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the index case. Statistical Analysis We reported the time frame and other characteristics of prior cancer-related exclusion criteria using descriptive statistics (number, percent) and qualitatively assessed similarities and differences in the

were calculated for demographic and clinical characteristics. For the comparison of respondents reporting current CIPN symptoms to those without symptoms, t tests were used for continuous variables and chi-square tests were used for categorical

%) had additional nodal disease. Table 1. Demographic and Clinicopathologic Characteristics In terms of adjuvant therapy, 176 (53%) of 329 patients received RT, 245 (75%) received chemotherapy, and 272 (83%) received endocrine therapy ( Table 1 ). Records

Patient Characteristics Hospital and ED Costs Hospital treatment costs were estimated using Australian Refined Diagnosis Related Groups (AR-DRGs) and episode of care LoS. Cost estimates were obtained from the National Hospital Cost Data Collection

considered colon and rectal cancer together, whereas patient characteristics, complication risks, and clinical outcomes are different in colon versus rectal cancer. 10 Furthermore, to provide clues for possible quality improvement, other outcomes require

recorded, as were demographic data and tumor characteristics, such as pathology size and tumor marker profile. Statistical analysis was performed using Fisher exact test and Student unpaired t -test, with a P value <.05 being considered statistically

additional treatments. Demographic and Clinical Characteristics Using data from the SEER registry, we determined age, sex, race, Hispanic ethnicity, marital status, area income, cancer stage, and disease subsite. 13 Dual Medicaid insurance and Charlson

Southwestern Medical Center deemed the study exempt given the use of public deidentified data. Statistical Analysis Baseline Characteristics Baseline characteristics, including demographic and socioeconomic variables, were reported for the entire cohort (N=34

into clinical care paths. Further, cancer treatment is becoming increasingly personalized to the patient and tumor characteristics, thus increasing the complexity of decision-making. Methods: We developed a method to model guideline recommendations

.4 (SAS Institute Inc.) and Splus 8.2 (TIBCO Software Inc) were used for all analyses. Results Patient Characteristics We identified 350 adult patients who were prescribed MB oral rinse for oral pain from mucositis related to cancer therapy