2018
DOI: 10.1186/s12874-018-0476-z
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Advantages of a multi-state approach in surgical research: how intermediate events and risk factor profile affect the prognosis of a patient with locally advanced rectal cancer

Abstract: BackgroundStandard survival analysis fails to give insight into what happens to a patient after a first outcome event (like first relapse of a disease). Multi-state models are a useful tool for analyzing survival data when different treatments and results (intermediate events) can occur. Aim of this study was to implement a multi-state model on data of patients with rectal cancer to illustrate the advantages of multi-state analysis in comparison to standard survival analysis.MethodsWe re-analyzed data from the… Show more

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Cited by 15 publications
(19 citation statements)
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“…To characterize fluctuating autoantibody states over time and in recognition of the asymmetric nature of follow‐up, we created multistate models to analyze the likelihood of converting from one autoantibody state to another (e.g., ACPA and RF positive to ACPA negative and RF positive). A multistate model is a model for time‐to‐event data in which all subjects start at an initial state and visit intermediate states (ACPA/RF +/−), possibly more than once , or enter an absorbing state of inflammatory arthritis at which time the end point is met and observation/follow‐up ceases. Multistate models can be thought of as a generalization of both survival analysis and discrete‐time Markov models, with the rates of transition between states being described as hazards or instantaneous risks .…”
Section: Methodsmentioning
confidence: 99%
“…To characterize fluctuating autoantibody states over time and in recognition of the asymmetric nature of follow‐up, we created multistate models to analyze the likelihood of converting from one autoantibody state to another (e.g., ACPA and RF positive to ACPA negative and RF positive). A multistate model is a model for time‐to‐event data in which all subjects start at an initial state and visit intermediate states (ACPA/RF +/−), possibly more than once , or enter an absorbing state of inflammatory arthritis at which time the end point is met and observation/follow‐up ceases. Multistate models can be thought of as a generalization of both survival analysis and discrete‐time Markov models, with the rates of transition between states being described as hazards or instantaneous risks .…”
Section: Methodsmentioning
confidence: 99%
“…Although MSM can be used to calculate traditional endpoints, such as incidence of a particular event or disease category, choice of the specific structure of the model is not necessarily clear‐cut. Further, Manzini et al highlighted the need for sufficient numbers of observed transitions throughout the MSM structure and difficulties in dealing with missing data in this context 14 . Le Rademacher et al acknowledged that there are barriers to their use in practice including availability of easily accessible validated software, and interpretation of the results of multistate model analyses 17 …”
Section: Introductionmentioning
confidence: 99%
“…5 They are also commonly used in health economics decision models. 13 However, despite recent research concluding that they are a promising tool for use in clinical trials, 14 to our knowledge, there is only one publication assessing their potential in terms of type I error and power via a simulation study. 15 The authors used data from trials in the stroke setting and considered multistate models with 4, 5, 6, and 7 states compared with repeated logistic regression.…”
mentioning
confidence: 99%
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“…Another example is repeated hospitalisations in patients with heart failure, where interest lies in the time spent in hospital (during each episode and in total) [ 2 ]. Further applications include other cancers (colorectal [ 3 , 4 ], ovarian [ 5 ] and acute myeloid leukemia [ 6 ]), progression to diabetes [ 7 ], health-care associated urinary tract infections [ 8 ] and pleural effusion following allogeneic hematopoietic stem cell transplantation [ 9 ].…”
Section: Introductionmentioning
confidence: 99%