Non Small Cell Lung CancerNCT05537922
I3LUNG: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy
An observational study of Non Small Cell Lung Cancer and Lung Cancer Metastatic, run by Fondazione IRCCS Istituto Nazionale dei Tumori, Milano at 4 sites in 4 countries.
Trial summary
I3LUNG is an international project aiming to develop a medical device to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Non Small Cell Lung Cancer, Lung Cancer Metastatic, Lung Cancer, Nonsmall Cell
- How many people
- 2,200 participants
- Where
- 4 sitesin 4 countries
- Study dates
- 1 Oct 2022to 1 Oct 2027
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
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
Study population: The retrospective cohort consists of aNSCLC patients treated with IO. Data from an estimated 2000 patients treated with IO-based therapy will be collected from all the clinical partners (INT, GHD, VHIO, MH, SZMC and UOC). Informed consent for the study will be obtained before enrolment. If not feasible, i.e. patients not alive, the approval to Privacy Guarantee will be obtained. In the prospective phase, the study cohort consists of aNSCLC patients candidate for first-line IO-based therapy with available surgical samples (enough to perform OMICs). Baseline data of an estimated 200 patients from 5 clinical centers (INT, GHD, VHIO, MH and SZMC) will be collected including complete clinical, multi- OMICs analysis, imaging of CT and PET scan at baseline IO, behavioral, health economic, QoL measurements with based-sensor techniques and standard QoL. Informed consent for the study will be obtained before enrolment.
Who may be able to join
- Age >/= 18 years.
- Eastern Cooperative Oncology Group (ECOG) performance status </= 2.
- Histologically confirmed diagnosis of stage IIIB/C-IV Non-Small-Cell Lung Cancer
- Received any line immunotherapy (maintenance therapy with Durvalumab is allowed) for retrospective cohort; clinical indication for frontline treatment with immunotherapy as first line treatment for prospective cohort.
- Patients with CNS metastasis are allowed
- Patients with driver genomic alterations are allowed (only for retrospective cohort)
- Evidence of a personally signed and dated ICF indicating that the patient has been informed of and understands all pertinent aspects of the study before enrolment (only for prospective cohort)
- Availability of at least one FFPE block for -omics data generation (only for prospective cohort)
Who cannot join
- Patients without minimal treatment information data to be included in the retrospective cohort
- Prior treatment for advanced disease (only for prospective cohort)
- Unavailability or inability to comply with the requested study procedures, including compilation of QoL questionnaires
Trial locations and contacts
4 sites in 4 countries. Contact the study team or a site near you to ask about taking part.
4 sites in 4 countries
United States1 site, 1 recruiting
- Recruiting
University of Chicago
Chicago, Illinois, 60637
Marina Garassino
Greece1 site, 1 recruiting
- Recruiting
Metropolitan Hospital
Athens
Elena Linardou
Israel1 site, 1 recruiting
- Recruiting
Shaare Zedek Medical Center
Jerusalem
Nir Peled
Spain1 site, 1 recruiting
- Recruiting
Vall D'Hebron Institute of Oncology
Barcelona
Enriqueta Felip
About this study
I3LUNG is an international project aiming to develop a medical device to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data). This objective will be reached through a retrospective - setting up a transnational platform of available data from 2000 patients - and a prospective - multi-omics prospective data collection in 200 NSCLS patients - study phase.
The retrospective cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model), that will be used in the prospective study phase to create a first version of the PDSS tool, an AI-based tool to provide an easy and ready-to-use access to predictive models, increasing care appropriateness, reducing the negative impacts of prolonged and toxic treatments on wellbeing and healthcare costs.
The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. This cohort will be used to validate the results obtained from the retrospective model through the creation of a new model (P-Model), which will be used to create the final PDSS tool.
Read the detailed description
The I3LUNG project aims to achieve the highest performance in personalized medicine through Artificial Intelligence/Machine Learning (AI/ML) modelled on multimodal patients' data, together with implementing an AI/ML model in a real-life setting. A set of patient-centered ML tools designed and validated for the project, which make use of the novel virtual patient AVATAR entity for predicting progression and outcome. To maximize its impact, the use of Trustworthy explanaible AI methodology will integrate the AI's inherent performances with the input of human intuition to construct a responsible AI application able to fully implement truly individualized treatment decisions in NSCLC interpretable and trustworthy for clinicians. The final objective is the establishment of a Worldwide Data Sharing and Elaboration Platform (DSEP). The DSEP will provide guiding tools for patients, providing information to generate awareness on treatments. Lastly, it gives access to researchers and the general scientific community to the most up-to-date data sources on NSCLC.
