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Journal of the National Cancer... Jul 2022The goals of the "Future of Cancer Health Economics Research" virtual conference were to identify challenges, gaps, and unmet needs for conducting cancer health...
The goals of the "Future of Cancer Health Economics Research" virtual conference were to identify challenges, gaps, and unmet needs for conducting cancer health economics research; and develop suggestions and ideas to address these challenges and to support the development of this field. The conference involved multiple presentations and panels featuring several key themes, including data limitations and fragmentation; improving research methods; role and impacts of structural and policy factors; and the transdisciplinary nature of this field. The conference also highlighted emerging areas such as communicating results with nonresearchers; balancing data accessibility and data security; emphasizing the needs of trainees; and including health equity as a focus in cancer health economics research. From this conference, it is clear that cancer health economics research can have substantial impacts on how cancer care is delivered and how related health-care policies are developed and implemented. To support further growth and development, this field should continue to welcome individuals from multiple disciplines and enhance opportunities for training in economics and in analytic methods and perspectives from across the social and clinical sciences. Researchers should continue to engage with diverse stakeholders throughout the cancer community, building collaborations and focusing on the goal of improving health and well-being.
Topics: Economics, Medical; Health Policy; Humans; Neoplasms
PubMed: 35788382
DOI: 10.1093/jncimonographs/lgac005 -
Frontiers in Public Health 2022Workplace accidents can cause a catastrophic loss to the company including human injuries and fatalities. Occupational injury reports may provide a detailed description...
Workplace accidents can cause a catastrophic loss to the company including human injuries and fatalities. Occupational injury reports may provide a detailed description of how the incidents occurred. Thus, the narrative is a useful information to extract, classify and analyze occupational injury. This study provides a systematic review of text mining and Natural Language Processing (NLP) applications to extract text narratives from occupational injury reports. A systematic search was conducted through multiple databases including Scopus, PubMed, and Science Direct. Only original studies that examined the application of machine and deep learning-based Natural Language Processing models for occupational injury analysis were incorporated in this study. A total of 27, out of 210 articles were reviewed in this study by adopting the Preferred Reporting Items for Systematic Review (PRISMA). This review highlighted that various machine and deep learning-based NLP models such as K-means, Naïve Bayes, Support Vector Machine, Decision Tree, and K-Nearest Neighbors were applied to predict occupational injury. On top of these models, deep neural networks are also included in classifying the type of accidents and identifying the causal factors. However, there is a paucity in using the deep learning models in extracting the occupational injury reports. This is due to these techniques are pretty much very recent and making inroads into decision-making in occupational safety and health as a whole. Despite that, this paper believed that there is a huge and promising potential to explore the application of NLP and text-based analytics in this occupational injury research field. Therefore, the improvement of data balancing techniques and the development of an automated decision-making support system for occupational injury by applying the deep learning-based NLP models are the recommendations given for future research.
Topics: Bayes Theorem; Data Mining; Humans; Machine Learning; Natural Language Processing; Occupational Injuries
PubMed: 36187621
DOI: 10.3389/fpubh.2022.984099 -
The Journal of Physical Chemistry. B Aug 2019The coassembly of different building blocks into supramolecular copolymers provides a promising avenue to control their properties and to thereby expand the potential of...
The coassembly of different building blocks into supramolecular copolymers provides a promising avenue to control their properties and to thereby expand the potential of supramolecular polymers in applications. However, contrary to covalent copolymerization which nowadays can be well controlled, the control over sequence, polymer length, and morphology in supramolecular copolymers is to date less developed, and their structures are more determined by the delicate balance in binding free energies between the distinct building blocks than by kinetics. Consequently, to rationalize the structures of supramolecular copolymers, a thorough understanding of their thermodynamic behavior is needed. Though this is well established for single-component assemblies and over the past years several models have been proposed for specific copolymerization cases, a generally applicable model for supramolecular cooperative copolymers is still lacking. Here, we provide a generalization of our earlier mass-balance models for supramolecular copolymerizations that encompasses all our earlier models. In this model, the binding free energies of each pair of monomer types in each aggregate type can be set independently. We provide scripts to solve the model numerically for any (co)polymerization of one or two types of monomer into an arbitrary number of distinct aggregate types. We illustrate the applicability of the model on data from literature as well as on new experimental data of triarylamine triamide-based copolymers in three distinct solvents. We show that apart from common properties such as the degree of polymerization and length distributions, our approach also allows us to investigate properties such as the copolymer microstructure, that is, the internal ordering of monomers within the copolymers. Moreover, we show that in some cases, also intriguing analytical approximations can be derived from the mass balances.
PubMed: 31287320
DOI: 10.1021/acs.jpcb.9b04373 -
Digestive Diseases and Sciences Mar 2015There is a wide choice of fecal occult blood tests (FOBTs) for colorectal cancer screening. (Review)
Review
UNLABELLED
There is a wide choice of fecal occult blood tests (FOBTs) for colorectal cancer screening.
