[Endoscopic Resection of Early Gastric Cancer in Elderly]

Prevalence and unfavorable outcome of frailty in older adults with gastric cancer: a systematic review and meta-analysis

BACKGROUND AND AIM

Previous studies reported inconsistent results on the prevalence and prognostic implications of frailty among older adults with gastric cancer. This systematic review synthesized available literature pertaining on this topic to establish the prevalence and unfavorable outcomes of frailty in older adults with gastric cancer.

METHODS

A comprehensive search was conducted across multiple English databases including PubMed, Cochrane Library, CINAHL, Embase, and Web of Science as well as Chinese databases, namely, CNKI, Wan Fang, and CBM, from inception to July 4, 2023, to identify potential studies. Data related to the incidence of frailty and its unfavorable outcomes in older adults with gastric cancer were extracted. RevMan5.3 and R 4.2.2 were used to evaluate pooled prevalence, hazard ratios (HR), and 95% confidence interval (CI).

RESULTS

This review comprehensively selected 13 studies, comprising 9 cohort studies and 4 cross-sectional studies, on 44,117 older adults diagnosed with gastric cancer. The incidence of frailty among older adults with gastric cancer ranged from 10 to 71%. The pooled prevalence of frailty was 29% (95% CI 0.21-0.39). Frailty was found to be associated with an elevated risk of postoperative complications (HR = 1.99, 95% CI 1.45-2.73), prolonged postoperative hospital stay (HR = 2.68, 95% CI 2.38-3.02), likelihood of readmission (HR = 3.28, 95% CI 1.77-6.08), and an increased mortality risk (HR = 1.60, 95% CI 1.36-1.90).

CONCLUSIONS

Frailty was associated with a poor prognosis in older adults with gastric cancer. Clinical medical staff should focus on the frailty of older adults with gastric cancer, conduct large-scale, multicenter, and prospective studies and early screening of patients, and provide guidance for the implementation of prevention and treatment strategies.

The Role of Artificial Intelligence in Gastric Cancer: Surgical and Therapeutic Perspectives: A Comprehensive Review

Stomach cancer has a high annual mortality rate worldwide necessitating early detection and accurate treatment. Even experienced specialists can make erroneous judgments based on several factors. Artificial intelligence (AI) technologies are being developed rapidly to assist in this field. Here, we aimed to determine how AI technology is used in gastric cancer diagnosis and analyze how it helps patients and surgeons. Early detection and correct treatment of early gastric cancer (EGC) can greatly increase survival rates. To determine this, it is important to accurately determine the diagnosis and depth of the lesion and the presence or absence of metastasis to the lymph nodes, and suggest an appropriate treatment method. The deep learning algorithm, which has learned gastric lesion endoscopyimages, morphological characteristics, and patient clinical information, detects gastric lesions with high accuracy, sensitivity, and specificity, and predicts morphological characteristics. Through this, AI assists the judgment of specialists to help select the correct treatment method among endoscopic procedures and radical resections and helps to predict the resection margins of lesions. Additionally, AI technology has increased the diagnostic rate of both relatively inexperienced and skilled endoscopic diagnosticians. However, there were limitations in the data used for learning, such as the amount of quantitatively insufficient data, retrospective study design, single-center design, and cases of non-various lesions. Nevertheless, this assisted endoscopic diagnosis technology that incorporates deep learning technology is sufficiently practical and future-oriented and can play an important role in suggesting accurate treatment plans to surgeons for resection of lesions in the treatment of EGC.