BPII depressed, unipolar depressed (UD) patients and age–sex–education matched healthy controls (HC) underwent 3 T MRIs with diffusion tensor imaging. Diagnostic ratings included Structured Clinical Interview for DSM Disorders (SCID), Montgomery-Åsberg Depression Rating Scale (MADRS), Young Mania Rating Scale (YMRS) and Hamilton Anxiety Rating Scale (HAM-A). Patients were clinically depressed . Compared to UD, BPII had increased family bipolarity , hypomanic symptoms , lifetime number of depressive episodes , lifetime and current-year number of episodes  and longer illness duration . BPII showed no increased WM disruptions vs UD or HC in any of the 15 a priori WM tracts. UD had lower right superior longitudinal fasciculus (SLF)  axial diffusivity (AD) (1.14 vs 1.17 (BPII), 1.16 (HC); F = 6.93,  Depression dominates the course of BPII and is the commonest mode of clinical presentation of the disorder. This phenomenological overlap with unipolar depression (UD) belies important clinical differences—poorer response to antidepressants, younger onset, higher recurrence, atypical features, cognitive impairment and increased suicide rates compared with UD5. Understanding the neurobiological differences between BPII depression and UD should yield important insights into the core etiological mechanisms differentiating between bipolar and unipolar illnesses and guide therapeutic development.Bipolar II disorder (BPII) is the commonest subtype of bipolar disorders9, with more widespread disruptions compared to UD12. There has been a paucity of direct comparisons between UD and BPII, and the findings above were mostly based on bipolar I (BPI) samples. Findings from the few studies pertaining to BPII were also less consistent. One study reported increased fiber alterations in temporal and inferior prefrontal region in BPII13. while others found sparing of WM disruption in uncinate fasciculus14 and the corpus callosum9. It is also uncertain whether the contradicting findings were attributable to heterogeneity in illness chronicity (7.3–18.8 years)13. In fact, while WM disruptions has been proposed as an endophenotypic/trait marker of bipolarity15, oxidative stress from longer illnesses with more illness episodes may result in increased myelin disruption in bipolar disorders16. Heterogeneity in illness chronicity in the samples may therefore potentially contribute to the inconsistent findings. In addition, exposure to medications such as lithium17, antipsychotics17, anticonvulsants18, antidepressants19 in Bipolar Disorder (BD) has been known to result in changes in WM integrity that may further add heterogeneity to the results. This may be especially relevant to UD vs BPII comparisons in view of the considerable difference in medications prescribed for these two conditions. We therefore set out to examine WM abnormalities in treatment-naïve BPII subjects relatively close to onset, in comparison with UD and healthy controls (HC). DTI derived indices of WM integrity  are obtained for 15 a priori, well-characterized white matter tracts implicated in BD20. The between-group differences are examined with a multi-variate statistical model to differentiate BPII from UD.Diffusion tensor imaging (DTI) studies on bipolar disorders have found white matter (WM) connectivity disruption, consistent with a model of emotional dysregulation, in the fronto-limbic circuitry , inter-hemispheric circuitry , the fronto-parieto-temporal long associative fibers, and frontal and temporal regions, compared to healthy subjectsp = 0.46), gender , and years of education  amongst the three groups  was significantly higher in BPII. The bipolar patients have had on average 5 years since first depressive onset, numerically but not significantly longer than UD . BPII patients had larger lifetime number of depressive episodes , number of episodes in the past year , lifetime number of episodes , family history of hypomania (HM), and bipolarity Index  than UD. HC had significantly higher estimated IQ score than BPII (p = 0.03) and UD (p = 0.01) patients  (Supplementary Table All patients were currently in a major depressive episode (MDE), as defined in the text revision of the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR), of at least moderate severity. UD and BPII patients had no significant between-group difference in Montgomery–Åsberg Depression Rating Scale (MADRS) scores  or functional impairment , but mean current Young Mania Rating Scale (YMRS) score  of2 = 0.15). No significant group differences of DTI measures were found in any of the remaining tracts , 7.82 × 10−4 (BPII), 7.74 × 10−4 (HC); F = 5.28, 95% CI of FB 0.001, 5.02). Post-hoc one-way ANOVA showed significant effect of age in BPII only , but not UD and HC (observed F fell within 95% CI of bootstrapped FB).To explore the effect of age on the DTI measures in each diagnostic group, group-by-age ANOVA with bootstrapping was conducted (Supplementary Table ps > 0.05), adjusted for age, sex and education level.Permutation tests with threshold-free cluster enhancement (TFCE) revealed no significant between-group voxel-wise difference of FA, AD and RD  results are illustrated in Fig. According to the scree plot, two components were found to account for 61.9% of variance in our data Fig. a.Component 1 included three variables of medium-to-high negative loadings, namely lifetime total number of MDE, lifetime total number of episodes and the number of episodes in the past year.Component 2 included three medium-to-high negative loadings for right SLF  axial diffusivity, current YMRS score and family history of bipolar disorder.These two components were then entered into linear discriminant analysis  to (5)) to clarify the effect of inclusion of right SLF  AD in the model , Further studies including probands and unaffected siblings of both BPI and BPII for comparison would be needed.Firstly, before we disregard the potential impact of WM in the bipolar subtypes, we need to consider firstly, that the lack of a BPI group precluded direct comparison with BPII subjects in our study, while two previous studies did report relative sparing of WM changes in uncinate fasciculus and corpus callosum in BPII compared to BPI and unaffected siblings23, and continued to be seen after medications were stopped for > 2 months25. On the other hand, studies on the effect of medications on brain structure in BD are conflicting. An earlier review suggested that medications generally did not contribute to structural differences between BD and HC, and where the effect was present, it was usually normalizing26. However, the authors also noted that many of the comparisons between medicated and unmedicated subjects were underpowered , and a recent meta-analysis identified reduced FA in patients receiving antipsychotics and anticonvulsants in multiple regions of interest18. Multiple lines of evidences support the neuroprotective effects of mood stabilizers and lithium28, although one study did observe reduced FA only in lithium-treated but not lithium-free BD versus HC29. Clarifying the effects of different drugs in medicated samples requires overcoming numerous challenges in sample size limitations, variations in medication load, combinations and adherence, the common occurrence of polypharmacy managing bipolarity, and also complex symptomatic differences that influence choice of medication use.Secondly, our sample was medication-naïve. It is premature to conclude if the absence of WM disruption in our BPII sample was attributable to medication naivety. To begin with, structural and functional changes have been shown to commence in BD before receiving any medication30, but reduced FA in superior frontal regions was reported in a small sample of medication-naïve adolescent BP-I patients in their first manic episode (n = 11)31. While medications are not expected to entirely explain the heterogeneity of the WM findings as noted above, examination of treatment-naïve samples should allow better comparability and removal of its confounding effects especially in the comparison of structural connectivity measures between bipolar and unipolar samples.Unfortunately, examination of unmedicated samples have been rare. One study of unmedicated (eight of the 18 patients were treatment-naïve) pediatric BP-I patients did not find any WM disruptions18, could be attributable to neuroprogression. Neuroprogression in bipolar disorder refers to the accumulation of biological disruptions, such as increase in pro-inflammatory cytokines and reduction in neurotrophins, following acute mood instability which progressively increase patients’ vulnerability to subsequent affective episodes32. This is consistent with previously reported correlations of illness chronicity with impaired WM integrity33, although WM disruptions had also been found in samples with shorter illness durations (0.2–5.6 years)9, individuals at high familial risk of BD who have not experienced any affective episodes6, and changes in brain volume and functional connectivity have been shown in first-episode BD patients34. Late onset and short disease duration were also found in the ENIGMA meta-analysis to be correlated with higher FA in multiple ROIs18. In fact, our observation of significant group-by-age interaction in MD, with age affecting MD in the right ILF specifically in BPII (but not UD and HC) appears consistent with existing evidence of neuroprogression leading to WM damage as a specific phenomenon in bipolar disorder.Alternatively, the paucity of white matter disruption in these young (average age 23), treatment-naïve bipolar II patients with an average of 5 years of illness may suggest that the wide spread WM disruptions summarised in the ENIGMA meta-analysis, with average age of 39.6 and on average 15.47 years since illness onset35 in medication-naïve UD but not individuals with BPII. Decreased AD has previously been reported in first-episode treatment-naïve UD patients, but in left rather than right SLF36. The lack of between-group