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Sentinel Node Positive Melanoma Patients: Prediction and Prognostic Significance of Nonsentinel Node Metastases and Development of a Survival Tree Model

  • Melanomas
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Completion lymph node dissection (CLND) following positive sentinel node biopsy (SNB) for melanoma detects additional nonsentinel node (NSN) metastases in approximately 20% of cases. This study aimed to establish whether NSN status can be predicted, to determine its effect on survival, and to develop survival tree models for the sentinel node (SN) positive population.

Materials and Methods

Sydney Melanoma Unit (SMU) patients with at least 1 positive SN, meeting inclusion criteria and treated between October 1992 and June 2005, were identified from the Unit database. Survival characteristics, potential predictors of survival, and NSN status were assessed using the Kaplan–Meier method, Cox regression model, and logistic regression analyses, respectively. Classification tree analysis was performed to identify groups with distinctly different survival characteristics.

Results

A total of 323 SN-positive melanoma patients met the inclusion criteria. On multivariate analysis, age, gender, primary tumor thickness, mitotic rate, number of positive NSNs, or total number of positive nodes were statistically significant predictors of survival. NSN metastasis, found at CLND in 19% of patients, was only predicted to a statistically significant degree by ulceration. Multivariate analyses demonstrated that survival was more closely related to number of positive NSNs than total number of positive nodes. Classification tree analysis revealed 4 prognostically distinct survival groups.

Conclusions

Patients with NSN metastases could not be reliably identified prior to CLND. Prognosis following CLND was more closely related to number of positive NSNs than total number of positive nodes. Classification tree analysis defined distinctly different survival groups more accurately than use of single-factor analysis.

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Author information

Authors and Affiliations

  1. Melanoma Institute Australia (formerly Sydney Melanoma Unit), Sydney, NSW, Australia

    Martin Wiener MBChB, Katharine M. Acland MRCP, Helen M. Shaw PhD, Richard A. Scolyer MD, Julie B. Winstanley PhD, CStat & John F. Thompson MD

  2. Discipline of Surgery, The University of Sydney, Sydney, NSW, Australia

    Helen M. Shaw PhD & John F. Thompson MD

  3. Biostatistics and Bioinformatics Unit, Comprehensive Cancer Center, University of Alabama, Birmingham, AL, USA

    Seng-Jaw Soong PhD

  4. Department of Biostatistics, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Hui-Yi Lin PhD & Dung-Tsa Chen PhD

  5. Department of Anatomical Pathology, Royal Prince Alfred Hospital, Sydney, NSW, Australia

    Richard A. Scolyer MD

  6. Discipline of Pathology, The University of Sydney, Sydney, NSW, Australia

    Richard A. Scolyer MD

Authors
  1. Martin Wiener MBChB
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  2. Katharine M. Acland MRCP
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  3. Helen M. Shaw PhD
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  5. Hui-Yi Lin PhD
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  6. Dung-Tsa Chen PhD
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  7. Richard A. Scolyer MD
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  8. Julie B. Winstanley PhD, CStat
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  9. John F. Thompson MD
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Corresponding author

Correspondence to John F. Thompson MD.

Additional information

Drs. Wiener and Acland contributed equally to this work.

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Wiener, M., Acland, K.M., Shaw, H.M. et al. Sentinel Node Positive Melanoma Patients: Prediction and Prognostic Significance of Nonsentinel Node Metastases and Development of a Survival Tree Model. Ann Surg Oncol 17, 1995–2005 (2010). https://doi.org/10.1245/s10434-010-1049-5

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  • DOI: https://doi.org/10.1245/s10434-010-1049-5

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