A Novel Surrogate Nomogram Capable of Predicting OncotypeDX Recurrence Score©
Matthew G Davey1,2, Amirhossein Jalali3,4, Éanna J Ryan2
1The Lambe Institute for Translational Research, National University of Ireland, H91 TK33 Galway, Ireland.
Journal of Personalized Medicine
|July 27, 2022
Summary
This study developed a user-friendly online nomogram to predict the OncotypeDX Recurrence Score (RS) for early-stage breast cancer patients, overcoming limitations of traditional testing.
Area of Science:
- Oncology
- Genomics
- Biostatistics
Background:
- The OncotypeDX Recurrence Score (RS) is a 21-gene assay for early-stage ER+/HER2− breast cancer prognosis and chemotherapy guidance.
- Limitations include high cost and lengthy turnaround times for RS testing.
Purpose of the Study:
- To develop a user-friendly nomogram that accurately predicts the OncotypeDX Recurrence Score (RS).
- To provide a faster, more accessible alternative for predicting RS in clinical practice.
Main Methods:
- Multivariable linear regression and receiver operating characteristic (ROC) analyses were used to identify predictors of RS and RS > 25.
- A dynamic, user-friendly online nomogram was developed using R (version 4.0.3) with training (70.3%) and test (29.7%) datasets.
- The study included 448 consecutive patients who underwent RS testing.
Main Results:
- Postmenopausal status, grade 3 disease, and estrogen receptor (ER) score independently predicted RS (AUC = 0.719).
- Grade 3 disease, decreased ER score, and decreased progesterone receptor score independently predicted RS > 25 (AUC = 0.740).
- The developed online nomogram demonstrated predictive capability for RS outcomes.
Conclusions:
- An online, user-friendly nomogram was successfully designed and validated.
- The nomogram utilizes routinely available clinicopathological parameters to predict outcomes of the 21-gene RS assay.
- This tool offers a practical solution to overcome the cost and time constraints associated with traditional RS testing.
