| 1. |
- Baglioni, Chiara, et al.
(författare)
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The European Academy for Cognitive Behavioural Therapy for Insomnia : An initiative of the European Insomnia Network to promote implementation and dissemination of treatment
- 2020
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Ingår i: Journal of Sleep Research. - : Wiley. - 0962-1105 .- 1365-2869. ; 29:2
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Tidskriftsartikel (refereegranskat)abstract
- Insomnia, the most prevalent sleep disorder worldwide, confers marked risks for both physical and mental health. Furthermore, insomnia is associated with considerable direct and indirect healthcare costs. Recent guidelines in the US and Europe unequivocally conclude that cognitive behavioural therapy for insomnia (CBT-I) should be the first-line treatment for the disorder. Current treatment approaches are in stark contrast to these clear recommendations, not least across Europe, where, if any treatment at all is delivered, hypnotic medication still is the dominant therapeutic modality. To address this situation, a Task Force of the European Sleep Research Society and the European Insomnia Network met in May 2018. The Task Force proposed establishing a European CBT-I Academy that would enable a Europe-wide system of standardized CBT-I training and training centre accreditation. This article summarizes the deliberations of the Task Force concerning definition and ingredients of CBT-I, preconditions for health professionals to teach CBT-I, the way in which CBT-I should be taught, who should be taught CBT-I and to whom CBT-I should be administered. Furthermore, diverse aspects of CBT-I care and delivery were discussed and incorporated into a stepped-care model for insomnia.
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| 2. |
- Couch, Fergus J., et al.
(författare)
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Identification of four novel susceptibility loci for oestrogen receptor negative breast cancer
- 2016
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 7:11375, s. 1-13
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Tidskriftsartikel (refereegranskat)abstract
- Common variants in 94 loci have been associated with breast cancer including 15 loci with genome-wide significant associations (P<5 x 10(-8)) with oestrogen receptor (ER)-negative breast cancer and BRCA1-associated breast cancer risk. In this study, to identify new ER-negative susceptibility loci, we performed a meta-analysis of 11 genome-wide association studies (GWAS) consisting of 4,939 ER-negative cases and 14,352 controls, combined with 7,333 ER-negative cases and 42,468 controls and 15,252 BRCA1 mutation carriers genotyped on the iCOGS array. We identify four previously unidentified loci including two loci at 13q22 near KLF5, a 2p23.2 locus near WDR43 and a 2q33 locus near PPIL3 that display genome-wide significant associations with ER-negative breast cancer. In addition, 19 known breast cancer risk loci have genome-wide significant associations and 40 had moderate associations (P<0.05) with ER-negative disease. Using functional and eQTL studies we implicate TRMT61B and WDR43 at 2p23.2 and PPIL3 at 2q33 in ER-negative breast cancer aetiology. All ER-negative loci combined account for similar to 11% of familial relative risk for ER-negative disease and may contribute to improved ER-negative and BRCA1 breast cancer risk prediction.
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| 3. |
- Elfer, Katherine, et al.
(författare)
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Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms
- 2022
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Ingår i: Journal of Medical Imaging. - 2329-4302. ; 9:4, s. 1-14
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Validation of artificial intelligence (AI) algorithms in digital pathology with a reference standard is necessary before widespread clinical use, but few examples focus on creating a reference standard based on pathologist annotations. This work assesses the results of a pilot study that collects density estimates of stromal tumor-infiltrating lymphocytes (sTILs) in breast cancer biopsy specimens. This work will inform the creation of a validation dataset for the evaluation of AI algorithms fit for a regulatory purpose. Approach: Collaborators and crowdsourced pathologists contributed glass slides, digital images, and annotations. Here, "annotations" refer to any marks, segmentations, measurements, or labels a pathologist adds to a report, image, region of interest (ROI), or biological feature. Pathologists estimated sTILs density in 640 ROIs from hematoxylin and eosin stained slides of 64 patients via two modalities: an optical light microscope and two digital image viewing platforms. Results: The pilot study generated 7373 sTILs density estimates from 29 pathologists. Analysis of annotations found the variability of density estimates per ROI increases with the mean; the root mean square differences were 4.46, 14.25, and 26.25 as the mean density ranged from 0% to 10%, 11% to 40%, and 41% to 100%, respectively. The pilot study informs three areas of improvement for future work: technical workflows, annotation platforms, and agreement analysis methods. Upgrades to the workflows and platforms will improve operability and increase annotation speed and consistency. Conclusions: Exploratory data analysis demonstrates the need to develop new statistical approaches for agreement. The pilot study dataset and analysis methods are publicly available to allow community feedback. The development and results of the validation dataset will be publicly available to serve as an instructive tool that can be replicated by developers and researchers.
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| 4. |
- Elfer, Katherine, et al.
(författare)
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Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
- 2024
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Ingår i: Modern Pathology : an official journal of the United States and Canadian Academy of Pathology, Inc. - 1530-0285. ; 37:4
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Tidskriftsartikel (refereegranskat)abstract
- This work advances and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the CONSORT (Consolidated Standards of Reporting Trials) and SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) checklists and the proposed AI extensions to the STARD (Standards for Reporting Diagnostic Accuracy) and TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing datasets. Prior work by Wahab et al. proposed an annotation workflow and quality checklist for computational pathology annotations. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as CLEARR-AI: The Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence.
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| 5. |
- Garcia, Victor, et al.
