scholarly journals Current Status of Biomarkers in Anti-N-Methyl-D-Aspartate Receptor Encephalitis

2021 ◽  
Vol 22 (23) ◽  
pp. 13127
Author(s):  
Nicolás Lundahl Ciano-Petersen ◽  
Pablo Cabezudo-García ◽  
Sergio Muñiz-Castrillo ◽  
Jérôme Honnorat ◽  
Pedro Jesús Serrano-Castro ◽  
...  
Keyword(s):  
Treatment Response ◽  
Rare Diseases ◽  
Clinical Decision Making ◽  
Autoimmune Disorder ◽  
Clinical Score ◽  
Clinical Decision ◽  
Current Status ◽  
Clinical Activity ◽  
Aspartate Receptor ◽  
Nmdar Encephalitis

The discovery of biomarkers in rare diseases is of paramount importance to allow a better diagnosis, improve predictions of outcomes, and prompt the development of new treatments. Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a rare autoimmune disorder associated with the presence of antibodies targeting the GluN1 subunit of the NMDAR. Since it was discovered in 2007, large efforts have been made towards the identification of clinical, paraclinical, and molecular biomarkers to better understand the immune mechanisms that govern the course of the disease as well as to define predictors of treatment response and long-term outcomes. However, most of these biomarkers are still in an exploratory phase, with only a few candidates reaching the final phases of the always-complex process of biomarker development, mainly due to the low incidence of the disease and its recent description. Clinical and paraclinical markers are probably the most widely explored in anti-NMDAR encephalitis, five of them combined in a clinical score to predict 1 year outcome. On the contrary, soluble molecules, such as persistent antibody positivity, antibody titers, cytokines, and other inflammatory mediators, have been proposed as biomarkers of clinical activity, inflammation, prognosis, and treatment response, but further studies are required for their clinical validation including larger and more homogenous cohorts of patients. Similarly, genetic susceptibility biomarkers are still in the exploratory phase and, therefore, weak conclusions can for now only be achieved. Thus, further studies are warranted to define biomarkers and unravel the underlying mechanisms driving rare diseases such as anti-NMDAR encephalitis. Future international collaborative studies with prospective designs that enable the enrollment of large cohorts will allow for the identification and validation of novel biomarkers for clinical decision-making.

scholarly journals Emerging role of free triiodothyronine in patients with anti-N-methyl-D-aspartate receptor encephalitis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Tuo Ji ◽  
Zhi Huang ◽  
Yajun Lian ◽  
Chengze Wang ◽  
Qiaoman Zhang
Keyword(s):  
Clinical Decision Making ◽  
Clinical Decision ◽  
Nonparametric Tests ◽  
Clinical Prediction ◽  
Free Triiodothyronine ◽  
Icu Admission ◽  
Aspartate Receptor ◽  
Nmdar Encephalitis

AbstractWe aimed to investigate the role of free triiodothyronine (FT3) in patients with anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis. 137 consecutive inpatients (2016–2019) were registered prospectively and followed up for 12 months. 96 eligible patients were included in the study. The modified Rankin scale (mRS) score was collected, and the score of 3–6 was defined as a poor outcome. The patients were equally classified into 3 subgroups based on their FT3 levels obtained within 24 h of admission, and the subgroup differences were analyzed by parametric or nonparametric tests as appropriate. Logistic regression analysis was performed. We found that there was no difference in the mRS scores upon admission among 3 subgroups, however, patients in the low-FT3 subgroup tended to have higher disease severity during hospitalization and worse outcome in follow-up visits, represented by higher chances of intense care unit (ICU) admission (P < 0.001), longer hospital stay (P < 0.001), greater maximum mRS scores during hospitalization (P = 0.011), lower rates of getting clinical improvement within 4 weeks of starting treatment (P = 0.006), and higher percentages of poor 1-year outcome (P = 0.002). The level of FT3 was an independent factor correlated with ICU admission (P = 0.002) and might be a potential predictor for 1-year outcome. Our preliminary results suggest that the FT3 may be a risk factor involved in the evolution and progression of anti-NMDAR encephalitis, whereas the underline mechanisms remain to be explored. Attention should be paid to these patients with relatively low FT3 upon admission, which might possibly aid clinical prediction and guide clinical decision-making.

