1,034 research outputs found
Breast cancer distant recurrence lead time interval by detection method in an institutional cohort.
BACKGROUND: Lead time, the interval between screen detection and when a disease would have become clinically evident, has been cited to explain longer survival times in mammography detected breast cancer cases (BC).
METHODS: An institutional retrospective cohort study of BC outcomes related to detection method (mammography (MamD) vs. patient (PtD)). Cases were first primary invasive stage I-III BC, age 40-74âyears (n =â6603), 1999-2016. Survival time was divided into 1) distant disease-free interval (DDFI) and 2) distant disease-specific survival (DDSS) as two separate time interval outcomes. We measured statistical association between detection method and diagnostic, treatment and outcome variables using bivariate comparisons, Cox proportional hazards analyses and mean comparisons. Outcomes were distant recurrence (n =â422), DDFI and DDSS.
RESULTS: 39% of cases were PtD (n =â2566) and 61% were MamD (n =â4037). MamD cases had a higher percentage of Stage I tumors [MamD 69% stage I vs. PtD 31%, p \u3câ.001]. Rate of distant recurrence was 11% among PtD BC cases (n =â289) vs. 3% of MamD (n =â133) (p \u3câ.001). Order of factor entry into the distant recurrence time interval (DDFI) model was 1) TNM stage (p \u3câ.001), 2) HR/HER2 status (p \u3câ.001), 3) histologic grade (p =â.005) and 4) detection method (p \u3câ.001). Unadjusted PtD DDFI mean time was 4.34âyears and MamD 5.52âyears (p \u3câ.001), however when stratified by stage, the most significant factor relative to distant recurrence, there was no significant difference between PtD and MamD BC. Distant disease specific survival time did not differ by detection method.
CONCLUSION: We observed breast cancer distant disease-free interval to be primarily associated with stage at diagnosis and tumor characteristics with less contribution of detection method to the full model. Patient and mammography detected breast cancer mean lead time to distant recurrence differed significantly by detection method for all stages but not significantly within stage with no difference in time from distant recurrence to death. Lead time difference related to detection method appears to be present but may be less influential than other factors in distant disease-free and disease specific survival
Timing interactions in social simulations: The voter model
The recent availability of huge high resolution datasets on human activities
has revealed the heavy-tailed nature of the interevent time distributions. In
social simulations of interacting agents the standard approach has been to use
Poisson processes to update the state of the agents, which gives rise to very
homogeneous activity patterns with a well defined characteristic interevent
time. As a paradigmatic opinion model we investigate the voter model and review
the standard update rules and propose two new update rules which are able to
account for heterogeneous activity patterns. For the new update rules each node
gets updated with a probability that depends on the time since the last event
of the node, where an event can be an update attempt (exogenous update) or a
change of state (endogenous update). We find that both update rules can give
rise to power law interevent time distributions, although the endogenous one
more robustly. Apart from that for the exogenous update rule and the standard
update rules the voter model does not reach consensus in the infinite size
limit, while for the endogenous update there exist a coarsening process that
drives the system toward consensus configurations.Comment: Book Chapter, 23 pages, 9 figures, 5 table
Circadian pattern and burstiness in mobile phone communication
The temporal communication patterns of human individuals are known to be
inhomogeneous or bursty, which is reflected as the heavy tail behavior in the
inter-event time distribution. As the cause of such bursty behavior two main
mechanisms have been suggested: a) Inhomogeneities due to the circadian and
weekly activity patterns and b) inhomogeneities rooted in human task execution
behavior. Here we investigate the roles of these mechanisms by developing and
then applying systematic de-seasoning methods to remove the circadian and
weekly patterns from the time-series of mobile phone communication events of
individuals. We find that the heavy tails in the inter-event time distributions
remain robustly with respect to this procedure, which clearly indicates that
the human task execution based mechanism is a possible cause for the remaining
burstiness in temporal mobile phone communication patterns.Comment: 17 pages, 12 figure
Classification of complications of epilepsy surgery and invasive diagnostic procedures: A proposed protocol and feasibility study
Objective: In epilepsy surgery, which aims to treat seizures and thereby to improve the lives of persons with drug-resistant epilepsy, the chances of attaining seizure relief must be carefully weighed against the risks of complications and expected adverse events. The interpretation of data regarding complications of epilepsy surgery and invasive diagnostic procedures is hampered by a lack of uniform definitions and method of data collection. Methods: Based on a review of previous definitions and classifications of complications, we developed a proposal for a new classification. This proposal was then subject to revisions after expert opinion within E-pilepsy, an EU-funded European pilot network of reference centers in refractory epilepsy and epilepsy surgery, later incorporated into the ERN (European Reference Network) EpiCARE. This version was discussed with recognized experts, and a final protocol was agreed to after further revision. The final protocol was evaluated in practical use over 1Â year in three of the participating centers. One hundred seventy-four consecutive procedures were included with 35 reported complications. Results: This report presents a multidimensional classification of complications in epilepsy surgery and invasive diagnostic procedures, where complications are characterized in terms of their immediate effects, resulting permanent symptoms, and consequences on activities of daily living. Significance: We propose that the protocol will be helpful in the work to promote safety in epilepsy surgery and for future studies designed to identify risk factors for complications. Further work is needed to address the reporting of outcomes as regards neuropsychological function, activities of daily living, and quality of life
