Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Individualized Dynamic Prediction of Survival under Time-Varying
  Treatment Strategies   Often in follow-up studies intermediate events occur in some patients, such
as reinterventions or adverse events. These intermediate events directly affect
the shapes of their longitudinal profiles. Our work is motivated by two studies
in which such intermediate events have been recorded during follow-up. The
first study concerns Congenital Heart Diseased patients who were followed-up
echocardiographically, with several patients undergoing reintervention. The
second study concerns patients who participated in the SPRINT study and
experienced adverse events during follow-up. We are interested in the change of
the longitudinal profiles after the occurrence of the intermediate event and in
utilizing this information to improve the accuracy of the dynamic prediction
for their risk.
  To achieve this, we propose a flexible joint modeling framework for the
longitudinal and survival data that includes the intermediate event as a
time-varying binary covariate in both the longitudinal and survival submodels.
We consider a set of joint models that postulate different effects of the
intermediate event in the longitudinal profile and the risk of the clinical
endpoint, with different formulations for their association while allowing its
parametrization to change after the occurrence of the intermediate event. Based
on these models we derive dynamic predictions of conditional survival
probabilities which are adaptive to different scenarios with respect to the
occurrence of the intermediate event. We evaluate the accuracy of these
predictions with a simulation study using the time-dependent area under the
receiver operating characteristic curve and the expected prediction error
adjusted to our setting. The results suggest that accounting for the changes in
the longitudinal profiles and the instantaneous risk for the clinical endpoint
is important, and improves the accuracy of the dynamic predictions.

8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
7
The categories of this paper are: hep-th
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph