Artificial Intelligence for Optimal Anemia Management in End-stage Renal Disease: The Anemia Control Model (ACM) Trial

NCT ID: NCT03214627

Last Updated: 2020-01-07

Basic Information

• Recruitment Status: TERMINATED
• Clinical Phase: NA
• Total Enrollment: 88 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2018-12-10
• Study Completion Date: 2019-05-21

Brief Summary

Fresenius Medical Care has developed a computer software programme called the Anaemia Control Management (ACM) software to assist in the anaemia management of patients with chronic kidney disease (CKD) undergoing hemodialysis. This trial is designed to assess the effectiveness of this ACM software on anaemia management in routine clinical practice. However, all ultimate decisions on therapeutic or diagnostic procedures, treatments, management of the disease, or resource utilisation will be at the discretion of the Investigator. The trial consists of a retrospective (historical) control period and a prospective (going forward) period. During the prospective period, the ACM will be used to assist the Investigators' decision making and will help the Investigators to administer a personalised intravenous (IV) iron and red blood cell stimulating agent (ESA) therapy, whereas treatment according to standard of care will be documented retrospectively for the same patients during the retrospective period of the trial. Thus, patients can serve as their own control.

Detailed Description

Fresenius Medical Care has developed an algorithm that uses a data-driven computational intelligence model based on an artificial neural network architecture (ACM) to generate individualised ESA dose recommendations from a history of dose and response information and specific patient demographic characteristics.

The ACM has been validated and complies with the European requirements for medical devices. The ACM was classified as a Class I medical device in accordance with Directive 93/42/EEC. A proof of concept trial was conducted in 3 NephroCare dialysis clinics (managed by Fresenius) in the Czech Republic, Portugal, and Spain. It could be shown that the introduction of ACM-guided therapy led to a significant decrease in median darbepoetin doses and to a significant increase in on-target haemoglobin (Hb) values along with a decrease in Hb fluctuation. Moreover, a retrospective trial conducted in NephroCare clinics in Portugal, suggested that ACM is able to reliably predict the long-term response to ESA and iron therapy in patients undergoing haemodialysis.

The current trial will test the applicability of the ACM outside of Fresenius clinics in a public hospital setting in the UK. Both intravenous (IV) iron and ESA doses will be recommended by the algorithm. The effectiveness of ACM-guided therapy on several anaemia outcomes will be assessed in adult patients with End Stage Renal Disease (ESRD).This trial will be conducted at 1 main unit and 5 satellite units at King's College Hospital, London, UK, in patients with ESRD who are routinely undergoing haemodialysis.

This trial is designed to assess the effectiveness of the ACM software on anaemia management in routine clinical practice. However, all ultimate decisions on therapeutic or diagnostic procedures, treatments, management of the disease, or resource utilisation will be at the discretion of the Investigator.

The trial will consist of a retrospective control period and a prospective period. During the prospective period, the ACM will be used to facilitate the Investigators' decision making and will help the Investigators to administer a personalised IV iron and ESA therapy, whereas treatment according to standard of care will be documented retrospectively for the same patients during the retrospective period of the trial. Thus, patients can serve as their own control.

The planned overall duration of the trial is 18 months (12 months recruitment period + 6 months until last patient last visit). The planned duration of prospective treatment for an individual patient will be 6 months. The collection of retrospective data from medical records covering a period of 6 months will take place as soon as the Informed Consent Form (ICF) is signed but at the latest at baseline.

Data will be collected at designated time Points (monthly) throughout the Trial once the ICF is signed: at the latest at baseline (collection of retrospective data), at baseline (start of prospective documentation), and for the observation time points (Month 1 to Month 6). However, examinations will follow routine clinical practice at the site according to the Investigator's decision.

Conditions

Anemia; End Stage Renal Disease

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: OTHER
• Blinding Strategy: NONE

Study Groups

Anemia Control Model IV iron and ESA

Anemia Control Model (ACM) algorithm to recommend monthly IV and ESA dose over a 6 month period

IV iron: given monthly as required - dosing recommendation by ACM over 6 a month period

Erythropoiesis-Stimulating Agent (ESA): given monthly as required - dosing recommendation by ACM over 6 a month period

Group Type: EXPERIMENTAL

Anemia Control Model (ACM)

Intervention Type: DEVICE

The ACM is mainly composed of 2 sub-Systems - predictor model which, depending on the input data, forecasts the response to anaemia drug therapy for a specific patient. The predictor model is implemented as a feed-forward artificial neural network. The ACM is an algorithm that extracts the optimal policy to achieve the established clinical outcome for anaemia management using the predictor model.

