Gastric Cancers
Conditions
Keywords
gastric cancer, machine learning, serum biomarkers
Brief summary
Gastric cancer is one of the most common cancers worldwide, especially in East Asia. Although surgery remains the main treatment, patients may experience postoperative complications and have varying long-term survival outcomes. Early identification of high-risk patients before surgery is important for improving treatment decisions and patient management. This study aims to develop a prediction model based on routinely available preoperative blood test results and clinical characteristics to estimate the risk of postoperative complications and long-term survival in patients with gastric cancer. The model will be developed and validated using data from multiple medical centers. By using easily accessible clinical information, this study seeks to provide a practical tool to help clinicians better assess patient risk before surgery, support personalized treatment planning, and improve overall patient outcomes.
Interventions
be diagnosed as gastric cancer
Sponsors
Study design
Eligibility
Inclusion criteria
* patients aged ≥18 years; * patients diagnosed with gastric cancer by pathological biopsy before surgery; * patients without chemotherapy, radiotherapy, targeted and immunotherapy before enrolment; * willing to participate in this study and sign the informed consent; * complete clinical data.
Exclusion criteria
* patients with other primary malignant tumours other than gastric cancer; * patients with systemic diseases such as severe cardiopulmonary insufficiency that affect the choice of treatment plan; * patients who are not suitable for enrolment as assessed by the investigator; * incomplete clinical data.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| the incidence of gastric cancer | From 18 years old until the developing gastric cancer, through study completion, an average of 5 year. | the diagnosis time of gastric cancer |