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Comparison of PREMM5 and PREMMplus Risk Assessment Models to Identify Lynch Syndrome.

Leah H Biller1,2,3, Kate Mittendorf4, Miki Horiguchi1,2

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PREMM5 and PREMMplus both effectively identify Lynch syndrome (LS) risk with high negative predictive values. PREMM5 offers superior discrimination, while PREMMplus shows higher sensitivity for LS identification.

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Area of Science:

  • Genetics
  • Oncology
  • Risk Assessment

Background:

  • Clinical risk assessment models aid in identifying hereditary cancer susceptibility.
  • Comparing multigene prediction models with syndrome-specific models for individual syndromes like Lynch syndrome (LS) is crucial.

Purpose of the Study:

  • To compare the PREMMplus (19-gene) model with the PREMM5 (LS-specific) model for identifying individuals with Lynch syndrome.
  • To evaluate the performance of these models in assessing LS risk.

Main Methods:

  • Analysis of two cohorts (commercial laboratory and genetics clinic) totaling 18,252 patients with a history of LS-associated cancer.
  • Calculation of PREMMplus and PREMM5 scores for all patients.
  • Evaluation of sensitivity, specificity, positive predictive value, and negative predictive value (NPV) using a 2.5% score cutoff; ROC-AUC used for discrimination assessment.

Main Results:

  • PREMMplus demonstrated higher sensitivity than PREMM5 in both cohorts.
  • PREMM5 exhibited superior discriminatory capacity (ROC-AUC) compared to PREMMplus in both cohorts.
  • Both models achieved high negative predictive values (NPV ≥98.8%) for identifying LS carriers.

Conclusions:

  • Both PREMM5 and PREMMplus are valuable tools for identifying individuals at risk of Lynch syndrome, demonstrating high NPVs.
  • The selection between PREMM5 and PREMMplus may depend on specific risk assessment objectives and the patient population being evaluated.