IV iron

Intervention Type: DRUG

IV iron given monthly as required - dose determined by the ACM and as agreed by the investigator

Erythropoiesis-Stimulating Agent (ESA)

Intervention Type: DRUG

ESA given monthly as required over 6 months - dose determined by the ACM and as agreed by the investigator

Interventions

Anemia Control Model (ACM)

The ACM is mainly composed of 2 sub-Systems - predictor model which, depending on the input data, forecasts the response to anaemia drug therapy for a specific patient. The predictor model is implemented as a feed-forward artificial neural network. The ACM is an algorithm that extracts the optimal policy to achieve the established clinical outcome for anaemia management using the predictor model.

Intervention Type: DEVICE

IV iron

IV iron given monthly as required - dose determined by the ACM and as agreed by the investigator

Intervention Type: DRUG

Erythropoiesis-Stimulating Agent (ESA)

ESA given monthly as required over 6 months - dose determined by the ACM and as agreed by the investigator

Intervention Type: DRUG

Other Intervention Names

Venofer; iron sucrose; epoetin beta

Eligibility Criteria

Inclusion Criteria

• Age 19 to 90 years
• On haemodialysis for the past 18 months prior to baseline
• Treatment with IV iron sucrose during the past 6 months according to the respective Summary of Product Characteristics (SmPC)
• Treatment with epoetin beta during the past 6 months according to the respective SmPC
• Regular Hb measurements and at least 5 (standard of care, approximately monthly) Hb measurements during the past 6 months
• Ferritin measurements during the past 6 months (at least 2 measurements)
• Signed informed consent

Exclusion Criteria

• Life expectancy <6 months
• One or more Hb measurements <8 g/dl during the control period
• Living-donor transplant scheduled within the next 6 months
• Scheduled for switch to peritoneal dialysis or home haemodialysis
• Blood transfusion during the past 9 months
• Pregnancy or breast feeding
• Active infection
• Current malignancy or haematological disorder
• Previous severe hypersensitivity reaction to IV iron sucrose
• Serious allergic reactions to darbepoetin alfa or epoetin alfa/beta/zeta, respectively
• Current treatment with PEGylated erythropoietin
• Surgery in the past 6 months
• Surgery scheduled within the next 6 months
• Participation in a clinical trial in the past 7 months

• Minimum Eligible Age: 19 Years
• Maximum Eligible Age: 90 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Worldwide Clinical Trials

OTHER

Sponsor Role: collaborator

Fresenius Medical Care Deutschland GmbH

INDUSTRY

Sponsor Role: collaborator

Vifor Fresenius Medical Care Renal Pharma

INDUSTRY

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Iain Macdougall

Role: PRINCIPAL_INVESTIGATOR

King's College Hospital NHS Trust

Locations

Kings College Hospital

London, , United Kingdom

Countries

United Kingdom

References

Barbieri C, Mari F, Stopper A, Gatti E, Escandell-Montero P, Martinez-Martinez JM, Martin-Guerrero JD. A new machine learning approach for predicting the response to anemia treatment in a large cohort of End Stage Renal Disease patients undergoing dialysis. Comput Biol Med. 2015 Jun;61:56-61. doi: 10.1016/j.compbiomed.2015.03.019. Epub 2015 Mar 23.

Reference Type: BACKGROUND

PMID: 25864164 (View on PubMed)

Barbieri C, Molina M, Ponce P, Tothova M, Cattinelli I, Ion Titapiccolo J, Mari F, Amato C, Leipold F, Wehmeyer W, Stuard S, Stopper A, Canaud B. An international observational study suggests that artificial intelligence for clinical decision support optimizes anemia management in hemodialysis patients. Kidney Int. 2016 Aug;90(2):422-429. doi: 10.1016/j.kint.2016.03.036. Epub 2016 Jun 2.

Reference Type: BACKGROUND

PMID: 27262365 (View on PubMed)

Barbieri C, Bolzoni E, Mari F, Cattinelli I, Bellocchio F, Martin JD, Amato C, Stopper A, Gatti E, Macdougall IC, Stuard S, Canaud B. Performance of a Predictive Model for Long-Term Hemoglobin Response to Darbepoetin and Iron Administration in a Large Cohort of Hemodialysis Patients. PLoS One. 2016 Mar 3;11(3):e0148938. doi: 10.1371/journal.pone.0148938. eCollection 2016.

Reference Type: BACKGROUND

PMID: 26939055 (View on PubMed)

Other Identifiers

VEN-DEV-401

Identifier Type: -

Identifier Source: org_study_id