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Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

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Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
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Several factors can increase the risk of cancer in an individual. About 50% of cancer cases can be prevented by adopting a healthy lifestyle, regular exercise, eating healthy, and following a modest cancer prevention diet. Epidemiological studies have consistently shown that populations with vegetable and fruit-rich diets have reduced the incidence of cancer. On the other hand, populations who have a diet rich in animal fat, red meat, junk food, or high calories are predisposed to cancer.
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Related Experiment Video

Updated: Mar 18, 2026

Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors
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Next Generation Sequencing for the Detection of Actionable Mutations in Solid and Liquid Tumors

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Risk Factors for Lung Cancer Mortality in a Referral Center.

H Jamaati1, P Baghaei, M Sharifianfard

  • 1Chronic Respiratory Diseases Research Center, National Research Institute of Tuberculosis and Lung Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran E-mail : adkhosravi@yahoo.com, pbaghaei@gmail.com.

Asian Pacific Journal of Cancer Prevention : APJCP
|July 1, 2016
PubMed
Summary

Lung cancer survival is poor, with over half of patients dying. Older age (≥55) and a history of smoking significantly increase the risk of death for lung cancer patients.

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Area of Science:

  • Oncology
  • Public Health
  • Epidemiology

Background:

  • Lung cancer is a leading cause of mortality globally and in Iran.
  • Rising incidence necessitates understanding survival factors.
  • This study focuses on a referral center in Tehran, Iran.

Purpose of the Study:

  • To identify factors impacting lung cancer patient survival.
  • To determine risk factors for all-cause mortality in lung cancer patients.
  • To provide prognostic statistics for lung cancer management.

Main Methods:

  • Retrospective analysis of 933 adult lung cancer cases (2011-2015).
  • Utilized a referral center for lung diseases.
  • Multivariate analysis (Cox analysis) to identify mortality risk factors.

Main Results:

  • Overall mortality rate was 53.4%, with 49.3% dying in-hospital.
  • Median follow-up was 7 months.
  • Adenocarcinoma was the most common type (13-month median survival).
  • Age ≥55 and smoking history were significant predictors of mortality; gender was not.

Conclusions:

  • Lung cancer patient survival is poor.
  • Patients aged 55 and older with a smoking history face elevated mortality risk.
  • Hospital-based registries are valuable for prognostic assessment; further research into mortality causes is needed.