Volume 109, Issue 7 pp. 721-725
Research Article

A pre-operative nomogram for decision making in oncological surgical emergencies

Frédéric Dumont MD

Corresponding Author

Frédéric Dumont MD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

Correspondence: Frédéric Dumont, MD, Department of Surgical Oncology, Institut Gustave Roussy, 114 rue Edouard Vaillant, 94805 Villejuif Cedex, France. Fax: +33-1-42-11-53-30. E-mail: [email protected]Search for more papers by this author
Chafika Mazouni MD, PhD

Chafika Mazouni MD, PhD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

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Georgina Bitsakou MD

Georgina Bitsakou MD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

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Philippe Morice MD, PhD

Philippe Morice MD, PhD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

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Diane Goéré MD, PhD

Diane Goéré MD, PhD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

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Charles Honoré MD

Charles Honoré MD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

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Dominique Elias MD, PhD

Dominique Elias MD, PhD

Department of Surgical Oncology, Institut Gustave Roussy, Villejuif, France

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First published: 06 January 2014
Citations: 11
The authors have no conflicts of interest and source of funding. The subject of study had no commercial interest, no financial or material support.

Abstract

Background

The purpose of the study was to propose a clinical decision-making tool for predicting mortality in patients undergoing emergency abdominal surgery with a palliative intent in the oncology setting.

Methods

Identification of all emergency surgical procedures performed in a Department of Oncologic Surgery in a Comprehensive Cancer Center between January 2008 and January 2013. Multivariate logistic and Cox regression models were used to identify factors predicitve of mortality at 3 months and survival probabilities. Models were internally validated using bootstrapping and calibration.

Results

The mortality rates were 30% at 1 month, 46.7% at 3 months and 83.3% at the end of the study. One model based on the albumin level and the P-POSSUM score (AUC: 0.725) adequately predicted mortality at 3 months. A survival nomogram predicted mortality with a concordance index (CI) of 0.718, using the following factors: WHO performance status (P = 0.02), albumin level (P < 0.01) and P-POSSUM score (P < 0.01). The origin or the extent of the carcinoma did not own sufficient pronostic impact to be selected in this model.

Conclusions

Pre-operative mortality risk scores can be developed in a palliative context. Physicians counselling and surgical decision making should be based on the use of these tools. J. Surg. Oncol 2014; 109:721–725. © 2014 Wiley Periodicals, Inc.

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