Assessment and Improvement of Drug Data Structuredness From Electronic Health Records: Algorithm Development and Validation.

BACKGROUND: Digitization offers a multitude of opportunities to gain insights into current diagnostics and therapies from retrospective data. In this context, real-world data and their accessibility are of increasing importance to support unbiased and reliable research on big data. However, routinely collected data are not readily usable for research owing to the unstructured nature of health care systems and a lack of interoperability between these systems. This challenge is evident in drug data. OBJECTIVE: This study aimed to present an approach that identifies and increases the structuredness of drug data while ensuring standardization according to Anatomical Therapeutic Chemical (ATC) classification. METHODS: Our approach was based on available drug prescriptions and a drug catalog and consisted of 4 steps. First, we performed an initial analysis of the structuredness of local drug data to define a point of comparison for the effectiveness of the overall approach. Second, we applied 3 algorithms to unstructured data that translated text into ATC codes based on string comparisons in terms of ingredients and product names and performed similarity comparisons based on Levenshtein distance. Third, we validated the results of the 3 algorithms with expert knowledge based on the 1000 most frequently used prescription texts. Fourth, we performed a final validation to determine the increased degree of structuredness. RESULTS: Initially, 47.73% (n=843,980) of 1,768,153 drug prescriptions were classified as structured. With the application of the 3 algorithms, we were able to increase the degree of structuredness to 85.18% (n=1,506,059) based on the 1000 most frequent medication prescriptions. In this regard, the combination of algorithms 1, 2, and 3 resulted in a correctness level of 100% (with 57,264 ATC codes identified), algorithms 1 and 3 resulted in 99.6% (with 152,404 codes identified), and algorithms 1 and 2 resulted in 95.9% (with 39,472 codes identified). CONCLUSIONS: As shown in the first analysis steps of our approach, the availability of a product catalog to select during the documentation process is not sufficient to generate structured data. Our 4-step approach reduces the problems and reliably increases the structuredness automatically. Similarity matching shows promising results, particularly for entries with no connection to a product catalog. However, further enhancement of the correctness of such a similarity matching algorithm needs to be investigated in future work.

Implementation and Effectiveness of Novel Therapeutic Substances for Advanced Malignant Melanoma in Saxony, Germany, 2010-2020-Cohort Study Based on Administrative Data.

(1) Background: Targeted (TT) and immune checkpoint inhibitor (ICI) therapies have become available in the routine care of metastatic melanoma in recent years. (2) Objective: We compared mortality in patients with metastatic melanoma and different systemic therapies. (3) Methods: A retrospective cohort study, based on pseudonymized health insurance data of about two million individuals from Saxony, Germany, was conducted for the years 2010 to 2020. Only patients with an advanced stage, i.e., distant metastases were considered for the main analysis. Relative survival since metastasis and predicted survivor curves derived from a Cox model were used to assess potential differences in mortality. (4) Results: Relative survival was highest in the subgroup with sequential use of ICI and TT. All treatments except interferon had significant hazard ratios (HR) in the Cox model with time-dependent effects indicating a protective effect after treatment initiation (HR 0.01-0.146) but decreasing over time (HR 1.351-2.310). The predicted survivor curves revealed best survival under ICI-TT treatment and worst survival under TT treatment alone. (5) Conclusions: We found real-world evidence for survival benefits of patients with metastatic melanoma who received sequential ICI and TT treatment. It is conceivable that the observed high survival differences were overestimated due to bias, such as confounding by indication.

Analysis of secondary care data to evaluate the clinical relevance of the drug-drug interaction between amlodipine and simvastatin.

BACKGROUND: Pharmacokinetic analyses revealed an increase in the bioavailability of simvastatin when co-administered with amlodipine [Nishio S et al. Hypertensin research 2005; Son H et al. Drug metabolism and pharmacokinetics 2014]. This may induce an increased risk of muscle toxicity for patients who receive this combination. So far, no in vivo data on the clinical relevance of this interaction exist. The objective of the present analysis was to determine the number of patients with concomitant treatment of amlodipine and simvastatin. Subsequently, the data was analyzed for the indication of muscular discomfort. Patients with combined prescription of amlodipine and another hydroxymethylglutaryl-CoA-reductase inhibitor except simvastatin or patients receiving simvastatin without amlodipine served as control groups. METHODS: The present analysis used secondary data from the health insurance company AOK PLUS including information regarding diagnosis and drug prescriptions. RESULTS: In total, 67.081 patients corresponding to 4.93% of the analyzed collective received a combined prescription of amlodipine and simvastatin. The absolute frequency increased continuously over time. Muscular discomfort was detected in a) 6.20% of the patients receiving amlodipine and simvastatin, b) 6.60% of the patients receiving amlodipine and another hydroxymethylglutaryl-CoA- reductase inhibitor and c) 8.04% of the patients with simvastatin only. CONCLUSIONS: The present analysis shows an increasing trend of combined prescriptions of amlodipine and simvastatin. Evidence for simvastatin dose adaptation or therapy switch to another hydroxymethylglutaryl-CoA-reductase inhibitor, however, was not found. Muscular discomfort does not occur more often in patients with amlodipine and simvastatin compared to the two control groups. The results of the present analysis reveal no evidence for a clinically relevant interaction between amlodipine and simvastatin.

Impact of altered endogenous IgG on unspecific mAb clearance.

Immunodeficient mice are crucial models to evaluate the efficacy of monoclonal antibodies (mAbs). When studying mAb pharmacokinetics (PK), protection from elimination by binding to the neonatal Fc receptor (FcRn) is known to be a major process influencing the unspecific clearance of endogenous and therapeutic IgG. The concentration of endogenous IgG in immunodeficient mice, however is reduced, and this effect on the FcRn protection mechanism and subsequently on unspecific mAb clearance is unknown, yet of great importance for the interpretation of mAb PK data. We used a PBPK modelling approach to elucidate the influence of altered endogenous IgG concentrations on unspecific mAb clearance. To this end, we used PK data in immunodeficient mice, i.e. nude and severe combined immunodeficiency mice. To avoid impact of target-mediated clearance processes, we focussed on mAbs without affinity to a target antigen in these mice. In addition, intravenous immunoglobulin (IVIG) data of immunocompetent mice was used to study the impact of increased total IgG concentrations on unspecific therapeutic antibody clearance. The unspecific clearance is linear, whenever therapeutic IgG concentrations, i.e. mAb and IVIG concentrations are lower than FcRn; it can be non-linear if therapeutic IgG concentrations are larger than FcRn and endogenous IgG concentrations (e.g., under IVIG therapy). Unspecific mAb clearance of immunodeficient mice is effectively linear (under mAb doses as typically used in human). Studying the impact of reduced endogenous IgG concentrations on unspecific mAb clearance is of great relevance for the extrapolation to clinical species, e.g., when predicting mAb PK in immunosuppressed cancer patients.