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In addition to my clinical research in head and neck and lung cancer, I work on the application of computer science and machine learning to cancer research. I develop tools for analyzing large datasets to improve outcomes and safety of cancer treatment. I developed a machine learning prognostic model using data from around 13,000 patients with metastatic cancer which performs better than traditional models and physicians [PubMed ID 33313792]. We recently completed a prospective randomized study in thousands of patients in which the model was used to help improve advance care planning conversations.I also work on the methods underpinning observational and predictive modeling research. My open source nnet-survival software that allows use of neural networks for survival modeling has been used by researchers internationally. In collaboration with the Stanford Research Informatics Center, I examined how electronic medical record (EMR) survival outcome data compares to gold-standard data from a cancer registry [PubMed ID 35802836]. The EMR data captured less than 50% of deaths, a finding that affects many studies being published that use EMR outcomes data.
Trial of XRD-0394, a Kinase Inhibitor, in Combination With Palliative Radiotherapy in Advanced Cancer Patients
XRD-0394 is a novel, potent, oral, small molecule dual inhibitor of ataxia telangiectasia
mutated kinase (ATM) and deoxyribonucleic acid (DNA)-dependent protein kinase (DNA-PK) that
has selectivity compared with other phosphatidylinositol 3-kinase-related kinase (PIKK)
family enzymes. This is a first-time-in-human study, which means that it is the first time
the study drug is being used in humans. The purpose of the study is to evaluate the safety
and tolerability of single doses of XRD-0394 administered with palliative radiotherapy (RT)
to subjects with metastatic, locally advanced, or recurrent cancer. The pharmacokinetic (PK)
profile and pharmacodynamic (PD) effects of single-dose XRD-0394 administered in combination
with palliative RT will also be characterized.
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Testing Docetaxel-Cetuximab or the Addition of an Immunotherapy Drug, Atezolizumab, to the Usual Chemotherapy and Radiation Therapy in High-Risk Head and Neck Cancer
This phase II/III trial studies how well radiation therapy works when given together with
cisplatin, docetaxel, cetuximab, and/or atezolizumab after surgery in treating patients with
high-risk stage III-IV head and neck cancer the begins in the thin, flat cells (squamous
cell). Specialized radiation therapy that delivers a high dose of radiation directly to the
tumor may kill more tumor cells and cause less damage to normal tissue. Drugs used in
chemotherapy, such as cisplatin and docetaxel, work in different ways to stop the growth of
tumor cells, either by killing the cells or by stopping them from dividing. Cetuximab is a
monoclonal antibody that may interfere with the ability of tumor cells to grow and spread.
Immunotherapy with monoclonal antibodies, such as atezolizumab, may help the body's immune
system attack the cancer, and may interfere with the ability of tumor cells to grow and
spread. The purpose of this study is to compare the usual treatment (radiation therapy with
cisplatin chemotherapy) to using radiation therapy with docetaxel and cetuximab chemotherapy,
and using the usual treatment plus an immunotherapy drug, atezolizumab.
Radical-Dose Image Guided Radiation Therapy in Treating Patients With Metastatic Non-small Cell Lung Cancer Undergoing Immunotherapy
This phase II trial studies how well radical-dose image guided radiation therapy works in
treating patients with non-small cell lung cancer that has spread to other places in the body
who are undergoing immunotherapy. Radiation therapy uses high energy x-rays to kill tumor
cells and shrink tumors. Giving radical-dose image guided radiation therapy to patients with
non-small cell lung cancer may help to improve response to immunotherapy anti-cancer
Stanford is currently not accepting patients for this trial.
For more information, please contact Kim Nguyen, 650-497-8966.