Evidence map›Paper›PMID 29637120›Full record

ArticleBMJ paediatrics open2017

Validation of a classification system for treatment-related mortality in children with cancer.

Hadeel Hassan, Menie Rompola, Adam Woolf Glaser, Sally Elizabeth Kinsey, Robert Stephen Phillips

Abstract read
In one paragraph

Article in BMJ paediatrics open, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–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

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

5 authors.

Hadeel HassanDepartment of Paediatric Haematology and Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.ORCID 0000-0002-8266-1659
Menie RompolaDepartment of Paediatric Haematology and Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Adam Woolf GlaserDepartment of Paediatric Haematology and Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Sally Elizabeth KinseyDepartment of Paediatric Haematology and Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.
Robert Stephen PhillipsDepartment of Paediatric Haematology and Oncology, Leeds Teaching Hospitals NHS Trust, Leeds, UK.

Funding

Department of Health PDF-2014-07-072Medical Research Council G0800472
6 · The paper itself

Abstract

backgroundDeath not directly due to cancer has been termed 'treatment-related mortality' (TRM). Appreciating the differences between TRM and disease-related death is critical in directing strategies to improve supportive care, interventions delivered or disease progression. Recently, a global collaboration developed and validated a consensus-based classification tool and attribution system.

objectivesTo evaluate the reliability of the newly developed consensus-based definition of TRM and explore the use of the cause-of-death attribution system outside the centre it was initially validated (Toronto, Canada). In the initial study, reviewers listed multiple causes of death. In this study, reviewers identified a primary cause for simplicity.

settingThe paediatric haematology and oncology department at Leeds Teaching Hospital in Leeds, UK.

participantsTwo consultants and two clinical research associates (CRAs).

methodsThirty medical records of the most recent deaths in children with cancer, 2 and 4 weeks prior to death, were anonymised and presented to the participants. Reviewers independently classified deaths as 'treatment related mortality' or 'not treatment related' according to the algorithm developed. When TRM occurred, reviewers applied the cause-of-death attribution system to identify the primary cause of death. Inter-relater reliability was assessed using the kappa statistic (k). MAIN OUTCOME: Inter-relater reliability between CRA and consultants.

resultsReliability of the classification was deemed 'very good' between CRA and consultants (k=0.86, 95% CI 0.72 to 0.97). Ten deaths were classified as TRM, of which infection was the most frequent cause identified. Reviewers disagreed on the primary cause of death (eg, respiratory vs infection) when applying the cause-of-death attribution system in six cases and probable and possible causes in four cases. The study identified how the algorithm may not detect TRM in patients receiving non-curative therapy.

conclusionsThe classification and cause of death attribution system could be implemented in different healthcare settings. Adaptation of the classification tool in patients receiving non-curative interventions and the cause of death attribution system should be considered.

Indexed as

haematologyoncologypalliative care

Identifiers

PMID29637120
PMCPMC5862234

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