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Related Concept Videos

Kaplan-Meier Approach01:24

Kaplan-Meier Approach

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The Kaplan-Meier estimator is a non-parametric method used to estimate the survival function from time-to-event data. In medical research, it is frequently employed to measure the proportion of patients surviving for a certain period after treatment. This estimator is fundamental in analyzing time-to-event data, making it indispensable in clinical trials, epidemiological studies, and reliability engineering. By estimating survival probabilities, researchers can evaluate treatment effectiveness,...
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Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
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Related Experiment Video

Updated: May 12, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
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Enhancing TNM Stage Completeness Using the SEER Summary Stage: A Nationwide Study From Korea.

Chang Kyun Choi1, Mina Suh2,3, Kyu-Won Jung4,5

  • 1Division of Cancer Early Detection, National Cancer Control Institute, National Cancer Center, Goyang, Korea.

Journal of Preventive Medicine and Public Health = Yebang Uihakhoe Chi
|May 9, 2025
PubMed
Summary

Integrating Surveillance, Epidemiology, and End Results (SEER) Summary Stage data improves cancer staging completeness. This enhancement impacts survival rate calculations, particularly for liver cancer, necessitating further research.

Keywords:
Neoplasm stagingPopulation registersSEER program

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Area of Science:

  • Oncology
  • Cancer Research
  • Public Health Surveillance

Background:

  • Accurate cancer staging is crucial for patient prognosis and treatment.
  • The Tumor-Node-Metastasis (TNM) staging system is a standard in oncology.
  • Gaps in TNM staging data can hinder effective cancer care planning.

Purpose of the Study:

  • To evaluate the feasibility of improving TNM staging completeness.
  • To assess the impact of integrating SEER Summary Stage data into TNM staging.
  • To analyze changes in 5-year relative survival rates after data supplementation.

Main Methods:

  • Analysis of data from 173,061 stomach, 159,199 colorectal, 89,639 liver, 137,103 lung, and 110,286 breast cancer patients in South Korea (2012-2017).
  • Supplementation of missing TNM stage data using SEER Summary Stage information.
  • Comparison of staging completeness and survival rates before and after data integration.

Main Results:

  • Significant reduction in missing TNM data across all studied cancer types.
  • Stomach cancer saw a 50.6% decrease in missing data; liver cancer, 21.5%; breast cancer, 13.6%.
  • Survival rates were affected, notably a decrease in Stage IV liver cancer survival from 17.7% to 7.9%.

Conclusions:

  • Integrating SEER Summary Stage data effectively enhances TNM staging completeness.
  • The observed changes in survival rates highlight the importance of complete staging data.
  • Further research incorporating treatment details is recommended for a comprehensive evaluation.