Persistent seropositivity in oophorectomy-resistant anti-NMDA receptor encephalitis

2021 ◽  
Vol 14 (9) ◽  
pp. e241878
Author(s):  
Susmit Tripathi ◽  
Nara M Michaelson ◽  
Alan Segal
Keyword(s):  
Clinical Decision Making ◽  
Serum Antibody ◽  
Disease Patient ◽  
Clinical Decision ◽  
High Serum ◽  
Nmda Receptor Encephalitis ◽  
Resistant Disease ◽  
Nmdar Encephalitis ◽  
Antibody Titres ◽  
Case Basis

To discuss (1) the significance of seropositivity in anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis and (2) clinical decision making in oophorectomy resistant disease. Patient A (a 35-year-old woman) had high CSF and serum anti-NMDA antibody titres, a complicated hospital course, little improvement with first and second-line therapies, and remained with high CSF and serum antibody titres despite unilateral oophorectomy, requiring a nearly 13-month long hospitalisation. Conversely, patient B (a 29-year-old woman) had low CSF titres, seronegative disease and quickly recovered to her baseline with first line therapies and oophorectomy. Anti-NMDAR antibodies are themselves pathological, causing signalling dysfunction and internalisation of the NMDAR. Seropositivity with anti-NMDAR antibodies likely reflects leakage from the blood–brain barrier, with high serum titres being a downstream effect of high CSF titres. Empiric bilateral oophorectomies is controversial but appropriate on a case-by-case basis in extremely treatment-resistant NMDAR encephalitis given the possibility of antigenic microteratomas, which may not be detected on imaging or even bilateral ovarian biopsies.

How to Decide Whether to Offer and Use “Nonstandard” Therapies in Patients with Advanced Sarcomas and Gastrointestinal Stromal Tumors: Global Variations in Clinical Practice, Assessment, and Access to Therapies in Diseases with Limited Incidence and Data

2012 ◽  
pp. 645-650 ◽  
Author(s):  
Stefan Sleijfer ◽  
Ian Judson ◽  
George D. Demetri
Keyword(s):  
Clinical Practice ◽  
Rare Diseases ◽  
Clinical Benefit ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Base ◽  
Stromal Tumors ◽  
Appropriate Care ◽  
Social Interests ◽  
Practice Assessment

Overview: As cancer is more generally recognized as a collection of various rare diseases rather than a homogeneous illness, sarcomas have become a model for the manner in which data can and cannot be used to drive clinical decision making. In this article, we explore the limitations of data generated in rare diseases such as sarcomas to provide an evidence base for clinical practice. How should patients be treated if there is no “standard” that offers “proof” of clinical benefit? By asking this question, we also raise the issue of what constitutes “clinical benefit”—and how to measure that—for patients with sarcomas and other rare diseases. As physicians become more accountable for decisions—and yet are always accountable to the patients and families who rely on them to provide the best and most appropriate care—oncologists must be cognizant of the limitations of data in rare diseases and be ready to justify actions that are in the best medical and social interests of patients.

scholarly journals Cognitive and Social Functioning Deficits after Anti-N-Methyl-D-Aspartate Receptor Encephalitis: An Exploratory Case Series

2016 ◽  
Vol 22 (8) ◽  
pp. 828-838 ◽  
Author(s):  
Gemma L. McKeon ◽  
James G. Scott ◽  
Donna M. Spooner ◽  
Alexander E. Ryan ◽  
Stefan Blum ◽  
...  
Keyword(s):  
Social Cognition ◽  
Social Functioning ◽  
Visual Memory ◽  
Case Series ◽  
Autoimmune Disorder ◽  
Neurocognitive Deficits ◽  
Normal Limits ◽  
Aspartate Receptor ◽  
Nmdar Encephalitis ◽  
Multi Stage

