Clinical trial NCT06329648: Distributed Learning of Edic and CardIac Dose Effects in Lung Cancer
Official title: Distributed Learning of Edic and CardIac Dose Effects in Lung Cancer
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: NSCLC
Lead sponsor: The Netherlands Cancer Institute
Sponsor class: OTHER
First posted: 2024-03-26
Enrollment: 20000
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: This study has been designed as a retrospective, non-experimental, non-control, multiplecentre cohort investigation.

Brief summary: Cardiac dose was not a major concern in lung radiotherapy patients until the results of the RTOG (Radiation Therapy Oncology Group) 0617 trial, which showed an association between cardiac dose and survival. Since then, many papers have studied the association between cardiac (substructure) dose and either survival or cardiac toxicity. Ideally, cardiac toxicity would be separated from survival. However, scoring cardiac toxicity prospectively was not standard practice, and retrospective scoring is challenging because of the overlap of cardiac toxicity symptoms and lung cancer (treatment) symptoms. Therefore in real world cohorts, cardiac toxicity is usually not scored properly and most larger studies pragmatically consider overall survival as primary endpoint, and the relation between cardiac dose and cardiac toxicity is not well established for lung cancer patients.

Cardiac toxicity might not be the only factor in decreased survival; toxicity of the immune system might be a competing risk or a major contributing factor, where dose to the heart is a surrogate for dose to blood. Dose to the immune system is defined as EDIC (Effective Dose to circulating Immune Cells), comprising heart dose, lung dose and body dose combined. As EDIC dose and cardiac dose partly overlap, a large cohort with substantial variation will be required to disentangle the two effects. Such vast amounts of routine care data are immediately available in many radiotherapy centers all over the world. The problem we face is not the lack of routine care data, but making such data available for analysis. DECIDE adopts a federated learning approach, which implies that data does not have to be centralized within a single institution to be fit for use. We aim to include an unprecedentedly large-scale cohort of 20,000 patients.

In this proposal, we need to add on scientific and technological innovations that exploit the existing federated learning framework to scale up to supporting \>25 simultaneously connected partners. We will be training (generalized) linear epidemiological models as well as new computer vision-based models for outcome predictions. As cause-specific survival (cardiac toxicity or immune toxicity) is unavailable or unreliable in major studies, we will use the more pragmatic endpoint of survival. By elucidating the clinical contributions of whole heart dose, cardiac substructure dose and EDIC dose in combination with known clinical risk factors, the desired impact is to change clinical practice for lung cancer radiotherapy and improve survival.


Eligibility criteria: Inclusion Criteria:

* Pathologically confirmed primary diagnosis of non-small cell lung cancer (NSCLC) stage I - III
* Subjects must have been treated by primary radiotherapy - e.g. 3D-conformal, intensity modulated, arc therapy or stereotactic body radiotherapy - and either with or without chemotherapy.
* Mandatory data elements (see below) are available

Exclusion Criteria:

* Subjects under 18 years of age.
* Vulnerable groups or individuals (as per WMA Helsinki Declaration) that have not given consent to be treated with radiotherapy by a qualified physician at the participating centre.
* Primary cancer was not NSCLC or SCLC.
* Surgical resection of lung (wedge, lobectomy, etc.) prior to radiotherapy.
* CT studies and corresponding GTV delineations were previously made publicly available via open access data repositories.

Primary outcomes:
measure: Optimize EDIC dose
timeFrame: 4 years
Secondary outcomes:
measure: cardiac toxicity
timeFrame: 4 years
Other outcomes:
Locations:
Study officials:
affiliation: The Netherlands Cancer Institute
name: Barbara Stam, PhD
role: PRINCIPAL_INVESTIGATOR
References: