Evidence map›Paper›PMID 18059401›Full record

SynthesisBritish journal of cancer2008

Influences on pre-hospital delay in the diagnosis of colorectal cancer: a systematic review.

E Mitchell, S Macdonald, N C Campbell, D Weller, U Macleod

Abstract readSystematic Review
In one paragraph

Synthesis in British journal of cancer, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers, 8 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
107citing papers in PubMed, 8 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

107 citing papers in PubMed, 8 syntheses or guidelines pooled it.

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47 more citing papers are in PubMed but not listed here.

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.

E MitchellSchool of Health and Social Care, Glasgow Caledonian University, Cowcaddens Road, Glasgow G4 0BA, UK. liz.mitchell2@googlemail.com
S Macdonald
N C Campbell
D Weller
U Macleod

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Colorectal cancer is a major global health problem, with survival varying according to stage at diagnosis. Delayed diagnosis can result from patient, practitioner or hospital delay. This paper reports the results of a review of the factors influencing pre-hospital delay - the time between a patient first noticing a cancer symptom and presenting to primary care or between first presentation and referral to secondary care. A systematic methodology was applied, including extensive searches of the literature published from 1970 to 2003, systematic data extraction, quality assessment and narrative data synthesis. Fifty-four studies were included. Patients' non-recognition of symptom seriousness increased delay, as did symptom denial. Patient delay was greater for rectal than colon cancers and the presence of more serious symptoms, such as pain, reduced delay. There appears to be no relationship between delay and patients' age, sex or socioeconomic status. Initial misdiagnosis, inadequate examination and inaccurate investigations increased practitioner delay. Use of referral guidelines may reduce delay, although evidence is currently limited. No intervention studies were identified. If delayed diagnosis is to be reduced, there must be increased recognition of the significance of symptoms among patients, and development and evaluation of interventions that are designed to ensure appropriate diagnosis and examination by practitioners.

Indexed as

Quality of Health CareTime ManagementClinical Trials as TopicColorectal NeoplasmsHospital Communication SystemsHospitalizationHumansPractice Patterns, Physicians'Primary Health CareReferral and Consultation

Identifiers

PMID18059401
PMCPMC2359711

What OpenQuestion holds

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LicenceCC BY
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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.