Objectives: To facilitate clinical and translational research, imaging and non-imaging clinical data from multiple disparate systems must be aggregated for analysis. Study participant records from various sources are linked together and to patient records when possible to address research questions while ensuring patient privacy. This paper presents a novel tool that pseudonymizes participant identifiers (PIDs) using a researcher-driven automated process that takes advantage of application-programming interface (API) and the Perl Open-Source Digital Imaging and Communications in Medicine Archive (POSDA) to further de-identify PIDs. The tool, on-demand cohort and API participant identifier pseudonymization (O-CAPP), employs a pseudonymization method based on the type of incoming research data. Methods: For images, pseudonymization of PIDs is done using API calls that receive PIDs present in Digital Imaging and Communications in Medicine (DICOM) headers and returns the pseudonymized identifiers. For non-imaging clinical research data, PIDs provided by study principal investigators (PIs) are pseudonymized using a nightly automated process. The pseudonymized PIDs (P-PIDs) along with other protected health information is further de-identified using POSDA. Results: A sample of 250 PIDs pseudonymized by O-CAPP were selected and successfully validated. Of those, 125 PIDs that were pseudonymized by the nightly automated process were validated by multiple clinical trial investigators (CTIs). For the other 125, CTIs validated radiologic image pseudonymization by API request based on the provided PID and P-PID mappings. Conclusions We developed a novel approach of an ondemand pseudonymization process that will aide researchers in obtaining a comprehensive and holistic view of study participant data without compromising patient privacy.

PURPOSE: Appendiceal tumors are a heterogeneous group of diseases that include typical neuroendocrine tumors (TNET), goblet cell carcinoids (GCC), and atypical GCC. Atypical GCC are classified into signet-ring cell cancers (SRCC) and poorly differentiated appendiceal adenocarcinoids. The prognosis and management of these diseases is unclear because there are no prospective studies. The aim of this study is to assess the characteristics and outcome of appendiceal TNET, GCC, and SRCC patients. MATERIALS AND METHODS: Appendiceal TNET, GCC, and SRCC patients diagnosed between 1973 and 2011 were identified in the Surveillance Epidemiology and End Results (SEER) database. Demographics, type of surgery, and clinicopathologic characteristics were collected. Survival functions were estimated by the Kaplan-Meier method, and log-rank test was used to assess the difference in overall survival (OS) among the three histologies. RESULTS: The SEER database yielded 1,021 TNET patients, 1,582 with GCC, and 534 SRCC patients. TNET presented at a younger age (p < 0.001). Patients with SRCC presented with advanced stage disease (p < 0.001). The median OS (mOS) for GCC and TNET patients was not reached; mOS for SRCC was 24 months. Multivariate analysis stratified for stage revealed significantly longer survival for TNET and GCC than SRCC (p < 0.001). CONCLUSION: This is the largest report to date for appendiceal neuroendocrine tumor patients, suggesting a spectrum of diseases with different characteristics and outcomes. In this report, we present a treatment approach for this complex spectrum of disease, based on the experience of Ohio State and Emory Universities investigators.
Appendiceal Neoplasms ; Carcinoid Tumor ; Demography ; Disease Management ; Epidemiology ; Goblet Cells ; Humans ; Multivariate Analysis ; Neuroendocrine Tumors ; Ohio ; Prognosis ; Prospective Studies ; Research Personnel