Overdispersion in service systems

In this thesis service systems with nonstandard arrival processes are studied. In order to mimic real arrival data, we choose to incorporate overdispersion in the models. This feature is abundantly present in (arrival) data of e.g., emergency departments and call centers and corresponds to the phenomenon that the variance of the number of arrivals is larger than its mean. Throughout this thesis, overdispersion is explained by the presence of a 'random environment', which is modeled using Poisson mixtures or Markov modulation. The general objective is to derive limiting results for the distribution of the resulting models. We mainly study infinite-server models under a specific twofold scaling (in space and time); for these models approximations for performance measures such as tail probabilities are presented and their accuracy is tested. The twofold scaling gives rise to different asymptotic regimes, depending on the built-in scaling parameter. We also derive exact tail asymptotics for a Lévy-type generalization of these scaled infinite-server models. Infinite-server systems have the advantage of being amenable for analysis, in contrast to finite-server systems, which in return can often be directly linked to real-world settings. The numerical examples concerning staffing applications are based on the observation that infinite-server models can be used to approximate their finite-server counterparts. Finally, this thesis also deals with single-server queues, combined with different types of overdispersed arrival stream models. Various heavy-traffic theorems are stated and proved, and for a specific example we test the accuracy of the resulting approximation for the distribution of the single-server queue

Performance of an easy-to-use prediction model for renal patient survival: an external validation study using data from the ERA-EDTA Registry

Clinical epidemiolog

Cross-Sectional Study on MRI Restaging After Chemoradiotherapy and Interval to Surgery in Rectal Cancer: Influence on Short- and Long-Term Outcomes

Background. The time interval between CRT and surgery in rectal cancer patients is still the subject of debate. The aim of this study was to first evaluate the nationwide use of restaging magnetic resonance imaging (MRI) and its impact on timing of surgery, and, second, to evaluate the impact of timing of surgery after chemoradiotherapy (CRT) on short- and long-term outcomes.Methods. Patients were selected from a collaborative rectal cancer research project including 71 Dutch centres, and were subdivided into two groups according to time interval from the start of preoperative CRT to surgery (= 14 weeks), and the long-interval group included a higher proportion of cT4 stage and multivisceral resection patients. Pathological complete response rate (n = 34 [15.2%] vs. n = 47 [18.7%], p = 0.305) and CRM involvement (9.7% vs. 15.9%, p = 0.145) did not significantly differ. Thirty-day surgical complications were similar (20.1% vs. 23.1%, p = 0.943), however no significant differences were found for local and distant recurrence rates, disease-free survival, and overall survival.Conclusions. These real-life data, reflecting routine daily practice in The Netherlands, showed substantial variability in the use and timing of restaging MRI after preoperative CRT for rectal cancer, as well as time interval to surgery. Surgery before or after 14 weeks from the start of CRT resulted in similar short- and long-term outcomes.Surgical oncolog

Benchmarking recent national practice in rectal cancer treatment with landmark randomized controlled trials

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