User-centered design of the C3-cloud platform for elderly with multiple diseases - functional requirements and application testing

The number of patients with multimorbidity has been steadily increasing in the modern aging societies. The European C3-Cloud project provides a multidisciplinary and patient-centered “Collaborative Care and Cure-system” for the management of elderly with multimorbidity, enabling continuous coordination of care activities between multidisciplinary care teams (MDTs), patients and informal caregivers (ICG). In this study various components of the infrastructure were tested to fulfill the functional requirements and the entire system was subjected to an early application testing involving different groups of end-users. MDTs from participating European regions were involved in requirement elicitation and test formulation, resulting in 57 questions, distributed via an internet platform to 48 test participants (22 MDTs, 26 patients) from three pilot sites. The results indicate a high level of satisfaction with all components. Early testing also provided feedback for technical improvement of the entire system, and the paper points out useful evaluation methods

Outcome of hematopoietic stem cell transplantation is similar for patients with a partial in vitro T-cell-depleted graft compared with a non-T-cell-depleted graft when stratified by the refined disease risk index

Comparisons of hematopoietic stem cell transplantation (HSCT) methods in retrospective studies are often hampered by the heterogeneity of comparison groups. The refined disease risk index (DRI) is a potentially interesting tool to compare HSCT protocols as it is based on the disease type and burden at transplant and stratifies patients into four prognostic groups for overall survival (OS). We included 265 patients with partial T-cell-depleted graft (TDEP) and 163 non-TDEP patients in a retrospective study and compared outcomes following stratification using the refined DRI. The 2-year OS rate for TDEP patients was 81.6, 60.9 and 43.3% for the low-, intermediate- and high-risk groups, respectively (P<0.001). For non-TDEP patients, the 2-year OS rate was 62.9, 48.8, 44.2 and 7.6% for the low-, intermediate-, high- and very-high-risk groups, respectively (P<0.001). There was no significant difference when comparing OS between TDEP and non-TDEP for the low-, intermediate- and high-risk groups, but TDEP patients had less acute GvHD grades II-IV. In conclusion, we confirm that the refined DRI is a valuable tool to compare the outcomes of different HSCT protocols. We demonstrate also that TDEP did not impact on the outcome of HSCT, but it did reduce the incidence of acute GvHD.Bone Marrow Transplantation advance online publication, 7 March 2016; doi:10.1038/bmt.2016.34

Autoimmune hemolytic anemia and autoimmune thrombocytopenia at diagnosis and during follow-up of Hodgkin lymphoma

Autoimmune hemolytic anemia and thrombocytopenia (AIHA/AITP) frequently complicate the course of non-Hodgkin lymphomas, especially low-grade, but they are very rarely observed in Hodgkin lymphoma (HL). Consequently the frequency and the profile of patients with HL-associated AIHA/AITP have not been well defined. Among 1029 patients with HL diagnosed between 1990 and 2010, two cases of AIHA (0.19%) and three of AITP (0.29%) were identified at the presentation of disease. These patients were significantly older, and more frequently had features of advanced disease and non-nodular sclerosing histology, compared to the majority of patients, who did not have autoimmune cytopenias at diagnosis. ABVD combination chemotherapy (doxorubicin, bleomycin, vinblastine, dacarbazine) provided effective control of HL and the autoimmune condition as well. During approximately 6600 person-years of follow-up for the remaining 1024 patients, seven (0.7%) patients developed autoimmune cytopenias (three AITP, three AIHA, one autoimmune pancytopenia) for a 10- and 15-year actuarial incidence of 0.95% and 1.40%, respectively. Their features did not differ compared to the general population of adult HL. In this large series of consecutive, unselected patients, those who presented with autoimmune cytopenias had a particular demographic and disease-related profile. In contrast, patients developing autoimmune cytopenias during follow-up did not appear to differ significantly from those who did not. © 2012 Informa UK, Ltd

A framework for validating AI in precision medicine: considerations from the European ITFoC consortium

International audienceBackground: Artificial intelligence (AI) has the potential to transform our healthcare systems significantly. New AI technologies based on machine learning approaches should play a key role in clinical decision-making in the future. However, their implementation in health care settings remains limited, mostly due to a lack of robust validation procedures. There is a need to develop reliable assessment frameworks for the clinical validation of AI. We present here an approach for assessing AI for predicting treatment response in triple-negative breast cancer (TNBC), using real-world data and molecular-omics data from clinical data warehouses and biobanks. Methods: The European "ITFoC (Information Technology for the Future Of Cancer)" consortium designed a framework for the clinical validation of AI technologies for predicting treatment response in oncology. Results: This framework is based on seven key steps specifying: (1) the intended use of AI, (2) the target population, (3) the timing of AI evaluation, (4) the datasets used for evaluation, (5) the procedures used for ensuring data safety (including data quality, privacy and security), (6) the metrics used for measuring performance, and (7) the procedures used to ensure that the AI is explainable. This framework forms the basis of a validation platform that we are building for the "ITFoC Challenge". This community-wide competition will make it possible to assess and compare AI algorithms for predicting the response to TNBC treatments with external real-world datasets. Conclusions: The predictive performance and safety of AI technologies must be assessed in a robust, unbiased and transparent manner before their implementation in healthcare settings. We believe that the consideration of the ITFoC consortium will contribute to the safe transfer and implementation of AI in clinical settings, in the context of precision oncology and personalized care

An Integrated Care Platform System (C3-Cloud) for Care Planning, Decision Support, and Empowerment of Patients With Multimorbidity: Protocol for a Technology Trial

Background: There is an increasing need to organize the care around the patient and not the disease, while considering the complex realities of multiple physical and psychosocial conditions, and polypharmacy. Integrated patient-centered care delivery platforms have been developed for both patients and clinicians. These platforms could provide a promising way to achieve a collaborative environment that improves the provision of integrated care for patients via enhanced information and communication technology solutions for semiautomated clinical decision support. Objective: The Collaborative Care and Cure Cloud project (C3-Cloud) has developed 2 collaborative computer platforms for patients and members of the multidisciplinary team (MDT) and deployed these in 3 different European settings. The objective of this study is to pilot test the platforms and evaluate their impact on patients with 2 or more chronic conditions (diabetes mellitus type 2, heart failure, kidney failure, depression), their informal caregivers, health care professionals, and, to some extent, health care systems. Methods: This paper describes the protocol for conducting an evaluation of user experience, acceptability, and usefulness of the platforms. For this, 2 “testing and evaluation” phases have been defined, involving multiple qualitative methods (focus groups and surveys) and advanced impact modeling (predictive modeling and cost-benefit analysis). Patients and health care professionals were identified and recruited from 3 partnering regions in Spain, Sweden, and the United Kingdom via electronic health record screening. Results: The technology trial in this 4-year funded project (2016-2020) concluded in April 2020. The pilot technology trial for evaluation phases 3 and 4 was launched in November 2019 and carried out until April 2020. Data collection for these phases is completed with promising results on platform acceptance and socioeconomic impact. We believe that the phased, iterative approach taken is useful as it involves relevant stakeholders at crucial stages in the platform development and allows for a sound user acceptance assessment of the final product. Conclusions: Patients with multiple chronic conditions often experience shortcomings in the care they receive. It is hoped that personalized care plan platforms for patients and collaboration platforms for members of MDTs can help tackle the specific challenges of clinical guideline reconciliation for patients with multimorbidity and improve the management of polypharmacy. The initial evaluative phases have indicated promising results of platform usability. Results of phases 3 and 4 were methodologically useful, yet limited due to the COVID-19 pandemic