scholarly journals P536 Early prediction of intravenous corticosteroid therapy failure in moderate–severe ulcerative colitis

2020 ◽  
Vol 14 (Supplement_1) ◽  
pp. S458-S458
Author(s):  
A Croft ◽  
A Lord ◽  
G Radford-Smith

Abstract Background An episode of acute severe ulcerative colitis (UC) is a watershed event during the disease course with a heightened risk of colectomy during and following these episodes.1 The prompt identification of these events followed by the early implementation of appropriate treatment is essential to obtaining the best clinical outcomes for these unwell patients. The majority of published risk scores predicting the important clinical outcomes of intravenous corticosteroid therapy failure and colectomy-by-discharge rely on clinical data from days 1–3 of therapy.2 There is a paucity of tools that allow for a simple and individualised prediction of risk of corticosteroid therapy failure during the earliest stages of admission. Methods Data were prospectively obtained from 349 presentations of moderate–severe UC requiring hospital admission to a tertiary referral hospital. The failure of intravenous corticosteroid therapy was strictly defined by the (Oxford) Day 3 and Day 7 criteria.3 Seventeen clinical, laboratory and endoscopic variables all available within 24 h of hospital presentation were assessed for their ability to differentiate intravenous corticosteroid therapy responders from non-responders. A stepwise generalised linear model was formulated based on the results of the initial univariate analyses. Results Intravenous corticosteroid therapy failure occurred in 208/349 (60%) of presentations. The formulated risk score included the variables of oral corticosteroid therapy failure, bowel frequency and serum albumin concentration with or without the Mayo endoscopic subscore (MES). With the addition of the MES, the area under the curve (AUC) of the risk score was 0.758. When the positive predictive value of the score (threshold) for correctly predicting intravenous corticosteroid therapy failure was set at 85%, 105/275 (38%) of presentations with available data were identified as high risk for corticosteroid therapy failure (Figure 1). Conclusion This practical risk assessment tool provides clinicians with a personalised prediction of the likelihood of success of a course of intravenous corticosteroid therapy in moderate–severe UC. It enables the identification of individuals at high risk of treatment failure who may be suitable for consideration of early treatment escalation or screening for appropriate clinical trials. References

2021 ◽  
Vol 15 (Supplement_1) ◽  
pp. S357-S357
Author(s):  
P Kakkadasam Ramaswamy ◽  
D Subhaharan ◽  
L Willmann ◽  
J Edwards ◽  
D Shukla ◽  
...  

Abstract Background The efficacy of Infliximab and Cyclosporin A as medical rescue therapy in patients with corticosteroid refractory acute severe ulcerative colitis (ASUC) is well established. We aimed to identify predictors of failure of medical rescue therapy and colectomy during the same admission in this population. Methods Patients hospitalized with ASUC who received infliximab or cyclosporin A after failing intravenous corticosteroid therapy between 1st January 2013 to 31stJuly, 2020 at two Australian tertiary IBD centres were retrospectively analysed. Patients who underwent colectomy during the same admission after medical rescue therapy were defined as non-responders. Logistic regression analysis was performed to identify predictors of colectomy during same admission. Results 226 episodes of ASUC [110 (48.7%) female, median disease duration 2 years] were analysed. 104 (46%) episodes required rescue therapy [94 episodes received medical rescue (16 cyclosporine/78 Infliximab) and 10 underwent direct colectomy]. In patients receiving medical rescue therapy, 16 (17%) underwent colectomy during same admission and 28 (29.8%) underwent colectomy by 12 months. On multivariable analysis, UCEIS score at admission [Coef 0.100 (0.02-0.17), p 0.011] and CRP on Day 3 post-rescue therapy [Coef 0.004 (0.0007-0.007), p 0.018] were significant for predicting colectomy during the same admission. A score with 1 point for each variable (UCEIS score ≥ 7 and CRP value of ≥ 22 mg/L on day 3 post medical rescue therapy) was developed. A score of 2 points had sensitivity 57%, specificity 97%, PPV 80%, NPV 91%, accuracy 89% for predicting colectomy during the same admission and sensitivity 33%, specificity 94%, PPV 80%, NPV 67%, accuracy 69% for predicting colectomy at 12 months. Conclusion UCEIS and CRP on day 3 after rescue therapy are predictors of non-response to medical rescue therapy and need for colectomy during the admission for the ASUC episode. Combination of UCEIS ≥ 7 and CRP ≥ 22mg/L on day 3 post medical rescue therapy has a PPV of 80% for colectomy during same admission and at 12 months. The score can be used to make decisions about colectomy or further medical rescue therapy.


