QT-RIBRATING: A Deep Learning Method to Evaluate QT on Ribociclib

Sponsor
CMC Ambroise Paré (Other)
Overall Status
Not yet recruiting
CT.gov ID
NCT05623397
Collaborator
(none)
60
4
24
15
0.6

Study Details

Study Description

Brief Summary

"Deep-learning" is a fast-growing method of machine learning (artificial intelligence, AI) which is arousing the interest of the scientific committee in many medical fields. These methods make it possible to generate matches between raw inputs (such as the digital signal from the ECG) and the desired outputs (for example, the measurement of QTc). Unlike traditional machine learning methods, which require manual extraction of structured and predefined data from raw input, deep-learning methods learn these functionalities directly from raw data, without pre-defined guidelines. With the advent of big-data and the recent exponential increase in computing power, these methods can produce models with exceptional performance. The investigators recently used this type of method using multi-layered artificial neural networks, to create an application based on a model that directly transforms the raw digital data of ECGs (.xml) into a measure of QTc comparable to those respecting the highest standards concerning reproducibility.

The main purpose of this trial is to study the performance of our DL-AI model for QTc measurement (vs. best standards of QTc measurements, TCM) applied to the recommended ECG monitoring following ribociclib prescription for breast cancer patients in routine clinical care. The investigators will acquire ECG with diverse devices including simplified devices (one/three lead acquisition, low frequency sampling rate: 125-500 Htz) to determine if they'll be equally performant versus 12-lead acquisition machine to evaluate QTc in this setting.

Condition or Disease Intervention/Treatment Phase
  • Other: Acquisition of a digitized ECG by four modalities within 20 minutes

Study Design

Study Type:
Observational
Anticipated Enrollment :
60 participants
Observational Model:
Cohort
Time Perspective:
Prospective
Official Title:
QT on RIBociclib measuRed by ArTificial INteliGence
Anticipated Study Start Date :
Dec 1, 2022
Anticipated Primary Completion Date :
Dec 1, 2024
Anticipated Study Completion Date :
Dec 1, 2024

Arms and Interventions

Arm Intervention/Treatment
Breast cancer patients administered ribociclib.

Prospective cohort of consecutive breast cancer patients requiring ribociclib for their standard of care at the clinically indicated dose, as per treating physician prescription (600mg to 200mg/day for 21 days per 28 days cycle). Association with other hormone-derived therapeutics will be allowed.

Other: Acquisition of a digitized ECG by four modalities within 20 minutes
Patients will have three visits during the cycle for a given dose (600mg/day, 400mg/day or 200mg/day): Baseline , Day 14, Day 28 At each visit, the patient will have the acquisition of a digitized ECG by four modalities within 20 minutes (A 10 second triplicate ECG with WELCH-ALYN ELI-280® with the three 10sec ECGs collected at approximatively 2-minute intervals, 10 min holter acquisition with a CGM HI-patch ®, a 3 minutes acquisition with AliveCore 6L® device and a 5 minutes acquisition with QT-medical ® device). Concomitantly with the ECG acquisition, patients will have blood sampling for measurements of variables clinically important for assessment of QTc including potassium, fasting blood glucose, calcemia, magnesium, estradiol, progesterone, FSH, LH, D4-androstenedione, total and free testosterone, SHBG and TSH. Blood concentration of ribociclib will be also assessed.

Outcome Measures

Primary Outcome Measures

  1. Compare the values of QTc generated by method 1 (overlap method on triplicate of 10 seconds ECG concatenated, TCM; the method of reference) versus method 2 relying on AI methodology in patients' candidate for ribociclib start [One visit the day of ribociclib start (before ribociclib intake)]

    Comparison of the 2 methods (TCM vs. DL-AI) to demonstrate if there is a clinically relevant mean QTc difference ≥ 5msec between the 2 methods.