Within the I3LUNG project, an ad-hoc IPDAS for NSCLC patients will be developed. Patient decision aids are tools that might be used by patients either before or within a consultation with physicians. Patient decision aids explicitly represent the decision to be made and provide patients with user-friendly information about each treatment option by focusing on harms and benefits. This tool could allow patients to explain and clarify the high complexity of the information provided by the AI/ML approach. These decisional support systems have been demonstrated to be effective in empowering patients, improving their knowledge, promoting their active participation in clinical decision-making about treatments, and improving overall patient satisfaction with care while decreasing decisional conflict and decisional regret (26-30).
Finally, within the I3LUNG project it will be assessed whether using the IPDAS during the clinical consultation would foster the quality of the shared decision-making as well as the quality of the doctor-patient communication. Alongside the evaluation of the impact of the IPDAS, it will be also evaluated whether the inclusion of the AI/ML predictive models in clinical practice will be added value in supporting oncologists' clinical decision-making and decreasing cognitive fatigue and decisional conflict.
I3LUNG adopts a two-pronged approach to develop a medical device through the creation and validation of retrospective and prospective AI-based models to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data) through a retrospective - setting up a transnational platform of available data from 2000 patients - and a prospective - multi-omics prospective data collection in 200 NSCLS patients - study phase.
The retrospective part of the I3LUNG project includes the analysis of a multicentric retrospective cohort of more than 2,000 patients. This cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model), that will be used in the prospective study phase to create a first version of the PDSS tool, an AI-based tool to provide an easy and ready-to-use access to predictive models, increasing care appropriateness, reducing the negative impacts of prolonged and toxic treatments on wellbeing and healthcare costs. Also, CT and PET scans will be collected and a first radiomic signature will be created to feed the R-Model.
The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. This cohort will be used to validate the results obtained from the retrospective model through the creation of a new model (P-Model), which will be used to create the final PDSS tool.
- Conditions
- Non Small Cell Lung Cancer, Lung Cancer Metastatic, Lung Cancer, Nonsmall Cell, Lung Adenocarcinoma
- Keywords
- NSCLC, Artificial Intelligence, Immunotherapy
- Medical subject headings
- Carcinoma, Non-Small-Cell Lung, Adenocarcinoma of Lung
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| Retrospective Cohort | This cohort includes the analysis of a multicentric retrospective cohort of more than 2,000 patients. This cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model). All available clinical data will be collected. Also, CT and PET scans will be collected and a first radiomic signature. | |
| Prospective Cohort | The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Response Rate
Prediction of response to immune checkpoint inhibitors in NSCLC
Measured: 8 weeks (i.e. first radiological evaluation)
Secondary outcomes (2)
PFS
Progression Free Survival in NSCLC treated with immune checkpoint inhibitors
Measured: From date of enrollment until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 120 months
OS
Overall Survival in NSCLC treated with immune checkpoint inhibitors
Measured: From date of enrollment until the date of death from any cause, assessed up to 120 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted13 Sep 2022
- Study start1 Oct 2022
- Primary completion1 Oct 2025 (estimated)
- Study completion1 Oct 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (1)Papers the sponsor has linked to this study.
- Other trials for Non Small Cell Lung CancerStudies of the same condition, open and under way.
- More trials run by Fondazione IRCCS Istituto Nazionale dei Tumori, MilanoThe sponsor's other registered studies.
- 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
- Observational
- Observational model
- Cohort
- Time perspective
- Other
- Enrolment
- 2,200 participants (estimated)
Sponsor and investigators
- Sponsor type
- University, hospital or other
- Collaborators
- Vall d'Hebron Institute of Oncology, Shaare Zedek Medical Center, LungenClinic Grosshansdorf, Metropolitan Hospital, Athens, University of Chicago
- Responsible party
- Principal investigator, Arsela Prelaj, Fondazione IRCCS Istituto Nazionale dei Tumori, Milano
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT05537922
- Sponsor's protocol ID
- INT147/22
- Status last verified
- Jan 2023
- First submitted
- 5 Sep 2022
- Last updated
- 6 Jan 2023
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
Publications
Lo Russo G, Prelaj A, Dolezal J, Beninato T, Agnelli L, Triulzi T, Fabbri A, Lorenzini D, Ferrara R, Brambilla M, Occhipinti M, Mazzeo L, Provenzano L, Spagnoletti A, Viscardi G, Sgambelluri F, Brich S, Miskovic V, Pedrocchi ALG, Trovo' F, Manglaviti S, Giani C, Ambrosini P, Leporati R, Franza A, McCulloch J, Torelli T, Anichini A, Mortarini R, Trinchieri G, Pruneri G, Torri V, De Braud F, Proto C, Ganzinelli M, Garassino MC. PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 <50%: a multiomics analysis. J Immunother Cancer. 2023 Jun;11(6):e006833. doi: 10.1136/jitc-2023-006833.
