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Measurable residual disease (MRD) measured using multiparameter flowcytometry (MFC) has proven to be an important prognostic biomarker in acute myeloid leukemia (AML). In addition, MRD is increasingly used to guide consolidation treatment towards a non-allogenic stem cell transplantation treatment for MRD-negative patients in the ELN-2017 intermediate risk group. Currently, measurement of MFC-MRD in bone marrow is used for clinical decision making after 2 cycles of induction chemotherapy. However, measurement after 1 cycle has also been shown to have prognostic value, so the optimal time point remains a question of debate. We assessed the independent prognostic value of MRD results at either time point and concordance between these for 273 AML patients treated within and according to the HOVON-SAKK 92, 102, 103 and 132 trials. Cumulative incidence of relapse, event free survival and overall survival were significantly better for MRD-negative (<0.1%) patients compared to MRD-positive patients after cycle 1 and cycle 2 (p ≤ 0.002, for all comparisons). A total of 196 patients (71.8%) were MRD-negative after cycle 1, of which the vast majority remained negative after cycle 2 (180 patients; 91.8%). In contrast, of the 77 MRD-positive patients after cycle 1, only 41 patients (53.2%) remained positive. A cost reduction of –€571,751 per 100 patients could be achieved by initiating the donor search based on the MRD-result after cycle 1. This equals to a 50.7% cost reduction compared to the current care strategy in which the donor search is initiated for all patients. These results show that MRD after cycle 1 has prognostic value and is highly concordant with MRD status after cycle 2. When MRD-MFC is used to guide consolidation treatment (allo vs non-allo) in intermediate risk patients, allogeneic donor search may be postponed or omitted after cycle 1. Since the majority of MRD-negative patients remain negative after cycle 2, this could safely reduce the number of allogeneic donor searches and reduce costs. [ABSTRACT FROM AUTHOR]

Measurable residual disease (MRD) measured using multiparameter flow-cytometry (MFC) has proven to be an important prognostic biomarker in acute myeloid leukemia (AML). In addition, MRD is increasingly used to guide consolidation treatment towards a non-allogenic stem cell transplantation treatment for MRD-negative patients in the ELN-2017 intermediate risk group. Currently, measurement of MFC-MRD in bone marrow is used for clinical decision making after 2 cycles of induction chemotherapy. However, measurement after 1 cycle has also been shown to have prognostic value, so the optimal time point remains a question of debate. We assessed the independent prognostic value of MRD results at either time point and concordance between these for 273 AML patients treated within and according to the HOVON-SAKK 92, 102, 103 and 132 trials. Cumulative incidence of relapse, event free survival and overall survival were significantly better for MRD-negative (

PurposeTo evaluate mammography uptake and subsequent breast cancer diagnoses, as well as the prospect of additive cancer detection via a liquid biopsy multi-cancer early detection (MCED) screening test during a routine preventive care exam (PCE).MethodsPatients with incident breast cancer were identified from five years of longitudinal Blue Health Intelligence® (BHI®) claims data (2014-19) and their screening mammogram and PCE utilization were characterized. Ordinal logistic regression analyses were performed to identify the association of a biennial screening mammogram with stage at diagnosis. Additional screening opportunities for breast cancer during a PCE within two years before diagnosis were identified, and the method extrapolated to all cancers, including those without recommended screening modalities.ResultsClaims for biennial screening mammograms and the time from screening to diagnosis were found to be predictors of breast cancer stage at diagnosis. When compared to women who received a screening mammogram proximal to their breast cancer diagnosis (0-4 months), women who were adherent to guidelines but had a longer time window from their screening mammogram to diagnosis (4-24 months) had a 87% increased odds of a later-stage (stages III or IV) breast cancer diagnosis (p-value

