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Implementing an automated monitoring process in a digital, longitudinal observational cohort study
(2021)
Background: Clinical data collection requires correct and complete data sets in order to perform correct statistical analysis and draw valid conclusions. While in randomized clinical trials much effort concentrates on data monitoring, this is rarely the case in observational studies- due to high numbers of cases and often-restricted resources. We have developed a valid and cost-effective monitoring tool, which can substantially contribute to an increased data quality in observational research.
Methods: An automated digital monitoring system for cohort studies developed by the German Rheumatism Research Centre (DRFZ) was tested within the disease register RABBIT-SpA, a longitudinal observational study including patients with axial spondyloarthritis and psoriatic arthritis. Physicians and patients complete electronic case report forms (eCRF) twice a year for up to 10 years. Automatic plausibility checks were implemented to verify all data after entry into the eCRF. To identify conflicts that cannot be found by this approach, all possible conflicts were compiled into a catalog. This “conflict catalog” was used to create queries, which are displayed as part of the eCRF. The proportion of queried eCRFs and responses were analyzed by descriptive methods. For the analysis of responses, the type of conflict was assigned to either a single conflict only (affecting individual items) or a conflict that required the entire eCRF to be queried.
Results: Data from 1883 patients was analyzed. A total of n = 3145 eCRFs submitted between baseline (T0) and T3 (12 months) had conflicts (40–64%). Fifty-six to 100% of the queries regarding eCRFs that were completely missing were answered. A mean of 1.4 to 2.4 single conflicts occurred per eCRF, of which 59–69% were answered. The most common missing values were CRP, ESR, Schober’s test, data on systemic glucocorticoid therapy, and presence of enthesitis.
Conclusion: Providing high data quality in large observational cohort studies is a major challenge, which requires careful monitoring. An automated monitoring process was successfully implemented and well accepted by the study centers. Two thirds of the queries were answered with new data. While conventional manual monitoring is resource-intensive and may itself create new sources of errors, automated processes are a convenient way to augment data quality.
Objectives: Immune checkpoint inhibitors have become the standard of care for metastatic non–small-cell lung cancer (NSCLC) progressing during or after platinum-based chemotherapy. Real-world clinical practice tends to represent more diverse patient characteristics than randomized clinical trials. We sought to evaluate overall survival (OS) outcomes in the total study population and in key subsets of patients who received nivolumab for previously treated advanced NSCLC in real-world settings in France, Germany, or Canada.
Materials and methods: Data were pooled from two prospective observational cohort studies, EVIDENS and ENLARGE, and a retrospective registry in Canada. Patients included in this analysis were aged ≥18 years, had stage IIIB/IV NSCLC, and received nivolumab after at least one prior line of systemic therapy. OS was estimated in the pooled population and in various subgroups using the Kaplan-Meier method. Timing of data collection varied across cohorts (2015–2019).
Results: Of the 2585 patients included in this analyses, 1235 (47.8 %) were treated in France, 881 (34.1 %) in Germany, and 469 (18.1 %) in Canada. Median OS for the total study population was 11.3 months (95 % CI: 10.5–12.2); this was similar across France, Germany, and Canada. The OS rate was 49 % at 1 year and 28 % at 2 years for the total study population. In univariable Cox analyses, the presence of epidermal growth factor receptor mutations in nonsquamous disease, liver, or bone metastases were associated with significantly shorter OS, whereas tumor programmed death ligand 1 expression and Eastern Cooperative Oncology Group performance status 0–1 were associated with significantly prolonged OS. Similar OS was noted across subgroups of age and prior lines of therapy.
Conclusion: OS rates in patients receiving nivolumab for previously treated advanced NSCLC in real-world clinical practice closely mirrored those in phase 3 studies, suggesting similar effectiveness of nivolumab in clinical trials and clinical practice.
Background: In Germany, about 20% of the total population have a migration background. Differences exist between migrants and non-migrants in terms of health care access and utilisation. Colorectal cancer is the second most common malignant tumour in Germany, and incidence, staging and survival chances depend, amongst other things, on ethnicity and lifestyle. The current study investigates whether stage at diagnosis differs between migrants and non-migrants with colorectal cancer in an area of high migration and attempts to identify factors that can explain any differences.
Methods/Design: Data on tumour and migration status will be collected for 1,200 consecutive patients that have received a new, histologically verified diagnosis of colorectal cancer in a high migration area in Germany in the previous three months. The recruitment process is expected to take 16 months and will include gastroenterological private practices and certified centres for intestinal diseases. Descriptive and analytical analysis will be performed: the distribution of variables for migrants versus non-migrants and participants versus non-participants will be analysed using appropriate χ2-, t-, F- or Wilcoxon tests. Multivariable, logistic regression models will be performed, with the dependent variable being the dichotomized stage of the tumour (UICC stage I versus more advanced than UICC stage I). Odds ratios and associated 95%-confidence intervals will be calculated. Furthermore, ordered logistic regression models will be estimated, with the exact stage of the tumour at diagnosis as the dependent variable. Predictors used in the ordered logistic regression will be patient characteristics that are specific to migrants as well as patient characteristics that are not. Interaction models will be estimated in order to investigate whether the effects of patient characteristics on stage of tumour at the time of the initial diagnosis is different in migrants, compared to non-migrants.
Discussion: An association of migration status or other socioeconomic variables with stage at diagnosis of colorectal cancer would be an important finding with respect to equal health care access among migrants. It would point to access barriers or different symptom appraisal and, in the long term, could contribute to the development of new health care concepts for migrants.
Trial registration: German Clinical Trials Register DRKS00005056.