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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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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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Lung Cancer Statistics.

Lindsey A Torre1, Rebecca L Siegel1, Ahmedin Jemal2

  • 1Surveillance and Health Services Research, Intramural Research Department, American Cancer Society, 250 Williams Street, 30303, Atlanta, Georgia, USA.

Advances in Experimental Medicine and Biology
|December 16, 2015
PubMed
Summary
This summary is machine-generated.

Lung cancer remains a leading cause of cancer death globally and in the US. Incidence and mortality patterns show significant variations by demographics and geography, influenced by historical smoking trends.

Keywords:
AgeAge-standardized rate (ASR)Cancer burdenCancer incidenceCancer mortalityCancer statisticsFive-year relative survivalGlobalGlobal patternsInternationalLung cancerRace/ethnicitySocioeconomic status (SES) geographic variationTrendsUnited States

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Area of Science:

  • Oncology
  • Epidemiology
  • Public Health

Background:

  • Lung cancer is the primary cause of cancer mortality in the United States and a leading cause worldwide.
  • Significant disparities in lung cancer rates exist across sex, age, race/ethnicity, socioeconomic status, and geographic locations.

Purpose of the Study:

  • To review and analyze lung cancer incidence and mortality patterns.
  • To examine global and United States-specific trends in lung cancer.
  • To understand the impact of historical smoking patterns on current lung cancer epidemiology.

Main Methods:

  • Review of existing epidemiological data on lung cancer incidence and mortality.
  • Analysis of trends stratified by demographic factors (sex, age, race/ethnicity, socioeconomic status).
  • Geographic mapping of lung cancer rates in the US and globally.

Main Results:

  • Lung cancer mortality rates are highest among males, Black individuals, those of lower socioeconomic status, and in the US Mid-South.
  • Globally, lung cancer rates are highest in regions with early smoking uptake (North America, Europe), though decreasing there.
  • Rates are increasing in low- and middle-income countries, which now represent over 50% of lung cancer deaths.

Conclusions:

  • Lung cancer epidemiology is complex and influenced by diverse factors, including smoking history and socioeconomic determinants.
  • Disparities in lung cancer burden necessitate targeted public health interventions.
  • Understanding geographic and demographic variations is crucial for effective lung cancer control strategies.