Validation of an algorithm that determines stroke diagnostic code accuracy in a Japanese hospital-based cancer registry using electronic medical records

Additive association of blood pressure and short stature with stroke incidence in 450,000 Japanese adults: the Shizuoka study

Short stature was suggested to be a risk factor for cardiovascular events. Because short stature increases central blood pressure, this study aimed to investigate a longitudinal association between short stature, blood pressure, and incidence of cardiovascular disease by the analysis of insurance-based real-world dataset. We analyzed data from 463,844 adults aged 40 or older with a mean age of 66.7 enrolled in National Health Insurance, excluding individuals who experienced a stroke or myocardial infarction, or required long-term care. Data from annual health checkups were used to obtain baseline clinical information. Comorbidities and incidences of stroke and myocardial infarction were obtained from the insurance data. During a 5.5-year follow-up period, we observed 11,027 cases of stroke. Adults of a short stature exhibited a higher incidence rate in both men (≤155 cm: 99.7, >175 cm: 24.4) and women (≤140 cm: 85.9, >160 cm: 13.7). Although those in the short stature group had higher blood pressure, and often took antihypertensive drugs, the inverse association between height and stroke incidence was independent of these factors (hazard ratio for 5 cm shorter in height; men: 1.06 [1.03-1.09], women: 1.11 [1.06-1.13]). Short stature and blood pressure showed additive association with stoke incidence (log-rank p < 0.001). No significant association was observed with myocardial infarction (men: 1.01 [0.95-1.06], women: 1.06 [0.98-1.14]). In a longitudinal analysis of a large general Japanese population, short stature was linked to an increased risk of stroke in both genders in any blood pressure range.

Driver gene KRAS aggravates cancer-associated stroke outcomes

The incidence of cancer-associated stroke has increased with the prolonged survival times of cancer patients. Recent genetic studies have led to progress in cancer therapeutics, but relationships between oncogenic mutations and stroke remain elusive. Here, we focused on the driver gene KRAS, which is the predominant RAS isoform mutated in multiple cancer types, in cancer associated stroke study. KRASG13D/- and parental human colorectal carcinoma HCT116 cells were inoculated into mice that were then subjected to a photochemically-induced thrombosis model to establish ischemic stroke. We found that cancer inoculation exacerbated neurological deficits after stroke. Moreover, mice inoculated with KRASG13D/- cells showed worse neurological deficits after stroke compared with mice inoculated with parental cells. Stroke promoted tumor growth, and the KRASG13D/- allele enhanced this growth. Brain RNA sequencing analysis and serum ELISA showed that chemokines and cytokines mediating pro-inflammatory responses were upregulated in mice inoculated with KRASG13D/- cells compared with those inoculated with parental cells. STAT3 phosphorylation was promoted following ischemic stroke in the KRASG13D/- group compared with in the parental group, and STAT3 inhibition significantly ameliorated stroke outcomes by mitigating microglia/macrophage polarization. Finally, we compared the prognosis and mortality of colorectal cancer patients with or without stroke onset between 1 January 2007 and 31 December 2020 using a hospital-based cancer registry and found that colorectal cancer patients with stroke onset within 3 months after cancer diagnosis had a worse prognosis. Our work suggests an interplay between KRAS and ischemic stroke that may offer insight into future treatments for cancer-associated stroke.

Status of screening and preventive efforts against diabetic kidney disease between 2013 and 2018: analysis using an administrative database from Kyoto-city, Japan

Background

Japan has the second highest prevalence of dialysis use in the world. Approximately 40% of patients who begin dialysis have diabetic kidney disease (DKD). Local governments and medical facilities are required to provide preventive measures against worsening diabetes mellitus (DM). However, the percentage of patients with DM who receive such screening or interventions for DKD is unclear. This study aimed to reveal to what extent screening for DKD and preventive measures against worsening DKD are performed in patients with DM, using an administrative database in a municipality.

Methods

This was a cross-sectional study that used the Kyoto-city's administrative medical and long-term care database. Patients with a diagnosis of DM and receiving antidiabetic medication between 2013 and 2018 were defined as patients with DM and included. Patients with DKD were defined as those diagnosed with diabetic nephropathy or those with chronic kidney disease. We described the characteristics of patients with DM, diabetic complications, and extent of DKD screenings and preventive efforts against worsening of DM by fiscal year.

