Clinical trial NCT06788366: AI-HOPE Lung Cancer: Building a Predictive Tool for Metastatic Lung Cancer
Official title: AI-HOPE Lung Cancer: Building a Predictive Tool for Metastatic Lung Cancer
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: NSCLC Stage IV
Lead sponsor: IRCCS San Raffaele
Sponsor class: OTHER
First posted: 2025-01-23
Enrollment: 2000
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: CROSS_SECTIONAL
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Patients with NSCLC stage IV treated with at least 1 cycle of first-line treatment

Brief summary: 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: Inclusion criteria:

* 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

Exclusion criteria:

* 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

Primary outcomes:
measure: Early progressive disease
timeFrame: 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 start
measure: Lung toxicity
timeFrame: From date of enrolment until the date of first documented immune-related pneumonitis of G3 or more, assessed up to 96 months
measure: Long survivors
timeFrame: At a 3-year cut-off
Secondary outcomes:
Other outcomes:
Locations:
city: Milan
country: Italy
facility: Francesca Rita Ogliari
Study officials:
References: