Optimizing drug selection from a prescription trajectory of one patient

Abstract It is unknown how sequential drug patterns convey information on a patient’s health status and treatment guidelines rarely account for this. Drug-agnostic longitudinal analyses of prescription trajectories in a population-wide setting are needed. In this cohort study, we used 24 years of data (1.1 billion prescriptions) from the Danish prescription registry to model the risk of sequentially redeeming a drug after another. Drug pairs were used to build multistep longitudinal prescription trajectories. These were subsequently used to stratify patients and calculate survival hazard ratios between the stratified groups. The similarity between prescription histories was used to determine individuals’ best treatment option. Over the course of 122 million person-years of observation, we identified 9 million common prescription trajectories and demonstrated their predictive power using hypertension as a case. Among patients treated with agents acting on the renin-angiotensin system we identified four groups: patients prescribed angiotensin converting enzyme (ACE) inhibitor without change, angiotensin receptor blockers (ARBs) without change, ACE with posterior change to ARB, and ARB posteriorly changed to ACE. In an adjusted time-to-event analysis, individuals treated with ACE compared to those treated with ARB had lower survival probability (hazard ratio, 0.73 [95% CI, 0.64–0.82]; P < 1 × 10−16). Replication in UK Biobank data showed the same trends. Prescription trajectories can provide novel insights into how individuals’ drug use change over time, identify suboptimal or futile prescriptions and suggest initial treatments different from first line therapies. Observations of this kind may also be important when updating treatment guidelines

Mapping of truncated O-glycans in cancers of epithelial and non-epithelial origin

BACKGROUND: Novel immunotherapies targeting cancer-associated truncated O-glycans Tn (GalNAcα-Ser/Thr) and STn (Neu5Acα2–6GalNacα-Ser/Thr) are promising strategies for cancer treatment. However, no comprehensive, antibody-based mapping of truncated O-glycans in tumours exist to guide drug development. METHODS: We used monoclonal antibodies to map the expression of truncated O-glycans in >700 tissue cores representing healthy and tumour tissues originating from breast, colon, lung, pancreas, skin, CNS and mesenchymal tissue. Patient-derived xenografts were used to evaluate Tn expression upon tumour engraftment. RESULTS: The Tn-antigen was highly expressed in breast (57%, n = 64), colorectal (51%, n = 140) and pancreatic (53%, n = 108) tumours, while STn was mainly observed in colorectal (80%, n = 140) and pancreatic (56%, n = 108) tumours. We observed no truncated O-glycans in mesenchymal tumours (n = 32) and low expression of Tn (5%, n = 87) and STn (1%, n = 75) in CNS tumours. No Tn-antigen was found in normal tissue (n = 124) while STn was occasionally observed in healthy gastrointestinal tissue. Surface expression of Tn-antigen was identified across several cancers. Tn and STn expression decreased with tumour grade, but not with cancer stage. Numerous xenografts maintained Tn expression. CONCLUSIONS: Surface expression of truncated O-glycans is limited to cancers of epithelial origin, making Tn and STn attractive immunological targets in the treatment of human carcinomas