PLoS ONE ◽  
2010 ◽  
Vol 5 (9) ◽  
pp. e13085 ◽  
Author(s):  
Boyko Kabakchiev ◽  
Dan Turner ◽  
Jeffrey Hyams ◽  
David Mack ◽  
Neal Leleiko ◽  
...  

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Carly A. Conran ◽  
Zhuqing Shi ◽  
William Kyle Resurreccion ◽  
Rong Na ◽  
Brian T. Helfand ◽  
...  

Abstract Background Genome-wide association studies have identified thousands of disease-associated single nucleotide polymorphisms (SNPs). A subset of these SNPs may be additively combined to generate genetic risk scores (GRSs) that confer risk for a specific disease. Although the clinical validity of GRSs to predict risk of specific diseases has been well established, there is still a great need to determine their clinical utility by applying GRSs in primary care for cancer risk assessment and targeted intervention. Methods This clinical study involved 281 primary care patients without a personal history of breast, prostate or colorectal cancer who were 40–70 years old. DNA was obtained from a pre-existing biobank at NorthShore University HealthSystem. GRSs for colorectal cancer and breast or prostate cancer were calculated and shared with participants through their primary care provider. Additional data was gathered using questionnaires as well as electronic medical record information. A t-test or Chi-square test was applied for comparison of demographic and key clinical variables among different groups. Results The median age of the 281 participants was 58 years and the majority were female (66.6%). One hundred one (36.9%) participants received 2 low risk scores, 99 (35.2%) received 1 low risk and 1 average risk score, 37 (13.2%) received 1 low risk and 1 high risk score, 23 (8.2%) received 2 average risk scores, 21 (7.5%) received 1 average risk and 1 high risk score, and no one received 2 high risk scores. Before receiving GRSs, younger patients and women reported significantly more worry about risk of developing cancer. After receiving GRSs, those who received at least one high GRS reported significantly more worry about developing cancer. There were no significant differences found between gender, age, or GRS with regards to participants’ reported optimism about their future health neither before nor after receiving GRS results. Conclusions Genetic risk scores that quantify an individual’s risk of developing breast, prostate and colorectal cancers as compared with a race-defined population average risk have potential clinical utility as a tool for risk stratification and to guide cancer screening in a primary care setting.


2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.


2020 ◽  
Author(s):  
Bin Wu ◽  
Yi Yao ◽  
Yi Dong ◽  
Si Qi Yang ◽  
Deng Jing Zhou ◽  
...  

Abstract Background:We aimed to investigate an immune-related long non-coding RNA (lncRNA) signature that may be exploited as a potential immunotherapy target in colon cancer. Materials and methods: Colon cancer samples from The Cancer Genome Atlas (TCGA) containing available clinical information and complete genomic mRNA expression data were used in our study. We then constructed immune-related lncRNA co-expression networks to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high-risk and low-risk groups were separated on the basis of the median risk score, which served as the cutoff value. An overall survival analysis was then performed to confirm that the risk score developed from screened immune-related lncRNAs could predict colon cancer prognosis. The prediction reliability was further evaluated in the independent prognostic analysis and receiver operating characteristic curve (ROC). A principal component analysis (PCA) and gene set enrichment analysis (GSEA) were performed for functional annotation. Results: Information for a total of 514 patients was included in our study. After multiplex analysis, 12 immune-related lncRNAs were confirmed as a signature to evaluate the risk scores for each patient with cancer. Patients in the low-risk group exhibited a longer overall survival (OS) than those in the high-risk group. Additionally, the risk scores were an independent factor, and the Area Under Curve (AUC) of ROC for accuracy prediction was 0.726. Moreover, the low-risk and high-risk groups displayed different immune statuses based on principal components and gene set enrichment analysis.Conclusions: Our study suggested that the signature consisting of 12 immune-related lncRNAs can provide an accessible approach to measuring the prognosis of colon cancer and may serve as a valuable antitumor immunotherapy.


2019 ◽  
pp. 60-62
Author(s):  
A. A. Yanishev ◽  
A. V. Bazaev ◽  
A. I. Abelevich ◽  
E. A. Babushkina

2020 ◽  
Vol 26 (10) ◽  
pp. 1524-1532
Author(s):  
Nienke Z Borren ◽  
Damian Plichta ◽  
Amit D Joshi ◽  
Gracia Bonilla ◽  
Ruslan Sadreyev ◽  
...  

