Ignite Creation Date:
2024-05-06 @ 3:30 PM
Last Modification Date:
2024-10-26 @ 1:51 PM
Study NCT ID:
NCT04655469
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-03-26
First Post:
2020-08-17
Brief Title:
Personal Health Train for Radiation Oncology in India and The Netherlands
Sponsor:
Maastricht Radiation Oncology
Organization:
Maastricht Radiation Oncology
Study Overview
Official Title:
Personal Health Train for Radiation Oncology in India and The Netherlands
Status:
ACTIVE_NOT_RECRUITING
Status Verified Date:
2024-03
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
TRAIN
Brief 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 eg 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
It will also allow the assessment of the effects of newly introduced radiation technology eg 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
Detailed 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 ie 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 - NWODeITy 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
The investigators have pioneered the innovative Personal Health Train approach whereby support for choosing the best treatment ie 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 - NWODeITy 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
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None