Abstract
Simple SummaryEsophageal cancer (EC) has a poor prognosis when the diagnosis is delayed, but curative treatment is possible if the diagnosis is timely. The disease subtly progresses before symptoms prompt patients to seek medical attention. Effective pre-symptomatic screening strategies may improve the outcome of the disease. Recent evidence provided insights into early diagnosis of EC via blood tests, advanced endoscopic imaging, and artificial intelligence. Accordingly, we reviewed available strategies to diagnose early EC. Esophageal cancer (EC) is the seventh most common cancer and the sixth cause of cancer death worldwide. Histologically, esophageal squamous cell carcinoma (ESCC) and esophageal adenocarcinoma (EAC) account for up to 90% and 20% of all ECs, respectively. Clinical symptoms such as dysphagia, odynophagia, and bolus impaction occur late in the natural history of the disease, and the diagnosis is often delayed. The prognosis of ESCC and EAC is poor in advanced stages, being survival rates less than 20% at five years. However, when the diagnosis is achieved early, curative treatment is possible, and survival exceeds 80%. For these reasons, mass screening strategies for EC are highly desirable, and several options are currently under investigation. Blood biomarkers offer an inexpensive, non-invasive screening strategy for cancers, and novel technologies have allowed the identification of candidate markers for EC. The esophagus is easily accessible via endoscopy, and endoscopic imaging represents the gold standard for cancer surveillance. However, lesion recognition during endoscopic procedures is hampered by interobserver variability. To fill this gap, artificial intelligence (AI) has recently been explored and provided encouraging results. In this review, we provide a summary of currently available options to achieve early diagnosis of EC, focusing on blood biomarkers, advanced endoscopy, and AI.
Highlights
In 2018 esophageal cancer (EC) was estimated to account for 508,000 deaths, being the seventh most common cancer and the sixth cause of cancer death worldwide [1]
In a meta-analysis [14], the sensitivity and specificity of CEA ranged from 8% to 70%, and from 57% to 100%, respectively, while its positive likelihood ratio (PLR) was 5.94 (95% confidence interval [CI], 3.24–10.89) meaning that patients with EC have a six-fold higher chance of having increased CEA levels compared to patients without EC [14]
In the diagnosis of esophageal squamous cell carcinoma (ESCC), artificial intelligence (AI) performed significantly better with narrow-band imaging (NBI) compared to white light endoscopy (WLE), achieving an area under the curve (AUC) of 0.92 and 0.83, respectively
Summary
In 2018 esophageal cancer (EC) was estimated to account for 508,000 deaths, being the seventh most common cancer and the sixth cause of cancer death worldwide [1]. EC includes esophageal squamous cell carcinoma (ESCC) and adenocarcinoma (EAC). ESCC accounts for up to 90% of ECs in lower-income countries and in those regions spanning from Asian republics to north-central China, known as the “esophageal cancer belt” [3,4]. Due to the late onset of clinical symptoms and the lack of early disease markers, EC is often diagnosed in advanced stages, when the prognosis is poor: ESCC has an overall 5-year survival rate of 18%, which decreases to less than 5%, when distant metastases are present at diagnosis [3]. When EAC is diagnosed in advanced stages, the disease has a 5-year survival rate of less than 20% [1,6]. We reviewed the most recent literature addressing the early detection of ESCC and EAC via blood testing, advanced upper endoscopy, and novel AI systems
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