ArXiv Preprint
Introduction: The Oncotype DX (ODX) test is a commercially available
molecular test for breast cancer assay that provides prognostic and predictive
breast cancer recurrence information for hormone positive, HER2-negative
patients. The aim of this study is to propose a novel methodology to assist
physicians in their decision-making. Methods: A retrospective study between
2012 and 2020 with 333 cases that underwent an ODX assay from three hospitals
in Bourgogne Franche-Comt{\'e} was conducted. Clinical and pathological reports
were used to collect the data. A methodology based on distributional random
forest was developed using 9 clinico-pathological characteristics. This
methodology can be used particularly to identify the patients of the training
cohort that share similarities with the new patient and to predict an estimate
of the distribution of the ODX score. Results: The mean age of participants id
56.9 years old. We have correctly classified 92% of patients in low risk and
40.2% of patients in high risk. The overall accuracy is 79.3%. The proportion
of low risk correct predicted value (PPV) is 82%. The percentage of high risk
correct predicted value (NPV) is approximately 62.3%. The F1-score and the Area
Under Curve (AUC) are of 0.87 and 0.759, respectively. Conclusion: The proposed
methodology makes it possible to predict the distribution of the ODX score for
a patient and provides an explanation of the predicted score. The use of the
methodology with the pathologist's expertise on the different histological and
immunohistochemical characteristics has a clinical impact to help oncologist in
decision-making regarding breast cancer therapy.
Zeina Al Masry, Romain Pic, Clément Dombry, Christine Devalland
2023-03-13