PubMed 37286305
Study at a glance
From the registry record, last updated by the sponsor on 6 Jan 2023. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- I3LUNG: Integrative Science, Intelligent Data Platform for Individualized LUNG Cancer Care With Immunotherapy
- ClinicalTrials.gov ID
- NCT05537922
- Acronym / sponsor ID
- INT147/22
- Conditions
- Non Small Cell Lung Cancer, Lung Cancer Metastatic, Lung Cancer, Nonsmall Cell, Lung Adenocarcinoma
- Keywords
- NSCLC, Artificial Intelligence, Immunotherapy
- Study type
- Observational
- Recruitment status
- Recruiting
- Enrolment
- 2,200 participants (estimated)
- Lead sponsor
- Fondazione IRCCS Istituto Nazionale dei Tumori, MilanoUniversity, hospital or other
- Collaborators
- Vall d'Hebron Institute of Oncology, Shaare Zedek Medical Center, LungenClinic Grosshansdorf, Metropolitan Hospital, Athens, University of Chicago
- Study start
- 1 Oct 2022 (actual)
- Primary completion
- 1 Oct 2025 (estimated)
- Study completion
- 1 Oct 2027 (estimated)
- First posted
- 13 Sep 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.
I3LUNG is an international project aiming to develop a medical device to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data). This objective will be reached through a retrospective - setting up a transnational platform of available data from 2000 patients - and a prospective - multi-omics prospective data collection in 200 NSCLS patients - study phase.
The retrospective cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model), that will be used in the prospective study phase to create a first version of the PDSS tool, an AI-based tool to provide an easy and ready-to-use access to predictive models, increasing care appropriateness, reducing the negative impacts of prolonged and toxic treatments on wellbeing and healthcare costs.
The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. This cohort will be used to validate the results obtained from the retrospective model through the creation of a new model (P-Model), which will be used to create the final PDSS tool.
Detailed description
The I3LUNG project aims to achieve the highest performance in personalized medicine through Artificial Intelligence/Machine Learning (AI/ML) modelled on multimodal patients' data, together with implementing an AI/ML model in a real-life setting. A set of patient-centered ML tools designed and validated for the project, which make use of the novel virtual patient AVATAR entity for predicting progression and outcome. To maximize its impact, the use of Trustworthy explanaible AI methodology will integrate the AI's inherent performances with the input of human intuition to construct a responsible AI application able to fully implement truly individualized treatment decisions in NSCLC interpretable and trustworthy for clinicians. The final objective is the establishment of a Worldwide Data Sharing and Elaboration Platform (DSEP). The DSEP will provide guiding tools for patients, providing information to generate awareness on treatments. Lastly, it gives access to researchers and the general scientific community to the most up-to-date data sources on NSCLC.
Within the I3LUNG project, an ad-hoc IPDAS for NSCLC patients will be developed. Patient decision aids are tools that might be used by patients either before or within a consultation with physicians. Patient decision aids explicitly represent the decision to be made and provide patients with user-friendly information about each treatment option by focusing on harms and benefits. This tool could allow patients to explain and clarify the high complexity of the information provided by the AI/ML approach. These decisional support systems have been demonstrated to be effective in empowering patients, improving their knowledge, promoting their active participation in clinical decision-making about treatments, and improving overall patient satisfaction with care while decreasing decisional conflict and decisional regret (26-30).
Finally, within the I3LUNG project it will be assessed whether using the IPDAS during the clinical consultation would foster the quality of the shared decision-making as well as the quality of the doctor-patient communication. Alongside the evaluation of the impact of the IPDAS, it will be also evaluated whether the inclusion of the AI/ML predictive models in clinical practice will be added value in supporting oncologists' clinical decision-making and decreasing cognitive fatigue and decisional conflict.
I3LUNG adopts a two-pronged approach to develop a medical device through the creation and validation of retrospective and prospective AI-based models to predict immunotherapy efficacy for NSCLC patients using the integration of multisource data (real word and multi-omics data) through a retrospective - setting up a transnational platform of available data from 2000 patients - and a prospective - multi-omics prospective data collection in 200 NSCLS patients - study phase.
