Related Experiment Video For diagnostic delay
Updated: Jun 24, 2025

MicroRNA Based Liquid Biopsy: The Experience of the Plasma miRNA Signature Classifier MSC for Lung Cancer Screening
Published on: October 26, 2017
Navigating the Pitfalls of Lung Cancer Screening: A Case Study on the Risks and Costs of Negative Screenings
Hoda Shabpiray1, Jerrin George1, Shivani Patel1
1Department of Medicine, The University of Toledo College of Medicine and Life Sciences, Toledo, USA.
Abstract:
Lung cancer is the leading cause of cancer-related deaths in the United States. Low-dose computed tomography is the preferred screening method for high-risk individuals. However, with a false-negative rate reaching 15%, this method can underestimate disease prevalence and delay necessary treatment. This case examines a 61-year-old female smoker with chronic obstructive pulmonary disease who initially received a negative result from screening. Her imaging findings were categorized as Lung Imaging Reporting and Data System (Lung-RADS) 2 but advanced to small cell lung carcinoma. This progression emphasizes the imperative of thoroughly evaluating screening results and patient history. False-negative results from screenings have profound implications, leading to delayed diagnoses, adversely affecting patient outcomes, and increasing healthcare costs. The necessity for vigilant follow-up enhanced diagnostic precision and transparent communication about limitations is paramount. An economic analysis emphasizes the significant financial impact of diagnosing lung cancer at advanced stages, highlighting the need for timely and accurate diagnostics. Comprehensive strategies, such as physician education, patient awareness, and stringent quality control, are crucial to improving the efficacy of lung cancer screening. Addressing the issue of false negatives is vital for enhancing early detection rates, decreasing healthcare expenses, and advancing patient care in lung cancer management. Continuous evaluation and adjustment of screening protocols are essential to reduce risks and optimize outcomes.
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