Literature DB >> 31432349

New CT-based diagnoses of torso cancer is low in the emergency department setting.

Inessa A Goldman1, Alain Cunqueiro1, Meir H Scheinfeld2.   

Abstract

PURPOSE: The incidence of new CT-based torso cancer diagnoses and the most commonly diagnosed cancer types in the emergency department (ED) setting are unknown. The purpose of our study was to determine the incidence and types of new CT-based torso cancer diagnoses in the ED.
METHODS: A total of 19,496 CT reports including all or parts of the torso from 2017 were searched for the keywords: "mass", "tumor", "neoplasm", "malignancy", or "cancer". Each report and corresponding medical record was evaluated for presence of a new cancer. Cases were scored as no cancer, subcentimeter lung nodule, known cancer, new cancer, or suspicious, but unconfirmed for new cancer. Each mass was characterized as symptom-related or incidental.
RESULTS: At least one keyword was found in 2086 reports. Of these 706, 126 and 905 were known cancer cases, subcentimeter lung nodules, and non-cancerous cases, respectively. There were 251 confirmed new cancers and 98 suspicious cases which lacked adequate diagnostic workup. Depending on whether only definite or definite and suspicious cases were included together, the number of new cancer cases per 100 torso CT exams was 1.3 or 1.8, respectively. Gastrointestinal, lung, pancreaticobiliary, urinary, and gynecologic cancers were most common. Only 58 of the confirmed cases (23%) were deemed as incidental findings.
CONCLUSION: CT-diagnosis of new torso cancers was uncommon in our setting. Still, while extensive knowledge of cancer staging may not be necessary for ED radiologists, knowledge of the most common types of cancer including gastrointestinal, lung, pancreaticobiliary, urinary, and gynecologic cancers may improve sensitivity for these diagnoses and may expedite appropriate referrals for the newly diagnosed patients.

Entities:  

Keywords:  CT; Cancer diagnosis; Cancer incidence; Diagnosis; Emergency department

Mesh:

Year:  2019        PMID: 31432349     DOI: 10.1007/s10140-019-01715-x

Source DB:  PubMed          Journal:  Emerg Radiol        ISSN: 1070-3004


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