Results

Across fiscal years, 25.8% to 27.5% of patient with DM had DKD. More than 3% of patients were on dialysis due DM in each fiscal year; approximately 15% started receiving dialysis that year. The percentage of patients who were regularly prescribed antidiabetic medication and received glycosylated hemoglobin testing ranged from 64.0% to 67.2% and from 30.6% to 36.5%, respectively. Urine microalbuminuria testing at least once a year occurred in 9.3% to 10.0%. The percentage of patients who received nutritional guidance ranged from 19.0% to 21.0%. Approximately 1% of patients received guidance for preventing DM from progressing to a disease that requires dialysis each fiscal year.

Conclusion

This study from Japan, where a super-aging society has developed, using an administrative database in a municipality covering most of the elderly population clearly demonstrated an evidence-practice gap in efforts to prevent worsening of DKD. Strengthening cooperation between government and medical facilities and support for providing preventive measures against DKD are urgently needed.

Survival and medical costs of non-small cell lung cancer patients according to the first-line treatment: An observational study using the Kyoto City Integrated Database

BACKGROUND

Lung cancer is the primary cause of cancer mortality and non-small cell lung cancer (NSCLC) accounts for the majority of lung cancer cases. New drug treatments have been developed since 2010 but there are concerns about the increase in medical costs. This study aimed to compare survival and medical costs among patients with NSCLC according to their initial treatment to estimate the impact of early NSCLC detection.

METHODS

Patients with primary NSCLC who filed insurance claims between April 2013 and March 2019 were identified using the Kyoto City Integrated Database. Patients were divided into two groups depending on their initial treatment: the resection group and drug or radiation group. The survival and medical costs were calculated.

RESULTS

A total of 2609 patients with primary NSCLC were identified. Among them, 1035 patients underwent resection. The 5-year survival was 75% for the resection group while below 25% for the drug or radiation group. At 6 months of survival, the median cumulative total cost was 2409 thousand yen (interquartile range [IQR] 1947-4012 thousand yen) in the resection group and 2951 thousand yen (IQR 1600-4706 thousand yen) in the drug or radiation group. At 4 years of survival, the cumulative median total cost was 5257 thousand yen (IQR 3808-8243 thousand yen) in the resection group and 10 202 thousand yen (IQR 4845-20 450 thousand yen) in the drug or radiation group.

CONCLUSIONS

As a first-line therapy in newly diagnosed patients with NSCLC, surgical resection is associated with longer survival and lower medical costs than pharmacotherapy or radiotherapy.

Temporal Trend in an Initial Treatment, Survival, and Medical Costs Among Patients With Lung Cancer Between 2013 and 2018 in Kyoto City, Japan

OBJECTIVES

This study aimed to identify the variation of treatment contents and outcomes and economic burden of lung cancer among the elderly population in Japan.

METHODS

New-onset primary lung cancer from April 2013 to March 2019 were identified by using the Kyoto City administrative database for National Health Insurance and Advanced Elderly Medical Service System. Patient characteristics, initial treatment, medical costs, and deaths were analyzed. Continuous variables were calculated using standard descriptive statistical methods.

RESULTS

A total of 4845 people who were diagnosed as having lung cancer and received any treatment between 2013 and 2018 were included in the study. The average age of patients was 73 to 74 years for a 6-year study period. The proportion of patients who received surgery, drug therapy, and radiation therapy as initial treatment was 31% to 42%, 36% to 44%, and 21% to 24%, respectively. Healthcare costs increased between fiscal year (FY) 2014 and FY 2018, with a particularly significant increase of 340 million for drug therapy, whereas the mortality rate in <2-year follow-up decreased from 42.7% in FY 2013 to 368% in FY 2016.

CONCLUSIONS

This cross-sectional study demonstrated that the improvement in the survival rate and proportion of surgery as an initial treatment was increased whereas drug therapy decreased and medical costs increased among patients with lung cancer over time. Based on these results, it is necessary to implement sustainable healthcare measures with a consideration of cost-effectiveness.

