Dataset Information

ORIHIME study: real-world treatment patterns and clinical outcomes of 338 patients with acquired hemophilia A from a Japanese administrative database.

ABSTRACT:

Background

Acquired hemophilia A (AHA) is a rare disorder, and clinical practices for treating AHA have not been fully clarified in Japan.

Objectives

This study aims to investigate the epidemiology of AHA and real-world treatment practices in Japan.

Patients/methods

This observational study was based on a health administrative database of hospitalized patients diagnosed with AHA who were treated with immunosuppressants.

Results

The study included 214 males and 124 females (mean age 75.7 years). The most frequently used bypassing agent was recombinant activated factor VII. The predominant choice of immunosuppressant for first-line treatment was steroid monotherapy. Median days from the index date to the start of rehabilitation was 65.0 for cardiovascular, 35.5 for respiratory and 23.0 for locomotor. The proportion of patients with an activities of daily living (ADL) score < 70 points was high at both first admission and final discharge (47.4% and 38.8%). The percentage of deaths during hospitalization was 18.6%.

Conclusions

This study clarified the treatment patterns and clinical outcomes of AHA in a large population in Japan. This was the first study showing ADL score distribution and time to rehabilitation. Further investigation is needed to develop better clinical practices for treatment of AHA.

SUBMITTER: Ogawa Y

PROVIDER: S-EPMC9813148 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

ORIHIME study: real-world treatment patterns and clinical outcomes of 338 patients with acquired hemophilia A from a Japanese administrative database.

Ogawa Yoshiyuki Y Amano Kagehiro K Matsuo-Tezuka Yukari Y Okada Norihiro N Murakami Yoichi Y Nakamura Takao T Yamaguchi-Suita Haruko H Nogami Keiji K

International journal of hematology 20221104 1

<h4>Background</h4>Acquired hemophilia A (AHA) is a rare disorder, and clinical practices for treating AHA have not been fully clarified in Japan.<h4>Objectives</h4>This study aims to investigate the epidemiology of AHA and real-world treatment practices in Japan.<h4>Patients/methods</h4>This observational study was based on a health administrative database of hospitalized patients diagnosed with AHA who were treated with immunosuppressants.<h4>Results</h4>The study included 214 males and 124 fe ...[more]

PMID: 36331704

Similar Datasets

Project description:Health records of patients hospitalized for osteoporotic fracture were analyzed. Prior to the index hospital admission, most patients were not receiving any antiosteoporotic treatment. During the index hospitalization visit, 25.5% of patients received antiosteoporotic treatment. The most common treatment regimens were active vitamin D3, bisphosphonates, and teriparatide.PurposeTo examine the real-world treatment patterns and factors associated with receipt of treatment among Japanese patients with osteoporotic fracture.MethodsWe retrospectively analyzed health records of patients who were hospitalized for osteoporotic fracture between February 2016 and February 2018 in Japan. The type and duration of treatment with antiosteoporotic medications prescribed during hospital stays and after discharge were examined using descriptive statistics. Demographic and clinical factors (e.g., age, previous diagnoses, Charlson Comorbidity Index scores) associated with osteoporotic treatment were explored using multivariable logistic regression.ResultsA total of 112,275 patient medical records were evaluated, including 56,574 records from patients with hip fracture, 26,681 records from patients with vertebrae fracture, and 29,020 patients with non-vertebral non-hip fractures. Prior to the index hospital admission, most patients (91.7%, n = 102,919) were not receiving any antiosteoporotic treatment. For those receiving treatment, active vitamin D3 (51.1%, n = 4778) and bisphosphonates (47.5%, n = 4441) were the most common. During the index hospitalization visit, 25.5% (n = 28,678) of patients received treatment for their fracture, including active vitamin D3 (n = 17,074), bisphosphonates (n = 10,007), and teriparatide (n = 4561). Upon discharge, 41.5% (n = 46,536) of patients returned to their home and 34.3% (n = 38,542) of patients were transferred to a different hospital or medical care facility. Variables associated with receipt of treatment at follow-up included older age, previous diagnoses of osteoporosis and fracture, and higher Charlson Comorbidity Index scores.ConclusionDespite osteoporotic fracture being a major health concern within older Japanese populations, treatment with antiosteoporotic medication regimens remains generally low.

Project description:IntroductionAdministrative claims data provide an important source for real-world evidence (RWE) generation, but incomplete reporting, such as for body mass index (BMI), limits the sample sizes that can be analyzed to address certain research questions. The objective of this study was to construct models by implementing machine-learning (ML) algorithms to predict BMI classifications (≥ 30, ≥ 35, and ≥ 40 kg/m2) in administrative healthcare claims databases, and then internally and externally validate them.MethodsFive advanced ML algorithms were implemented for each BMI classification on a random sampling of BMI readings from the Optum PanTher Electronic Health Record database (2%) and the Optum Clinformatics Date of Death (20%) database, while incorporating baseline demographic and clinical characteristics. Sensitivity analyses with oversampling ratios were conducted. Model performance was validated internally and externally.ResultsModels trained on the Super Learner ML algorithm (SLA) yielded the best BMI classification predictive performance. SLA model 1 utilized sociodemographic and clinical characteristics, including baseline BMI values; the area under the receiver operating characteristic curve (ROC AUC) was approximately 88% for the prediction of BMI classifications of ≥ 30, ≥ 35, and ≥ 40 kg/m2 (internal validation), while accuracy ranged from 87.9% to 92.8% and specificity ranged from 91.8% to 94.7%. SLA model 2 utilized sociodemographic information and clinical characteristics, excluding baseline BMI values; ROC AUC was approximately 73% for the prediction of BMI classifications of ≥ 30, ≥ 35, and ≥ 40 kg/m2 (internal validation), while accuracy ranged from 73.6% to 80.0% and specificity ranged from 71.6% to 85.9%. The external validation on the MarketScan Commercial Claims and Encounters database yielded relatively consistent results with slightly diminished performance.ConclusionThis study demonstrated the feasibility and validity of using ML algorithms to predict BMI classifications in administrative healthcare claims data to expand the utility for RWE generation.

Dataset Information

ORIHIME study: real-world treatment patterns and clinical outcomes of 338 patients with acquired hemophilia A from a Japanese administrative database.

Background

Objectives

Patients/methods

Results

Conclusions

Publications

ORIHIME study: real-world treatment patterns and clinical outcomes of 338 patients with acquired hemophilia A from a Japanese administrative database.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets