Evidence map›Paper›PMID 39234396›Full record

ArticleFrontiers in oncology2024

Estimated incidence of disruptions to event-free survival from non-metastatic cancers in New South Wales, Australia - a population-wide epidemiological study of linked cancer registry and treatment data.

Stephen Morrell, David Roder, David Currow, Alexander Engel, Elizabeth Hovey, Craig R Lewis, Winston Liauw, Jarad M Martin, Manish Patel, Stephen R Thompson and 1 more

Abstract read
In one paragraph

Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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

11 authors.

Stephen MorrellDivision of Cancer Services and Information, Cancer Institute NSW, St Leonards, NSW, Australia.
David RoderCancer Epidemiology and Population Health, University of South Australia, Adelaide, SA, Australia.
David CurrowFaculty of Science, Medicine and Health, University of Wollongong, Wollongong, NSW, Australia.
Alexander EngelFaculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Elizabeth HoveyDepartment of Medical Oncology, Prince of Wales Hospital, Randwick, NSW, Australia.
Craig R LewisDepartment of Medical Oncology, Prince of Wales Hospital, Randwick, NSW, Australia.
Winston LiauwSchool of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Kensington, NSW, Australia.
Jarad M MartinSchool of Medicine and Public Health, University of Newcastle, Newcastle, NSW, Australia.
Manish PatelWestern Clinical School, Faculty of Medicine and Health, University of Sydney, Sydney, NSW, Australia.
Stephen R ThompsonSchool of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Kensington, NSW, Australia.
Tracey O'BrienCancer Institute NSW, St Leonards, NSW, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Population cancer registries record primary cancer incidence, mortality and survival for whole populations, but not more timely outcomes such as cancer recurrence, secondary cancers or other complications that disrupt event-free survival. Nonetheless, indirect evidence may be inferred from treatment data to provide indicators of recurrence and like events, which can facilitate earlier assessment of care outcomes. The present study aims to infer such evidence by applying algorithms to linked cancer registry and treatment data obtained from hospitals and universal health insurance claims applicable to the New South Wales (NSW) population of Australia. Materials and methods: Primary invasive cancers from the NSW Cancer Registry (NSWCR), diagnosed in 2001-2018 with localized or regionalized summary stage, were linked to treatment data for five common Australian cancers: breast, colon/rectum, lung, prostate, and skin (melanomas). Clinicians specializing in each cancer type provided guidance on expected treatment pathways and departures to indicate remission and subsequent recurrence or other disruptive events. A sample survey of patients and clinicians served to test initial population-wide results. Following consequent refinement of the algorithms, estimates of recurrence and like events were generated. Their plausibility was assessed by their correspondence with expected outcomes by tumor type and summary stage at diagnosis and by their associations with cancer survival. Results: Kaplan-Meier product limit estimates indicated that 5-year cumulative probabilities of recurrence and other disruptive events were lower, and median times to these events longer, for those staged as localized rather than regionalized. For localized and regionalized cancers respectively, these were: breast - 7% (866 days) and 34% (570 days); colon/rectum - 15% (732 days) and 25% (641 days); lung - 46% (552 days) and 66% (404 days); melanoma - 11% (893 days) and 38% (611 days); and prostate - 14% (742 days) and 39% (478 days). Cases with markers for these events had poorer longer-term survival. Conclusions: These population-wide estimates of recurrence and like events are approximations only. Absent more direct measures, they nonetheless may inform service planning by indicating population or treatment sub-groups at increased risk of recurrence and like events sooner than waiting for deaths to occur.

Indexed as

breastcancercolorectallungmelanomaprostaterecurrence and other disruptive eventssurvival

Identifiers

PMID39234396
PMCPMC11371594

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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.