Accepted for/Published in: JMIR Perioperative Medicine
Date Submitted: Oct 31, 2021
Date Accepted: Oct 6, 2022
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Can machine learning be used to reduce overtreatment of the axilla in breast cancer? Results from a retrospective cohort study
ABSTRACT
Background:
Patients with early breast cancer undergoing primary surgery who have low axillary nodal burden can safely forego axillary node clearance (ANC). However, routine use of axillary ultrasound (AUS) leads to 43% of patients in this group having ANC unnecessarily following a positive AUS. The intersection of machine learning with medicine can provide innovative ways to understand specific risk within large patient data sets, but this has not yet been trialled in the arena of axillary node management in breast cancer.
Objective:
To assess if machine learning techniques could be used to improve pre-operative identification of patients with low and high axillary metastatic burden.
Methods:
A single-centre retrospective analysis was performed on patients with breast cancer who had a preoperative axillary ultrasound, and the specificity and sensitivity of AUS were calculated. Machine learning and standard statistical methods were applied to the data to see if, when used preoperatively, they could have improved the accuracy of AUS to better discern between high and low axillary burden.
Results:
The study included 459 patients; 31% (n=142) had a positive AUS, and, among this group, 62% (n=88) had two or fewer macrometastatic nodes at ANC. When applied to the dataset, logistic regression outperformed AUS and machine learning methods with a specificity of 0.950, correctly identifying 66 patients in this group who had been incorrectly classed as having high axillary burden by AUS alone. Of all the methods, the artificial neural network had the highest accuracy (0.919). Interestingly, AUS had the highest sensitivity of all methods (0.777), underlining its utility in this setting.
Conclusions:
Machine learning greatly improves identification of the important subgroup of patients with no palpable axillary disease, positive ultrasound, and more than two metastatically involved nodes. A negative ultrasound in patients with no palpable lymphadenopathy is highly indicative of low burden and it is unclear if sentinel node biopsy adds value in this situation. Clinical Trial: n/a
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