Large-scale evidence generation and evaluation across a network of databases for type 2 diabetes mellitus (LEGEND-T2DM): a protocol for a series of multinational, real-world comparative cardiovascular effectiveness and safety studies

INTRODUCTION

Therapeutic options for type 2 diabetes mellitus (T2DM) have expanded over the last decade with the emergence of cardioprotective novel agents, but without such data for older drugs, leaving a critical gap in our understanding of the relative effects of T2DM agents on cardiovascular risk.

METHODS AND ANALYSIS

The large-scale evidence generations across a network of databases for T2DM (LEGEND-T2DM) initiative is a series of systematic, large-scale, multinational, real-world comparative cardiovascular effectiveness and safety studies of all four major second-line anti-hyperglycaemic agents, including sodium-glucose co-transporter-2 inhibitor, glucagon-like peptide-1 receptor agonist, dipeptidyl peptidase-4 inhibitor and sulfonylureas. LEGEND-T2DM will leverage the Observational Health Data Sciences and Informatics (OHDSI) community that provides access to a global network of administrative claims and electronic health record data sources, representing 190 million patients in the USA and about 50 million internationally. LEGEND-T2DM will identify all adult, patients with T2DM who newly initiate a traditionally second-line T2DM agent. Using an active comparator, new-user cohort design, LEGEND-T2DM will execute all pairwise class-versus-class and drug-versus-drug comparisons in each data source, producing extensive study diagnostics that assess reliability and generalisability through cohort balance and equipoise to examine the relative risk of cardiovascular and safety outcomes. The primary cardiovascular outcomes include a composite of major adverse cardiovascular events and a series of safety outcomes. The study will pursue data-driven, large-scale propensity adjustment for measured confounding, a large set of negative control outcome experiments to address unmeasured and systematic bias.

ETHICS AND DISSEMINATION

The study ensures data safety through a federated analytic approach and follows research best practices, including prespecification and full disclosure of results. LEGEND-T2DM is dedicated to open science and transparency and will publicly share all analytic code from reproducible cohort definitions through turn-key software, enabling other research groups to leverage our methods, data and results to verify and extend our findings.

High neutrophil/lymphocyte ratio at cancer diagnosis predicts incidence of stroke in cancer patients

Although cancer increases the incidence and severity of ischaemic stroke, there is no reliable method for predicting ischaemic stroke in cancer patients. To evaluate the prognostic capacity of the neutrophil-to-lymphocyte ratio at cancer diagnosis for predicting the incidence of ischaemic stroke, we used a hospital-based cancer registry that contained clinical data from all patients treated for cancer at Osaka University Hospital between 2007 and 2015. The neutrophil-to-lymphocyte ratio was calculated after dividing absolute neutrophil counts by absolute lymphocyte counts. These counts were obtained within 1 month after cancer diagnosis. The primary endpoint was new-onset ischaemic stroke within 2 years after cancer diagnosis. Of the 18 217 included cancer patients (median age: 65.2 years), 69 (0.38%) had ischaemic stroke. Unadjusted Cox regression analysis stratified by cancer site demonstrated that each 1-unit increase in the neutrophil-to-lymphocyte ratio was associated with a significant 7.2% increase in the risk of an ischaemic stroke event (95% confidence interval 1.041–1.103, P < 0.001). Survival tree analysis and the Kaplan–Meier method suggested that patients with and without atrial fibrillation who had increased neutrophil-to-lymphocyte ratios had a higher risk of ischaemic stroke. Multivariate Cox proportional hazard models, adjusted for cancer site and stage, revealed that patients with high neutrophil-to-lymphocyte ratios (>15) had higher ischaemic stroke risk than patients with low neutrophil-to-lymphocyte ratios (<5). This was true among cancer patients both with (hazard ratio 11.598; 95% confidence interval 0.953–141.181) and without (hazard ratio 7.877; 95% confidence interval 2.351–26.389) atrial fibrillation. The neutrophil-to-lymphocyte ratio at cancer diagnosis is associated with the incidence of ischaemic stroke among cancer patients and might thus be useful for identifying patients at high risk of ischaemic stroke, allowing us to guide future preventive interventions.

Validation of Acute Myocardial Infarction and Heart Failure Diagnoses in Hospitalized Patients With the Nationwide Claim-Based JROAD-DPC Database

Background: Big data systems such as diagnosis procedure combination (DPC) datasets have recently been used for research purposes. However, there have been few validation studies to determine the accuracy of diagnoses. The aim of this study was to validate and evaluate 2 diagnoses, namely acute myocardial infarction (AMI) and heart failure (HF), using International Classification of Diseases, 10th revision (ICD-10) codes in the Japanese Registry Of All cardiac and vascular Disease (JROAD)-DPC database.

