Unique ID issued by UMIN | UMIN000050850 |
---|---|
Receipt number | R000057832 |
Scientific Title | Association between Hypoxia Inducible Factor Prolyl Hydoxylase Inhibitor or Erythropoiesis-Stimulating Agents and Cardiovascular Disease: a retrospective cohort study with overlap propensity score weighting |
Date of disclosure of the study information | 2023/09/01 |
Last modified on | 2023/04/05 13:21:24 |
Association between Hypoxia Inducible Factor Prolyl Hydoxylase Inhibitor or Erythropoiesis-Stimulating Agents and Cardiovascular Disease: a retrospective cohort study with overlap propensity score weighting
Association between HIF-PHIs or ESAs and CVD: a retrospective cohort study with overlap propensity score weighting
Association between Hypoxia Inducible Factor Prolyl Hydoxylase Inhibitor or Erythropoiesis-Stimulating Agents and Cardiovascular Disease: a retrospective cohort study with overlap propensity score weighting
Association between HIF-PHIs or ESAs and CVD: a retrospective cohort study with overlap propensity score weighting
Japan |
Renal anemia
Medicine in general | Nephrology |
Others
NO
The objective of this study was to use a Japanese healthcare record database to investigate whether ULT in patients with asymptomatic hyperuricemia could reduce the development of CVD.
Efficacy
The composite outcome of cardiovascular diseases including coronary artery disease (I210-4, I219), stroke (I600-11, I613-6, I619, I629-36, I638-9), heart failure (I500-1, I509, I110), atrial fibrillation (I480-4, I489)
all cause mortality, artery disease (I210-4, I219), stroke (I600-11, I613-6, I619, I629-36, I638-9), heart failure (I500-1, I509, I110), atrial fibrillation (I480-4, I489)
Observational
18 | years-old | <= |
Not applicable |
Male and Female
-Age >=18 years.
-Patients with at least one observation of eGFR < 60 ml/min/1.73 m2 in blood test data
-Received HIF-PH inhibitors or ESAs.
Patients without a six-month lookback period before the index date.
Patients with a diagnosis of CVD prior to the index date (date of first dose of HIF-PH inhibitor or ESA preparation) (see primary endpoint for definition).
5000
1st name | Hiroyuki |
Middle name | |
Last name | Hashimoto |
Graduate School of Medicine and Public Health, Kyoto University
Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health
606-8501
Yoshida-Konoe-cho, Sakyo-ku, Kyoto
0757539469
hashimoto.hiroyuki.36w@st.kyoto-u.ac.jp
1st name | Hiroyuki |
Middle name | |
Last name | Hashimoto |
Graduate School of Medicine and Public Health, Kyoto University
Department of Pharmacoepidemiology, Graduate School of Medicine and Public Health
606-8501
Yoshida-Konoe-cho, Sakyo-ku, Kyoto
0757539469
hashimoto.hiroyuki.36w@st.kyoto-u.ac.jp
Graduate School of Medicine and Public Health, Kyoto University
Hiroyuki Hashimoto
Grant-in-Aid for Scientific Research from the Japan Society for the Promotion of Science
Government offices of other countries
Kyoto University Graduate School and Faculty of Medicine, Ethics Committee
Yoshida-Konoe-cho, Sakyo-ku, Kyoto
0757534680
ethcom@kuhp.kyoto-u.ac.jp
NO
2023 | Year | 09 | Month | 01 | Day |
Unpublished
Preinitiation
2023 | Year | 08 | Month | 01 | Day |
2023 | Year | 08 | Month | 02 | Day |
2023 | Year | 09 | Month | 30 | Day |
1 Design
retrospective cohort study
2 Methods
2.1 Data source
The database is provided by JMDC Inc. This data set consists of records of medical check-ups and Japanese health insurance claims and medical checkups from several health insurance associations. The data was accumulated since 2005 and a cumulative population of approximately 14 million people (as of February 2022).
3 Observation, examination, survey and reporting items and schedule
3.1 Measurement items
date of birth, gender, smoking history, BMI, type of claims data, date of medical treatment, laboratory data, comorbidities, ICD10 codes, month when treatment started, year of treatment, outcome, ATC (Anatomical Therapeutic Chemical) classification code, date of prescription, etc.
Follow-up will start from the index date and end on the earliest of the following dates:
-Last visit to the relevant medical institution
-Death
-Last date of the data period of the provided dataset
-Discontinuation of HIF-PHI, ESA or crossover
(considered to be discontinuation after a three-month period of non-dosing)
4 Summary of analysis
4.1 Primary endpoints
Composite outcome of the following cardiovascular disease
-Coronary artery disease
-Stroke
-Heart failure
-Atrial fibrillation
4.2 Secondary endpoints
All-cause mortality, coronary artery disease, stroke, heart failure, atrial fibrillation
4.3 Main methods of analysis
The development of CVD is measured from the index date at which HIF-PHIs or ESAs were prescribed. A propensity score is calculated using logistic regression analysis and weighted using overlap weighting method. Explanatory variables will be used to calculate the propensity score. As the main analysis, data with missing values are excluded. In addition, Cox regression analysis will be performed to calculate the association between target drugs and CVD incidence. On-treatment analysis will be performed as the main analysis, where crossovers will be treated as censored cases.
2023 | Year | 04 | Month | 14 | Day |
2023 | Year | 04 | Month | 05 | Day |
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000057832