difference in RD with reduced axial diffusivity suggested that impaired axonal integrity, instead of myelin loss, explained the reduction of MD, which is a scalar estimate of mean water diffusivity perpendicular and parallel to the tract37. The difference was unlikely related to clinical severity or chronicity effects, as UD and BPII groups had similar depressive and anxiety severity scores, number of comorbid disorders and significantly fewer affective episodes in UD. The two groups’ similar percentages of patients with family depressive history also did not suggest stronger biological loading in the UD group.The significant reduction in UD patients, compared to BPII and HC, of AD in the right SLF, may reflect increased WM disruption38. Interestingly, in the BPII group, AD in right SLF correlated negatively with bipolarity index, suggesting a potential relationship between inherent and manifest bipolarity and axonal damage, but given the multidimensional nature of this index39, it would require larger samples to elucidate whether it was the family bipolarity, course or symptom characteristics that explained the correlation. The positive correlation of family history of MDD with AD in right SLF in the BPII group is in conflict with the negative correlation observed in the UD sample. Although consistent with our ANOVA result that BPII group has increased AD in right SLF, this finding suggests that familial risk of depressive disorder may relate to increased axonal integrity in patients with bipolar disorder. This finding needs to be further examined in larger samples, which could benefit from combined analysis of comparable samples in multi-centre studies.The negative correlation between family history of MDD and AD in the right SLF UD group may suggest a link of heritable susceptibility to depressive disorder to impaired axonal integrity in UD. Indeed, altered WM integrity in multiple ROIs including bilateral SLF, has been shown in healthy adolescents at familial risk for affective disorders40 to be associated with depressive symptoms and a possible trait marker for late-life depression. For right SLF  integrity (AD) to co-vary only with trait (family bipolarity) and symptom (hypomanic) markers of bipolarity in the PCA results in the present study, and to discriminate UD from BPII with good sensitivity and specificity in LDA among the depressed patients, along with a separate component that indicates episodic recurrence (known marker for bipolarity), in fact suggested right SLF  integrity to be a potential discriminant marker for bipolar II vs unipolar depression that is independent of course characteristics. However, the sensitivity and specificity in this exploratory LDA was likely inflated by the application of this model on the same samples from which the measures were chosen based on one-way ANOVAs to differentiate the two samples. To compensate for this shortcoming, we performed another LDA with leave-one-out cross-validation and found similar prediction accuracies  between UD and BPII were specific to BPII or applicable to BPI as well. Fifth, the exclusion of psychosis or substance use has allowed us to conduct a more homogeneous investigation, but may have also limited us from accessing a fuller spectrum of bipolarity which would be associated with these two conditions. Lastly, we do not have data on the subjects’ body mass index, which were reported to be associated with WM abnormalities43. Although none of our young and medication-naïve patients reported metabolic syndromes, general medical illnesses frequently comorbid with BD such as obesity, hypertension and diabetes44, may confound the WM disruptions observed in DTI studies and should be included in further research.There are other limitations that need to be considered in interpreting the findings here. Firstly, WM integrity is only one of many factors affecting DTI indices45. On the one hand, these methods allow automated and straightforward processing of DTI data, which is best suited for exploratory analyses. On the other hand, more advanced imaging and processing approaches are useful for characterizing the structural, as well as functional, connectivity in bipolar II disorder holistically. Indeed, the state-of-the-art HCP has enabled advances in imaging and processing pipelines that improve efficiency and accuracy of MRI data analysis46. For example, the ‘multi-band’ pulse sequences47 and customized scanners with increased maximum gradient strength benefit diffusion MRI by enhancing spatial resolution (1.25 mm)48, which facilitates identification of cross-fibers. Scanners with increased diffusion gradient directions have also been developed to improve sensitivity of tractography and support more sophisticated models50. An increasing body of research has used probabilistic tractography to build connection matrix that summarizes the macroscopic connectivity of every brain area. In addition, whole brain connectomics analysis of this dataset is under way, which is hoped to shed light on differences in the network characteristics of these BPII and UD patients. Further efforts will also benefit from alignment with the state-of-the-art HCP pipelines in image acquisition and pre-processing.The imaging and DTI processing approaches adopted in our study may have shortcomings compared to those used in the Human Connectome Project (HCP). The global probabilistic tractography used in this study (TRACULA) enabled fast and automated quantification of WM tracts in individual subject’s space, eliminating the inaccuracies caused by inter-subject registration. However, with this approach, a single FA (and other DTI indices) was used to quantify the diffusion asymmetry of the entire tract, which might have diluted any WM abnormalities that were not present universally along the tract. Also, tractography was performed for the 15 WM tracts pre-defined by the toolbox only, which may overlook the possibility of other tracts and brain areas that relate to the psychopathological conditions of interest. Alternatively, TBSS enabled voxel-wise comparison of WM tracts between different groups of participants, but reliability has been proven to depend heavily on the specific DTI-derived measure and the pre-processing steps In summary, in this first DTI study comparing young and treatment-naïve BPII and UD patients, we could not find evidence of increased WM disruption in BPII disorder. Whether this represents a contemporaneous subtype difference between BPI and BPII merits direct, treatment-naïve, comparison. The discrepancy of our findings from previous BPII studies also belies the methodological salience in examining patients stratified by medication status and illness chronicity. Nonetheless, that we could not find evidence of WM disruption in medication-naïve young adults with on average 5 years of illness history suggest that the WM disruptions otherwise found in more chronically ill bipolar patients may be substantially attributable to effects of illness chronicity. The findings also encourage longitudinal examination for the specific effects of accumulated illness and recurrence in BPII disorder, which would help establish the biological underpinning of bipolarity to the extent that it is observable versus BPI and UD.51, and (4) no prior exposure to any psychotropic drug treatment in their life time. Exclusion criteria included: (1) current and lifetime histories of psychoses, (2) substance misuse, (3) organic brain syndromes, and/or (4) evidence of intellectual disability. Healthy volunteers without personal or family history of any mental disorders were recruited from online advertisements and a public health centre.Treatment-naïve, currently depressed subjects were recruited from individuals presenting to either of three specialist psychiatric clinics during the years 2014–2018 for scheduling a new appointment. Inclusion criteria were (1) aged 18–30, (2) currently satisfying the criteria for DSM-IV-TR Major Depressive Episode, (3) either meeting DSM-IV-TR criteria for Major Depressive Disorder, with no history of hypomanic episodes (for UD), or meeting research diagnostic criteria (RDC) for Bipolar II Disorder (BPII) (DSM-IV-TR MDE with history of hypomanic episodes of at least 2-day duration)Written informed consent was obtained from all subjects/patients. The authors assert that all procedures contributing to this work comply with the ethical standards of the relevant national and institutional committees on human experimentation and with the Helsinki Declaration of 1975, as revised in 2008. All procedures involving human subjects/patients were approved by the New Territories East Cluster—Chinese University of Hong Kong Clinical Research Ethics Committee (CREC Ref. No.: 2014.168).53. All lifetime affective episodes were enquired year by year from the first onset of depression using a modified life-chart method based on SCID-I. Repeated interviews were conducted to enhance detection of past hypomanic episodes.Diagnostic assessments were conducted by trained interviewers using the Chinese bilingual version of the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), adapted to facilitate diagnosis of current and lifetime hypomanic episodes under the supervision of an experienced clinician academic psychiatrist54, YMRS55, and HAM-A56. Current health-related quality of life was evaluated with the SF-3657, validated for Chinese settings58. Medication history was directly enquired with participants and caregivers, and checked against the territory-wide public hospital computer registry. We also assessed for the Bipolarity Index, a clinician-rated scale across five domains: signs and symptoms, age of onset, course of illness, responses to treatment and family history denoting bipolarity as a dimensional construct39. General intelligence was measured with the three-subtest short form of Wechsler Adult Intelligence Scale-III (WAIS-III)60.Current-week affective symptoms were rated by trained clinician interviewers using the