Solid TumorIASAACNCT05412420
Artificial Intelligence to Search for Abnormalities in Ambulatory Cancer Patients
A study testing Patient Self-Reporting of Symptoms in people with Solid Tumor, run by Institut de Cancérologie de Lorraine at 1 site in France.
Trial summary
During treatment, cancer patients may experience side effects related to their disease but also to the different treatments they receive. Currently, adverse effects and toxicities are well codified in the oncology community, notably via the NCI CTCAE criteria. Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Solid Tumor
- What is being tested?
- Patient Self-Reporting of Symptoms
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 500 participants
- Where
- 1 siteFrance
- Study dates
- 3 Aug 2022to 13 Oct 2023
- Phase
- Interventional
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- Follow-up for a solid tumor
- Chemotherapy treatment (oral and/or injectable) scheduled or in progress
- Life expectancy > 3 months
- Performance Status (PS) < 3
- Have an internet connection or assistance to answer questions throughout the study (nurse, family members, etc.)
- Patient having understood, signed and dated the consent form
- Patient affiliated to the social security system
Who cannot join
- Lack of means to answer the online questionnaires
- Patient in another therapeutic trial with an experimental molecule
- Patients and their families who cannot read or speak French
- Persons deprived of liberty or under guardianship (including curatorship)
Trial locations and contacts
1 site in 1 country.
About this study
During treatment, cancer patients may experience side effects related to their disease but also to the different treatments they receive.
Currently, adverse effects and toxicities are well codified in the oncology community, notably via the NCI CTCAE criteria.
Read more
Unlike objective data such as a blood sample or a CTscan, a major bias in patient assessment is the subjective assessment of the physician or its team at a given time, which may not reflect the overall situation (for better or worse). Several studies had already highlighted the discrepancies between medical and patient data collection.
Self-assessment of symptoms is one way to overcome this bias. Moreover, there are now a large number of solutions that allow to perform these self-assessments at home.
Thanks to these tools, there are now two situations, the scheduled evaluation (before a chemotherapy treatment, or after a surgical procedure for instance) and the unscheduled situations, where it is the patient himself who can trigger an evaluation form.
These new evaluation methods also allow to take a quality of life approach. Patient-reported outcomes (PROs) is now a valid evidence-based assay to detect patient's symptoms and therefore provide helpful clinical information to healthcare providers.
The goal of this study is to go one step further than the previous PROs studies and evaluate the ability to train a machine learning algorithm to detect at-risk situations and lay the foundation for a viable solution for future prospective and randomized trials.
- Conditions
- Solid Tumor
- Being tested
- Patient Self-Reporting of Symptoms
- Keywords
- Electronic survey, Artificial intelligence, Quality of life, Patient-Reported Outcomes (PROs), Symptom management, eHealth, Machine learning
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Patient Self-Reporting of SymptomsOther
At baseline, clinical research staff will:
- verify the possibility of an internet connection at the patient's home
- help the patient to fill in the 1st questionnaire (baseline questionnaire - frailty)
Every two weeks for 3 months:
- patients complete questionnaires via app (toxicity; quality of life, medication adherence)
- responses are verified by clinical research staff
- In case of severe symptoms, the clinician contacts the patient and arranges for management.
At the end of the study :
- patients answer a satisfaction questionnaire
| Study group | Role | What they receive |
|---|---|---|
| Patient Self-Reporting of Symptoms | Experimental | Not described Receives: Other: Patient Self-Reporting of Symptoms |
What is being measured
The primary outcome is the main question the study is designed to answer.
Number of unscheduled medical consultations or re-hospitalisations
The number of unscheduled medical consultations or re-hospitalisations will be assessed based on abnormalities identified through the patient's self-report of symptoms.
Measured: 3 months
Secondary outcomes (7)
Patient Satisfaction
Patient satisfaction will be assessed according to the Patient Assessment Chronic Illness Care Questionnaire (1= almost never : 5 = almost always)
Measured: 3 months
Occurrence of toxicities
The occurrence of toxicities will be evaluated according to the NCI-CTCAE v5.0 classification
Measured: 3 months
Dose of treatments
The total dose of treatments given will be calculated from the total dose of chemotherapy received per course and the collection of dose adjustments.
Measured: 3 months
Adherence to oral treatment
Adherence to oral treatments will be assessed by the Morisky questionnaire
Measured: 3 months
Handling of the digital tool
Handling of the digital tool will be assessed by the System Usability Scale ( 0 =Strongly disagree; 10=Strongly agree)
Measured: 3 months
Anticipation of the preparation of injectable chemotherapy
Anticipation of injectable chemotherapy preparations will be evaluated based on the number of treatments ordered and actually administered, without the need to call the patient.