(författare)
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Development of Training Materials for Pathologists to Provide Machine Learning Validation Data of Tumor-Infiltrating Lymphocytes in Breast Cancer
- 2022
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 14:10, s. 1-14
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Tidskriftsartikel (refereegranskat)abstract
- The High Throughput Truthing project aims to develop a dataset for validating artificial intelligence and machine learning models (AI/ML) fit for regulatory purposes. The context of this AI/ML validation dataset is the reporting of stromal tumor-infiltrating lymphocytes (sTILs) density evaluations in hematoxylin and eosin-stained invasive breast cancer biopsy specimens. After completing the pilot study, we found notable variability in the sTILs estimates as well as inconsistencies and gaps in the provided training to pathologists. Using the pilot study data and an expert panel, we created custom training materials to improve pathologist annotation quality for the pivotal study. We categorized regions of interest (ROIs) based on their mean sTILs density and selected ROIs with the highest and lowest sTILs variability. In a series of eight one-hour sessions, the expert panel reviewed each ROI and provided verbal density estimates and comments on features that confounded the sTILs evaluation. We aggregated and shaped the comments to identify pitfalls and instructions to improve our training materials. From these selected ROIs, we created a training set and proficiency test set to improve pathologist training with the goal to improve data collection for the pivotal study. We are not exploring AI/ML performance in this paper. Instead, we are creating materials that will train crowd-sourced pathologists to be the reference standard in a pivotal study to create an AI/ML model validation dataset. The issues discussed here are also important for clinicians to understand about the evaluation of sTILs in clinical practice and can provide insight to developers of AI/ML models.
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| 6. |
- Gonzalez-Ericsson, Paula, et al.
(författare)
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The path to a better biomarker: application of a risk management framework for the implementation of PD‐L1 and TILs as immuno‐oncology biomarkers into breast cancer clinical trials and daily practice
- 2020
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Ingår i: Journal of Pathology. - : Wiley. - 1096-9896 .- 0022-3417. ; 250:5, s. 667-684
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Forskningsöversikt (refereegranskat)abstract
- 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 ≥1% 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–stained 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.
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| 7. |
- Ly, Amy, et al.
(författare)
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Training pathologists to assess stromal tumour-infiltrating lymphocytes in breast cancer synergises efforts in clinical care and scientific research
- 2024
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Ingår i: Histopathology. - 0309-0167 .- 1365-2559. ; 84:6, s. 915-923
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Forskningsöversikt (refereegranskat)abstract
- A growing body of research supports stromal tumour-infiltrating lymphocyte (TIL) density in breast cancer to be a robust prognostic and predicive biomarker. The gold standard for stromal TIL density quantitation in breast cancer is pathologist visual assessment using haematoxylin and eosin-stained slides. Artificial intelligence/machine-learning algorithms are in development to automate the stromal TIL scoring process, and must be validated against a reference standard such as pathologist visual assessment. Visual TIL assessment may suffer from significant interobserver variability. To improve interobserver agreement, regulatory science experts at the US Food and Drug Administration partnered with academic pathologists internationally to create a freely available online continuing medical education (CME) course to train pathologists in assessing breast cancer stromal TILs using an interactive format with expert commentary. Here we describe and provide a user guide to this CME course, whose content was designed to improve pathologist accuracy in scoring breast cancer TILs. We also suggest subsequent steps to translate knowledge into clinical practice with proficiency testing.
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| 8. |
- Pavel, Marianne E, et al.
(författare)
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Everolimus plus octreotide long-acting repeatable for the treatment of advanced neuroendocrine tumours associated with carcinoid syndrome (RADIANT-2) : a randomised, placebo-controlled, phase 3 study
- 2011
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Ingår i: The Lancet. - 0140-6736 .- 1474-547X. ; 378:9808, s. 2005-2012
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Tidskriftsartikel (refereegranskat)abstract
- Background Everolimus, an oral inhibitor of the mammalian target of rapamycin (mTOR), has shown antitumour activity in patients with advanced pancreatic neuroendocrine tumours. We aimed to assess the combination of everolimus plus octreotide long-acting repeatable (LAR) in patients with low-grade or intermediate-grade neuroendocrine tumours (carcinoid). Methods We did a randomised, double-blind, placebo-controlled, phase 3 study comparing 10 mg per day oral everolimus with placebo, both in conjunction with 30 mg intramuscular octreotide LAR every 28 days. Randomisation was by interactive voice response systems. Participants were aged 18 years or older, with low-grade or intermediate-grade advanced (unresectable locally advanced or distant metastatic) neuroendocrine tumours, and disease progression established by radiological assessment within the past 12 months. Our primary endpoint was progression-free survival. Adjusted for two interim analyses, the prespecified boundary at final analysis was p <= 0.0246. This study is registered at ClinicalTrials.gov, number NCT00412061. Findings 429 individuals were randomly assigned to study groups; 357 participants discontinued study treatment and one was lost to follow-up. Median progression-free survival by central review was 16.4 (95% CI 13.7-21.2) months in the everolimus plus octreotide LAR group and 11.3 (8.4-14.6) months in the placebo plus octreotide LAR group (hazard ratio 0.77, 95% CI 0.59-1.00; one-sided log-rank test p=0.026). Drug-related adverse events (everolimus plus octreotide LAR vs placebo plus octreotide LAR) were mostly grade 1 or 2, and adverse events of all grades included stomatitis (62% vs 14%), rash (37% vs 12%), fatigue (31% vs 23%), and diarrhoea (27% vs 16%). Interpretation Everolimus plus octreotide LAR, compared with placebo plus octreotide LAR, improved progression-free survival in patients with advanced neuroendocrine tumours associated with carcinoid syndrome.
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