Purpose: To evaluate mammography uptake and subsequent breast cancer diagnoses, as well as the prospect of additive cancer detection via a liquid biopsy multi-cancer early detection (MCED) screening test during a routine preventive care exam (PCE). Methods: Patients with incident breast cancer were identified from five years of longitudinal Blue Health Intelligence® (BHI®) claims data (2014-19) and their screening mammogram and PCE utilization were characterized. Ordinal logistic regression analyses were performed to identify the association of a biennial screening mammogram with stage at diagnosis. Additional screening opportunities for breast cancer during a PCE within two years before diagnosis were identified, and the method extrapolated to all cancers, including those without recommended screening modalities. Results: Claims for biennial screening mammograms and the time from screening to diagnosis were found to be predictors of breast cancer stage at diagnosis. When compared to women who received a screening mammogram proximal to their breast cancer diagnosis (0-4 months), women who were adherent to guidelines but had a longer time window from their screening mammogram to diagnosis (4-24 months) had a 87% increased odds of a later-stage (stages III or IV) breast cancer diagnosis (p-value <0.001), while women with no biennial screening mammogram had a 155% increased odds of a later-stage breast cancer diagnosis (p-value <0.001). This highlights the importance of screening in the earlier detection of breast cancer. Of incident breast cancer cases, 23% had no evidence of a screening mammogram in the two years before diagnosis. However, 49% of these women had a PCE within that time. Thus, an additional 11% of breast cancer cases could have been screened if a MCED test had been available during a PCE. Additionally, MCED tests have the potential to target up to 58% of the top 5 cancers that are the leading causes of cancer death currently without a USPSTF recommended screening modality (prostate, pancreatic, liver, lymphoma, and ovarian cancer). Conclusion: The study used claims data to demonstrate the association of cancer screening with cancer stage at diagnosis and demonstrates the unmet potential for a MCED screening test which could be ordered during a PCE. [ABSTRACT FROM AUTHOR]

Infectious disease outbreaks can have significant impact on individual health, national economies, and social well-being. Through early detection of an infectious disease, the outbreak can be contained at the local level, thereby reducing adverse effects on populations. Significant time and funding have been invested to improve disease detection timeliness. However, current evaluation methods do not provide evidence-based suggestions or measurements on how to detect outbreaks earlier. Key conditions for earlier detection and their influencing factors remain unclear and unmeasured. Without clarity about conditions and influencing factors, attempts to improve disease detection remain ad hoc and unsystematic.Methods: We developed a generic five-step disease detection model and a novel methodology to use for data collection, analysis, and interpretation. Data was collected in two workshops in Southeast Europe (n = 33 participants) and Southern and East Africa (n = 19 participants), representing mid- and low-income countries. Through systematic, qualitative, and quantitative data analyses, we identified key conditions for earlier detection and prioritized factors that influence them. As participants joined a workshop format and not an experimental setting, no ethics approval was required.Findings: Our analyses suggest that governance is the most important condition for earlier detection in both regions. Facilitating factors for earlier detection are risk communication activities such as information sharing, communication, and collaboration activities. Impeding factors are lack of communication, coordination, and leadership.Interpretation: Governance and risk communication are key influencers for earlier detection in both regions. However, inadequate technical capacity, commonly assumed to be a leading factor impeding early outbreak detection, was not found a leading factor. This insight may be used to pinpoint further improvement strategies.

Background: Diagnostic delays impact the quality of life and survival of patients with brain tumors. Earlier and expeditious diagnoses in these patients are crucial to reduce the morbidities and mortalities associated with brain tumors. A simple, rapid blood test that can be administered easily in a primary care setting to efficiently identify symptomatic patients who are most likely to have a brain tumor would enable quicker referral to brain imaging for those who need it most., Methods: Blood serum samples from 603 patients were prospectively collected and analyzed. Patients either had non-specific symptoms that could be indicative of a brain tumor on presentation to the Emergency Department, or a new brain tumor diagnosis and referral to the neurosurgical unit, NHS Lothian, Scotland. Patient blood serum samples were analyzed using the Dxcover® Brain Cancer liquid biopsy. This technology utilizes infrared spectroscopy combined with a diagnostic algorithm to predict the presence of intracranial disease., Results: Our liquid biopsy approach reported an area under the receiver operating characteristic curve of 0.8. The sensitivity-tuned model achieves a 96% sensitivity with 45% specificity (NPV 99.3%) and identified 100% of glioblastoma multiforme patients. When tuned for a higher specificity, the model yields a sensitivity of 47% with 90% specificity (PPV 28.4%)., Conclusions: This simple, non-invasive blood test facilitates the triage and radiographic diagnosis of brain tumor patients while providing reassurance to healthy patients. Minimizing time to diagnosis would facilitate the identification of brain tumor patients at an earlier stage, enabling more effective, less morbid surgical and adjuvant care., (© The Author(s) 2022. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology.)

