Publications by authors named "Garrett Green"

Background: The Irish Out-of-Hospital Cardiac Arrest registry (OHCAR) collects data based on the internationally recognised Utstein template. The Utstein comparator group (bystander witnessed and initial shockable rhythm) has specific relevance in benchmarking out-of-hospital cardiac arrest (OHCA) health system performance.

Aims: To describe OHCA in the Utstein comparator group during 2012 to 2020 in Ireland.

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Treatments for locoregionally advanced head and neck cancer (LAHNC) negatively impact swallowing function, but the long-term incidence of severe toxicity requiring esophageal dilation is not well-documented in the population. The aim of this study was to compare the incidence of long-term esophageal dilation across varying treatments for LAHNC. We identified 5,223 patients with LAHNC diagnosed from 2000 to 2009 in the SEER-Medicare database.

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Purpose: Validated models are needed to justify strategies to define planning target volumes (PTVs) for intact cervical cancer used in clinical practice. Our objective was to independently validate a previously published shape model, using data collected prospectively from clinical trials.

Methods And Materials: We analyzed 42 patients with intact cervical cancer treated with daily fractionated pelvic intensity modulated radiation therapy and concurrent chemotherapy in one of 2 prospective clinical trials.

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As genetic information becomes more readily available, there is increasing demand from both patients and providers to develop personalized approaches to cancer care. Investigators are increasingly reporting numbers of studies correlating genomic signatures and other biomarkers to survival endpoints. The extent to which cancer-specific and non-specific effects are reported in contemporary studies is unknown.

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Purpose: To compare a novel generalized competing event (GCE) model versus the standard Cox proportional hazards regression model for stratifying elderly patients with cancer who are at risk for competing events.

Methods: We identified 84,319 patients with nonmetastatic prostate, head and neck, and breast cancers from the SEER-Medicare database. Using demographic, tumor, and clinical characteristics, we trained risk scores on the basis of GCE versus Cox models for cancer-specific mortality and all-cause mortality.

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