Temporal changes in childhood cancer incidence and survival by stage at diagnosis in Australia, 2000-2017

Danny R Youlden1,2, Peter D Baade1,2,3, A Lindsay Frazier4

  • 1Viertel Cancer Research Centre, Cancer Council Queensland, Brisbane, Australia.

Insights

Childhood cancer survival in Australia improved due to better management, not earlier diagnosis. The Toronto Paediatric Cancer Stage Guidelines aid global data comparison for childhood cancers.

Area of Science:

  • Pediatric Oncology
  • Cancer Epidemiology
  • Clinical Data Management

Background:

  • The Toronto Paediatric Cancer Stage Guidelines standardize data collection for childhood cancers.
  • Consistent staging is crucial for registry data and comparative studies.

Purpose of the Study:

  • To evaluate changes in stage-specific incidence and survival for childhood cancers in Australia.
  • To compare data from 2000-2008 with 2009-2017 using the Australian Childhood Cancer Registry.

Main Methods:

  • Retrospective observational cohort study of children diagnosed between 2000-2017.
  • Utilized the Australian Childhood Cancer Registry, with mortality data up to December 2020.
  • Analyzed incidence shifts using chi-square tests and survival differences with flexible parametric models.

Main Results:

  • Stage was assigned using Toronto Guidelines for 96% of the cohort.
  • Observed incidence changes in retinoblastoma (Stage 0 increase) and hepatoblastoma (metastatic increase).
  • Significant survival gains noted for metastatic rhabdomyosarcoma, medulloblastoma (M3), and neuroblastoma.

Conclusions:

  • Improved childhood cancer survival in Australia is attributed to refined management, not altered diagnosis stage.
  • International adoption of Toronto Guidelines will enable robust cross-country survival evaluations.
Abstract

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...
381
Tumor Progression02:07

Tumor Progression

Tumor progression is a phenomenon where the pre-formed tumor acquires successive mutations to become clinically more aggressive and malignant. In the 1950s, Foulds first described the stepwise progression of cancer cells through successive stages.
Colon cancer is one of the best-documented examples of tumor progression. Early mutation in the APC gene in colon cells causes a small growth on the colon wall called a polyp. With time, this polyp grows into a benign, pre-cancerous tumor. Further...
6.4K
Introduction To Survival Analysis01:18

Introduction To Survival Analysis

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...
276
Actuarial Approach01:20

Actuarial Approach

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,...
96
Comparing the Survival Analysis of Two or More Groups01:20

Comparing the Survival Analysis of Two or More Groups

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...
222
Longitudinal Research02:20

Longitudinal Research

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...
12.0K