AbstractBackground: Anti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a recently described life-threatening autoimmune disorder associated with a characteristic multi-stage neuropsychiatric syndrome. Although it is known that the majority of patients experience neuropsychological disturbance post-treatment, some aspects of the cognitive profile remain unclear. Methods: This study sought to investigate patterns of cognitive functioning in a sample of anti-NMDAR encephalitis patients. Seven (6F:1M; mean age, 26.4 years; range, 16–37 years) treated patients completed a comprehensive set of neurocognitive and social functioning measures. Performance was analyzed using normative data (where available), and comparison with matched controls (10F:4M; mean age, 25.8 years; range, 16–38 years). Results: Individual cognitive profiles ranged from within normal limits to extensive dysfunction. Relative to controls, the patient group’s performance was affected in the domains of verbal/ visual memory, working memory, attention, processing speed, executive functioning, and social cognition. The patient group also reported significantly higher levels of anxiety compared to controls. Conclusions: These results add to the accumulating evidence that neurocognitive deficits, consistent with the distribution and functions of the NMDAR system can persist during recovery from anti-NMDAR encephalitis. This is the first study to provide evidence of performance decrements on measures of social cognition, including some involving theory of mind. (JINS, 2016, 22, 828–838)

scholarly journals Cognitive Computing-Based CDSS in Medical Practice

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Jun Chen ◽  
Chao Lu ◽  
Haifeng Huang ◽  
Dongwei Zhu ◽  
Qing Yang ◽  
...  
Keyword(s):  
Health Care ◽  
Medical Practice ◽  
General Framework ◽  
Clinical Decision Making ◽  
High Efficiency ◽  
Clinical Decision ◽  
Machine Intelligence ◽  
Medical Community ◽  
Current Status ◽  
Cognitive Computing

Importance. The last decade has witnessed the advances of cognitive computing technologies that learn at scale and reason with purpose in medicine studies. From the diagnosis of diseases till the generation of treatment plans, cognitive computing encompasses both data-driven and knowledge-driven machine intelligence to assist health care roles in clinical decision-making. This review provides a comprehensive perspective from both research and industrial efforts on cognitive computing-based CDSS over the last decade. Highlights. (1) A holistic review of both research papers and industrial practice about cognitive computing-based CDSS is conducted to identify the necessity and the characteristics as well as the general framework of constructing the system. (2) Several of the typical applications of cognitive computing-based CDSS as well as the existing systems in real medical practice are introduced in detail under the general framework. (3) The limitations of the current cognitive computing-based CDSS is discussed that sheds light on the future work in this direction. Conclusion. Different from medical content providers, cognitive computing-based CDSS provides probabilistic clinical decision support by automatically learning and inferencing from medical big data. The characteristics of managing multimodal data and computerizing medical knowledge distinguish cognitive computing-based CDSS from other categories. Given the current status of primary health care like high diagnostic error rate and shortage of medical resources, it is time to introduce cognitive computing-based CDSS to the medical community which is supposed to be more open-minded and embrace the convenience and low cost but high efficiency brought by cognitive computing-based CDSS.

scholarly journals Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer

2021 ◽  
Author(s):  
S Taavitsainen ◽  
N Engedal ◽  
S Cao ◽  
F Handle ◽  
S Prekovic ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Single Cell ◽  
Treatment Response ◽  
Rna Sequencing ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Early Treatment Response ◽  
Clinical Models ◽  
Cell Subpopulations ◽  
Accessible Chromatin