The development of methodologies that allow to evaluate great volumes of plants and to detect in an early and fast way the searched characters facilitates greatly the works of selection in the Breeding Programs of banana and plantains. Five mutants of plantain hybrid 'FHIA-21' (Musa AAAB), treated with physical mutagenic agents (Gamma radiations, 60Co source), those that had been selected previously in the field by their low height were used for the studies. 'Grande naine' (Musa AAA) susceptible, 'FHIA-20' (Musa AAAB) as resistant and 'FHIA- 21' without irradiation were used as controls . They were multiplied in vitro and acclimatized for (60 days). The plants were inoculated with mycelia suspensions of Mycosphaerella fijiensis at a concentration of 1× 105. ml-1 by means of a brush by abaxial leaf surface of the four first open leaves. Affectation degrees caused by the pathogen were evaluated after 15, 30, 45 and 60 days plants had been inoculation. The first sympthoms appeared in the cultivar 'Grande naine' to the 45 days plants had been inoculated . Mutant 'IBP 14-23' stood out with the lowest values of affectation to the damages caused by Mycosphaerella fijiensis, when compared to the rest of mutants studied, corroborating its behavior in field. [ABSTRACT FROM AUTHOR]

Infectious disease outbreaks can have significant impact on individual health, national economies, and social well-being. Through early detection of an infectious disease, the outbreak can be contained at the local level, thereby reducing adverse effects on populations. Significant time and funding have been invested to improve disease detection timeliness. However, current evaluation methods do not provide evidence-based suggestions or measurements on how to detect outbreaks earlier. Key conditions for earlier detection and their influencing factors remain unclear and unmeasured. Without clarity about conditions and influencing factors, attempts to improve disease detection remain ad hoc and unsystematic. Methods: We developed a generic five-step disease detection model and a novel methodology to use for data collection, analysis, and interpretation. Data was collected in two workshops in Southeast Europe ( n = 33 participants) and Southern and East Africa ( n = 19 participants), representing mid- and low-income countries. Through systematic, qualitative, and quantitative data analyses, we identified key conditions for earlier detection and prioritized factors that influence them. As participants joined a workshop format and not an experimental setting, no ethics approval was required. Findings: Our analyses suggest that governance is the most important condition for earlier detection in both regions. Facilitating factors for earlier detection are risk communication activities such as information sharing, communication, and collaboration activities. Impeding factors are lack of communication, coordination, and leadership. Interpretation: Governance and risk communication are key influencers for earlier detection in both regions. However, inadequate technical capacity, commonly assumed to be a leading factor impeding early outbreak detection, was not found a leading factor. This insight may be used to pinpoint further improvement strategies., (Copyright © 2020 Steele, Orefuwa, Bino, Singer, Lutwama and Dickmann.)

Background: To improve the early diagnosis of hepatocellular carcinoma (HCC), more effective diagnostic biomarkers are needed. A combination of biomarkers is reported to distinguish individuals with early-stage HCC from at-risk individuals., Methods: Participants in this study were recruited from six hospitals in China. Literature review was used to choose 19 candidate proteins, a case-control study in the discovery stage was used to identify five proteins (P5) that constituted a diagnostic model. In the training and validation stages, the effectiveness of P5 for detecting early-stage HCC was tested (cross-sectional study). Finally, a nested case-control study independent of the other stages was set up to evaluate the P5 in the preclinical diagnosis of HCC., Findings: Between February 2013 and June 2017, a total of 1396 participants were recruited. A panel of 5 proteins (P5: OPN, GDF15, NSE, TRAP5 and OPG) showed high diagnostic accuracy when differentiating the early-stage HCC from the at-risk group, with AUCs of 0·892, 0·907 and 0·852 for the training stage, validation cohort 1 and cohort 2 data sets, respectively. In the prediction set, the sensitivity of P5 for diagnosing preclinical HCC increased with time, starting from 12 months before to the time of definitive clinical diagnosis (range, 46·15% to 86·67%)., Interpretation: The P5 panel has the potential to screen populations at high risk of developing HCC and can enable the early diagnosis of HCC., Funding: Research supported by grants from eight funds. All sources of funding were declared at the end of the text., Competing Interests: Declaration of competing interest The authors declare no conflicts of interest., (Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.)

Since the G8 dementia summit in 2013, a number of initiatives have been established with the aim of facilitating the discovery of a disease-modifying treatment for dementia by 2025. This report is a summary of the findings and recommendations of a meeting titled "Tackling gaps in developing life-changing treatments for dementia", hosted by Alzheimer's Research UK in May 2018. The aim of the meeting was to identify, review, and highlight the areas in dementia research that are not currently being addressed by existing initiatives. It reflects the views of leading experts in the field of neurodegeneration research challenged with developing a strategic action plan to address these gaps and make recommendations on how to achieve the G8 dementia summit goals. The plan calls for significant advances in (1) translating newly identified genetic risk factors into a better understanding of the impacted biological processes; (2) enhanced understanding of selective neuronal resilience to inform novel drug targets; (3) facilitating robust and reproducible drug-target validation; (4) appropriate and evidence-based selection of appropriate subjects for proof-of-concept clinical trials; (5) improving approaches to assess drug-target engagement in humans; and (6) innovative approaches in conducting clinical trials if we are able to detect disease 10-15 years earlier than we currently do today.