interviewer-administered MADRS2, 285 contiguous slices, sagittal plane, 0.6 mm R-L thickness, reconstruction matrix: 240′240, flip angle: 8°). To minimize the effects of patient motion to the quality of our raw data, padding was applied around to the participant's head to minimize motion during signal acquisition. At the end of each imaging sequence, image quality checks were made to ensure no gross motion artifacts were visible on the images.MR images were acquired using 3-T MRI scanner  using a standard 8-channel head coil for signal reception. High resolution structural images of the whole brain were acquired using a 3D T1-weighted sequence . Diffusion sensitizing gradients were applied along 32 non-linear directions with b = 1000 s/mm2, together with an acquisition without diffusion weighting (b = 0 s/mm2). A parallel imaging acceleration factor of 2.5 was used to reduce scan time.Diffusion-weighted imaging was performed using a single-shot echo planar imaging sequence . Lastly, the anatomical priors for 15 white-matter pathways (see below) were computed for TRACULA.The diffusion-weighted images (DWI) were pre-processed using Freesurfer, with the 42, an automated toolbox within Freesurfer, was applied to reconstruct the global probabilistic distribution of 15 a priori, well-characterized white matter tracts implicated in bipolar disorder20, including the anterior thalamic radiations (ATR), the cingulum cingulate gyrus (CING), the cingulum angular bundle (CAB), the inferior longitudinal fasciculus (ILF), the parietal part of the SLF, the temporal part of the SLF, the uncinate fasciculus (UNC), all bilaterally; and the forceps minor of the corpus callosum (CC). To assure validity of findings, we also included three tracts with no reported bipolar association as control, namely forceps major and bilateral corticospinal tracts. Specifically, diffusion distributions were estimated by applying the ball-and-stick model, using “bedpostX” of FSL, followed by fitting the shape of each white-matter pathway to the results of the ball-and-stick model of diffusion and the anatomical priors for white-matter pathways computed during the pre-processing stage. Subsequently, we examined DTI-derived connectivity indices, including FA, MD, RD and AD (see below).TRACULA (TRActs Constrained by UnderLying Anatomy)trac-all (see above) were projected onto the mean FA skeleton that represents the centre of white-matter tracts, thresholded at FA = 0.2.Tract-based spatial statistics (TBSS) was conducted using FSL for voxel-wise analysis of white matter tracts. FA, AD and RD images created using Freesurfer’s 64. Group differences of demographic and cognitive variables were analysed using one-way ANOVA for continuous variables and Chi-Squared test for categorical variables. Post-hoc group comparisons were performed with false discovery rate (FDR) correction. Differences of clinical measures between UD and BPII patients were analysed by means of independent t-tests for continuous variables, and Chi-Square test for categorical variables. Where unequal variances existed between groups, Welch’s tests were used.Statistical tests for demographic, clinical and imaging (TRACULA) data were performed using R Statistical SoftwareGroup differences of FA, MD, RD and AD of unilateral tracts were analysed using one-way ANOVA, with WAIS-III IQ scores included in the model as covariate. In view of the small sample size and unequal variances of DTI data across groups, we performed data resampling by bootstrapping with 1000 iterations. With each bootstrap sample, we conducted a one-way ANOVA and extracted the bootstrapped r. Correlation was tested for each patient group separately and also with both groups combined. For all correlation tests, bootstrapping was conducted with 1000 iterations. Specifically, with each bootstrap sample, we extracted the r was not within the 95% CIs of We examined the correlations between the DTI and clinical data in our patient samples by calculating the Pearson’s In view of multicollinearity in the clinical and imaging measures, principal components analysis (PCA) was performed, instead of linear regression, to assess the multivariate linear relationships among the clinical and DTI measures in the UD and BPII groups, on DTI measures and clinical variables with significant group differences. Varimax rotation was applied to the component loadings. We examined the scree plot and extracted components with eigenvalue greater than 1 to identify the number of components sufficient to explain the variance in the data. The components obtained from the PCA were then entered into a linear discriminant analysis (LDA) to examine the classification between UD and BPII groups based on the DTI and clinical variables. A maximum likelihood method was used, assuming the variables were continuous and normally distributed. To compensate for the relatively small sample size, we performed an LDA with leave-one-out cross-validation and found similar prediction accuracies (see Supplementary Table Supplementary Information.


The epithelial-mesenchymal transition (EMT) process is involved in cancer cell metastasis and immune system activation. Hence, identification of gene expression signatures capable of predicting the EMT status of cancer cells is essential for development of therapeutic strategies. However, quantitative identification of EMT markers is limited by batch effects, the platform used, or normalization methods. We hypothesized that a set of EMT-related relative expression orderings are highly stable in epithelial samples yet are reversed in mesenchymal samples. To test this hypothesis, we analyzed transcriptome data for ovarian cancer cohorts from publicly available databases, to develop a qualitative 16-gene pair signature (16-GPS) that effectively distinguishes the mesenchymal from epithelial phenotype. Our method was superior to previous quantitative methods in terms of classification accuracy and applicability to individualized patients without requiring data normalization. Patients with mesenchymal-like ovarian cancer showed poorer overall survival compared to patients with epithelial-like ovarian cancer. Additionally, EMT score was positively correlated with expression of immune checkpoint genes and metastasis. We, therefore, established a robust EMT 16-GPS that is independent of detection platform, batch effects and individual variations, and which represents a qualitative signature for investigating the EMT and providing insights into immunotherapy for ovarian cancer patients. CDH1) and gain of the cytoskeletal protein vimentin (encoded by VIM) [The epithelial-mesenchymal transition (EMT) is the transition of cells from an epithelial phenotype to mesenchymal . Importa by VIM) .OvCa is a highly metastatic malignant gynecologic neoplasm. Most OvCa cases are diagnosed at advanced stages, resulting in an often poor prognosis . As suchCDH2), Forkhead box protein C2 (FOXC2), Snail family transcriptional repressor 1, fibronectin 1, and matrix metalloproteinase 2, has become a popular approach in current research [VIM, CDH2, and FOXC2 [. conducted an integrated analysis of the immune landscape through EMT scores derived from the 16-gene signature [. conducted an integrated, global analysis of genomic and proteomic profiles associated with the EMT across 1,934 tumors and developed a signature comprised of 77 unique EMT genes correlated with known core EMT markers across diverse tumor types [. defined a 249 gene expression signature derived from a meta-analysis of differential gene expression in breast cancer cell lines, which was found to be closely associated with the claudin-low and metaplastic breast cancer subtypes, and negatively correlated with the pathological complete response [Developing an EMT signature based on the expression values of EMT-related markers, such as cadherin 2  of genes are stable in some cancer types, such as in primary cancer tissues, however, are typically reversed in the corresponding metastatic cancer tissues . This biIn this study, we hypothesized that a set of REOs between genes exists and is highly stable in patients with epithelial-type cancer, while showing the opposite effect in patients with mesenchymal-type cancer, enabling use of this gene set as a predictive signature for EMT status.We collected data from three cohorts with EMT labels from TCGA (n = 459) to identify EMT-associated genes, as shown in P = 0.0233, log-rank test, To identify qualitative EMT signatures, we performed gene expression analysis based on the REO strategy. The discovery workflow is briefly described in P < 0.05, Fisher’s exact test). After optimization of data with expression reversal ratios of greater than 75% and gene pairs including at least one EMT-associated DEG, we obtained a list of 16 gene pairs  is shown in COL5A2 and FAP were significantly upregulated in mesenchymal OvCa samples compared with epithelial OvCa samples .The gene pair with EMT-associated DEGs , PDL2, and cytotoxic T lymphocyte-associated protein 4 (CTLA4) showed higher expression levels in mesenchymal-like samples than in epithelial-like samples in the GSE9891 dataset  to predict EMT status in patients with OvCa based on within-sample REOs. The prediction efficiency of the 16-GPS outperformed other signatures. Notably, within independent OvCa cohorts, patients with mesenchymal-like OvCa, predicted by 16-GPS, showed poorer prognosis than those with epithelial-like OvCa following administration of platinum-based adjuvant chemotherapy. Additionally, patients with metastatic OvCa had higher EMT scores, confirming the reliability of the 16-GPS. Finally, our results showed that immune checkpoint-related genes tend to be upregulated in mesenchymal-like OvCa.COL5A2, FAP), which were among the top 10 genes overexpressed in the fibroblastic signature [COL5A2 and FAP are known EMT-associated genes that are included in the upregulated EMT core signature. Notably, COL5A2 regulates the assembly of heterotypic fibers by encoding an α