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A Novel Nomogram for Peritoneal Mesothelioma Predicts Survival

Annals of Surgical Oncology volume 20, pages 555–561 (2013)Cite this article

Abstract

Background

Malignant peritoneal mesothelioma (MPM) is a rare disease treated with cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC). Estimation of personalized survival times can potentially guide treatment and surveillance.

Methods

We analyzed 104 patients who underwent CRS and cisplatin-based HIPEC for MPM. By means of 25 demographic, laboratory, operative, and histopathological variables, we developed a novel nomogram using machine-learned Bayesian belief networks with stepwise training, testing, and cross-validation.

Results

The mean peritoneal carcinomatosis index (PCI) was 15, and 66 % of patients had a completeness of cytoreduction (CC) score of 0 or 1. Eighty-seven percent of patients had epithelioid histology. The median follow-up time was 49 (1–195) months. The 3- and 5-year overall survivals (OS) were 58 and 46 %, respectively. The histological subtype, pre-CRS PCI, and preoperative serum CA-125 had the greatest impact on OS and were included in the nomogram. The mean areas under the receiver operating characteristic curve for the 10-fold cross-validation of the 3- and 5-year models were 0.77 and 0.74, respectively. The graphical calculator or nomogram uses color coding to assist the clinician in quickly estimating individualized patient-specific survival before surgery.

Conclusions

Machine-learned Bayesian belief network analysis generated a novel nomogram predicting 3- and 5-year OS in patients treated with CRS and HIPEC for MPM. Pre-CRS estimation of survival times may potentially individualize patient care by influencing the use of systemic therapy and frequency of diagnostic imaging, and might prevent CRS in patients unlikely to achieve favorable outcomes despite surgical intervention.

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Acknowledgment

Supported by an NIH intramural grant.

Disclaimer

The views expressed in this manuscript are those of the authors and do not reflect the official policy of the NIH/NCI or Department of the Army, the Department of Defense or the United States Government.

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Authors and Affiliations

  1. GI and Hepatobiliary Malignancies Section, Surgery Branch, National Cancer Institute/NIH, Bethesda, MD, USA

    Nicholas P. Schaub MD, Marybeth S. Hughes MD, Tatiana Beresnev MD, Udai S. Kammula MD, Prakash Pandalai MD, Giao Q. Phan MD, Udo Rudloff MD, PhD & Itzhak Avital MD

  2. Laboratory of Pathology, National Cancer Institute/NIH, Bethesda, MD, USA

    Meghna Alimchandani MD & Martha Quezado MD

  3. Solid Tumor Immunotherapy Section, Laboratory of Molecular Biology, National Cancer Institute/NIH, Bethesda, MD, USA

    Raffit Hassan MD

  4. DecisionQ Corporation, Washington, DC, USA

    Phil Kalina MS & John S. Eberhardt BS

  5. Division of Surgical Oncology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA

    David L. Bartlett MD & James F. Pingpank MD

  6. Department of Surgery, Montefiore Medical Center/Albert Einstein College of Medicine, New York, NY, USA

    Steven K. Libutti MD

  7. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Richard E. Royal MD

  8. Department of Surgery, Division of Surgical Oncology, Walter Reed National Military Medical Center, Bethesda, MD, USA

    Alexander Stojadinovic MD

  9. Division of Surgical Oncology, Department of Surgery and the Marlene and Stewart Greenebaum Cancer Center, University of Maryland School of Medicine, Baltimore, MD, USA

    H. Richard Alexander

  10. Bon Secours Cancer Institute, Richmond, VA, USA

    Itzhak Avital MD

Authors
  1. Nicholas P. Schaub MD
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  2. Meghna Alimchandani MD
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  3. Martha Quezado MD
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  4. Phil Kalina MS
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  6. Marybeth S. Hughes MD
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  7. Tatiana Beresnev MD
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  8. Raffit Hassan MD
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  9. David L. Bartlett MD
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  10. Steven K. Libutti MD
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  11. James F. Pingpank MD
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  12. Richard E. Royal MD
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  13. Udai S. Kammula MD
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  14. Prakash Pandalai MD
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  15. Giao Q. Phan MD
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  16. Alexander Stojadinovic MD
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  17. Udo Rudloff MD, PhD
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  18. H. Richard Alexander
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  19. Itzhak Avital MD
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Corresponding author

Correspondence to Udo Rudloff MD, PhD.

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Schaub, N.P., Alimchandani, M., Quezado, M. et al. A Novel Nomogram for Peritoneal Mesothelioma Predicts Survival. Ann Surg Oncol 20, 555–561 (2013). https://doi.org/10.1245/s10434-012-2651-5

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  • DOI: https://doi.org/10.1245/s10434-012-2651-5

Keywords

  • Overall Survival
  • Bayesian Belief Network
  • Malignant Peritoneal Mesothelioma
  • Early Postoperative Intraperitoneal Chemotherapy
  • Peritoneal Carcinomatosis Index