Non-Small Cell Lung Cancer Coverage from Every Angle

How Accurate Are Chest X-rays in Detecting Lung Cancer?

By: Dana A. Elya, MS, RD, CDN
Posted: Wednesday, November 13, 2019

A systematic review article by Stephen H. Bradley, of the University of Leeds, United Kingdom, and colleagues suggests that chest x-ray may have a false-negative rate of at least 20% in the diagnosis of lung cancer. Although chest x-ray remains the first-line modality for suspected lung cancer in primary care in the United Kingdom, they noted, high-risk patients who have a negative chest x-ray may require further investigation. The study findings were published in the British Journal of General Practice.

“X-ray has been with us for a long time, but surprisingly, there has been very little research into how accurate it is for diagnosing lung cancer,” the investigators noted. “If chest x-ray were a novel technology, it is debatable whether the available evidence would be deemed sufficient to support its implementation as a diagnostic test for lung cancer.”

The systematic review was performed to determine the sensitivity of chest x-rays in the detection of lung cancer. Data were assembled from MEDLINE, EMBASE, and the Cochrane Library. From a total of 21 studies, the authors identified 3 that reported the sensitivity of chest x-ray and had a low risk of bias. Two primary care studies reported sensitivities of 76.8% and 79.3%, and one secondary care study reported a sensitivity of 79.7%. The highest-quality studies suggest that the sensitivity of chest x-ray for symptomatic lung cancer is somewhere between 77% and 80%.

“[UK] lung cancer outcomes still lag behind other high-income countries, with less patients diagnosed at early stages of the illness,” the authors concluded. “There are likely to be many reasons for this, but this research suggests that one factor could be our reliance on chest x-ray, compared to other countries that make more use of tests like computed tomography scans.”

Disclosure: The study authors’ disclosure information can be found at

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