Measured: 3 months
Predicting the occurrence of sarcopenia
The occurrence of sarcopenia will be measured by the body mass/fat mass ratio using the CT scan performed for tumor evaluation
Measured: 3 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted9 Jun 2022
- Study start3 Aug 2022
- Primary completion13 Oct 2023
- Study completion13 Oct 2023
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Solid TumorStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Enrolment
- 500 participants (actual)
Sponsor and investigators
- Lead sponsor
- Institut de Cancérologie de Lorraine
- Sponsor type
- University, hospital or other
- Responsible party
- Sponsor
- Investigators
- LAMBERT AURELIEN, MD, Principal investigator, Institut de Cancérologie de Lorraine
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05412420
- Sponsor's protocol ID
- 2022-A01034-39
- Acronym
- IASAAC
- Status last verified
- Nov 2023
- First submitted
- 30 May 2022
- Last updated
- 30 Nov 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 30 Nov 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Artificial Intelligence to Search for Abnormalities in Ambulatory Cancer Patients
- ClinicalTrials.gov ID
- NCT05412420
- Acronym / sponsor ID
- IASAAC / 2022-A01034-39
- Conditions
- Solid Tumor
- Keywords
- Electronic survey, Artificial intelligence, Quality of life, Patient-Reported Outcomes (PROs), Symptom management, eHealth, Machine learning
- Study type
- Interventional
- Recruitment status
- Completed
- Enrolment
- 500 participants (actual)
- Lead sponsor
- Institut de Cancérologie de LorraineUniversity, hospital or other
- Study start
- 3 Aug 2022 (actual)
- Primary completion
- 13 Oct 2023 (actual)
- Study completion
- 13 Oct 2023 (actual)
- First posted
- 9 Jun 2022 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
During treatment, cancer patients may experience side effects related to their disease but also to the different treatments they receive.
Currently, adverse effects and toxicities are well codified in the oncology community, notably via the NCI CTCAE criteria.
Unlike objective data such as a blood sample or a CTscan, a major bias in patient assessment is the subjective assessment of the physician or its team at a given time, which may not reflect the overall situation (for better or worse). Several studies had already highlighted the discrepancies between medical and patient data collection.
Self-assessment of symptoms is one way to overcome this bias. Moreover, there are now a large number of solutions that allow to perform these self-assessments at home.
Thanks to these tools, there are now two situations, the scheduled evaluation (before a chemotherapy treatment, or after a surgical procedure for instance) and the unscheduled situations, where it is the patient himself who can trigger an evaluation form.
These new evaluation methods also allow to take a quality of life approach. Patient-reported outcomes (PROs) is now a valid evidence-based assay to detect patient's symptoms and therefore provide helpful clinical information to healthcare providers.
The goal of this study is to go one step further than the previous PROs studies and evaluate the ability to train a machine learning algorithm to detect at-risk situations and lay the foundation for a viable solution for future prospective and randomized trials.
Study design
- Primary purpose
- Prevention
- Allocation
- Not applicable
- Intervention model
- Single group
- Masking
- None (open label)
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| Patient Self-Reporting of Symptoms | Experimental | Other: Patient Self-Reporting of Symptoms |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- Follow-up for a solid tumor
- Chemotherapy treatment (oral and/or injectable) scheduled or in progress
- Life expectancy > 3 months
- Performance Status (PS) < 3
- Have an internet connection or assistance to answer questions throughout the study (nurse, family members, etc.)
Key exclusion criteria (4 listed)
- Lack of means to answer the online questionnaires
- Patient in another therapeutic trial with an experimental molecule
- Patients and their families who cannot read or speak French
- Persons deprived of liberty or under guardianship (including curatorship)
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Patient Self-Reporting of SymptomsAt baseline, clinical research staff will: * verify the possibility of an internet connection at the patient's home * help the patient to fill in the 1st questionnaire (baseline questionnaire - frailty) Every two weeks for 3 months: * patients complete questionnaires via app (toxicity; quality of life, medication adherence) * responses are verified by clinical research staff * In case of severe symptoms, the clinician contacts the patient and arranges for management. At the end of the study : - patients answer a satisfaction questionnaire | Other | Patient Self-Reporting of Symptoms |
Primary outcome
Number of unscheduled medical consultations or re-hospitalisations
Time frame: 3 months
The number of unscheduled medical consultations or re-hospitalisations will be assessed based on abnormalities identified through the patient's self-report of symptoms.
7 secondary outcomes
Patient Satisfaction
Time frame: 3 months
Occurrence of toxicities
Time frame: 3 months
Dose of treatments
Time frame: 3 months
Adherence to oral treatment
Time frame: 3 months
Handling of the digital tool
Time frame: 3 months
Anticipation of the preparation of injectable chemotherapy
Time frame: 3 months
Predicting the occurrence of sarcopenia
Time frame: 3 months
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 30 Nov 2023.
- Individual participant dataSharing planned: No
Related trials for Solid Tumor
RecruitingPhase 1/2
Study of INBRX-106 and INBRX-106 in Combination With Pembrolizumab (Keytruda®) in Subjects With Locally Advanced or Metastatic Solid Tumors (Hexavalent OX40 Agonist)
Solid Tumor, Non-Small Cell Lung Cancer
Active, not recruitingPhase 1
A Study to Assess Safety, Tolerability, and Pharmacokinetics of ABSK043 in Patients With Advanced Solid Tumor
Neoplasms
Active, not recruitingPhase 3
A Safety and Efficacy Extension Study of Pertuzumab in Patients With Solid Tumors Previously Enrolled in a Hoffmann-La Roche-Sponsored Pertuzumab Clinical Trial
Solid Tumors
RecruitingPhase 1
IL-12 Genetically Engineered Myeloid Cells in Participants With Relapsed, Refractory Solid Tumors
Relapsed Solid Tumor Malignancies, Refractory Solid Tumor Malignancies
RecruitingObservational study
Immune Checkpoint Inhibitor Toxicity Risk Prediction in Solid Tumors
Malignant Solid Neoplasm
Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
LAMBERT AURELIEN, MD principal investigator
Institut de Cancérologie de Lorraine
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing Patient Self-Reporting of Symptoms in people with Solid Tumor, run by Institut de Cancérologie de Lorraine at 1 site in France.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 4 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 30 Nov 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in France. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Number of unscheduled medical consultations or re-hospitalisations (time frame: 3 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 30 Nov 2023.