chain for a low abundance fibrillar collagen molecule. As a mesenchymal marker, COL5A2 is upregulated in mesenchymal-like tumors [COL5A2 and FAP were highly expressed in individual patients. Nevertheless, based on REOs, we were able to identify the reference genes paired with COL5A2 or FAP, which could be applied to individual patients as the EMT signature.The 16-GPS contains two EMT-associated DEGs . We had predicted the EMT status of TCGA lung adenocarcinoma patients with administration of platinum-based adjuvant chemotherapy. However, overall survival between mesenchymal-like patients and epithelial-like patients did not show significant difference . In our following study, we will explore the prediction and prognostic efficacy of 16-GPS in other cancers, such as breast cancer and liver cancer.Nevertheless, there were some limitations to the REO-based approach. The stable gene pairs were defined according to a predetermined percentage  in our study, and this threshold is flexible. Notably, strict control of the percentage could be beneficial for identifying more reliable gene pairs. During the two-step optimization, the reversal ratio was required to be greater than 75% in mesenchymal samples; this threshold was selected to expand the coverage of mesenchymal samples by reversed gene pairs. In addition, in our analysis of the correlation between metastasis and EMT score, one of the samples scored abnormally, which may have been caused by incomplete detection of genes in 16-GPS by the sequencing platform. Although Da Yang et al network , some ca network . In our  network , 27. We In summary, we developed an REO-based signature consisting of 16 gene pairs to predict the EMT status for OvCa patients. This approach was highly robust against experimental batch effects and is applicable to individual patients. The 18-gene panel may, therefore, be effective in predicting patients with OvCa who may benefit from platinum-based treatment. In the future, it may be possible to design a reverse transcription PCR kit to compare the expression levels of each gene pair in individual patients; however, this approach must be further validated in clinical trials. Moreover, we plan to apply the 16-GPS to other cancer types, including breast and lung cancer.http://gdac.broadinstitute.org/), the Gene Expression Omnibus  and Australia project in International Cancer Genome Consortium . The OvCa cohort (n = 459), downloaded from TCGA data portal, had sufficient clinical information and was evaluated using the Affymetrix U133A platform for training the EMT signature. For 80 samples in which records of platinum chemotherapy were omitted, samples were excluded from survival analysis. The EMT status of TCGA OvCa, GSE9891 and GSE26712 datasets was defined by Da Yang et al. [Gene expression data from patients with OvCa were collected from TCGA data portal, the Broad Institute’s GDAC Firehose .All probe-level mRNA profiles were annotated to Entrez gene IDs using R software. If a gene was mapped to multiple probe sets, the expression value for the gene was generated by calculating the average values. If a probe was mapped to multiple genes, the probe was excluded from subsequent analysis. Level 3 Affymetrix gene expression data were obtained from GDAC  procedure for multiple testing to control the false discovery rate (FDR). Genes with FDRs less than 5% were defined as DEGs. Subsequently, DEGs  were identified from TCGA based on the rank of expression. The expression of these genes was postulated to be significantly associated with EMT status.DEGs between epithelial and mesenchymal OvCa samples were determined by Wilcoxon rank-sum test based on the rank of gene expression within each sample. The i and gene j, where Gi > Gj or Gi < Gj; Gi and Gj denote the expression values of gene i and gene j, respectively. The EMT status  was also a binary value. For a gene pair (Gi and Gj), we defined the REO pattern of Gi > Gj as a stable REO if the number of samples with Gi > Gj accounted for more than 99% of the total number of epithelial samples.Within-sample REO was defined as a binary relationship between gene i > Gj) in more than 99% of epithelial samples, however, with a significantly reversed REO pattern (Gi < Gj) in mesenchymal samples tested by Fisher’s test with P values of less than 0.05. Finally, these reversed gene pairs were chosen as candidates for subsequent screen of an EMT signature  with values of rank differences less than 0 among the total gene pairs of the EMT signature. The EMT signature identified in our study included 16 gene pairs (n = 16) (2). According to (3), samples were divided into the mesenchymal-like group (EMT score ≥ 0.5) or epithelial-like group (EMT score < 0.5).where rank difference denotes the difference between the ranks of two genes within each pair (1). For one OvCa sample, EMT score was calculated as the proportion of gene pairs .The area under the curve (AUC) of the receiver operating characteristic (ROC) curve was used to assess binary classification performance of the signature. Statistical analyses were performed with the Wilcoxon rank-sum test for 2-group comparisons. A value Supplementary Figure 1Supplementary Table 1Supplementary Table 2


Very few cost-utility analyses have either evaluated direct-acting antivirals (DAAs) on hepatitis C virus (HCV) genotype 6 patients or undertaken societal perspective. Recently, DAAs have been introduced into the Vietnamese health insurance drug list for chronic hepatitis C (CHC) treatment without empirical cost-effectiveness evidence. This study was conducted to generate these data on DAAs among CHC patients with genotypes 1 and 6 in Vietnam.A hybrid decision-tree and Markov model was employed to compare costs and quality-adjusted life-years (QALYs) of available DAAs, including (1) sofosbuvir/ledipasvir, (2) sofosbuvir/velpatasvir, and (3) sofosbuvir plus daclatasvir, with pegylated-interferon plus ribavirin (PR). Primary data collection was conducted in Vietnam to identify costs and utility values. Incremental cost-effectiveness ratios were estimated from societal and payer perspectives. Uncertainty and scenario analyses and value of information analyses were performed.All DAAs were cost-saving as compared with PR in CHC patients with genotypes 1 and 6 in Vietnam, and sofosbuvir/velpatasvir was the most cost-saving regimen, from both societal and payer perspectives. From the societal perspective, DAAs were associated with the increment of quality-adjusted life-years by 1.33 to 1.35 and decrement of costs by $6519 to $7246. Uncertainty and scenario analyses confirmed the robustness of base-case results, whereas the value of information analyses suggested the need for further research on relative treatment efficacies among DAA regimens.Allocating resources for DAA treatment for HCV genotype 1 and 6 is surely a rewarding public health investment in Vietnam. It is recommended that the government rapidly scale up treatment and enable financial accessibility for HCV patients. •There have already been several cost-utility analyses of direct-acting antiviral (DAA) regimens conducted, but very few have either evaluated DAA regimens on hepatitis C virus (HCV) genotype 6 patients or undertaken a societal perspective. Our study has addressed this gap in knowledge by being among the first cost-utility analyses of DAA regimens on HCV genotype 6 patients using a societal perspective.•In this study, sofosbuvir/velpatasvir (SOF/VEL), sofosbuvir/ledipasvir (SOF/LDV), and sofosbuvir plus daclatasvir (SOF+DCV) are found to be cost-saving compared with pegylated-interferon plus ribavirin (PR) in HCV patients with genotypes 1 and 6 in Vietnam, from both societal and payer perspectives. Among 3 DAAs, SOF/VEL is the most cost-effective, followed by SOF/LDV as the second, and SOF+DCV as the third. These results remain robust across all government’s copayment rates for DAAs. Our result would be particularly useful for countries with a high prevalence of HCV genotype 6 such as Laos, Cambodia, Myanmar, or Thailand. Three regimens were included: (1) sofosbuvir/ledipasvir (SOF/LDV), (2) sofosbuvir/velpatasvir (SOF/VEL), and (3) sofosbuvir plus daclatasvir (SOF+DCV), while also retaining the old standard of HCV treatment, pegylated-interferon plus ribavirin (PR).,,,The model simulated cohorts of patients infected with HCV genotype 1 and 6 in Vietnam because these 2 genotypes are the most prevalent.11A hybrid of decision-tree and Markov models adapted from Kapol et alPatients entered a decision tree at the initiation of treatment and were chosen to receive either DAA regimens or PR. Upon completion of each regimen, patients could move to 1 of corresponding 4 health states based on their status of sustained virologic response (SVR)—the indication of successful treatment. CHC and CC patients who achieved SVR were assumed to be cured, but CC patients could still progress to hepatocellular carcinoma (HCC),The Markov model was based on the natural history of hepatitis C, and the classification of health states was in line with the current treatment guidelines in Vietnam.Costs and health outcomes were estimated in a lifetime period with 1-year cycle length. A within-cycle correction method, the Simpson’s one-third rule correction method,,The CUA from a societal perspective estimated cost components such as direct medical and direct non-medical costs, including time cost associated with the treatment of patients and their caregivers . The indirect costs  were excluded to avoid a double-counting issue in the CUA.,All DAA regimens in the current Vietnamese health insurance drug list,The model considered the following input parameters, classified into 4 major groups: transition probabilities, treatment efficacy, costs, and utilities .Table 1I,,,The disease-related transition probabilities were obtained from Japan owing to the unavailability of data in Vietnam. Among Asian countries, Japan was found to have the most comprehensive set of transition probabilities estimated from their own population.Treatment efficacy of HCV antivirals was measured by the rate of SVR at the 12th week after stopping antivirals (SVR12). For HCV genotype 1, a systematic search of existing meta-analyses on the efficacy of DAA regimens in genotype 1 was performed, which identified 7 relevant meta-analyses.Direct medical, direct non-medical, and time costs associated with treatment were obtained from primary data collection in Vietnam’s 2 central-level hospitals, Bach Mai Hospital and the National Hospital of Tropical Diseases, in 2019. Ethics approval for the study was granted by the Institutional Review Board of the Hanoi University of Public Health, Vietnam, on July 24, 2018.), and palliative care for patients who failed to achieve SVR12. Direct medical costs were estimated by applying a cost-at-charge approach. In costing, the usual practice is to assume that market price was a reasonable approximation of monetary cost.Direct medical costs included costs of antivirals , treatment monitoring  of patients and their caregivers. These costs were estimated by prospectively interviewing patients or their caregivers.Direct non-medical costs included travel, accommodation, meals, and other relevant non-medical costs (or their caregivers) in seeking care and waiting and receiving care at hospital (or aiding patients to do so). These time costs were valuated using the human capital approach. The number of days lost were prospectively collected from interviewing patients or their caregivers.Time costs were the costs of time loss associated with the treatment, which were borne by patients ,The health outcome of choice was quality-adjusted life-years (QALYs), which is the multiplication of life years (LYs) by utility score. The utility of each health state was obtained from primary data collection using the EQ-5D-5L questionnaireTotal costs, LYs, and QALYs for each treatment were estimated in a lifetime period. In addition, lifetime cumulative incidence of HCV-related complications was calculated by cumulatively adding up the number of HCV-related complications from the first cycle to the last cycle in the model.To estimate the cost-effectiveness of each regimen compared with PR, an incremental cost-effectiveness ratio, calculated by an incremental cost divided by an incremental LY or QALY, was estimated and compared with the cost-effectiveness threshold of 1 GDP per capita of Vietnam per QALY gained. Furthermore, the corresponding net monetary benefit (NMB) of all 3 DAA regimens was compared in order to rank their cost-effectiveness.To test the robustness of the base-case results, a deterministic 1-way sensitivity analysis was performed by stochastically varying 1 parameter at a time between its lower and upper limits, and the corresponding change of NMB was captured and shown graphically as a tornado diagram. Key parameters varied including discount rates  and expected value of partial perfect information (EVPPI) in order to estimate the expected value of further information to resolve the current uncertainty and to identify which type of information would be the most worthwhile.,https://doi.org/10.1016/j.jval.2020.03.018). Consequently, the 5-year affected population, given the annual discount rate of 3%, was 3711 persons.The time horizon for estimating EVPI for population was set at 5 years, which was assumed to be the lifespan of these DAA regimens. The annual affected population was calculated by multiplying the prevalent number of CHC and CC patients with genotypes 1 and 6pairwise EVPI (each DAA compared with PR) and general EVPI  were estimated. The EVPI was estimated by different ceiling ratios, whereas the EVPPI used the ceiling ratios of 1 GDP per capita of Vietnam and was run by 100 outer loops and 100 inner loops.Both https://doi.org/10.1016/j.jval.2020.03.018). Regarding the cumulative incidence of CC .The lifetime cumulative new cases of HCV-related complications  were projected in the model. Compared with PR, all DAA regimens were associated with lower cumulative incidence of all complications. Specifically, DAA regimens decreased the cumulative incidence of DC by 95.3% to 97.1%, whereas the incidence of HCC and LRD was reduced by 23.5% to 23.9% and by 39.8% to 40.6%, respectively. In all cases, SOF/VEL always resulted in the lowest incidence, thereby demonstrating the highest effectiveness in terms of avoiding HCV-related complications .The base-case cost-effectiveness analysis indicated that all DAA regimens dominated PR , based on both societal and payer perspectives . From a Among 3 DAA regimens, SOF/VEL was associated with the lowest lifetime cost at $4055 per patient and was found to be the most efficacious at 15.09 QALYs. Furthermore, in order to directly compare the cost-effectiveness among the 3 DAA regimens, the corresponding NMB of all 3 DAA regimens was calculated, which showed that SOF/VEL was the most cost-effective regimen, followed by SOF/LDV as the second, and SOF+DCV as the third, from both perspectives .https://doi.org/10.1016/j.jval.2020.03.018).Different scenarios of government’s co-payment rates (50%-100%) were explored. In all scenarios, 3 DAAs remained cost-saving in comparison to PR, and SOF/VEL remained the most cost-effective regimen, regardless of the copayment rates, from both perspectives .One-way deterministic sensitivity analysis was shown graphically as a tornado diagram , which iThe probabilistic sensitivity analysis, performed from a societal perspective, confirmed the robustness of the base-case cost-effectiveness result, of which all DAA regimens dominated PR, and SOF/VEL was the most cost-saving regimen. Specifically, the cost-effectiveness plane showed the cost-saving result of DAA regimens in 100% of the 1000 simulations, whereas the cost-effectiveness acceptability curve indicated that at all willingness-to-pay thresholds, SOF/VEL always remained the most cost-effective regimen .Figure 3The pairwise EVPI for population (each DAA regimen compared to PR) was zero at all willingness-to-pay values , suggestThe general EVPI for population (3 DAA regimens and PR compared to each other) was $8.4 million at the willingness to pay of 1 GDP per capita of Vietnam , correspThe 5-year general EVPPI at the willingness to pay of 1 GDP per capita of Vietnam was estimated on all major parameter groups, including DAAs’ treatment efficacy, direct medical cost, direct non-medical and time cost, transition probabilities, utilities, and epidemiology . The uncIn this study, the cost-effectiveness of all available DAA regimens in the Vietnamese health insurance drug listThe robustness of these findings was tested by performing extensive deterministic and probabilistic sensitivity analyses, which found that DAAs always remained cost-saving despite all key parameters being varied across wide yet plausible ranges. The most influential parameters were similar to those reported by other modeling studies in the field.In addition, the result of EVPI for the population indicated a small degree of uncertainty in the CUA results in all willingness-to-pay scenarios, and the decision to adopt DAA regimens would not be likely to change even under perfect information. Nevertheless, if policy makers demand more certain recommendation in terms of cost-effectiveness ranking among DAA regimens, further research to obtain better data on relative treatment efficacies among DAA regimens or better cost estimation might be worthwhile.The cost-saving results of DAA regimens in Vietnam were mainly attributed to the significantly lower DAA prices in Vietnam compared with their original prices. The reduced prices were due to the result of voluntary license agreements signed by the originator companies, which allowed HCV patients to access generic DAAs. Currently, more than 100 countries around the world have benefited from the license agreements, including a majority of LMICs.To meet the World Health Organization’s goal of eliminating HCV as a public health threat by 2030,This study has several limitations. First, our model assumed that all patients complied with the treatment, although dropouts were likely to occur in reality, which may overestimate the benefits of DAA regimens. Second, we assumed that patients had no comorbidities, but in reality, comorbidities may be common at 50 years old; therefore, we may underestimate the benefits of DAA regimens. Third, we did not consider the benefits of HCV treatments in preventing transmissions in society; however, it is expected that the cost-effectiveness results of DAA regimens would be more favorable if this public health benefit were taken into account. Fourth, our model did not include liver transplantation as a health state because it was neither included in the health insurance package nor currently widely accessible in Vietnam. Lastly, owing to the unavailability of some epidemiological data in Vietnam, such as annual age-specific incidence and prevalence of HCV and its complications, in addition to the lack of longitudinal studies on HCV patients, we cannot perform the model calibration to fit actual data in the Vietnamese context. However, the results of all uncertainty analyses have confirmed the robustness of our cost-effectiveness results.,In conclusion, this study has demonstrated that all 3 DAA regimens in the Vietnamese health insurance drug list  are cost-saving in HCV patients with genotypes 1 and 6 from both societal and payer perspectives; thus, allocating resources for DAA treatment is surely a rewarding public health investment. Our results may be particularly useful for countries with a high prevalence of HCV genotype 6. Furthermore, because more current evidence suggesting that DAAs might be effective for advanced-stage HCV patients,In the DAAs era, the elimination of HCV as a public health threat would be feasible, as illustrated by the evidence that we have presented, yet this could not be accomplished without seamless political commitments, a responsive health system, and strong public support.