AbstractProstate cancer is profoundly heterogeneous and patients would benefit from methods that stratify clinically indolent from more aggressive forms of the disease. We employed single-cell assay for transposase-accessible chromatin (ATAC) and RNA sequencing in models of early treatment response and resistance to enzalutamide. In doing so, we identified pre-existing and treatment-persistent cell subpopulations that possess transcriptional stem-like features and regenerative potential when subjected to treatment. We found distinct chromatin landscapes associated with enzalutamide treatment and resistance that are linked to alternative transcriptional programs. Transcriptional profiles characteristic of persistent stem-like cells were able to stratify the treatment response of patients. Ultimately, we show that defining changes in chromatin and gene expression in single-cell populations from pre-clinical models can reveal hitherto unrecognized molecular predictors of treatment response. This suggests that high analytical resolution of pre-clinical models may powerfully inform clinical decision-making.

Are We Ready to Include Prognostic Factors in Inflammatory Bowel Disease Trials?

2019 ◽  
Vol 25 (1) ◽  
pp. 64-68 ◽  
Author(s):  
Christopher R. Lindholm ◽  
Corey A. Siegel
Keyword(s):  
Inflammatory Bowel Disease ◽  
Clinical Trials ◽  
Bowel Disease ◽  
Clinical Decision Making ◽  
Scoring Systems ◽  
Clinical Decision ◽  
Chronic Inflammatory Disease ◽  
Response To Therapy ◽  
Clinical Activity ◽  
Inflammatory Bowel

Inflammatory bowel disease (IBD) is a chronic inflammatory disease characterized by periodic episodes of flares and remission. Treatment is aimed at healing the bowel, to ultimately decrease hospitalization rates, need for surgeries and overall disability. In more recent years, treatment has transitioned from a reactive approach to a more proactive approach focusing on treating disease earlier and preventing complications. The challenge lies in identifying patients who need more intensive treatment early and trying to determine who will respond to which medications. Biomarkers and clinical activity scoring systems can be used to help guide treatment decisions. However, IBDs are very heterogeneous and the significance of these biomarkers can be difficult to discern on an individual basis. Recently, prognostic tools have been developed to aid in determining a patient’s prognosis as well as their likelihood to respond to different therapies. Despite this progress, clinical trials have not routinely adopted this approach in their study design. Tools for stratification of disease severity and to personalize treatment choices have the potential to improve our studies both by enriching the patient population and further guiding clinical decision making in practice. This review aims to discuss biomarkers, current prognosticating tools, tools that determine response to therapy and how incorporating these into clinical trials will be beneficial.

scholarly journals Molecular Markers for Bladder Cancer Screening, Early Diagnosis, and Surveillance: The WHO/ICUD Consensus

2014 ◽  
Vol 94 (1) ◽  
pp. 1-24 ◽  
Author(s):  
Bernd J. Schmitz-Dräger ◽  
Michael Droller ◽  
Vinata B. Lokeshwar ◽  
Yair Lotan ◽  
M''Liss A. Hudson ◽  
...  
Keyword(s):  
Decision Making ◽  
Bladder Cancer ◽  
Molecular Markers ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Urine Cytology ◽  
Added Value ◽  
Current Status ◽  
Low Grade ◽  
Screening And Surveillance

Due to the lack of disease-specific symptoms, diagnosis and follow-up of bladder cancer has remained a challenge to the urologic community. Cystoscopy, commonly accepted as a gold standard for the detection of bladder cancer, is invasive and relatively expensive, while urine cytology is of limited value specifically in low-grade disease. Over the last decades, numerous molecular assays for the diagnosis of urothelial cancer have been developed and investigated with regard to their clinical use. However, although all of these assays have been shown to have superior sensitivity as compared to urine cytology, none of them has been included in clinical guidelines. The key reason for this situation is that none of the assays has been included into clinical decision-making so far. We reviewed the current status and performance of modern molecular urine tests following systematic analysis of the value and limitations of commercially available assays. Despite considerable advances in recent years, the authors feel that at this stage the added value of molecular markers for the diagnosis of urothelial tumors has not yet been identified. Current data suggest that some of these markers may have the potential to play a role in screening and surveillance of bladder cancer. Well-designed protocols and prospective, controlled trials will be needed to provide the basis to determine whether integration of molecular markers into clinical decision-making will be of value in the future.

