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Related Concept Videos

Cancer Survival Analysis01:21

Cancer Survival Analysis

334
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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Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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Survival analysis is a cornerstone of medical research, used to evaluate the time until an event of interest occurs, such as death, disease recurrence, or recovery. Unlike standard statistical methods, survival analysis is particularly adept at handling censored data—instances where the event has not occurred for some participants by the end of the study or remains unobserved. To address these unique challenges, specialized techniques like the Kaplan-Meier estimator, log-rank test, and...
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Actuarial Approach01:20

Actuarial Approach

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The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
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Kaplan-Meier Approach01:24

Kaplan-Meier Approach

111
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,...
111
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

197
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
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Targeted Cancer Therapies02:57

Targeted Cancer Therapies

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The targeted cancer therapies, also known as “molecular targeted therapies,” take advantage of the molecular and genetic differences between the cancer cells and the normal cells. It needs a thorough understanding of the cancer cells to develop drugs that can target specific molecular aspects that drive the growth, progression, and spread of cancer cells without affecting the growth and survival of other normal cells in the body.
There are several types of targeted therapies against...
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  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Long-term Survival Trend Of Gynecological Cancer: A Systematic Review Of Population-based Cancer Registration Data.
  1. Home
  3. Research Domains
  5. Biomedical And Clinical Sciences
  7. Oncology And Carcinogenesis
  9. Predictive And Prognostic Markers
  11. Long-term Survival Trend Of Gynecological Cancer: A Systematic Review Of Population-based Cancer Registration Data.

Related Experiment Video

An Orthotopic Endometrial Cancer Model with Retroperitoneal Lymphadenopathy Made From In Vivo Propagated and Cultured VX2 Cells
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An Orthotopic Endometrial Cancer Model with Retroperitoneal Lymphadenopathy Made From In Vivo Propagated and Cultured VX2 Cells

Published on: September 12, 2019

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Long-Term Survival Trend of Gynecological Cancer: A Systematic Review of Population-Based Cancer Registration Data.

Xiao Hui Zhou1, Dan Ni Yang1, Yi Xin Zou2

  • 1Department of Epidemiology & State Key Laboratory of Systems Medicine for Cancer, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China;School of Public Health, Shanghai Jiaotong University School of Medicine, Shanghai 200025, China.

Biomedical and Environmental Sciences : BES
|August 28, 2024

View abstract on PubMed

Summary
This summary is machine-generated.

Global survival rates for gynecological cancers, including cervical, endometrial, and ovarian cancers, have improved over four decades. Survival is better in developed countries, but older patients and advanced stages show poorer outcomes.

Keywords:
Cancer registryGynecology cancerObserved survival studyRelative survival rate

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Area of Science:

  • Gynecologic Oncology
  • Epidemiology
  • Cancer Survival Analysis

Background:

  • Gynecological cancers pose a significant global health burden on women.
  • Understanding survival patterns is crucial for improving patient outcomes.
  • Trends in cervical, endometrial, and ovarian cancer survival require ongoing monitoring.

Conclusions:

  • Global survival rates for gynecological cancers have increased over the past four decades.
  • Survival rates are higher in developed countries, with a slow upward trend.
  • Future research should prioritize enhancing survival, especially for ovarian cancer patients.
Time trend