Cases of inflammatory bowel disease (IBD) during treatment with interleukin (IL)-17 antagonists have been reported from trials in psoriasis, psoriatic arthritis, and ankylosing spondylitis. The aim of this study was to assess the overall risk for development of IBD due to IL-17 inhibition.Systematic review and meta-analysis of studies conducted 2010–2018 of treatment with IL-17 antagonists in patients with psoriasis, psoriatic arthritis, ankylosing spondylitis, and rheumatoid arthritis. We compared risk of IBD development in anti-IL-17 treated patients compared to placebo treatments. We also computed incident rates of IBD overall. A ‘worst case scenario’ defining subjects ambiguous for prevalent versus incident cases for the latter was also applied.Sixty-six studies of 14,390 patients exposed to induction and 19,380 patients exposed to induction and/or maintenance treatment were included. During induction, 11 incident cases of IBD were reported, whereas 33 cases were diagnosed during the entire treatment period. There was no difference in the pooled risk of new-onset IBD during induction studies for both the best-case [risk difference (RD) 0.0001 ] and worst-case scenario [RD 0.0008 ]. The risk of IBD was not different from placebo when including data from maintenance and long-term extension studies .The risk for development of IBD in patients treated with IL-17 antagonists is not elevated. Prospective surveillance of patients treated with IL-17 antagonists with symptom and biomarker assessments is warranted to assess for onset of IBD in these patients. The inflammatory bowel diseases (IBD), Crohn’s disease (CD) and ulcerative colitis (UC), are chronic inflammatory conditions which can affect various segments of the gastrointestinal tract and the colon only, respectively. Typical symptoms include diarrhea, abdominal pain and rectal bleeding, as well as development of stenoses, abscesses and fistulas in case of CD.IBD manifests in genetically susceptible patients, potentially triggered by environmental factors and/or perturbations of the gut microbiota leading to a dysregulated mucosal immune system and development of chronic intestinal inflammation , 2. In gThe interleukin-17 family cytokines (IL-17A to IL-17F) that signal via several IL-17 receptors (IL-17R A to E)  are stroNotably, inhibition of IL-17A has been shown to worsen colitis in mouse models , 14 and In order to expand the picture on the potential induction of IBD beyond the observed increased background risk in IMIDs, we conducted an in-depth systematic review and meta-analysis of studies with three different IL-17 inhibitors  in patients with chronic plaque psoriasis, psoriatic arthritis, ankylosing spondylitis and rheumatoid arthritis to determine whether incidence of IBD is elevated in patients treated with IL-17 antagonists compared to those treated with placebo.Systematic review and meta-analysis were conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols. The review protocol was registered on PROSPERO (registration no. CRD42018109276).st 2018 in order to identify studies with IL-17 inhibitors in patients with IMIDs reporting cases with IBD, A systematic literature search on PubMed, EMBASE and clinicaltrials.gov using the Medical Subject Headings (MeSH) terms “Secukinumab”, “Ixekizumab”, “Brodalumab”, and “psoriasis”, “psoriatic arthritis”, “ankylosing spondylitis”, or “rheumatoid arthritis” was conducted with a cut-off date of August 31For data extraction the original publications including supplementary material, if available, were reviewed. Data of interest comprised information on the publication itself , study characteristics  and reports of adverse events of special interest . For unpublished studies identified through clinicaltrials.gov, we retrieved data from the European Medical Agency (EMA).If no case of new-onset IBD was reported in a publication, we assumed that there was no such event. In some studies, detailed specifications into CD versus UC and/or new-onset cases (incident cases) versus subjects with flares of preexisting disease  were not provided. Therefore, two different scenarios were assumed in the analysis process: a ‘worst case scenario’, for which all cases unclear for incident versus prevalent cases were considered new diagnoses, and a ‘best case scenario’, for which all unclear cases were considered as prevalent ones.In placebo-controlled studies, we analyzed the risk of new onset IBD in patients treated with IL-17 inhibitors compared to patients receiving placebo using the Mantel-Haenszel risk difference in a random-effects model.Incidence rates (IRs) were calculated for all studies as the number of outcomes per 1,000 patient-years with 95% confidence intervals. Due to the low number of events, we combined all incident cases of CD and UC to incident IBD cases. As the individual treatment duration of patients was not available in all included studies, the number of person years was calculated by multiplying the number of patients with the treatment duration for each study. In studies in which no cases of IBD were reported, a correction of 0.05 was added to all columns. This would allow for inclusion of studies with zero total events, which is generally recommended when conducting meta-analyses where risk difference is the primary effect measure, as it provides a narrower range of confidence interval and decreases between-study heterogeneity .IRs for all studies (both placebo-controlled and open-label extension studies) were pooled using a random-effects model. Data on incident cases from induction studies were analyzed separately to those encompassing the reported entire study period. Sub-group analyses were performed per individual drug and per indication. Data from studies comparing IL-17 inhibitors to active comparator arms was also used to calculate IRs, but we did not compare the risk of IBD in anti-IL-17 treated patients to that of active comparators given a very heterogeneous group of comparators were used in the different studies.2 statistic, as described in the Cochrane Handbook of Systematic reviews  and worst-case scenario [RD 0.0008 ]. The same was the case for studies of the entire treatment period [RD 0.0007  and RD 0.0022 ]. Pooled RD are summarized in Figs We also assessed the incidence rates of IBD in the group of patients treated with IL-17 inhibitors. After combining new-onset IBD cases across all studies by the less conservative worst-case scenario we observed a pooled incidence rate of 0.37 per 1,000 patient-years  for the entire treatment period . In the Individual study quality assessments are provided in This meta-analysis of over 19,000 patients treated with SEC, IXE and BRO for psoriasis, psoriatic arthritis, ankylosing spondylitis and rheumatoid arthritis spanning an exposure for over six years, did not observe an increased risk of incident IBD in these patients. In our analysis, 47 cases of IBD , and IXE . Notably, in trials assessing efficacy and safety of BRO only one event of CD was documented . This fiRegarding the studied indications, most randomized patients were afflicted with psoriasis, while fewer patients were treated for psoriatic arthritis, ankylosing spondylitis or rheumatoid arthritis. Among these indications, most incident cases occurred in patients with ankylosing spondylitis , followed by psoriasis  and psoriatic arthritis . These findings suggest a potentially increased risk for occurrence of IBD under inhibition of IL-17. However, these results have to be interpreted with caution as the studies included were heterogeneous. Furthermore, an inherently increased co-aggregation of various IMIDs such as CD, UC, psoriasis and psoriatic arthritis could contribute to an increased number of IBD incident cases in the reviewed anti-IL-17/IL-17R studies In most trials, IBD was not pre-defined as an adverse event of interest and cases were only spontaneously reported. It is not clear if gastroenterologists were involved in case adjudication, and whether patients underwent diagnostic procedures to confirm a diagnosis of IBD. In some studies, occurrence of IBD was not specifically mentioned –46, poteWe had to exclude some publications from our meta-analysis due to repetition and partially dissenting reporting of numbers of patients with IBD from study results of phase III trials and their long-term extensions, a circumstance that most likely only marginally impacts our findings. In some publications the number of patients with IBD at baseline remained elusive. We addressed ambiguities in the distinction between incident versus prevalent cases of IBD under IL-17 blockade by running our meta-analysis on two different scenarios: a conservative best case scenario, by which unclear cases are accounted as incident ones and a more progressive worst case scenario, which defined unclear cases as prevalent ones. Even though those analyses led to obvious shifts in diagnoses of incident cases, this did not impact our overall results. Another limitation of our study is that we did not have access to the individuals’ exposure time. We therefore were not able to explore potential relationships on duration of drug exposure and occurrence and magnitude of adverse events of special interest. Also based on our data, we cannot conclude whether these potentially IBD-inducing effects of IL-17 directed therapies are permanent or reversible upon cessation of treatment.Finally, the results of our analysis should be interpreted with caution due to several reasons. The duration of follow-up was short in many trials and both