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A clinical scoring system to predict long-term arthralgia in Chikungunya disease: A cohort study.

ABSTRACT: BACKGROUND:Chikungunya virus (CHIKV) has caused worldwide epidemics that impose a major burden on health systems. Approximately half of infected individuals develop chronic debilitating arthralgia, affecting their quality of life. Here, we identified the relevant clinical and demographic variables in the acute phase of CHIKV infection prospectively linked to chronic arthralgia to elaborate a prognostic scoring system. METHODS:Acute CHIKV infection cases (n = 134) confirmed by serology or molecular test were examined <10 days of disease onset and followed for one year to evaluate for disease progression. Potential risk factors for chronic arthralgia were evaluated by multivariate analysis to develop a prognostic scoring system, which was subsequently tested in an independent validation cohort consisting of 42 individuals. RESULTS:A total of 107 out of 134 (80%) acute CHIKV-confirmed cases from the derivation cohort were re-examined one year after enrollment. Chronic arthralgia post-CHIKV infection was diagnosed in 64 (60%). Five of the 12 parameters evaluated in the acute phase were statistically associated with persistent arthralgia and were further tested by Bayesian analysis. These variables were weighted to yield a prognosis score denominated SHERA (Sex, Hypertension, Edema, Retroocular pain, Age), which exhibited 81.3% accuracy in predicting long-term arthralgia post-CHIKV infection in the derivation cohort, and 76.5% accuracy in the validation cohort. CONCLUSIONS:The simplified and externally validated prognostic scoring system, SHERA, is a useful method to screen acutely CHIKV-infected patients at elevated risk of chronic arthralgia who will benefit from specific interventions. This tool could guide public health policies, particularly in resource-constrained settings.

SUBMITTER: de Moraes L

PROVIDER: S-EPMC7373495 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature

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A clinical scoring system to predict long-term arthralgia in Chikungunya disease: A cohort study.

de Moraes Laise L Cerqueira-Silva Thiago T Nobrega Victor V Akrami Kevan K Santos Luciane Amorim LA Orge Cibele C Casais Paula P Cambui Lais L Rampazzo Rita de Cássia Pontello RCP Trinta Karen Soares KS Montalbano Camila Amato CA Teixeira Maria Jania MJ Cavalcante Luciano Pamplona LP Andrade Bruno B BB Cunha Rivaldo Venâncio da RVD Krieger Marco Aurélio MA Barral-Netto Manoel M Barral Aldina A Khouri Ricardo R Boaventura Viviane Sampaio VS

PLoS neglected tropical diseases 20200721 7

<h4>Background</h4>Chikungunya virus (CHIKV) has caused worldwide epidemics that impose a major burden on health systems. Approximately half of infected individuals develop chronic debilitating arthralgia, affecting their quality of life. Here, we identified the relevant clinical and demographic variables in the acute phase of CHIKV infection prospectively linked to chronic arthralgia to elaborate a prognostic scoring system.<h4>Methods</h4>Acute CHIKV infection cases (n = 134) confirmed by sero ...[more]

PMID: 32693402

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Project description:To develop a simple scoring system based on baseline inflammatory and nutritional markers to predict the long-term prognosis of patients with nasopharyngeal carcinoma (NPC). Conducted a retrospective analysis of clinical data from 1024 newly diagnosed non-metastatic NPC patients. A total of 15 pre-treatment inflammatory and nutritional markers were collected as candidate variables. Receiver operating characteristic (ROC) curves were used to determine the optimal cutoff points for each parameter. Survival analysis was performed using Kaplan-Meier method and Cox regression analysis. Besides, the Inflammation Nutrition Risk Score (INRS) was calculated for each patient by assigning each independent prognostic factor a score of 1. Multivariate Cox regression analysis showed that serum albumin (ALB), systemic immune-inflammation index, and monocyte count (M) were independent prognostic factors for OS (P < 0.05). Survival analysis showed that higher INRS was associated with a worsened prognosis. Patients in the high-risk group had shorter OS than in the low-risk group. In the training group, the 3-, 5-, and 8-years OS rates for the low-risk group versus high-risk group were 92.5% versus 87.8%, 87.4% versus 75.1%, and 84.6% versus 62.2%, respectively (P < 0.05). In the validation group, the 3-, 5-, and 8-years OS rates for the low-risk group vs. high-risk group were 95.0% versus 86.4%, 92.1% versus 82.2%, and 89.5% versus 74.3%, respectively (P < 0.05). Further subgroup analysis showed a significant difference in the OS between the high-risk group and low-risk group in patients with locally advanced disease (P < 0.05). The ROC curve demonstrated that INRS had a similar predictive value for long-term survival in NPC patients compared to TNM staging and serum EBV-DNA levels. Pretreatment ALB, M, and SIRI are independent prognostic factors for long-term survival in patients with NPC. INRS constructed based on these three factors can serve as a long-term prognostic indicator for NPC.

Project description:BackgroundEfferocytosis suppresses antitumour immune responses by inducing the release and secretion of cytokines. Long non-coding ribonucleic acids (lncRNAs) have various functions in different forms of programmed cell death and in immune regulation. This study aims to explore the potential role of efferocytosis-related lncRNAs as biomarkers in pancreatic adenocarcinoma (PAAD).MethodsTranscriptome profiles, simple nucleotide variations and clinical data of patients with PAAD were extracted from The Cancer Genome Atlas (TCGA) database. Co-expression algorithms identified efferocytosis-related lncRNAs. The efferocytosis-related lncRNA scoring system (ERLncSys) was established using Cox regression and the Least Absolute Shrinkage and Selection Operator algorithm. Additionally, Kaplan-Meier (K-M) curves, Cox regression, receiver operating characteristic (ROC) curves and clinical parameter stratification analyses were used to evaluate ERlncSys. Moreover, ERlncSys was explored through Gene Set Variation Analysis, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses. Furthermore, the TIMER platform, ESTIMATE algorithm, single sample Gene Set Enrichment Analysis and immune checkpoint analysis were utilised to explore the predictive power of ERlncSys for the tumour immune microenvironment (TIME). Finally, a consensus clustering algorithm identified distinct molecular profiles among patients with PAAD, aiding in the identification of potential beneficiaries for immunotherapy.ResultsK-M, Cox regression and ROC analyses confirmed the robust prognostic efficacy of ERlncSys. Clinical stratification analysis indicated the broad applicability of ERlncSys in PAAD. Additionally, mmunological analyses indicated that ERlncSys can determine immune cell infiltration status in the TIME. Furthermore, consensus clustering analysis based on ERlncSys divided the TCGA-PAAD cohort into two clusters. Cluster 1 exhibited characteristics consistent with an immune 'hot tumour' compared to cluster 2, suggesting cluster 1 is a more suitable population for immune checkpoint inhibitor therapy.ConclusionThe established ErlncSys aids in predicting the prognosis and understanding the TIME landscape of patients with PAAD. In turn, it facilitates the identification of optimal candidates for immunotherapy. This study introduces novel insights into the potential value of efferocytosis-related lncRNAs as biomarkers in PAAD.

Dataset Information

A clinical scoring system to predict long-term arthralgia in Chikungunya disease: A cohort study.

Publications

A clinical scoring system to predict long-term arthralgia in Chikungunya disease: A cohort study.

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