Methods and Results: ICD-10 codes I21.0–I21.9 and I50.0–I50.9 were used to identify AMI and HF, respectively, in the JROAD-DPC database. Diagnoses of AMI and HF were validated in clinical datasets assessing sensitivity and positive predictive value (PPV). Over 1–2 years, 742 patients hospitalized for AMI and 1,368 patients hospitalized for HF were identified in the DPC dataset. Sensitivity and PPV for AMI were 78.9% and 78.8%, respectively. When emergency hospitalization was included as a criterion, PPV increased to 84.9%. For HF, sensitivity and PPV were 84.7% and 57.0%, respectively. When emergency hospitalization and acute HF were included as criteria, PPV increased to 83.0%.

Conclusions: Using ICD-10 codes for AMI and HF diagnoses among hospitalized patients, the DPC dataset showed acceptable concordance with clinical datasets. PPV increased when any conditions of hospitalization were included, especially in HF.

Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review

Background

Electronic medical records (EMRs) contain large amounts of rich clinical information. Developing EMR-based case definitions, also known as EMR phenotyping, is an active area of research that has implications for epidemiology, clinical care, and health services research.

Objective

This review aims to describe and assess the present landscape of EMR-based case phenotyping for the Charlson conditions.

Methods

A scoping review of EMR-based algorithms for defining the Charlson comorbidity index conditions was completed. This study covered articles published between January 2000 and April 2020, both inclusive. Embase (Excerpta Medica database) and MEDLINE (Medical Literature Analysis and Retrieval System Online) were searched using keywords developed in the following 3 domains: terms related to EMR, terms related to case finding, and disease-specific terms. The manuscript follows the Preferred Reporting Items for Systematic reviews and Meta-analyses extension for Scoping Reviews (PRISMA) guidelines.

Results

A total of 274 articles representing 299 algorithms were assessed and summarized. Most studies were undertaken in the United States (181/299, 60.5%), followed by the United Kingdom (42/299, 14.0%) and Canada (15/299, 5.0%). These algorithms were mostly developed either in primary care (103/299, 34.4%) or inpatient (168/299, 56.2%) settings. Diabetes, congestive heart failure, myocardial infarction, and rheumatology had the highest number of developed algorithms. Data-driven and clinical rule–based approaches have been identified. EMR-based phenotype and algorithm development reflect the data access allowed by respective health systems, and algorithms vary in their performance.

Conclusions

Recognizing similarities and differences in health systems, data collection strategies, extraction, data release protocols, and existing clinical pathways is critical to algorithm development strategies. Several strategies to assist with phenotype-based case definitions have been proposed.

Monte Carlo Simulations Demonstrate Algorithmic Interventions Over Time Reduce Hospitalisation in Patients With Schizophrenia and Bipolar Disorder

Non-adherence with pharmacologic treatment is associated with increased rates of relapse and rehospitalisation among patients with schizophrenia and bipolar disorder. To improve treatment response, remission, and recovery, research efforts are still needed to elucidate how to effectively map patient’s response to medication treatment including both therapeutic and adverse effects, compliance, and satisfaction in the prodromal phase of illness (ie, the time period in between direct clinical consultation and relapse). The Actionable Intime Insights (AI²) application draws information from Australian Medicare administrative claims records in real time when compliance with treatment does not meet best practice guidelines for managing chronic severe mental illness. Subsequently, the AI² application alerts clinicians and patients when patients do not adhere to guidelines for treatment. The aim of this study was to evaluate the impact of the AI² application on the risk of hospitalisation among simulated patients with schizophrenia and bipolar disorder. Monte Carlo simulation methodology was used to estimate the impact of the AI² intervention on the probability of hospitalisation over a 2-year period. Results indicated that when the AI² algorithmic intervention had an efficacy level of (>0.6), over 80% of actioned alerts were contributing to reduced hospitalisation risk among the simulated patients. Such findings indicate the potential utility of the AI² application should replication studies validate its methodologic and ecological rigour in real-world settings.