204 research outputs found
The Welfare Effects of Pfiesteria-Related Fish Kills in Seafood Markets: A Contingent Behavior Analysis
We use contingent behavior analysis to study the effects of Pfiesteria related fish kills on the demand for seafood in the Mid-Atlantic region. We use a phone-mail-phone survey to look at the effects of various information provision mechanisms used to ameliorate the effects of misinformation regarding fish kills. A set of demand difference models are estimated based on individual responses to multiple questions about seafood consumption with and without fish kills present and with various health risk information treatments. Random effects Tobit models are used to control for the panel nature of responses and natural censoring of the stated responses. We find that 1) Pfiesteria related fish kills have a significant negative effect on the demand for seafood, 2) seafood consumers are nonresponsive to expert risk information designed to reassure consumers that seafood is safe in the presence of a fish kill, and 3) a mandatory seafood inspection program completely eliminates avoidance costs incurred due to misinformation. We estimate that the aggregate avoidance costs incurred in the month immediately following a Pfiesteria related fish kill is 130 million.
Detection of distinct glycosylation patterns on human γ-glutamyl transpeptidase 1 using antibody-lectin sandwich array (ALSA) technology
Basic mechanisms of urgency: roles and benefits of pharmacotherapy
Introduction
Since urgency is key to the overactive bladder syndrome, we have reviewed the mechanisms underlying how bladder filling and urgency are sensed, what causes urgency and how this relates to medical therapy.
Materials and methods
Review of published literature.
Results
As urgency can only be assessed in cognitively intact humans, mechanistic studies of urgency often rely on proxy or surrogate parameters, such as detrusor overactivity, but these may not necessarily be reliable. There is an increasing evidence base to suggest that the sensation of ‘urgency’ differs from the normal physiological urge to void upon bladder filling. While the relative roles of alterations in afferent processes, central nervous processing, efferent mechanisms and in intrinsic bladder smooth muscle function remain unclear, and not necessarily mutually exclusive, several lines of evidence support an important role for the latter.
Conclusions
A better understanding of urgency and its causes may help to develop more effective treatments for voiding dysfunction
The path to a better biomarker: Application of a risk management framework for the implementation of PD-L1 and TILs as immuno-oncology biomarkers in breast cancer clinical trials and daily practice
Immune checkpoint inhibitor therapies targeting PD-1/PD-L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD-L1 expression on immune cells occupying 651% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab-paclitaxel. However, concerns regarding variability between immunohistochemical PD-L1 assay performance and inter-reader reproducibility have been raised. High tumor-infiltrating lymphocytes (TILs) have also been associated with response to PD-1/PD-L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin\u2013stained slides and have shown reliable inter-reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD-L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD-L1 and TIL analyses as a more comprehensive immuno-oncological biomarker for patient selection for PD-1/PD-L1 inhibition-based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk-management framework that may help mitigate the risks of suboptimal patient selection for immuno-therapeutic approaches in clinical trials and daily practice based on combined TILs/PD-L1 assessment in BC. \ua9 2020 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd
Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: a report of the international immuno-oncology biomarker working group
The clinical significance of the tumor-immune interaction in breast cancer is now established, and tumor-infiltrating lymphocytes (TILs) have emerged as predictive and prognostic biomarkers for patients with triple-negative (estrogen receptor, progesterone receptor, and HER2-negative) breast cancer and HER2-positive breast cancer. How computational assessments of TILs might complement manual TIL assessment in trial and daily practices is currently debated. Recent efforts to use machine learning (ML) to automatically evaluate TILs have shown promising results. We review state-of-the-art approaches and identify pitfalls and challenges of automated TIL evaluation by studying the root cause of ML discordances in comparison to manual TIL quantification. We categorize our findings into four main topics: (1) technical slide issues, (2) ML and image analysis aspects, (3) data challenges, and (4) validation issues. The main reason for discordant assessments is the inclusion of false-positive areas or cells identified by performance on certain tissue patterns or design choices in the computational implementation. To aid the adoption of ML for TIL assessment, we provide an in-depth discussion of ML and image analysis, including validation issues that need to be considered before reliable computational reporting of TILs can be incorporated into the trial and routine clinical management of patients with triple-negative breast cancer. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland
Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials
Stromal tumor-infiltrating lymphocytes (sTILs) are a potential predictive biomarker for immunotherapy response in metastatic triple-negative breast cancer (TNBC). To incorporate sTILs into clinical trials and diagnostics, reliable assessment is essential. In this review, we propose a new concept, namely the implementation of a risk-management framework that enables the use of sTILs as a stratification factor in clinical trials. We present the design of a biomarker risk-mitigation workflow that can be applied to any biomarker incorporation in clinical trials. We demonstrate the implementation of this concept using sTILs as an integral biomarker in a single-center phase II immunotherapy trial for metastatic TNBC (TONIC trial, NCT02499367), using this workflow to mitigate risks of suboptimal inclusion of sTILs in this specific trial. In this review, we demonstrate that a web-based scoring platform can mitigate potential risk factors when including sTILs in clinical trials, and we argue that this framework can be applied for any future biomarker-driven clinical trial setting
Application of a risk-management framework for integration of stromal tumor-infiltrating lymphocytes in clinical trials
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