Evidence map›Paper›PMID 30616086›Full record

Trial reportCancer epidemiology2019

Colorectal cancer ascertainment through cancer registries, hospital episode statistics, and self-reporting compared to confirmation by clinician: A cohort study nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS).

Darren S Thomas, Aleksandra Gentry-Maharaj, Andy Ryan, Evangelia-Ourania Fourkala, Sophia Apostolidou, Matthew Burnell, Wendy Alderton, Julie Barnes, John F Timms, Usha Menon

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in Cancer epidemiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
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  7. Effect of virtual reality-based mindfulness training model on anxiety, depression, and cancer-related fatigue in ovarian cancer patients during chemotherapy.Technology and health care : official journal of the European Society for Engineering and Medicine · 2024
    Article
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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

10 authors.

Darren S ThomasWomen's Cancer, Institute for Women's Health, University College London, London WC1E 6BT, UK.
Aleksandra Gentry-MaharajMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London WC1V 6LJ, UK.
Andy RyanWomen's Cancer, Institute for Women's Health, University College London, London WC1E 6BT, UK; MRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London WC1V 6LJ, UK.
Evangelia-Ourania FourkalaWomen's Cancer, Institute for Women's Health, University College London, London WC1E 6BT, UK.
Sophia ApostolidouMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London WC1V 6LJ, UK.
Matthew BurnellMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London WC1V 6LJ, UK.
Wendy AldertonAbcodia Ltd., UK.
Julie BarnesAbcodia Ltd., UK.
John F TimmsWomen's Cancer, Institute for Women's Health, University College London, London WC1E 6BT, UK.
Usha MenonMRC Clinical Trials Unit at UCL, Institute of Clinical Trials & Methodology, University College London, London WC1V 6LJ, UK. Electronic address: u.menon@ucl.ac.uk.

Funding

Cancer Research UKDepartment of HealthMedical Research Council G0801228Medical Research Council G9901012Medical Research Council MC_EX_G0800814Medical Research Council MC_EX_UU_G0800814Medical Research Council MC_UU_12023/24Medical Research Council MR/J006718/1
6 · The paper itself

Abstract

backgroundElectronic health records are frequently used for cancer epidemiology. We report on their quality for ascertaining colorectal cancer (CRC) in UK women.

methodsPopulation-based, retrospective cohort study nested within the UK Collaborative Trial of Ovarian Cancer Screening (UKCTOCS). Postmenopausal women aged 50-74 who were diagnosed with CRC during 2001-11 following randomisation to the UKCTOCS were identified and their diagnosis confirmed with their treating clinician. The sensitivity and positive predictive value (PPV) of cancer and death registries, hospital episode statistics, and self-reporting were calculated by pairwise comparisons to the treating clinician's confirmation, while specificity and negative predictive value were estimated relative to expected cases.

resultsNotification of CRC events were received for 1,085 women as of 24 May 2011. Responses were received from 61% (660/1,085) of clinicians contacted. Nineteen women were excluded (18 no diagnosis date, one diagnosed after cut-off). Of the 641 eligible, 514 had CRC, 24 had a benign polyp, and 103 had neither diagnosis. The sensitivity of cancer registrations at one- and six-years post-diagnosis was 92 (95% CI 90-94) and 99% (97-100), respectively, with a PPV of 95% (95% CI 92/93-97). The sensitivity & PPV of cancer registrations (at one-year post-diagnosis) & hospital episode statistics combined were 98 (96-99) and 92% (89-94), respectively.

conclusionsCancer and death registrations in the UK are a reliable resource for CRC ascertainment in women. Hospital episode statistics can supplement delays in cancer registration. Self-reporting seems less reliable.

Indexed as

Self ReportAgedAged, 80 and overColorectal NeoplasmsEarly Detection of CancerFemaleHospitalizationHumansMiddle AgedOvarian NeoplasmsPrognosisRegistriesRetrospective StudiesROC CurveUnited KingdomColorectal neoplasmsDeath certificatesElectronic health recordsHospital episode statisticsRegistriesSelf report

Identifiers

PMID30616086
PMCPMC6363963

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.