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Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Using Nomograms Wisely: Predicting Sentinel Node Positivity in Melanoma.

Priscila Rojas-Garcia1,2, Bryan Ma3, Eva Lindell Jonsson1,2

  • 1Department of Surgery, Tom Baker Cancer Centre, Calgary, AB, Canada.

Annals of Surgical Oncology
|August 14, 2024
PubMed
Summary
This summary is machine-generated.

Different melanoma prediction nomograms yield varied sentinel lymph node biopsy (SNB) risk scores. Factors like lymphovascular invasion significantly influence these predictions, highlighting the sensitivity of risk estimation tools.

Keywords:
Lymph node riskMlanomaNomogramsSentinel lymph node biopsyStage

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Area of Science:

  • Oncology
  • Dermatology
  • Surgical Pathology

Background:

  • Multiple validated nomograms exist for predicting sentinel node biopsy (SNB) risk in malignant melanoma.
  • These nomograms utilize varying clinical and histopathologic factors, leading to potential discrepancies in patient risk stratification.
  • This study investigates the variability in risk estimations among different SNB prediction models.

Purpose of the Study:

  • To compare the risk estimations provided by the MSKCC and MIA nomograms for sentinel node biopsy in malignant melanoma.
  • To identify the key histopathologic variables that contribute to significant differences in risk predictions between nomograms.

Main Methods:

  • Generation of 300 hypothetical thin melanoma cases with diverse clinical and pathological features using a random number generator.
  • Comparison of risk predictions between the MSKCC and MIA nomograms.
  • Application of chi-square tests and multivariate linear regression to analyze prediction differences and identify influential factors.

Main Results:

  • The MSKCC nomogram generally predicted lower risks compared to the MIA nomogram (p < 0.001).
  • A significantly higher proportion of patients had predicted risks exceeding 15% with the MIA nomogram (43%) versus the MSKCC nomogram (0.7%).
  • Lymphovascular invasion (LVI), mitosis, and melanoma subtype were identified as key factors driving prediction discrepancies (>10%) between the nomograms.

Conclusions:

  • Nomograms are valuable for predicting SNB risk in melanoma patients.
  • The choice of predictors included in a nomogram significantly impacts the resulting risk output, underscoring the sensitivity of these tools.