Evidence map›Paper›PMID 34664177›Full record

ArticleJournal of neuro-oncology2021

Incidence and survival for childhood central nervous system tumours in Australia, 1983-2016.

Danny R Youlden, Chloe Henshaw, Nicholas G Gottardo, Timothy Hassall, Joanne F Aitken

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Article in Journal of neuro-oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Danny R YouldenCancer Council Queensland, Brisbane, QLD, Australia. DannyYoulden@cancerqld.org.au.ORCID http://orcid.org/0000-0002-2721-9083
Chloe HenshawCancer Council Queensland, Brisbane, QLD, Australia.
Nicholas G GottardoDepartment of Paediatric and Adolescent Oncology/Haematology, Perth Children's Hospital, Perth, WA, Australia.
Timothy HassallOncology Unit, Children's Health Queensland Hospital and Health Service, Brisbane, QLD, Australia.
Joanne F AitkenCancer Council Queensland, Brisbane, QLD, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo investigate incidence and survival of childhood tumours of the central nervous system (CNS) by histological subtype, tumour behaviour and tumour grade.

methodsNational, population-based data on all children under 15 years old diagnosed with a CNS tumour between 1983 and 2016 were sourced from the Australian Childhood Cancer Registry. Incidence rate trends were calculated using Joinpoint regression. Relative survival was calculated using the cohort method, with changes in survival over time by cancer type and tumour grade assessed by multivariable flexible parametric survival modelling.

resultsThe study cohort included 4914 patients, with astrocytoma (n = 2181, 44%) and embryonal tumours (n = 931, 19%) the most common diagnostic subgroups. Almost half (n = 2181, 44%) of all tumours were classified as high grade (III or IV). Incidence rates increased by 29% between 1983 and 2016, with high grade tumours rising by an annual average of + 1.1% (95% CI =  + 0.7%, + 1.5%, p < 0.001). 5-year survival for all patients combined was 72% (95% CI = 71-74%), ranging from 50% (46-54%) for those with other gliomas to 81% (79-83%) for astrocytoma (p < 0.001). Survival improved over time for grade II and III ependymomas but not for patients with astrocytoma irrespective of grade.

conclusionImprovements in diagnostic technology leading to more precise tumour classification are likely to explain some of the differences in incidence rate trends by histological type and grade. While improvements in survival over time were noted for some tumours, outcomes remained poor among patients with high-grade astrocytoma.

Indexed as

Central Nervous System NeoplasmsAdolescentAstrocytomaAustraliaChildCohort StudiesHumansIncidenceInfantNeoplasm GradingRegistriesSurvival AnalysisAustraliaCentral nervous systemChildhood cancerIncidencePopulation-based registrySurvival

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.