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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

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...
Kaplan-Meier Approach01:24

Kaplan-Meier Approach

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,...
Cancer Prevention02:59

Cancer Prevention

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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Cancer Prevention02:59

Cancer Prevention

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: Jun 3, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Piloting performance measurement for Comprehensive Cancer Control programs.

Phyllis Rochester1, Deborah S Porterfield, Lisa C Richardson

  • 1Division of Cancer Prevention and Control, Centers for Disease Control and Prevention, Atlanta, Georgia 30341, USA.

Journal of Public Health Management and Practice : JPHMP
|April 6, 2011
PubMed
Summary
This summary is machine-generated.

This pilot study tested performance measures for Comprehensive Cancer Control (CCC) programs. The findings show these measures are feasible and provide valuable data for program improvement and accountability.

Related Experiment Videos

Last Updated: Jun 3, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
06:46

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery

Published on: September 27, 2024

Area of Science:

  • Public Health
  • Cancer Control
  • Program Evaluation

Background:

  • National Comprehensive Cancer Control (CCC) programs are funded by the Centers for Disease Control and Prevention (CDC).
  • Effective evaluation is crucial for program success and accountability.

Purpose of the Study:

  • To pilot test performance measures for CDC-funded CCC programs.
  • To assess the feasibility and utility of a standardized performance measures worksheet.

Main Methods:

  • A cross-sectional assessment in 2008 involving 69 CCC programs.
  • Development of a performance measures worksheet based on a CCC logic model.
  • Stakeholder involvement from funded programs, academia, and nonprofit organizations.

Main Results:

  • 61 out of 69 programs completed the performance measures worksheet.
  • Most programs reported coalition representation and cancer burden assessments.
  • Fewer programs reported having written evaluation plans or policy changes.

Conclusions:

  • The pilot test confirmed the feasibility of standardized performance measurement for CCC programs.
  • Performance measures provide valuable data for funders and feedback for program improvement.
  • Refined measures can enhance accountability and foster a culture of quality improvement.