Predicting Neutropenia Risk in Breast Cancer Patients from Pre- Chemotherapy Characteristics

The Open Bioinformatics Journal 31 December 2014 RESEARCH ARTICLE DOI: 10.2174/1875036201408010016


A previous study (Pittman, Hopman, Mates) of breast cancer patients undergoing curative chemotherapy (CT) found that the third most common reason for emergency department (ER) visits and hospital admission (HA) was febrile neutropenia. Factors associated with ER visits and HA included (1) stage of the cancer, (2) size of tumor, (3) adjuvant versus neo-adjuvant CT (“adjuvance”), and (4) number of CT cycles. We hypothesized that a statistically-significant predictor of neutropenia could be built based on some of these factors, so that risk of neutropenia predicted for a patient feeling unwell during CT could be used in weighing need to visit the ER. The number of CT cycles was not used as a factor so that the predictor could calculate the neutropenia risk for a patient before the first CT cycle. Different models were built corresponding to different pre-chemotherapy factors or combinations of factors. The single factor yielding the best classification accuracy was tumor size (Mathews’ correlation coefficient φ = +0.18, Fisher’s exact two-tailed probability P < 0.0374). The odds ratio of developing febrile neutropenia for the predicted high-risk group compared to the predicted low-risk group was 5.1875. Combining tumor size with adjuvance yielded a slightly more accurate predictor (Mathews’ correlation coefficient φ = +0.19, Fisher’s exact two-tailed probability P < 0.0331, odds ratio = 5.5093). Based on the observed odds ratios, we conclude that a simple predictor of neutropenia may have value in deciding whether to recommend an ER visit. The predictor is sufficiently fast that it can run conveniently as an Applet on a mobile computing device.

Keywords: Breast cancer, chemotherapy, classifier, nearest neighbor, neutropenia.
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