Bursty egocentric network evolution in Skype
In this study we analyze the dynamics of the contact list evolution of
millions of users of the Skype communication network. We find that egocentric
networks evolve heterogeneously in time as events of edge additions and
deletions of individuals are grouped in long bursty clusters, which are
separated by long inactive periods. We classify users by their link creation
dynamics and show that bursty peaks of contact additions are likely to appear
shortly after user account creation. We also study possible relations between
bursty contact addition activity and other user-initiated actions like free and
paid service adoption events. We show that bursts of contact additions are
associated with increases in activity and adoption - an observation that can
inform the design of targeted marketing tactics.Comment: 7 pages, 6 figures. Social Network Analysis and Mining (2013
Early risk factors for adolescent antisocial behaviour: an Australian longitudinal study
Objective: This investigation utilizes data from an Australian longitudinal study to identify early risk factors for adolescent antisocial behaviour. Method: Analyses are based on data from the Mater University Study of Pregnancy, an on-going longitudinal investigation of womenâs and childrenâs health and development involving over 8000 participants. Five types of risk factors (child characteristics, perinatal factors, maternal/familial characteristics, maternal pre- and post-natal substance use and parenting practices) were included in analyses and were based on maternal reports, child assessments and medical records. Adolescent antisocial behaviour was measured when children were 14 years old, using the delinquency subscale of the Child Behaviour Checklist. Results: Based on a series of logistic regression models, significant risk factors for adolescent antisocial behaviour included childrenâs prior problem behaviour (i.e. aggression and attention/restlessness problems at age 5 years) and marital instability, which doubled or tripled the odds of antisocial behaviour. Perinatal factors, maternal substance use, and parenting practices were relatively poor predictors of antisocial behaviour. Conclusions: Few studies have assessed early predictors of antisocial behaviour in Australia and the current results can be used to inform prevention programs that target risk factors likely to lead to problem outcomes for Australian youth
Emotional persistence in online chatting communities
How do users behave in online chatrooms, where they instantaneously read and
write posts? We analyzed about 2.5 million posts covering various topics in
Internet relay channels, and found that user activity patterns follow known
power-law and stretched exponential distributions, indicating that online chat
activity is not different from other forms of communication. Analysing the
emotional expressions (positive, negative, neutral) of users, we revealed a
remarkable persistence both for individual users and channels. I.e. despite
their anonymity, users tend to follow social norms in repeated interactions in
online chats, which results in a specific emotional "tone" of the channels. We
provide an agent-based model of emotional interaction, which recovers
qualitatively both the activity patterns in chatrooms and the emotional
persistence of users and channels. While our assumptions about agent's
emotional expressions are rooted in psychology, the model allows to test
different hypothesis regarding their emotional impact in online communication.Comment: 34 pages, 4 main and 12 supplementary figure
Local variation of hashtag spike trains and popularity in Twitter
We draw a parallel between hashtag time series and neuron spike trains. In
each case, the process presents complex dynamic patterns including temporal
correlations, burstiness, and all other types of nonstationarity. We propose
the adoption of the so-called local variation in order to uncover salient
dynamics, while properly detrending for the time-dependent features of a
signal. The methodology is tested on both real and randomized hashtag spike
trains, and identifies that popular hashtags present regular and so less bursty
behavior, suggesting its potential use for predicting online popularity in
social media.Comment: 7 pages, 7 figure
Universal features of correlated bursty behaviour
Inhomogeneous temporal processes, like those appearing in human
communications, neuron spike trains, and seismic signals, consist of
high-activity bursty intervals alternating with long low-activity periods. In
recent studies such bursty behavior has been characterized by a fat-tailed
inter-event time distribution, while temporal correlations were measured by the
autocorrelation function. However, these characteristic functions are not
capable to fully characterize temporally correlated heterogenous behavior. Here
we show that the distribution of the number of events in a bursty period serves
as a good indicator of the dependencies, leading to the universal observation
of power-law distribution in a broad class of phenomena. We find that the
correlations in these quite different systems can be commonly interpreted by
memory effects and described by a simple phenomenological model, which displays
temporal behavior qualitatively similar to that in real systems
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