GOAL
To highlight the issues applicable when choosing a FOBT, in particular which FOBT is best suited to the range of screening scenarios. Four scenarios characterize the constraints and expectations of screening programs: (1) limited colonoscopy resource with a need to constrain test positivity rate; (2) a priority for maximum colorectal neoplasia detection with little need to constrain colonoscopy workload; (3) an "adequate" endoscopy resource that allows balancing the benefits of detection with the burden of service provision; and (4) a need to maximize participation in screening. Guaiac-based FOBTs (gFOBTs) have significant deficiencies, and fecal immunochemical tests (FITs) for hemoglobin have emerged as better tests. gFOBTs are not sensitive to small bleeds, specificity can be affected by diet or drugs, participant acceptance can be low, laboratory quality control opportunities are limited, and they have a fixed hemoglobin concentration cutoff determining positivity. FITs are analytically more specific, capable of quantitation and hence provide flexibility to adjust cutoff concentration for positivity and the balance between sensitivity and specificity. FITs are clinically more sensitive for cancers and advanced adenomas, and because they are easier to use, acceptance rates are high.
CONCLUSIONS
FOBT must be chosen carefully to meet the needs of the applicable screening scenario. Quantitative FIT can be adjusted to suit Scenarios 1, 2 and 3, and for each, they are the test of choice. FITs are superior to gFOBT for Scenario 4 and gFOBT is only suitable for Scenario 1.
Topics: Colorectal Neoplasms; Feces; Hemoglobins; Humans; Immunologic Tests; Mass Screening; Occult Blood
PubMed: 25492500
DOI: 10.1007/s10620-014-3445-3 -
BMC Medical Research Methodology Aug 2021Randomization is the foundation of any clinical trial involving treatment comparison. It helps mitigate selection bias, promotes similarity of treatment groups with... (Randomized Controlled Trial)
Randomized Controlled Trial
BACKGROUND
Randomization is the foundation of any clinical trial involving treatment comparison. It helps mitigate selection bias, promotes similarity of treatment groups with respect to important known and unknown confounders, and contributes to the validity of statistical tests. Various restricted randomization procedures with different probabilistic structures and different statistical properties are available. The goal of this paper is to present a systematic roadmap for the choice and application of a restricted randomization procedure in a clinical trial.
METHODS
We survey available restricted randomization procedures for sequential allocation of subjects in a randomized, comparative, parallel group clinical trial with equal (1:1) allocation. We explore statistical properties of these procedures, including balance/randomness tradeoff, type I error rate and power. We perform head-to-head comparisons of different procedures through simulation under various experimental scenarios, including cases when common model assumptions are violated. We also provide some real-life clinical trial examples to illustrate the thinking process for selecting a randomization procedure for implementation in practice.
RESULTS
Restricted randomization procedures targeting 1:1 allocation vary in the degree of balance/randomness they induce, and more importantly, they vary in terms of validity and efficiency of statistical inference when common model assumptions are violated (e.g. when outcomes are affected by a linear time trend; measurement error distribution is misspecified; or selection bias is introduced in the experiment). Some procedures are more robust than others. Covariate-adjusted analysis may be essential to ensure validity of the results. Special considerations are required when selecting a randomization procedure for a clinical trial with very small sample size.
CONCLUSIONS
The choice of randomization design, data analytic technique (parametric or nonparametric), and analysis strategy (randomization-based or population model-based) are all very important considerations. Randomization-based tests are robust and valid alternatives to likelihood-based tests and should be considered more frequently by clinical investigators.
Topics: Computer Simulation; Humans; Likelihood Functions; Random Allocation; Sample Size; Selection Bias
PubMed: 34399696
DOI: 10.1186/s12874-021-01303-z -
Entropy (Basel, Switzerland) Mar 2021Balance and locomotion are two main complex functions, which require intact and efficient neuromuscular and sensory systems, and their proper integration. In many...
BACKGROUND
Balance and locomotion are two main complex functions, which require intact and efficient neuromuscular and sensory systems, and their proper integration. In many studies the assumption of their dependence is present, and some rehabilitation approaches are based on it. Other papers undermine this assumption. Therefore the aim of this study was to examine the possible dependence between gait and balance in patients with neurological or sensory integration problems, which affected their balance.
METHODS
75 patients (52 with neurological diseases, 23 with sensory integration problems) participated in the study. They underwent balance assessment on Kistler force plate in two conditions, six tests on a Balance Biodex System and instrumented gait analysis with VICON. The gait and balances parameters and indices, together with entropy and cyclograms were used for the analysis. Spearman correlation, multiple regression, cluster analysis, and discriminant analysis were used as analytical tools.
RESULTS
The analysis divided patients into 2 groups with 100% correctly classified cases. Some balance and gait measures are better in the first group, but some others in the second.