Commentary on Discussion Paper by Miles, A and Mezzich J.E. (2011). Person-centred medicine as an emergent model of clinical practice: The devil is in the details

2014 ◽  
Vol 2 (1) ◽  
pp. 67 ◽  
Author(s):  
Cathy Charles ◽  
Amiram Gafni
Keyword(s):  
Clinical Practice ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Integrated Model ◽  
Current Status ◽  
Evidence Based ◽  
Discussion Paper ◽  
Care Approach ◽  
Patient Values ◽  
Elementary Form

Miles and Mezzich have written a comprehensive review of the origins, development and current status of two influential international movements aimed at shaping the practice of medicine - evidence-based medicine (EBM) and patient-centred care. As the authors point out, these two movements have been largely independent of each other with little crossover of ideas as each pursues its own goals of trying to broaden its influence. Miles and Mezzich propose to take the strengths of both movements and to create a new integrated model of person-centred care (PCC) which is evidence-informed (rather than evidence-based) and incorporates a role for patient values in clinical decision-making. While laudable and logical to try to move forward with this approach which integrates two seemingly contradictory principles underlying each movement (clinical practice based on the findings of clinical research evidence and clinical practice that is responsive to patients’ values, preferences and beliefs), this task is not easy and, as the authors themselves note, the model that results from this process is still in elementary form. By proposing this new integrated model, the authors hope to stimulate further debate on the meaning of a person centred-care approach to medical practice.

scholarly journals Using patient self-reports to study heterogeneity of treatment effects in major depressive disorder

2016 ◽  
Vol 26 (1) ◽  
pp. 22-36 ◽  
Author(s):  
R. C. Kessler ◽  
H. M. van Loo ◽  
K. J. Wardenaar ◽  
R. M. Bossarte ◽  
L. A. Brenner ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Decision Support ◽  
Depressive Disorder ◽  
Treatment Outcomes ◽  
Treatment Response ◽  
Clinical Decision Support ◽  
Statistical Power ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Major Depressive

Backgrounds.Clinicians need guidance to address the heterogeneity of treatment responses of patients with major depressive disorder (MDD). While prediction schemes based on symptom clustering and biomarkers have so far not yielded results of sufficient strength to inform clinical decision-making, prediction schemes based on big data predictive analytic models might be more practically useful.Method.We review evidence suggesting that prediction equations based on symptoms and other easily-assessed clinical features found in previous research to predict MDD treatment outcomes might provide a foundation for developing predictive analytic clinical decision support models that could help clinicians select optimal (personalised) MDD treatments. These methods could also be useful in targeting patient subsamples for more expensive biomarker assessments.Results.Approximately two dozen baseline variables obtained from medical records or patient reports have been found repeatedly in MDD treatment trials to predict overall treatment outcomes (i.e., intervention v. control) or differential treatment outcomes (i.e., intervention A v. intervention B). Similar evidence has been found in observational studies of MDD persistence-severity. However, no treatment studies have yet attempted to develop treatment outcome equations using the full set of these predictors. Promising preliminary empirical results coupled with recent developments in statistical methodology suggest that models could be developed to provide useful clinical decision support in personalised treatment selection. These tools could also provide a strong foundation to increase statistical power in focused studies of biomarkers and MDD heterogeneity of treatment response in subsequent controlled trials.Conclusions.Coordinated efforts are needed to develop a protocol for systematically collecting information about established predictors of heterogeneity of MDD treatment response in large observational treatment studies, applying and refining these models in subsequent pragmatic trials, carrying out pooled secondary analyses to extract the maximum amount of information from these coordinated studies, and using this information to focus future discovery efforts in the segment of the patient population in which continued uncertainty about treatment response exists.

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