Clinical Trial Details
— Status: Active, not recruiting
Administrative data
| NCT number |
NCT04655469 |
| Other study ID # |
629.002.212 |
| Secondary ID |
|
| Status |
Active, not recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
April 10, 2020 |
| Est. completion date |
November 1, 2024 |
Study information
| Verified date |
March 2024 |
| Source |
Maastricht Radiation Oncology |
| Contact |
n/a |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
The primary and general objective of this protocol as the current standard of care is to
improve the quality of radiotherapy for HNC patients. This will ultimately be achieved by
optimizing locoregional tumour control and overall survival and by reducing radiation-induced
side effects.
It will also allow the assessment of the effects of newly introduced radiation technology
(e.g. proton therapy) for this particular group of patients.
The clinical introduction of this standard follow-up program (SFP) will allow for a
systematic and broad scale quality improvement cycle for HNC patients treated with
radiotherapy.
Description:
"Big data analytics in cancer care holds immense potential to unlock valuable clinical
insights from an abundance of patient medical records, aided by sophisticated statistical
models, that will lead to improved population-based outcomes and deeper personalization of
cancer treatment. However, the clinical data (which includes medical images, clinical
examinations and laboratory results) has been locked away in disconnected "silos" within
every clinic. Additionally, patient information is exceedingly sensitive to privacy issues
and confidentiality breaches.
The investigators have pioneered the innovative Personal Health Train approach, whereby
support for choosing the best treatment (i.e. decision support) is accessible without any
patient records ever leaving the clinic of origin. This extends our current work on an
extensible data architecture to learn from quantitative imaging data in India and The
Netherlands (without images being taken out of the clinic) - NWO/DeITy BIONIC. The
investigators have now developed numerous models of clinical outcome after treatment,
including those for undesirable side-effects of treatment. The investigators continue to lead
big data integration work within multicenter clinical decision support projects such as
KWF-ProTraIT and Horizon2020-BD2DECIDE.
The overall aim of the TRAIN project is to combine big data (including images, laboratory
tests and clinical examinations) to improve the outcomes for head & neck cancer patients in
both India and The Netherlands. The investigators will do this by creating data-driven
Decision Support Systems to predict which treatment gives the best outcome given individual
patient characteristics, and local diagnostic and treatment capabilities. Cancer specialists
in both countries will lead the design and clinical evaluation of this decision support
system, which could be deployed in multiple clinics across all of the settings encountered in
India and The Netherlands.
Head and neck cancer is a relatively rare condition in the Netherlands, such that the data
volume available to learn from is much smaller than in India. Conversely, Indian patients
typically present at a more advanced stage of cancer compared to Dutch patients. These
differences in patients and treatments can be leveraged by machine learning algorithms to
learn better predictive models. Decision support systems are essential, since guideline
deviations in both countries are common due to individual patient characteristics, patient
preferences and uneven distribution of treatment capacity outside major urban centers.
To achieve the above, The investigators first deploy the ICT infrastructure (in collaboration
with Philips India) to connect local hospital information systems so that clinical, imaging
and outcome data on head & neck cancer patients becomes findable, accessible, interoperable
and reusable (FAIR) big data. The investigators then deploy learning algorithms that traverse
the big data repositories of each participating hospital, using the privacy-preserving
Personal Health Train approach, to develop a decision support system. Cancer specialists in
India and the Netherlands will jointly evaluate the clinical utility of the decision support
system by means of a prospective randomized clinical trial."
