We present the Danish Disease Trajectory Browser (DTB), a tool for exploring almost 25 years of data from the Danish National Patient Register. In the dataset comprising 7.2 million patients and 122 million admissions, users can identify diagnosis pairs with statistically significant directionality and combine them to linear disease trajectories. Users can search for one or more disease codes (ICD-10 classification) and explore disease progression patterns via an array of functionalities. For example, a set of linear trajectories can be merged into a disease trajectory network displaying the entire multimorbidity spectrum of a disease in a single connected graph. Using data from the Danish Register for Causes of Death mortality is also included. The tool is disease-agnostic across both rare and common diseases and is showcased by exploring multimorbidity in Down syndrome (ICD-10 code Q90) and hypertension (ICD-10 code I10). Finally, we show how search results can be customized and exported from the browser in a format of choice (i.e. JSON, PNG, JPEG and CSV).

PURPOSE To evaluate the clinical benefit of nivolumab with or without ipilimumab in combination with stereotactic body radiotherapy (SBRT) in patients with refractory metastatic pancreatic cancer (mPC). METHODS Between November 2016 and December 2019, patients with refractory mPC were randomly assigned 1:1 to SBRT of 15 Gy with nivolumab or nivolumab/ipilimumab stratified by performance status (ClinicalTrials.gov identifier: NCT02866383 ). The primary end point was the clinical benefit rate (CBR), defined as the percentage of patients with complete or partial response (PR) or stable disease, according to RECIST 1.1. Simon's 2-stage phase II optimal design was used independently for both arms, with CBR determining expansion to the second stage. Secondary end points included safety, response rate, duration of response, progression-free survival, and overall survival. Exploratory analyses included biomarkers related to the benefits. RESULTS Eighty-four patients (41 SBRT/nivolumab and 43 SBRT/nivolumab/ipilimumab) received at least one dose of study treatment. CBR was 17.1% (8.0 to 30.6) for patients receiving SBRT/nivolumab and 37.2% (24.0 to 52.1) for SBRT/nivolumab/ipilimumab. PR was observed in one patient receiving SBRT/nivolumab and lasted for 4.6 months. Six patients receiving SBRT/nivolumab/ipilimumab achieved a PR with a median duration of response of 5.4 months (4.2 to not reached). Grade 3 or higher treatment-related adverse events occurred in 10 (24.4%) and 13 (30.2%) patients in the SBRT/nivolumab and SBRT/nivolumab/ipilimumab groups, respectively. Programmed cell death ligand-1 expression by tumor proportion score or combined positivity score of ≥ 1% was not associated with clinical benefits. On-treatment decreased serum interleukin-6, interleukin-8, and C-reactive protein levels were associated with better overall survival. CONCLUSION Clinically meaningful antitumor activity and favorable safety profiles were demonstrated after treatment with SBRT/nivolumab/ipilimumab in patients with refractory mPC. However, the contribution from SBRT is unknown. Further studies are warranted.

Pancreatic cancer is an aggressive disease that typically presents late with poor outcomes, indicating a pronounced need for early detection. In this study, we applied artificial intelligence methods to clinical data from 6 million patients (24,000 pancreatic cancer cases) in Denmark (Danish National Patient Registry (DNPR)) and from 3 million patients (3,900 cases) in the United States (US Veterans Affairs (US-VA)). We trained machine learning models on the sequence of disease codes in clinical histories and tested prediction of cancer occurrence within incremental time windows (CancerRiskNet). For cancer occurrence within 36 months, the performance of the best DNPR model has area under the receiver operating characteristic (AUROC) curve = 0.88 and decreases to AUROC (3m) = 0.83 when disease events within 3 months before cancer diagnosis are excluded from training, with an estimated relative risk of 59 for 1,000 highest-risk patients older than age 50 years. Cross-application of the Danish model to US-VA data had lower performance (AUROC = 0.71), and retraining was needed to improve performance (AUROC = 0.78, AUROC (3m) = 0.76). These results improve the ability to design realistic surveillance programs for patients at elevated risk, potentially benefiting lifespan and quality of life by early detection of this aggressive cancer.