Study to Develop a Tool to Estimate the Kidney Function in Databases Without Laboratory Data

NCT03605810 | Completed

• 1 other identifier: 20325
• Study Type: observational
• Target: 5,132,200
• Locations: 1 country
• Sites: 1

Brief Summary

Scientific analyses are frequently performed on e.g. health insurance databases to study the usage and effectiveness of drugs in real life. Kidney function is known to have an influence on a patients disease development and/or drug levels in blood. However, often direct measures for kidney function are not available in databases. This study plans to develop tools to classify the renal function of patients, which helps scientists to identify patient cohorts (groups of patients sharing same characteristics) for scientific analyses.

Conditions

Renal Function

Keywords

Renal function, eGRF, Atrial fibrillation, Coronary artery disease, Type 2 diabetes mellitus, Machine learning, Prognostic modeling

Outcome Measures

Primary Outcomes (1)

• Performance of classification to predict eGFR

  For numeric models cross-validated performance is measured as correlation via r\*2. Class based performances are measured as cross-validated sensitivities given pre-defined false discovery rates with following definition for positives and negatives: Observed eGFR class X: * positive: eGFR measured at begin of time frame is in class X * negative: eGFR measured at begin of time frame is not in class X Class predicted by model: * positive: eGFR predicted is class X * negative: eGFR predicted is not class X

  From eGRF values starting and lasting 180d + 370d

Study Arms (4)

eGFR-population

To be included in the eGFR-population, patients have to have at least one recorded eGFR value in the OPTUM CDM database between January 1, 2007 and December 31, 2016, be adults (\>18 years of age at the time of eGFR test) and have at least 370/180 days (180 days serves as sensitivity analysis) of continuous enrollment in medical and pharmacy insurance plans since eGFR test date.

Other: No Intervention

Atrial fibrillation (AF) sub-population

To be included in the AF sub-population patients need to satisfy the inclusion criteria for the eGFR-population; have two inpatient or outpatient diagnoses for AF or atrial flutter on two different days within the study period irrespective of time points when eGFR is measured. Patients with at least one inpatient or outpatient diagnosis or procedure code for mitral stenosis and prosthetic valves within the study period will be excluded.

Other: No Intervention

Coronary artery disease (CAD) sub-population

To be included in the CAD sub-population patients need to satisfy the inclusion criteria for the eGFR-population; have at least one inpatient CAD diagnosis within the study period irrespective of time points when eGFR is measured.

Other: No Intervention

Type 2 diabetes mellitus (T2DM) sub-population

To be included in the T2DM sub-population patients need to satisfy the inclusion criteria for the eGFR-population; have at least two inpatient or outpatient diagnosis of T2DM on two different days within the study period irrespective of time points when eGFR is measured.

Other: No Intervention

Interventions

No Intervention OTHER

This study is the development of algorithms/models to predict eGFR values and/or classes for patients at certain time point based on entries in claims database (demographic characteristics, clinical diagnoses, procedures and drug treatments) for a general population and a variety of use-cases (AF, CAD, T2DM patients sub-populations).

Atrial fibrillation (AF) sub-population; Coronary artery disease (CAD) sub-population; Type 2 diabetes mellitus (T2DM) sub-population; eGFR-population

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

Adult patients with at least one recorded eGFR value in the OPTUM CDM database between January 1, 2007 and December 31, 2016 will be included in the use-case 1 "eGFR population". Further cases refer to the sub-populations of the eGFR-population, namely * Atrial fibrillation (AF) sub-population; * Coronary artery disease (CAD) sub-population; * Type 2 diabetes mellitus (T2DM) sub-population.

To be included in the eGFR-population, patients have to have at least one recorded eGFR value in the OPTUM CDM database between January 1, 2007 and December 31, 2016, be adults (\>18 years of age at the time of eGFR test) and have at least 370/180 days (180 days serves as sensitivity analysis) of continuous enrollment in medical and pharmacy insurance plans since eGFR test date.

Contact the study team to discuss eligibility requirements. They can help determine if this study is right for you.

Sponsors & Collaborators

• Bayer: lead

Study Sites (1)

US OPTUM CDM database

Whippany, New Jersey, 07981, United States

Location

Related Links

• Click here to find results for studies related to Bayer products.

MeSH Terms

Conditions

Atrial Fibrillation; Coronary Artery Disease; Diabetes Mellitus, Type 2

Condition Hierarchy (Ancestors)

Arrhythmias, Cardiac; Heart Diseases; Cardiovascular Diseases; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Coronary Disease; Myocardial Ischemia; Arteriosclerosis; Arterial Occlusive Diseases; Vascular Diseases; Diabetes Mellitus; Glucose Metabolism Disorders; Metabolic Diseases; Nutritional and Metabolic Diseases; Endocrine System Diseases

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 23, 2018
• First Posted: July 30, 2018
• Study Start: July 15, 2018
• Primary Completion: December 31, 2018
• Study Completion: December 31, 2018
• Last Updated: December 10, 2019

Record last verified: 2019-12

Locations

US (1)