Objectives: To characterize treatment patterns and survival outcomes for patients with locally advanced or metastatic malignancy of the urothelial tract during a period immediately preceding the widespread use of immune checkpoint inhibitors in the UK. Patients and Methods:We retrospectively examined the electronic case notes of patients attending the Leeds Cancer Center, UK with locally advanced or metastatic urothelial carcinoma, receiving chemotherapy between January 2003 and March 2017. Patient characteristics, treatment patterns, and outcomes were collected. Summary and descriptive statistics were calculated for categorical and continuous variables as appropriate. The Kaplan-Meier method was used to estimate median survival and Cox regression proportional hazards model was used to explore relationships between clinical variables and outcome.Results: Two hundred and sixteen patients made up the study cohort, with a median age of 66 years (range: 35-83) and 72.7% being male. First-line treatment consisted of either a cisplatin-(44%) or carboplatin-based regimen (48%) in the majority of patients. Twenty seven percent of patients received a second-line of treatment (most commonly single-agent paclitaxel) following a first-line platinum containing regimen. Grade 4 neutropenia was observed in 19 and 27% of those treated with a first-line cisplatin-and carboplatin-based regimen, respectively. The median overall survival (mOS) of the study cohort was estimated to be 16.2 months (IQR: 10.6-28.3 months). Receipt by patients of cisplatin-based chemotherapy was associated with a longer mOS and this association persisted when survival analysis was adjusted for age, sex, performance status and presence of distant metastases. Conclusions:This study provides a useful benchmark for outcomes achieved in a real-world setting for patients with locally advanced or metastatic UC treated with chemotherapy in the immediate pre-immunotherapy era.

An understudied challenge within process mining is the area of process change over time. This is a particular concern in healthcare, where patterns of care emerge and evolve in response to individual patient needs and through complex interactions between people, process, technology and changing organisational structure. We propose a structured approach to analyse process change over time suitable for the complex domain of healthcare. Our approach applies a qualitative process comparison at three levels of abstraction: a holistic perspective summarizing patient pathways (process model level), a middle level perspective based on activity sequences for individuals (trace level), and a fine-grained detail focus on activities (activity level). Our aim is to identify points in time where a process changed (detection), to localise and characterise the change (localisation and characterisation), and to understand process evolution (unravelling). We illustrate the approach using a case study of cancer pathways in Leeds Cancer Centre where we found evidence of agreement in process change identified at the process model and activity levels, but not at the trace level. In the experiment we show that this qualitative approach provides a useful understanding of process change over time. Examining change at the three levels provides confirmatory evidence of process change where perspectives agree, while contradictory evidence can lead to focused discussions with domain experts. The approach should be of interest to others dealing with processes that undergo complex change over time.

Background The use of linked healthcare data in research has the potential to make major contributions to knowledge generation and service improvement. However, using healthcare data for secondary purposes raises legal and ethical concerns relating to confidentiality, privacy and data protection rights. Using a linkage and anonymisation approach that processes data lawfully and in line with ethical best practice to create an anonymous (non-personal) dataset can address these concerns, yet there is no set approach for defining all of the steps involved in such data flow end-to-end. We aimed to define such an approach with clear steps for dataset creation, and to describe its utilisation in a case study linking healthcare data. Methods We developed a data flow protocol that generates pseudonymous datasets that can be reversibly linked, or irreversibly linked to form an anonymous research dataset. It was designed and implemented by the Comprehensive Patient Records (CPR) study in Leeds, UK. Results We defined a clear approach that received ethico-legal approval for use in creating an anonymous research dataset. Our approach used individual-level linkage through a mechanism that is not computer-intensive and was rendered irreversible to both data providers and processors. We successfully applied it in the CPR study to hospital and general practice and community electronic health record data from two providers, along with patient reported outcomes, for 365,193 patients. The resultant anonymous research dataset is available via DATA-CAN, the Health Data Research Hub for Cancer in the UK. Conclusions Through ethical, legal and academic review, we believe that we contribute a defined approach that represents a framework that exceeds current minimum standards for effective pseudonymisation and anonymisation. This paper describes our methods and provides supporting information to facilitate the use of this approach in research.