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Assessment of Mortality Risk for Patients Undergoing Colorectal Surgery Using Regression Modeling

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Part of the Studies in Computational Intelligence book series (SCI, volume 606)

Abstract

Since its beginning in the 1990s, laparoscopic surgical technique has partly or event totally replaced the classical open technique in some branches of surgery. The surgical resection of colorectal cancer, which this paper is engaged in, is no exception. However, besides the well-known benefits of this technique, there are also less known disadvantages, which can significantly influence morbidity. In such a situation we can ask, which technique will guarantee longer survival time to the patient. The medical survival censored data of 866 patients were evaluated by the Cox proportional hazards model in order to answer this question and to find the other parameters, which can influence the survival time of the patient. The surgical techniques were compared separately for patients with surgical resection of colon and for patients with surgical resection of rectum, because these two types of techniques are inherently different. Survival analysis performed by the Cox proportional hazards model led in both cases to the same conclusion, namely that there is no statistically significant difference in survival times between the two groups of patients operated by different surgical techniques.

Keywords

Hazard Function Partial Likelihood Estimate Hazard Ratio Model Building Process Model Development Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This Paper has been prepared in the framework of the IT4Innovations Centre of Excellence project, reg. no. CZ.1.05/1.1.00/02.0070 supported by Operational Programme ‘Research and Development for Innovations’ funded by Structural Funds of the European Union and the Government of Czech Republic.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.IT4Innovations National Supercomputing CenterVŠB Technical University of OstravaOstravaCzech Republic
  2. 2.The Clinic of SurgeryUniversity Hospital OstravaOstravaCzech Republic

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