Abstract Background Inflammatory bowel diseases (IBD) are characterized by intermittent relapses, and their course is heterogeneous and unpredictable. Our aim was to determine the ability of protein, metabolite, or microbial biomarkers to predict relapse in patients with quiescent disease. Methods This prospective study enrolled patients with quiescent Crohn disease and ulcerative colitis, defined as the absence of clinical symptoms (Harvey-Bradshaw Index ≤ 4, Simple Clinical Colitis Activity Index ≤ 2) and endoscopic remission within the prior year. The primary outcome was relapse within 2 years, defined as symptomatic worsening accompanied by elevated inflammatory markers resulting in a change in therapy or IBD-related hospitalization or surgery. Biomarkers were tested in a derivation cohort, and their performance was examined in an independent validation cohort. Results Our prospective cohort study included 164 patients with IBD (108 with Crohn disease, 56 with ulcerative colitis). Upon follow-up for a median of 1 year, 22 patients (13.4%) experienced a relapse. Three protein biomarkers (interleukin-10, glial cell line–derived neurotrophic factor, and T-cell surface glycoprotein CD8 alpha chain) and 4 metabolomic markers (propionyl-L-carnitine, carnitine, sarcosine, and sorbitol) were associated with relapse in multivariable models. Proteomic and metabolomic risk scores independently predicted relapse with a combined area under the curve of 0.83. A high proteomic risk score (odds ratio = 9.11; 95% confidence interval, 1.90-43.61) or metabolomic risk score (odds ratio = 5.79; 95% confidence interval, 1.24-27.11) independently predicted a higher risk of relapse over 2 years. Fecal metagenomics showed an increased abundance of Proteobacteria (P = 0.0019, q = 0.019) and Fusobacteria (P = 0.0040, q = 0.020) and at the species level Lachnospiraceae_bacterium_2_1_58FAA (P = 0.000008, q = 0.0009) among the relapses. Conclusions Proteomic, metabolomic, and microbial biomarkers identify a proinflammatory state in quiescent IBD that predisposes to clinical relapse.


2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S104-S104
Author(s):  
Anja Richter ◽  
Evangelos Vassos ◽  
Matthew J Kempton ◽  
Mark van der Gaag ◽  
Lieuwe de Haan ◽  
...  

Abstract Background Genetic vulnerability to psychosis is polygenic, involving multiple genes with small individual effects (Psychiatric Genomics Consortium (PGC), 2014). The risk of psychosis is also related to environmental factors, such as childhood trauma (Lardinois et al, 2011). Although the onset of psychosis is thought to result from the interaction of genetic and environmental risk factors (Walker & Diforio, 1997), the extent to which the influence of childhood trauma depends on genetic susceptibility remains unclear. We sought to address this issue in a large prospective study of people at clinical high risk (CHR) for psychosis. These individuals present with psychotic and affective symptoms, and are at increased risk of developing both schizophreniform and affective psychoses. Methods We studied subjects of European ancestry, drawn from EU-GEI, a large multi-centre prospective study of people at CHR for psychosis. At baseline, DNA was obtained from subjects who met the CAARMS criteria for the CHR state (n=266) and healthy controls (HC; n=42). Childhood trauma was assessed using the childhood trauma questionnaire (CTQ), which comprises 5 subdomains: emotional abuse, physical abuse, sexual abuse, physical neglect, and emotional neglect. Polygenic risk scores (PRSs) for schizophrenia (SCZ), bipolar disorder (BD) and major depressive disorder (MDD) were constructed separately, using results from meta-analyses by the corresponding Disorder Working Groups of the PGC. The CHR subjects were clinically monitored for up to 5 years and clinical outcomes were assessed in terms of transition to psychosis (as defined by the CAARMS), remission from the CHR state (subject no longer meets CAARMS inclusion criteria) and level of functioning (GAF Disability Scale). Logistic regression models were used to investigate the association between each PRSs and childhood trauma as predictors of transition and remission, adjusted by population stratification using the first 10 principal components, age, sex and site. All findings are reported at p&lt;0.017, Bonferroni-corrected for the 3 PRSs. Results Within the CHR sample, the onset of psychosis during follow up was related to interactions between the BD PRS and the total childhood trauma score (OR=0.959, 95% CI 0.930–0.988, p=0.006), and between the BD PRS and physical abuse (OR=0.787, 95% CI 0.689–0.900, p&lt;0.001). Remission from the CHR state was related to an interaction between the SCZ PRS and childhood sexual abuse (OR: 1.110, 95% CI 1.004–1.226, p=0.041). Discussion These data indicate that clinical outcomes in CHR subjects are related to interactions between the polygenic risk for psychotic disorders and childhood adversity. The measurement of interactions between genomic and environmental risk factors may help to predict individual outcomes in people at high risk in a clinical setting.


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