Itinai.com biomedical laboratory close up still scene close u e4996bf4 1113 41b3 8fdd 0d1e6c918068 1
Itinai.com biomedical laboratory close up still scene close u e4996bf4 1113 41b3 8fdd 0d1e6c918068 1

Psychometric validation of the EORTC QLQ-OES18 in patients with advanced or metastatic esophageal squamous cell carcinoma

Abstract

The EORTC QLQ-OES18 is a tool used to measure symptoms in patients with advanced esophageal squamous cell carcinoma (ESCC). This study looked closely at how well this tool works in a specific patient group.

Methodology

Data from a large clinical trial (RATIONALE 302) was analyzed. This trial compared a new treatment called tislelizumab to standard chemotherapy for patients with advanced ESCC. We examined how reliable and valid the QLQ-OES18 tool was in this patient population.

Results

A total of 512 patients participated, with an average age of 61.5 years, and most of them were male. We found that three out of four sections of the QLQ-OES18, which cover symptoms like difficulty swallowing (dysphagia), eating issues, and pain, worked well in measuring what they are supposed to. The scores given by patients for pain matched with similar scores from another questionnaire, showing that the tool was reliable. We also saw expected trends in scores related to specific patient groups. However, many patients had low symptom levels at the start, making it hard to see significant improvements later on.

Conclusion

Overall, the EORTC QLQ-OES18 was effective at measuring symptoms in the studied population, especially for issues related to swallowing. However, some data limitations made it hard to interpret certain results.

Opportunities for Clinics and Patients

Define Measurable Outcomes

Establish clear goals for using the QLQ-OES18 in clinical practice to improve patient care.

Select AI Tools That Fit Clinical Needs

Choose AI solutions that are specifically designed to enhance the use of the QLQ-OES18 in clinical settings.

Implement Step by Step and Expand

Start with a small pilot project to test AI solutions in measuring patient outcomes, then track the results to understand their real-world impact.

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