CONCLUSIONS
This finding confirms the hypothesis that there is no direct link between gait and balance deficits.
PubMed: 33802894
DOI: 10.3390/e23030359 -
Current Opinion in Neurobiology Dec 2020New neurotechnologies fueled by the BRAIN Initiative now allow investigators to map, monitor and modulate complex neural circuits, enabling the pursuit of research... (Review)
Review
New neurotechnologies fueled by the BRAIN Initiative now allow investigators to map, monitor and modulate complex neural circuits, enabling the pursuit of research questions previously considered unapproachable. Yet it is the convergence of molecular neuroscience with the new systems neuroscience that promises the greatest future advances. This is particularly true for our understanding of nervous system disorders, some of which have known molecular drivers or pathology but result in unknown perturbations in circuit function. NIH-supported research on "BRAIN Circuits" programs integrate experimental, analytic, and theoretical capabilities for analysis of specific neural circuits and their contributions to perceptions, motivations, and actions. In this review, we describe the BRAIN priority areas, review our strategy for balancing early feasibility with mature projects, and the balance of individual with team science for this 'BRAIN Circuits' program. We also highlight the diverse portfolio of techniques, species, and neural systems represented in these projects.
Topics: Brain; Brain Mapping; Central Nervous System; Neurosciences
PubMed: 33279793
DOI: 10.1016/j.conb.2020.10.008 -
Nature Communications Jun 2022For most neuroimaging questions the range of possible analytic choices makes it unclear how to evaluate conclusions from any single analytic method. One possible way to...
For most neuroimaging questions the range of possible analytic choices makes it unclear how to evaluate conclusions from any single analytic method. One possible way to address this issue is to evaluate all possible analyses using a multiverse approach, however, this can be computationally challenging and sequential analyses on the same data can compromise predictive power. Here, we establish how active learning on a low-dimensional space capturing the inter-relationships between pipelines can efficiently approximate the full spectrum of analyses. This approach balances the benefits of a multiverse analysis without incurring the cost on computational and predictive power. We illustrate this approach with two functional MRI datasets (predicting brain age and autism diagnosis) demonstrating how a multiverse of analyses can be efficiently navigated and mapped out using active learning. Furthermore, our presented approach not only identifies the subset of analysis techniques that are best able to predict age or classify individuals with autism spectrum disorder and healthy controls, but it also allows the relationships between analyses to be quantified.
Topics: Autism Spectrum Disorder; Brain; Humans; Magnetic Resonance Imaging; Neuroimaging
PubMed: 35768409
DOI: 10.1038/s41467-022-31347-8 -
PLoS Computational Biology Feb 2021Epidemics may pose a significant dilemma for governments and individuals. The personal or public health consequences of inaction may be catastrophic; but the economic...
Epidemics may pose a significant dilemma for governments and individuals. The personal or public health consequences of inaction may be catastrophic; but the economic consequences of drastic response may likewise be catastrophic. In the face of these trade-offs, governments and individuals must therefore strike a balance between the economic and personal health costs of reducing social contacts and the public health costs of neglecting to do so. As risk of infection increases, potentially infectious contact between people is deliberately reduced either individually or by decree. This must be balanced against the social and economic costs of having fewer people in contact, and therefore active in the labor force or enrolled in school. Although the importance of adaptive social contact on epidemic outcomes has become increasingly recognized, the most important properties of coupled human-natural epidemic systems are still not well understood. We develop a theoretical model for adaptive, optimal control of the effective social contact rate using traditional epidemic modeling tools and a utility function with delayed information. This utility function trades off the population-wide contact rate with the expected cost and risk of increasing infections. Our analytical and computational analysis of this simple discrete-time deterministic strategic model reveals the existence of an endemic equilibrium, oscillatory dynamics around this equilibrium under some parametric conditions, and complex dynamic regimes that shift under small parameter perturbations. These results support the supposition that infectious disease dynamics under adaptive behavior change may have an indifference point, may produce oscillatory dynamics without other forcing, and constitute complex adaptive systems with associated dynamics. Implications for any epidemic in which adaptive behavior influences infectious disease dynamics include an expectation of fluctuations, for a considerable time, around a quasi-equilibrium that balances public health and economic priorities, that shows multiple peaks and surges in some scenarios, and that implies a high degree of uncertainty in mathematical projections.
Topics: COVID-19; Computer Simulation; Contact Tracing; Disease Susceptibility; Epidemics; Humans; Models, Biological; Oscillometry; Public Health; Risk; Social Behavior
PubMed: 33566839
DOI: 10.1371/journal.pcbi.1008639 -
Frontiers in Psychiatry 2022In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance...
BACKGROUND
In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC).
METHODS
For the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA.
RESULTS
Ten of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score.
CONCLUSION
ANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly.
PubMed: 35273528
DOI: 10.3389/fpsyt.2022.774251