Abstract
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.
Highlights
The present paper introduces a fast and efficient method to predict whether a breast cancer patient undergoing chemotherapy (CT) is at high risk of developing febrile neutropenia, using predictive factors available before the first chemotherapy cycle
This paper demonstrates that a Nearest Neighbour Classifier can be used to achieve statistically-significant prediction of risk of developing neutropenia based on factors available before the first chemotherapy cycle
Hopman, and Mates [8] report that over 50% of patients treated for early-stage breast cancer in the Southeast Ontario Local Health Integration Network (LHIN) receive primary prophylaxis with granulocyte colony-stimulating factors (G-CSFs), leading to less febrile neutropenia, but risk is still high for olderage patients, taxane-based CT, and use of the G-CSF filgrastim
Summary
The present paper introduces a fast and efficient method to predict whether a breast cancer patient undergoing chemotherapy (CT) is at high risk of developing febrile neutropenia, using predictive factors available before the first chemotherapy cycle. The motivation for this work is a recent study [1] into factors associated with emergency room visits and hospital admissions in patients undergoing curative chemotherapy for breast cancer in the Southeast Ontario Local Health Integration Network (LHIN). These patients have a higher risk of emergency room visits and hospital admission rates compared to other LHINs in Ontario, Canada. Another study [2] of neutropenia prediction using
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