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Model-guided therapy for hepatocellular carcinoma: a role for information technology in predictive, preventive and personalized medicine.

Berliner L, Lemke HU, vanSonnenberg E, Ashamalla H, Mattes MD, Dosik D, Hazin H, Shah S, Mohanty S, Verma S, Esposito G, Bargellini I, Battaglia V, Caramella D, Bartolozzi C, Morrison P - EPMA J (2014)

Bottom Line: We may, then, be able to develop a statistically valid methodology, on an individual basis, to predict certain diseases or conditions, to predict certain treatment outcomes, to prevent certain diseases or complications and to develop treatment regimens that are personalized for that particular patient.An IT system for predictive, preventive and personalized medicine (ITS-PM) for HCC is presented to provide a comprehensive system to provide unified access to general medical and patient-specific information for medical researchers and health care providers from different disciplines including hepatologists, gastroenterologists, medical and surgical oncologists, liver transplant teams, interventional radiologists and radiation oncologists.The article concludes with a review providing an outlook and recommendations for the application of MGT to enhance the medical management of HCC through PPPM.

View Article: PubMed Central - HTML - PubMed

Affiliation: New York Methodist Hospital, Brooklyn, NY 11215, USA ; Weill Medical College of Cornell University, New York, NY 10021, USA.

ABSTRACT
Predictive, preventive and personalized medicine (PPPM) may have the potential to eventually improve the nature of health care delivery. However, the tools required for a practical and comprehensive form of PPPM that is capable of handling the vast amounts of medical information that is currently available are currently lacking. This article reviews a rationale and method for combining and integrating diagnostic and therapeutic management with information technology (IT), in a manner that supports patients through their continuum of care. It is imperative that any program devised to explore and develop personalized health care delivery must be firmly rooted in clinically confirmed and accepted principles and technologies. Therefore, a use case, relating to hepatocellular carcinoma (HCC), was developed. The approach to the management of medical information we have taken is based on model theory and seeks to implement a form of model-guided therapy (MGT) that can be used as a decision support system in the treatment of patients with HCC. The IT structures to be utilized in MGT include a therapy imaging and model management system (TIMMS) and a digital patient model (DPM). The system that we propose will utilize patient modeling techniques to generate valid DPMs (which factor in age, physiologic condition, disease and co-morbidities, genetics, biomarkers and responses to previous treatments). We may, then, be able to develop a statistically valid methodology, on an individual basis, to predict certain diseases or conditions, to predict certain treatment outcomes, to prevent certain diseases or complications and to develop treatment regimens that are personalized for that particular patient. An IT system for predictive, preventive and personalized medicine (ITS-PM) for HCC is presented to provide a comprehensive system to provide unified access to general medical and patient-specific information for medical researchers and health care providers from different disciplines including hepatologists, gastroenterologists, medical and surgical oncologists, liver transplant teams, interventional radiologists and radiation oncologists. The article concludes with a review providing an outlook and recommendations for the application of MGT to enhance the medical management of HCC through PPPM.

No MeSH data available.


Related in: MedlinePlus

Alternative therapy chart: single lesions.
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Figure 10: Alternative therapy chart: single lesions.

Mentions: New algorithms are presented here that address issues and patient selection relating to alternatives in palliative treatments and efforts to achieve down-staging. Currently available treatments for HCC included in these algorithms are surgical resection, liver transplantation, percutaneous ablation, TACE, radioembolization with yttrium-90 microspheres, stereotactic body radiation therapy (SBRT) and systemic targeted therapy with the oral multikinase inhibitor, sorafenib. In accordance with the BCLC staging system, the efficacy and safety of each treatment modality depends on the stage of liver disease, performance status of the patient and severity of underlying liver disease.Treatment algorithms are presented here (FiguresĀ 9,10 and11) that represent extensions to the BCLC staging system algorithm by providing a flexible approach to alternative therapies and by introducing the possibility of down-staging and bridging therapy.


