PHD, Kent State University, 2024, College of Public Health

This study focused on evaluating the patient-reported psychological outcomes (PRPOs), including anxiety, depression, cancer-related post-traumatic stress disorder symptoms (CR-PTSD), fear of cancer recurrence (FCR), and post-traumatic growth (PTG), among surgically treated colorectal cancer (CRC) patients. Additionally, this study examined the association between coping strategies and these PRPOs. The research involved 23 CRC patients undergoing curative surgery. With the exception of FCR, which was measured only post-surgery, the study conducted assessments of all PRPOs and coping strategies at two crucial points: before and after the surgical intervention. Results demonstrated a significant reduction in anxiety levels post-surgery, while depression scores remained unchanged. PTG, particularly in the dimensions of Relating to Others and Appreciation of Life, showed significant increases, indicating potential positive psychological adaptation following surgery. In contrast, CR-PTSD symptoms were minor and exhibited negligible changes that were not statistically significant. For coping strategies, there was a significant improvement in problem-focused coping post-surgery, whereas emotion-focused and avoidant coping strategies remained unchanged. Despite improvements in certain psychological outcomes and coping strategies, the study identified a high frequency of FCR among participants post-surgery, with 70% reporting elevated levels (≥12). Regression analysis showed that problem-focused coping strategies were significantly associated with reduced anxiety levels and positively correlated with PTG factors over time. These findings highlight the importance of adaptive coping mechanisms in affecting psychological outcomes after CRC surgery. The persistent high levels of FCR post-surgery underline the need for targeted psychosocial interventions to address this prevalent concern among CRC survivors. In conclusion, this research underscores the complexity of psychological (open full item for complete abstract)

Committee: Melissa Zullo (Committee Chair); Joel Hughes (Committee Member); Lynette Phillips (Committee Member); Vinay Cheruvu (Committee Member) Subjects: Epidemiology; Health Care; Health Care Management; Oncology; Psychology; Public Health; Statistics; Surgery

PhD, University of Cincinnati, 2014, Pharmacy: Pharmaceutical Sciences/Biopharmaceutics

Background: Colorectal cancer (CRC) is a type of cancer which develops from uncontrolled cell growth in the colon or rectum. It is the third most commonly diagnosed cancer in males and the second in females. In epidemiologic research for CRC, advanced cancer stage is an important factor for determining disease development and treatment patterns. However, this variable is not available because medical claims databases is retrospective and only original built for financial analysis only. Algorithms to predict advanced CRC stage were developed based on the existing medical information in claims database. Method: Study cohorts were identified from the Surveillance Epidemiology and End Results (SEER)-Medicare database. Two algorithms were constructed based on covariates obtained from the database for different study periods, including demographic, treatment pattern variables. The training set was used to derive predictive equations by using logistic regression model, then applied to validation set for evaluating the predictive characteristics (sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV)). The developed algorithm were applied to MarketScan® Commercial Claims and Encounters Database and tested the predictive values. Results: The algorithm of predicting advanced CRC stage in 1999 to 2003 achieved sensitivity 50.3% and specificity 95.0%, PPV 66.78% and NPV 90.58% while the equation distinguishing CRC stage IV in 2004 to 2007 achieved sensitivity 56.8%, specificity 95.3%, PPV 71.86% and NPV 91.19%. All algorithms made better predictive values than the single ICD-9 metastatic diagnosis as the predictor. Then the algorithm for 1999 to 2003 was applied to MarketScan database. 9484 patients were predicted as non-advanced CRC group while 1097 patients were assigned to advanced CRC group. Conclusion Claims-based algorithms were developed to predict advanced cancer stage. These algorithms were shown to be successful in the recent stu (open full item for complete abstract)

Committee: Jianfei Guo Ph.D. (Committee Chair); Jane Pruemer Pharm.D. (Committee Member); Christina Kelton Ph.D. (Committee Member); Wei Pan Ph.D. (Committee Member); Patricia Wigle Pharm.D. (Committee Member) Subjects: Classical Studies; Pharmaceuticals