The retrospective part of the I3LUNG project includes the analysis of a multicentric retrospective cohort of more than 2,000 patients. This cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model), that will be used in the prospective study phase to create a first version of the PDSS tool, an AI-based tool to provide an easy and ready-to-use access to predictive models, increasing care appropriateness, reducing the negative impacts of prolonged and toxic treatments on wellbeing and healthcare costs. Also, CT and PET scans will be collected and a first radiomic signature will be created to feed the R-Model.
The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. This cohort will be used to validate the results obtained from the retrospective model through the creation of a new model (P-Model), which will be used to create the final PDSS tool.
Study design
- Observational model
- Cohort
- Time perspective
- Other
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Retrospective Cohort | – | –This cohort includes the analysis of a multicentric retrospective cohort of more than 2,000 patients. This cohort will be used to perform a preliminary knowledge extraction phase and to build a retrospective predictive model for IO (R-Model). All available clinical data will be collected. Also, CT and PET scans will be collected and a first radiomic signature. |
| Prospective Cohort | – | –The prospective part of the project includes the collection and the analysis of multi-OMICs data from a multicentric prospective cohort of about 200 patients. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- The retrospective cohort consists of aNSCLC patients treated with IO. Data from an estimated 2000 patients treated with IO-based therapy will be collected from all the clinical partners (INT, GHD, VHIO, MH, SZMC and UOC). Informed consent for the study will be obtained before enrolment. If not feasible, i.e. patients not alive, the approval to Privacy Guarantee will be obtained. In the prospective phase, the study cohort consists of aNSCLC patients candidate for first-line IO-based therapy with available surgical samples (enough to perform OMICs). Baseline data of an estimated 200 patients from 5 clinical centers (INT, GHD, VHIO, MH and SZMC) will be collected including complete clinical, multi- OMICs analysis, imaging of CT and PET scan at baseline IO, behavioral, health economic, QoL measurements with based-sensor techniques and standard QoL. Informed consent for the study will be obtained before enrolment.
Key inclusion criteria (8 listed)
- Age >/= 18 years.
- Eastern Cooperative Oncology Group (ECOG) performance status </= 2.
- Histologically confirmed diagnosis of stage IIIB/C-IV Non-Small-Cell Lung Cancer
- Received any line immunotherapy (maintenance therapy with Durvalumab is allowed) for retrospective cohort; clinical indication for frontline treatment with immunotherapy as first line treatment for prospective cohort.
- Patients with CNS metastasis are allowed
Key exclusion criteria (3 listed)
- Patients without minimal treatment information data to be included in the retrospective cohort
- Prior treatment for advanced disease (only for prospective cohort)
- Unavailability or inability to comply with the requested study procedures, including compilation of QoL questionnaires
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
Response Rate
Time frame: 8 weeks (i.e. first radiological evaluation)
Prediction of response to immune checkpoint inhibitors in NSCLC
2 secondary outcomes
PFS
Time frame: From date of enrollment until the date of first documented progression or date of death from any cause, whichever came first, assessed up to 120 months
OS
Time frame: From date of enrollment until the date of death from any cause, assessed up to 120 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 6 Jan 2023.
- Derived from this study: PubMed 37286305Lo Russo G, Prelaj A, Dolezal J, Beninato T, Agnelli L, Triulzi T, Fabbri A, Lorenzini D, Ferrara R, Brambilla M, Occhipinti M, Mazzeo L, Provenzano L, Spagnoletti A, Viscardi G, Sgambelluri F, Brich S, Miskovic V, Pedrocchi ALG, Trovo' F, Manglaviti S, Giani C, Ambrosini P, Leporati R, Franza A, McCulloch J, Torelli T, Anichini A, Mortarini R, Trinchieri G, Pruneri G, Torri V, De Braud F, Proto C, Ganzinelli M, Garassino MC. PEOPLE (NTC03447678), a phase II trial to test pembrolizumab as first-line treatment in patients with advanced NSCLC with PD-L1 <50%: a multiomics analysis. J Immunother Cancer. 2023 Jun;11(6):e006833. doi: 10.1136/jitc-2023-006833.
- I3LUNG Website LinkLink provided by the sponsor.
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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.
4 sites in 4 countries: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Non Small Cell Lung Cancer and Lung Cancer Metastatic, run by Fondazione IRCCS Istituto Nazionale dei Tumori, Milano at 4 sites in 4 countries.
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 8 inclusion and 3 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: looking for participants now, as of the sponsor's last update on 6 Jan 2023. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 4 sites in United States, Greece, Israel, Spain. 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?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Arsela Prelaj, MD (+39 022390 3647, arsela.prelaj@istitutotumori.mi.it), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Response Rate (time frame: 8 weeks (i.e. first radiological evaluation)). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT05537922, which also lists 1 linked publication.
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 6 Jan 2023.