follow-up times and incidence rates varied among trials, as did the study settings which therefore could bias the results. Furthermore, the number of studies with zero events among both the placebo and IL-17 inhibitor treated groups was high. Therefore, the power of the study is potentially limited. While the inclusion of such studies is recommended when conducting meta-analyses of risk differences , 47, it To date this review and meta-analysis is the most comprehensive analysis of data concerning a potential association between blocking IL-17 and occurrence of IBD. Another strength is that in this analysis we used several approaches to account for potential events of IBD, as information on new diagnosis or disease relapse was missing in several studies. In conclusion, while we did not find an increased risk for IBD after initiation of anti-IL-17 directed therapies, close monitoring of symptoms and biomarkers which may suggest IBD before and during treatment with SEC, IXE, and BRO appears reasonable. Further prospectively conducted studies investigating the occurrence of IBD in populations at risk  are warranted.S1 Checklist(DOC)Click here for additional data file.S1 Fig(TIF)Click here for additional data file.S2 Fig(JPG)Click here for additional data file.S3 Fig(JPG)Click here for additional data file.S4 Fig(JPG)Click here for additional data file.S5 Fig(JPG)Click here for additional data file.S6 Fig(JPG)Click here for additional data file.S7 Fig(JPG)Click here for additional data file.S8 Fig(JPG)Click here for additional data file.S9 Fig(JPG)Click here for additional data file.S10 FigA) Short-term, best-case, B) short-term, wort-case, C) entire, best-case, D) entire, worst-case.(TIFF)Click here for additional data file.S11 Fig(JPG)Click here for additional data file.S12 Fig(JPG)Click here for additional data file.S13 Fig(JPG)Click here for additional data file.S14 Fig(JPG)Click here for additional data file.S15 Fig(JPG)Click here for additional data file.S16 Fig(JPG)Click here for additional data file.S17 Fig(JPG)Click here for additional data file.S18 Fig(JPG)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Research on Legionnaires’ Disease (LD) suggests there may be long-term health complications, but data are limited. This study investigated whether Intensive Care Unit (ICU) admission during LD hospitalization may be associated with adverse health outcomes and characterized subsequent discharge diagnoses in patients with LD up to 5 years post-LD.We conducted a retrospective case series study with follow up for 5 years among patients hospitalized at a Department of Veterans Affairs (VA) Medical Center between 2005 and 2010 with LD. Data were collected from medical records on health history, LD severity (including ICU admission), and discharge diagnoses for 5 years post-LD or until death. We used ordinal logistic regression to explore associations between ICU admission and hospitalizations post-LD. Frequency counts were used to determine the most prevalent discharge diagnoses in the 5 years post-LD.Hosp 1.92 CI95% 1.25, 2.95). Fifty-five percent (161/292) had ≥ 1 hospitalization within 5 years post-LD. After accounting for pre-existing diagnosis codes in patients with at least one hospitalization in the 2 years prior to LD , three of the four most frequent new diagnoses in the 5 years post-LD were non-chronic conditions: acute renal failure , acute respiratory failure  and unspecified pneumonia .For the 292 patients with laboratory-confirmed LD, those admitted to the ICU during LD hospitalization were more likely to have a greater number of hospitalizations within 5 years compared to non-ICU patients (OROur findings indicate that LD requiring ICU admission is associated with more subsequent hospitalizations, a factor that could contribute to poorer future health for people with severe LD. In addition to chronic conditions prevalent in this study population, we found new diagnoses in the 5-year post-LD period including acute renal failure. With LD incidence increasing, more research is needed to understand conditions and factors that influence long term health after LD. Legionella [Legionella disease is likely much larger than reported. This under-recognition of LD cases complicates the examination of long-term health outcomes associated with LD, an important area of study given the adverse outcomes across organ systems from Legionella infection [Legionnaires’ Disease (LD) is a pneumonia with potential multi-system sequelae caused by bacteria in the genus gionella . The LD gionella , 3, withgionella . Becausegionella , the potnfection –8 and thnfection , 10.L. pneumophila and L. longbeachae found a total of four re-admissions within one year after discharge among 20 patients with LD caused by the former pathogen compared to two re-admissions in 24 patients with LD caused by the latter [While reports have assessed acute outcomes of LD , 12, rese latter . While tLegionella infection.To address knowledge gaps in understanding the health consequences of LD, our study leveraged the national electronic health record (EHR) system , 18 of tth revision, Clinical Modification, (ICD-9-CM) diagnosis code for LD (482.84).The VHA healthcare system is the largest integrated healthcare system in the U.S. and provides care to nearly 9 million enrolled military veterans at 170 medical centers across the U.S. and territories. Included were individuals discharged from a VA acute care facility from federal fiscal year (FY) 2005 through FY 2010  with an International Classification of Diseases, 9The study protocol was reviewed by the Cincinnati VA Medical Center Research Service for adherence to VA patient privacy policy and approved by the University of Cincinnati Institutional Review Board (IRB), the IRB of record for the Cincinnati VA Medical Center (IRB #2017–3328). The IRB waived informed consent for this retrospective case series study. No patient medical charts were altered in the course of this study, and the rights and welfare of patients included in the study were not adversely affected. Identifiable information was used for chart abstractions, and use of patient record data for analysis was approved by the VA Data Access Request Tracker.To identify patients with an LD discharge diagnosis between FY 2005 and FY 2010, we queried the VHA Patient Treatment Files (PTF) for the ICD-9-CM code for LD. For patients identified as having LD via this initial search, we confirmed the LD diagnosis through medical chart review for evidence of laboratory verification via urine antigen test, respiratory culture, or serology.For all patients with laboratory-confirmed LD , a clinician (N.R.) abstracted the EHR for details on clinical course during the admission for: pertinent respiratory and immune history, including chronic obstructive pulmonary disease (COPD), emphysema, asthma, cancer, smoking and human immunodeficiency virus (HIV) status; intensive care unit (ICU) admission data, including mechanical ventilation and sepsis diagnoses during the qualifying LD admission; and radiologic imaging results. ICU admission was considered a surrogate of LD case severity , 10.To collect data on long term health outcomes, we searched LD case patients’ medical records in the PTF for all subsequent inpatient hospitalizations at any VA hospital within the 5-year period after the LD qualifying admission. We recorded all ICD-9-CM discharge codes associated with any VA hospitalization during this follow-up period to investigate associations with LD case severity.To assess differences in demographic characteristics , pre-existing conditions , indicators of disease severity , and length of stay for the qualifying LD admission between ICU-admitted and non-ICU-admitted patients, we used two-sided t-tests for continuous variables and Fisher’s exact tests for categorical variables.We evaluated several criteria to determine adverse health outcomes in ICU and non-ICU groups. We used ordinal logistic regression and unconditional logistic regression to assess the association between ICU admission and number of hospitalizations in the 5-year follow-up period. For ordinal regression analyses, we defined the outcome variable by three groups: 0–1 subsequent hospitalizations, 2 subsequent hospitalizations, and 3 or more subsequent hospitalizations, according to the sample’s hospitalization tertiles. We assessed the proportional odds assumption using log-log survival curves and goodness of fit tests. To assess confounding, we condensed any diagnosis of emphysema, asthma, and COPD into one dichotomous chronic respiratory history variable to avoid over stratification of our limited sample. Similarly, we also condensed any diagnosis of HIV and current or past history of cancer into one dichotomous variable representing immunocompromised status. In the fully adjusted models, we included variables for age, respiratory history, smoking history, immunocompromised status, and race. To test for interaction, we jointly tested ICU with chronic respiratory history, age, and immunocompromised status, followed by backwards elimination for confounding assessment. We also used a separate model using only respiratory history as a confounder to assess the odds ratio for subsequent hospitalizations in ICU versus non-ICU LD patients.To evaluate differences in time to first hospitalization subsequent to the qualifying LD admission, between ICU and non-ICU groups, we fit Cox proportional hazard models to calculate hazard ratios. We considered age, respiratory history, smoking, and immunocompromised