AI-HOPE Lung Cancer: Building a Predictive Tool for Metastatic Lung Cancer
ConditionNSCLC Stage IV
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorIRCCS San Raffaele
About this trial
The goal of our project is building a predictive response algorithm for patients with metastatic lung cancer, exploiting an artificial intelligence platform. It will collect patient information from all areas (clinical, laboratory, radiological, pathological) and analyse them, understanding connections and correlations, both at baseline and at pre-specified timepoints. It would lead to the development of a reliable and constantly evolving predictive score, able to continuously re-weight the importance of each variable as new data come in.
Since the greatest clinical need is identifying non-responders to immunotherapy and chemo-immunotherapy combination (30% of all treated patients), these two populations are defined as the starting cohorts (Cohort A, immunotherapy alone, Cohort B, chemo-immunotherapy combinations).
For each cohort, three main questions are to be answered:
Q1) Early progressors (defined as progressive disease or death within three months of treatment or at first radiological restaging) Q2) Toxicity (with a special focus on severe toxicities G≥3) Q3) Long survivors (defined as patients reaching an overall survival of at least 1.5x median overall survival in registrative trials)
The early identification of non-responders, high-risk patients (or on the other hand, long survivors) would help their healthcare planning, providing individualised follow-up strategies or prompting their inclusion in alternative treatments (eg clinical trials).
For all cohorts, first data entry will be retrospective and second data entry will be prospective (as validation set).
Eligibility criteria
This trial does not accept healthy volunteersQualifiers
Patients with histological or cytological diagnosis of NSCLC
Stage IV according to investigator's staging procedures (or any locally advanced tumour not feasible for local radical treatment)
Treatment with at least 1 cycle of mono-immunotherapy or chemo-immunotherapy (as per clinical practice)
Availability of follow-up
Disqualifiers
Patients with other thoracic tumours non-NSCLC (i.e. SCLC)
Stage other than IV or feasible for radical treatment upfront
Treatment within clinical trials (with combination regimens different from the aforementioned combinations)
Lost to follow-up
Trial population
Patients with NSCLC stage IV treated with at least 1 cycle of first-line treatment
Trial design
Design model
Cohort
Time perspective
Cross-sectional
Treatments tested in this trial
Immunotherapy
DrugFirst-line regimen according to clinical practice
Chemotherapy
DrugFirst-line regimen according to clinical practice
Treatment groups
2,000 Participants
are divided into 2 treatment groupsGroup A: Mono-immunotherapy1 intervention
Group B: Chemo-immunotherapy2 interventions
Trial outcomes
Primary outcomes
1
Early progressive disease
Number of patients experiencing progressive disease (PD) as best response to first-line treatment
Time frame
From date of enrolment until the date of first documented disease progression or death, whichever comes first, assessed within 8 to 12 weeks from first-line treatment start2
Lung toxicity
Number of patients experiencing immune-related pneumonitis of G3 or more
Time frame
From date of enrolment until the date of first documented immune-related pneumonitis of G3 or more, assessed up to 96 months3
Long survivors
Numbero of patients experiencing an overall survival (time from treatment initiation to death) longer than 3 years (1.5x median overall survival from clinical trials)
Time frame
At a 3-year cut-offSponsors and contacts
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Source ClinicalTrials.gov