This study assesses the performance status in stage I-III triple negative breast cancer patients who are receiving neoadjuvant chemotherapy. Information collected in this study may help doctors learn if movement and fitness trackers can be used to predict side effects in cancer patients receiving chemotherapy.
PRIMARY OBJECTIVE: I. To determine if in-office movement trackers or baseline metabolic equivalents (METs) groups identify those patients who are at highest risk for severe adverse event (SAE)s on neoadjuvant chemotherapy. SECONDARY OBJECTIVES: I. To determine the association between the occurrence of SAEs, unexpected healthcare encounters, depending on the change in activity level classification between the baseline METs group and mid-treatment METs group (at month 3). II. Explore association between patient reported outcome (PRO) data and movement tracker data. OUTLINE: Patients complete movement assessment 5-15 days prior to the initiation of neoadjuvant chemotherapy and at day 1 of neoadjuvant chemotherapy. Patients' SAE data is collected. Patients are observed during their neoadjuvant chemotherapy for up to 6 months.
Study Type
OBSERVATIONAL
Enrollment
27
Complete movement assessment
SAE data is collected
M D Anderson Cancer Center
Houston, Texas, United States
The number of non-hematologic serious adverse events occurring during neoadjuvant chemotherapy (i.e. correlate Microsoft motion tracking data and baseline metabolic equivalents [METs] group with incidence of serious adverse events)
Time frame: Up to 6 months
The number of severe adverse event (SAE)s
Time frame: During the final 3 months of neoadjuvant chemotherapy
The number of SAEs based on laboratory results
Time frame: Over the final 3 months of neoadjuvant chemotherapy
The number of SAEs based on symptoms
Time frame: Over the final 3 months of neoadjuvant chemotherapy
The number of unexpected healthcare encounters
Time frame: In the final 3 months of neoadjuvant chemotherapy
Correlation between patient reported outcomes (PRO) data and movement tracker data
Will calculate the Pearson correlation between PRO data and movement tracker data. Will also fit a linear mixed model with PRO data as the dependent variable and movement tracker data as covariates. Intra-subject correlation will be adjusted in linear mixed model analysis.
Time frame: 6 months
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