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Gastritis III: Clinical Manifestations and Management01:23

Gastritis III: Clinical Manifestations and Management

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The clinical manifestations of gastritis can vary depending on the cause and type of gastritis, but some common symptoms may include the following.
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The patient with acute gastritis may have a rapid onset of symptoms, such as epigastric pain or discomfort, dyspepsia, anorexia, hiccups, or nausea and vomiting, which can last from a few hours to a few days. Erosive or hemorrhagic gastritis may cause bleeding, which may manifest as blood in vomit or as...
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Peptic ulcer disease (PUD) presents with diverse symptoms depending on the location and severity of the ulcer. Clinical manifestations of peptic ulcer include dull pain and a burning sensation in the mid-epigastric region.
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  3. Prognostic Value And Predictive Model Of Tumor Markers In Stage I To Iii Gastric Cancer Patients.
  1. Home
  3. Prognostic Value And Predictive Model Of Tumor Markers In Stage I To Iii Gastric Cancer Patients.

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Prognostic value and predictive model of tumor markers in stage I to III gastric cancer patients.

Ai-Hua Sun1, Xin-Yu Zhang1, Yang-Yang Huang2

  • 1Department of Radiotherapy Oncology, Huizhou Municipal Central Hospital, Huizhou 516001, Guangdong Province, China.

World Journal of Clinical Oncology
|August 28, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

A new statistical model effectively predicts gastric cancer prognosis using multiple serum tumor markers. Higher scores indicate poorer survival, aiding in personalized treatment strategies for patients with stages I-III gastric cancer.

Keywords:
Gastric cancerModelOverall survivalPrognosisTumor marker

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Area of Science:

  • Oncology
  • Biostatistics
  • Cancer Biomarkers

Background:

  • Preoperative serum tumor markers are crucial for gastric cancer diagnosis and treatment.
  • Limited studies have developed statistical models using multiple serum tumor indicators for prognosis.

Purpose of the Study:

  • To evaluate the prognostic value of tumor markers in gastric cancer.
  • To develop a predictive statistical model for gastric cancer prognosis in stages I-III.

Main Methods:

  • Included 1236 patients with stage I-III gastric cancer (Oct 2018-Apr 2020).
  • Analyzed serum tumor markers, clinical, and pathological data.
  • Utilized COX regression to establish a prognostic model and compared overall survival (OS).

Main Results:

  • Age, clinical stage, T/N stage, tumor size, and four serum markers (AFP, CEA, CA125, CA19-9) were significant prognostic factors.
  • The developed statistical model demonstrated that higher scores correlated with poorer OS (P < 0.05).
  • Provided 3-year OS rates and mean survival times stratified by score and stage (I-III).

Conclusions:

  • A statistical model incorporating multiple serum tumor markers effectively predicts gastric cancer prognosis.
  • This model can aid in personalized treatment and management strategies for gastric cancer patients.