Evidence map›Paper›PMID 30133466›Full record

ArticlePloS one2018

Can we assess Cancer Waiting Time targets with cancer survival? A population-based study of individually linked data from the National Cancer Waiting Times monitoring dataset in England, 2009-2013.

Chiara Di Girolamo, Sarah Walters, Carolynn Gildea, Sara Benitez Majano, Bernard Rachet, Melanie Morris

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers, 6 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
34citing papers in PubMed, 6 pooled it
2.6field-weighted citation impact, top 7% of its field
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

34 citing papers in PubMed, 6 syntheses or guidelines pooled it, 65 citations in OpenAlex.

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  10. The Effect of Pandemic on Lung Cancer Waiting Time - Tertiary Center Experience.Asian Pacific journal of cancer prevention : APJCP · 2024
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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

6 authors at 2 institutions in 2 countries.

Chiara Di GirolamoCancer Survival Group, Faculty of Epidemiology and Population Health, Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0002-6031-1009
Sarah WaltersCancer Survival Group, Faculty of Epidemiology and Population Health, Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.
Carolynn GildeaNational Cancer Registration and Analysis Service, Public Health England, Vulcan House Steel, Sheffield, United Kingdom.ORCID 0000-0003-4991-5757
Sara Benitez MajanoCancer Survival Group, Faculty of Epidemiology and Population Health, Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0001-8032-9794
Bernard RachetCancer Survival Group, Faculty of Epidemiology and Population Health, Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0001-5837-7773
Melanie MorrisCancer Survival Group, Faculty of Epidemiology and Population Health, Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom.ORCID 0000-0003-3819-8107
London School of Hygiene & Tropical Medicine · GBPublic Health England · GB

Funding

Cancer Research UK 18348Cancer Research UK 18525Cancer Research UK C7923/A18348
6 · The paper itself

Abstract

backgroundCancer Waiting Time targets have been integrated into successive cancer strategies as indicators of cancer care quality in England. These targets are reported in national statistics for all cancers combined, but there is mixed evidence of their benefits and it is unclear if meeting Cancer Waiting Time targets, as currently defined and published, is associated with improved survival for individual patients, and thus if survival is a good metric for judging the utility of the targets. METHODS AND

findingsWe used individually-linked data from the National Cancer Waiting Times Monitoring Dataset (CWT), the cancer registry and other routinely collected datasets. The study population consisted of all adult patients diagnosed in England (2009-2013) with colorectal (164,890), lung (171,208) or ovarian (24,545) cancer, of whom 82%, 76%, and 77%, respectively, had a CWT matching record. The main outcome was one-year net survival for all matched patients by target attainment ('met/not met'). The time to each type of treatment for the 31-day and 62-day targets was estimated using multivariable analyses, adjusting for age, sex, tumour stage and deprivation. The two-week wait (TWW) from GP referral to specialist consultation and 31-day target from decision to treat to start of treatment were met for more than 95% of patients, but the 62-day target from GP referral to start of treatment was missed more often. There was little evidence of an association between meeting the TWW target and one-year net survival, but for the 31-day and 62-day targets, survival was worse for those for whom the targets were met (e.g. colorectal cancer: survival 89.1% (95%CI 88.9-89.4) for patients with 31-day target met, 96.9% (95%CI 96.1-91.7) for patients for whom it was not met). Time-to-treatment analyses showed that treatments recorded as palliative were given earlier in time, than treatments with potentially curative intent. There are possible limitations in the accuracy of the categorisation of treatment variables which do not allow for fully distinguishing, for example, between curative and palliative intent; and it is difficult in these data to assess the appropriateness of treatment by stage. These limitations in the nature of the data do not affect the survival estimates found, but do mean that it is not possible to separate those patients for whom the times between referral, decision to treat and start of treatment could actually have an impact on the clinical outcomes. This means that the use of these survival measures to evaluate the targets would be misleading.

conclusionsBased on these individually-linked data, and for the cancers we looked at, we did not find that Cancer Waiting Time targets being met translates into improved one-year survival. Patients may benefit psychologically from limited waits which encourage timely treatment, but one-year survival is not a useful measure for evaluating Trust performance with regards to Cancer Waiting Time targets, which are not currently stratified by stage or treatment type. As such, the current composition of the data means target compliance needs further evaluation before being used for the assessment of clinical outcomes.

Indexed as

Databases, FactualQuality of Health CareAdultAgedAged, 80 and overDisease-Free SurvivalEnglandFemaleHumansMaleMiddle AgedNeoplasmsSurvival RateTime Factors

Identifiers

PMID30133466
PMCPMC6104918
OpenAlexW2888424695

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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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.