Annals of Surgical Oncology

, Volume 21, Issue 6, pp 2052–2058 | Cite as

A Simple Tumor Load-Based Nomogram for Surgery in Patients with Colorectal Liver and Peritoneal Metastases

  • Dominique Elias
  • Matthieu Faron
  • Diane Goéré
  • Frédéric Dumont
  • Charles Honoré
  • Valérie Boige
  • David Malka
  • Michel Ducreux
Gastrointestinal Oncology



The decision to perform optimal surgery when peritoneal metastases (PM) are associated with liver metastases (LM) is extremely complex. No guidelines exist. The purpose of this study was to present a simple and useful statistical tool that generates a graphical calculator (nomogram) to help the clinician rapidly estimate individualized patient-specific survival before undergoing optimal surgery.

Materials and Methods

An analysis of 287 patients with liver metastasis (LM), 119 patients with peritoneal metastasis (PM), and 37 patients with LM + PM, who underwent optimal surgery plus chemotherapy between 1995 and 2010 was performed. A minimal number of parameters were taken into account to obtain a nomogram that would be very simple to use. With the overall tumor load as the main prognostic factor, we included the number of lesions for LM and the peritoneal carcinomatosis score (PCI) for PM. The Cox model was used to generate the nomogram.


The 5-year overall survival was, respectively, 38.5, 36.5, and 26.4 % in the LM group, the PM group, and the LM + PM group. The summation of 3 parameters (the number of LM, the PCI, and the type of surgery [liver resection, HIPEC, or both]), makes it easy to calculate a score that graphically corresponds to an estimation of survival after optimal surgery (nomogram). It can be used for LM alone, PM alone, or both.


A graphic nomogram that is simple to calculate and easy to use enables us to rapidly appreciate the prognosis of patients according to the number of LM, the PCI, or both. This nomogram must be validated in prospective studies in other tertiary centers.


Overall Survival Liver Metastasis Liver Resection Peritoneal Metastasis Optimal Surgery 
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.



The authors thank Ms. Lorna Saint-Ange for editing.


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Copyright information

© Society of Surgical Oncology 2014

Authors and Affiliations

  • Dominique Elias
    • 1
  • Matthieu Faron
    • 3
  • Diane Goéré
    • 1
  • Frédéric Dumont
    • 1
  • Charles Honoré
    • 1
  • Valérie Boige
    • 2
  • David Malka
    • 2
  • Michel Ducreux
    • 2
  1. 1.Department of Oncologic SurgeryGustave RoussyVillejuifFrance
  2. 2.Department of Medical OncologyGustave RoussyVillejuifFrance
  3. 3.Department of StatisticsGustave RoussyVillejuifFrance

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