For stages III and IV CRC, the addition ofĬhemotherapy to surgical resection has been demonstrated to improve Optimal treatment for CRC is dependent on the stage of disease at The predictor for treatment delay has the most promise, and further studies will aid its refinement and improvement of its accuracy.Ĭolorectal cancer (CRC) is the third leading cause Therefore, predictors were developed for response to and adverse events from chemotherapy for patients with colorectal cancer patients. The best predictors resulted in area under the receiver operating characteristic curve values of: 0.542 for chemotherapy dose reduction, 0.612 for 5-year survival, 0.650 for cancer recurrence and 0.750 for treatment delay. Urine spectra were obtained for 62 patients. Using machine learning, predictors were generated and evaluated using 10-fold cross-validation. The 1H NMR spectrum of each urine sample was analyzed using Chenomx NMRSuite v7.0. Nuclear magnetic resonance (NMR) spectra of urine samples were acquired.

Patients provided urine samples for analysis prior to any intervention. Adverse events were subdivided as follows: Delays in treatment, dose reductions, hospitalizations and chemotherapy regime changes.

Data was collected concerning the chemotherapy regimen, adverse events associated with chemotherapy, disease progression and recurrence and 5-year survival. The exclusion criteria included chemotherapy for palliation and patients living outside of Alberta. A retrospective chart review of patients diagnosed with stage III or IV colorectal cancer between 20 was performed. The aim of the current study was to develop a urine metabolomics-based biomarker panel to predict adverse events and response to chemotherapy in patients with colorectal cancer. The ability to predict a patient's response to chemotherapy may be of great value for clinicians and patients when planning cancer treatment.

Colorectal cancer is the third leading cause of cancer-associated mortality in the western world.

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