Model-guided therapy for hepatocellular carcinoma: a role for information technology in predictive, preventive and personalized medicine.

Berliner L, Lemke HU, vanSonnenberg E, Ashamalla H, Mattes MD, Dosik D, Hazin H, Shah S, Mohanty S, Verma S, Esposito G, Bargellini I, Battaglia V, Caramella D, Bartolozzi C, Morrison P - EPMA J (2014)

Alternative therapy chart: single lesions.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4274760&req=5

Figure 10: Alternative therapy chart: single lesions.
Mentions: New algorithms are presented here that address issues and patient selection relating to alternatives in palliative treatments and efforts to achieve down-staging. Currently available treatments for HCC included in these algorithms are surgical resection, liver transplantation, percutaneous ablation, TACE, radioembolization with yttrium-90 microspheres, stereotactic body radiation therapy (SBRT) and systemic targeted therapy with the oral multikinase inhibitor, sorafenib. In accordance with the BCLC staging system, the efficacy and safety of each treatment modality depends on the stage of liver disease, performance status of the patient and severity of underlying liver disease.Treatment algorithms are presented here (FiguresĀ 9,10 and11) that represent extensions to the BCLC staging system algorithm by providing a flexible approach to alternative therapies and by introducing the possibility of down-staging and bridging therapy.

Bottom Line: We may, then, be able to develop a statistically valid methodology, on an individual basis, to predict certain diseases or conditions, to predict certain treatment outcomes, to prevent certain diseases or complications and to develop treatment regimens that are personalized for that particular patient.An IT system for predictive, preventive and personalized medicine (ITS-PM) for HCC is presented to provide a comprehensive system to provide unified access to general medical and patient-specific information for medical researchers and health care providers from different disciplines including hepatologists, gastroenterologists, medical and surgical oncologists, liver transplant teams, interventional radiologists and radiation oncologists.The article concludes with a review providing an outlook and recommendations for the application of MGT to enhance the medical management of HCC through PPPM.

View Article: PubMed Central - HTML - PubMed

Affiliation: New York Methodist Hospital, Brooklyn, NY 11215, USA ; Weill Medical College of Cornell University, New York, NY 10021, USA.

ABSTRACT
Predictive, preventive and personalized medicine (PPPM) may have the potential to eventually improve the nature of health care delivery. However, the tools required for a practical and comprehensive form of PPPM that is capable of handling the vast amounts of medical information that is currently available are currently lacking. This article reviews a rationale and method for combining and integrating diagnostic and therapeutic management with information technology (IT), in a manner that supports patients through their continuum of care. It is imperative that any program devised to explore and develop personalized health care delivery must be firmly rooted in clinically confirmed and accepted principles and technologies. Therefore, a use case, relating to hepatocellular carcinoma (HCC), was developed. The approach to the management of medical information we have taken is based on model theory and seeks to implement a form of model-guided therapy (MGT) that can be used as a decision support system in the treatment of patients with HCC. The IT structures to be utilized in MGT include a therapy imaging and model management system (TIMMS) and a digital patient model (DPM). The system that we propose will utilize patient modeling techniques to generate valid DPMs (which factor in age, physiologic condition, disease and co-morbidities, genetics, biomarkers and responses to previous treatments). We may, then, be able to develop a statistically valid methodology, on an individual basis, to predict certain diseases or conditions, to predict certain treatment outcomes, to prevent certain diseases or complications and to develop treatment regimens that are personalized for that particular patient. An IT system for predictive, preventive and personalized medicine (ITS-PM) for HCC is presented to provide a comprehensive system to provide unified access to general medical and patient-specific information for medical researchers and health care providers from different disciplines including hepatologists, gastroenterologists, medical and surgical oncologists, liver transplant teams, interventional radiologists and radiation oncologists. The article concludes with a review providing an outlook and recommendations for the application of MGT to enhance the medical management of HCC through PPPM.

No MeSH data available.


Related in: MedlinePlus