関連する実験動画
Updated: May 5, 2026

20:16
Detecting Anastasis In Vivo by CaspaseTracker Biosensor
Published on: February 1, 2018
8.8K
幼児がんの生存者における長期的な特定原因による死亡率
Raoul C Reulen1, David L Winter, Clare Frobisher
1Centre for Childhood Cancer Survivor Studies, School of Health and Population Sciences, Public Health Building, University of Birmingham, Edgbaston, Birmingham B15 2TT, England. r.c.reulen@bham.ac.uk
JAMA
|July 15, 2010
まとめ
幼児がんの生存者は,診断から数十年後でも,特に第2のがんや循環器疾患による長期的な死亡リスクの増加に直面しています. この研究は,これらの生存者の25年を超えた死亡のリスクが持続し,上昇していることを強調しています.
科学分野:
- 腫瘍学 腫瘍学
- エピデミオロジー エピデミオロジー
- 公衆衛生は公衆衛生である.
背景:
- 幼児がんの生存者は,一般の人々よりも早めの死亡率が高くなります.
- 特定の死因の長期的なリスク,特に診断後25年を超えては,まだ十分に調査されていない.
研究 の 目的:
- 5歳児がん生存者の大きなコホートにおける長期的,特定原因による死亡パターンを調査する.
- 幼児がんの生存者における死亡リスクを理解するために,後期のライフステージ.
主な方法:
- イギリスの小児がん生存者研究 (British Childhood Cancer Survivor Study) を利用し,人口ベースのコホートを作りました.
- 15歳未満で診断された5歳生存者17,981人を含む (1940年−1991年),2006年まで追跡された.
- 原因別標準死亡率 (SMR) と絶対過剰リスク (AER) を分析した.
主要な成果:
- 全体的な死亡率は予想より11倍高かった (SMR 10.7).
- 再発リスクは時間の経過とともに減少したものの,第2次原発がんや循環器疾患のリスクは,診断後45年を超えて大幅に増加した.
- 45歳以上では,第二発がんや循環器疾患が77%を占め,再発による死亡率は7%だった.
結論:
- 第2次原発がんおよび循環器疾患による過剰死亡率は,診断後 (25歳を超えて) 長い間,小児がんの生存者において持続しています.
- 死因の遅発は,長期の生存者ケアとフォローアップ戦略の重要な考慮事項です.
さらに関連する動画
関連する概念動画
Longitudinal Research
11.7K
Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
11.7K
Cancer Prevention
6.5K
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.
Some...
Some...
6.5K
Introduction To Survival Analysis
955
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...
The primary goal of survival analysis is to estimate survival time—the time...
955
Actuarial Approach
384
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,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
384
Assumptions of Survival Analysis
492
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
492
Cancer Survival Analysis
863
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...
863