Secondary Outcome Measures

  1. Compare the values of QTc generated by method 1 (overlap method after triplicate concatenation, TCM) versus method 2 (DL-AI) in patients' on/off ribociclib using a digitized 12-lead acquisition ECG device [One visit at day 14+/-3 and day 28+/-3 after start of ribociclib]

    Bland-Altman plots and intra-class correlation will be generated to compare QTc values obtained by TCM vs. DL-AI on ribociclib (Day 14+/-3 days after start) and off-ribociclib (Day 28 +/-3 of ribociclib cycles).

  2. Compare the values of QTc generated using method 2 (DL-AI) in patients' on/off ribociclib using a miniaturized and/or simplified ECG acquisition device (QT-Medical®, AliveCor®, a holter system (CGM HI-patch) versus using a digitized 12-lead acquisition [One visit at baseline before ribociclib start and then day 14+/-3 and day 28+/-3 after ribociclib start]

    Compare QTc values obtained by DL-AI on/off ribociclib using a standard digitized 12-lead acquisition device (WELCH-ALYN ELI-280) versus each of three other miniaturized and/or simplified ECG acquisition devices (QT- Medical®, AliveCor®, CGM HI-patch®).

  3. The clinico-demographic predictors of amplitude of QTc prolongation on ribociclib. [One visit at baseline before ribociclib start and then day 14+/-3 and day 28+/-3 after ribociclib start]

    Nonlinear mixed models will be used to study clinico-demographic determinants associated with magnitude of QTc prolongation on ribociclib.

  4. Learn ECG features at baseline using deep-learning predictors of magnitude of QTc prolongation on ribociclib [One visit at baseline before ribociclib start and then day 14+/-3 and day 28+/-3 after ribociclib start]

    Using deep-learning seeking for a model using ECG raw data at baseline to predict magnitude of QTc prolongation on ribociclib

Eligibility Criteria

Criteria

Ages Eligible for Study:
18 Years and Older
Sexes Eligible for Study:
Female
Accepts Healthy Volunteers:
No
Inclusion Criteria:
  • Adult female patients requiring start of ribociclib based therapy for a breast cancer in their standard of care, as per their summary of product characteristic's indications

  • Association with hormone-based therapy in combination is authorized (aromatase inhibitors or fulvestrant)

  • Able to provide an informed consent

Exclusion Criteria:
  • Any allergy or contra-indication to ribociclib as mentioned in their as summary of product characteristic's

  • Patients presenting a condition precluding accurate QTc measurements on electrocardiogram, i.e paced ventricular rhythm, multiples premature ventricular or supra-ventricular contractions, ventricular tachycardia, supraventricular arrhythmia (including atrial fibrillation, flutter or junctional rhythm)

  • Patients with an atrial pacing and sinus dysfunction

  • Patients presenting a contra-indication for ECG measurement, or with a device rendering ECG measurements impossible (i.e. Diaphragmatic pacing)

  • Patients presenting a contra-indication to ribociclib start; including association with prohibited drug potentializing the risk of TdP

Contacts and Locations

Locations

Site City State Country Postal Code
1 Groupe Ambroise Paré, Hartmann Neuilly-sur-Seine France 92200
2 Hôpital Tenon Paris France 75020
3 CIC - Hôpitaux Universitaires Pitié Salpêtrière, Paris, FRANCE Paris France 75651
4 Institut Gustave Roussy Villejuif France 94805

Sponsors and Collaborators

  • CMC Ambroise Paré

Investigators

None specified.

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.
Responsible Party:
CMC Ambroise Paré
ClinicalTrials.gov Identifier:
NCT05623397
Other Study ID Numbers:
  • 2021/03
First Posted:
Nov 21, 2022
Last Update Posted:
Nov 21, 2022
Last Verified:
Nov 1, 2022
Studies a U.S. FDA-regulated Drug Product:
No
Studies a U.S. FDA-regulated Device Product:
No
Keywords provided by CMC Ambroise Paré

Study Results

No Results Posted as of Nov 21, 2022