status as confounders in these models. A log-rank test was used to test the equality of the survival curves for ICU and non-ICU LD patients.We used frequency counts to identify the primary ICD-9-CM codes most often observed at the first subsequent hospitalization after the qualifying LD admission; we used the Fisher’s exact test to assess differences in frequencies of codes at subsequent hospitalizations between ICU and non-ICU LD cases. We also used frequency counts to find the primary ICD-9-CM codes most often newly observed in patients hospitalized in the 5 FYs after the qualifying LD admission. Patients were included in this analysis if they had at least one VA hospitalization in the two FYs prior to the qualifying LD admission  and at least one VA hospitalization in the 5 FYs after the qualifying LD admission; if diagnosis codes were present in a patient’s medical record pre-LD, those codes were not included in the frequency count for the post-LD period. Diagnosis codes in the qualifying LD admission were not used for this adjustment. Remaining diagnosis codes in the post-LD period were counted only once per patient at first appearance in the medical record. Frequencies for post-LD diagnosis codes were calculated at six time points: 6 months post-LD and annually thereafter for 5 FYs.The initial search of the national VA EHR for the ICD-9-CM diagnosis code for LD yielded 332 possible cases between FY 2005 –FY 2010 . Twenty-The median age of study subjects was 61 years, and the cohort was primarily male (97.3%), white (73.3%), and a reported smoker (65.8%) . While tOf the 292 patients in the sample, 131 (45%) had no subsequent hospitalization recorded in the VA EHR in the 5 years following their qualifying LD admission. Thirty-four (26%) of these 131 individuals died within the follow-up period. For the remaining 161 patients with record of at least one subsequent hospitalization in the following 5 years, 56 (35%) died in the follow-up period. The 30-day all-cause readmission rate from the LD qualifying admission was 16.2% (26/161).Crude 1.46, 95% CI: 1.06, 2.02 p = 0.02). While this association was attenuated after adjustment for respiratory history alone , it remained significant upon adjustment for age, smoking, respiratory history, and immunocompromised status . Age, respiratory history, smoking, immunocompromised status, and ICU admission were assessed for proportional hazards, and found to have no significant violations in graphical log-log survival curves, goodness of fit testing, and time-dependent variable testing.Average time to first hospitalization after the qualifying LD admission was 29.5 months in ICU-admitted LD patients and 36.1 months in non-ICU-admitted LD patients  . This prHosp 1.92 CI95% 1.25, 2.95 p<0.01) .Cases admitted to the ICU during the qualifying admission were more likely to have a greater number of hospitalizations within 5 years compared to non-ICU cases (OR p<0.01) . This asTo assess new health conditions after LD, we reviewed ICD-9-CM coding for hospitalizations in the 5 years post-LD after first removing codes that appeared in the patients’ medical records in the 2 years prior to LD. Of the 161 patients with at least one VA hospitalization in the 5 years after LD, 77 (48%) also had at least one VA hospitalization in the 2 years pre-LD. The most common new discharge diagnosis in the entire 5-year follow-up period for subsequent admissions in the 77 patients was acute renal failure  . When thDischarge coding for the 22 patients with acute renal failure post-LD but not pre-LD was examined further to see if these patients had other kidney-related conditions diagnosed in the pre-LD period. Of the 22 patients, 17 (77.3%) had no codes in the 2-years pre-LD corresponding with nephritis, nephrotic syndrome, and nephrosis (codes 580–589) or with hypertensive chronic kidney disease (codes 403 and 404). Eight of the 22 patients (36.4%) had no other kidney-related discharge diagnosis codes in the 5-years post LD. We also examined coding for the 22 patients in the qualifying LD admission for acute kidney failure; thirteen (59%) did not have the code in that visit. Finally, we reviewed the pre-LD period for the 22 patients for diabetes mellitus (code 250.*) since this condition can impact renal disease; 9 of the patients did not have diabetes mellitus codes in the pre-LD period.As the first large study to explore health-related outcomes of LD patients beyond 2 years, this work offers insights into the longer-term health outcomes potentially associated with LD. The 30-day all-cause readmission rate of 16.2% is similar to published 30-day readmission rates for pneumonia . This suUnspecified pneumonia was the most frequent discharge diagnosis for a first hospitalization after an LD admission, occurring more than twice as frequently as the next most common diagnosis. When we excluded discharge diagnosis codes from first hospitalizations within 30 or 60 days of the LD admission, unspecified pneumonia remained the most frequent diagnosis, indicating that these pneumonias were likely not continuations of the incident LD episode.With so little known about the long-term health consequences of LD, especially among cases not necessarily linked to an LD outbreak, this large descriptive study generates numerous hypotheses worthy of further exploration. Our study offers insight as to whether LD resulting in ICU admission impacts long term health. In our analysis, LD requiring ICU admission was associated with a higher mean number of hospitalizations in the 5-year follow-up period and a shorter time to first subsequent hospitalization than non-ICU LD cases. This included a non-significant but increased likelihood of subsequent hospitalizations for pneumonia. Our findings suggest that LD resulting in an ICU admission may play a role in increased morbidity after the LD episode. Future studies could attempt to discern if these findings are unique to LD, or if similar outcomes are observed following hospitalizations for pneumonias of other etiologies.Intensive care unit admission can be considered a surrogate for severity of illness, and the patients in our study with ICU admission during LD had significantly more severe illness than those not admitted to the ICU. We excluded the 17 patients who died with LD during their stay since they could not be assessed for long term health outcomes; all 17 patients were admitted to the ICU during their LD visit and their exclusion likely attenuated some of the differences observed in disease severity in our comparison of ICU- and non-ICU patients. Admission to the ICU for any reason is known to be associated with subsequent morbidity, especially in elderly populations, and further research is needed to determine whether the increased risk for subsequent hospitalizations observed here is different from the risk for rehospitalization following ICU admission for other reasons . But, onLegionella pneumonia have reported concomitant kidney injury that range from mild, temporary impairment to damage necessitating dialysis, indicating the potential for long-term adverse renal effects secondary to infection [Case studies of severe nfection –29. In tnfection , 31 remaOur study has some important strengths and limitations. First, this is the first study to attempt to examine health outcomes of LD cases regardless of their connection to an identified outbreak. The VA has had long-standing policy for preventing LD, including policy initiated in 2008 encouraging routine testing of pneumonia patients for LD . More reSecond, a particular strength of this study was the availability of medical records in the VA EHR system, allowing for long-term follow-up of a large cohort of LD patients. A comparable dataset in the U.S. is not as readily available from private sector healthcare records. The intent of this study was to identify and characterize hospitalized cases of LD in the VA medical system from FY 2005 to FY 2010, so we did not identify a comparison group, nor did we explore outpatient records related to non-hospitalized cases. Future use of the VA EHR for these efforts will build on the findings in this study.Utilization of data in VA medical records has some limitations. First, we were reliant on administrative discharge diagnosis coding for patients that had at least one admission to a VA facility in the 2 years prior to the qualifying LD visit as an indication of pre-existing conditions and subsequent new diagnoses post-LD. Use of discharge coding for health research in VA patients is well-established , 35–37, Legionella infection to accelerate the trajectory of other conditions such as acute renal illness. Differences between ICU-admitted and non-ICU admitted patients with LD were also highlighted, suggesting the need to follow ICU-admitted LD patients more closely after discharge to prevent readmissions and adverse health effects. Further research regarding the prevalence of pre-existing conditions and their effect on hospital course for LD and other pneumonias, differences in health outcomes after pneumonias of different etiologies, and the associations between those outcomes and the severity of incident pneumonia will add to understanding the epidemiology and health consequences of LD.This retrospective case series offers unique and important insights into the long-term health of patients with LD, including the potential for the S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 Table(DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 Table(DOCX)Click here for additional data file.