CT image biomarkers to improve patient-specific prediction of radiation-induced xerostomia and sticky saliva

While the clinical approval process is able to filter out medications whose utility does not offset their adverse drug reaction profile in humans, it is not well suited to characterizing lower frequency issues and idiosyncratic multi-drug interactions that can happen in real world diverse patient populations. With a growing abundance of real-world evidence databases containing hundreds of thousands of patient records, it is now feasible to build machine learning models that incorporate individual patient information to provide personalized adverse event predictions. In this study, we build models that integrate patient specific demographic, clinical, and genetic features (when available) with drug structure to predict adverse drug reactions. We develop an extensible graph convolutional approach to be able to integrate molecular effects from the variable number of medications a typical patient may be taking. Our model outperforms standard machine learning methods at the tasks of predicting hospitalization and death in the UK Biobank dataset yielding an R2 of 0.37 and an AUC of 0.90, respectively. We believe our model has potential for evaluating new therapeutic compounds for individualized toxicities in real world diverse populations. It can also be used to prioritize medications when there are multiple options being considered for treatment.

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A method of ultrasound simulation from patient-specific CT image data: A preliminary simulation study

2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) ◽

10.1109/isbi.2018.8363853 ◽

2018 ◽

Cited By ~ 1

Author(s):

Anila Satheesh B. ◽

Arun K. Thittai

Keyword(s):

Simulation Study ◽

Image Data ◽

Patient Specific ◽

Ct Image ◽

Ultrasound Simulation

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Premedications for Cancer Therapies: A Primer for the Hematology/Oncology Provider

Journal of the Advanced Practitioner in Oncology ◽

10.6004/jadpro.2021.12.8.4 ◽

2021 ◽

Vol 12 (8) ◽

Author(s):

Amber Clemmons, PharmD, BCOP ◽

Arpita Gandhi, PharmD, BCOP ◽

Andrea Clarke, PharmD ◽

Sarah Jimenez, APN-BC, AGACNP, AOCNP ◽

Thuy Le, MD ◽

...

Keyword(s):

Best Practices ◽

Adverse Events ◽

Chemotherapeutic Agents ◽

Patient Specific ◽

Cancer Therapies ◽

Quality Of Data ◽

Advanced Practitioner ◽

Patients At Risk ◽

Radiation Induced

Chemotherapeutic agents and radiation therapy are associated with numerous potential adverse events (AEs). Many of these common AEs, namely chemotherapy- or radiation-induced nausea and vomiting, hypersensitivity reactions, and edema, can lead to deleterious outcomes (such as treatment nonadherence or cessation, or poor clinical outcomes) if not prevented appropriately. The occurrence and severity of these AEs can be prevented with the correct prescribing of prophylactic medications, often called “premedications.” The advanced practitioner in hematology/oncology should have a good understanding of which chemotherapeutic agents are known to place patients at risk for these adverse events as well as be able to determine appropriate prophylactic medications to employ in the prevention of these adverse events. While several guidelines and literature exist regarding best practices for prophylaxis strategies, differences among guidelines and quality of data should be explored in order to accurately implement patient-specific recommendations. Herein, we review the existing literature for prophylaxis and summarize best practices.

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Deficiency of 15-LOX-1 Induces Radioresistance through Downregulation of MacroH2A2 in Colorectal Cancer

Cancers ◽

10.3390/cancers11111776 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1776 ◽

Cited By ~ 1

Author(s):

Yoo Jin Na ◽

Bo Ram Kim ◽

Jung Lim Kim ◽

Sanghee Kang ◽

Yoon A. Jeong ◽

...

Keyword(s):

Colorectal Cancer ◽

Dna Damage ◽

Specific Treatment ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Patient Specific ◽

Histone H2a ◽

Gene Set Enrichment ◽

Damage Response ◽

Radiation Induced

Despite the importance of radiation therapy, there are few radiation-related markers available for use in clinical practice. A larger catalog of such biomarkers is required to help clinicians decide when radiotherapy should be replaced with a patient-specific treatment. Arachidonate 15-lipoxygenase (15-LOX-1) enzyme is involved in polyunsaturated fatty acid metabolism. When colorectal cancer (CRC) cells were exposed to radiation, 15-LOX-1 was upregulated. To verify whether 15-LOX-1 protects against or induces DNA damage, we irradiated sh15-LOX-1 stable cells. We found that low 15-LOX-1 is correlated with radioresistance in CRC cells. These data suggest that the presence of 15-LOX-1 can be used as a marker for radiation-induced DNA damage. Consistent with this observation, gene-set-enrichment analysis based on microarray experiments showed that UV_RESPONSE was decreased in sh15-LOX-1 cells compared to shCon cells. Moreover, we discovered that the expression of the histone H2A variant macroH2A2 was sevenfold lower in sh15-LOX-1 cells. Overall, our findings present mechanistic evidence that macroH2A2 is transcriptionally regulated by 15-LOX-1 and suppresses the DNA damage response in irradiated cells by delaying H2AX activation.

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Prediction of hemodynamics after atrial septal defect closure using a framework of circulatory equilibrium in dogs

AJP Heart and Circulatory Physiology ◽

10.1152/ajpheart.00098.2020 ◽

2020 ◽

Vol 319 (5) ◽

pp. H938-H947

Author(s):

Kiyoshi Uike ◽

Keita Saku ◽

Takuya Nishikawa ◽

Kenichiro Yamamura ◽

Hazumu Nagata ◽

...

Keyword(s):

Atrial Septal Defect ◽

Septal Defect ◽

Safety Management ◽

Patient Specific ◽

Defect Closure ◽

Atrial Septal Defect Closure ◽

Shunt Flow ◽

Specific Prediction ◽

Asd Closure ◽

The Impact

We developed a framework to predict the impact of atrial septal defect (ASD) closure on hemodynamics by incorporating ASD shunt flow into the framework of circulatory equilibrium. The proposed framework accurately predicted hemodynamics after ASD closure. Patient-specific prediction of hemodynamics may be useful for safety management of ASD closure.

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