Evidence map›Paper›PMID 37509248›Full record

ArticleCancers2023

Pre-Referral Primary Care Blood Tests and Symptom Presentation before Cancer Diagnosis: National Cancer Diagnosis Audit Data.

Ben M Cranfield, Gary A Abel, Ruth Swann, Sarah F Moore, Sean McPhail, Greg P Rubin, Georgios Lyratzopoulos

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.4field-weighted citation impact, top 16% 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

5 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Variations in the investigation of colorectal cancer-related symptoms in Australian primary care: a retrospective cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026
    Article
  3. Article
  4. Article
  5. Article
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

7 authors at 5 institutions in 1 country.

Ben M CranfieldEpidemiology of Cancer Healthcare and Outcomes (ECHO) Research Group, Department of Behavioural Science and Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK.ORCID 0000-0002-9327-2392
Gary A AbelUniversity of Exeter Medical School, St Luke's Campus, Exeter EX1 2HZ, UK.
Ruth SwannNational Disease Registration Service, NHS England, Leeds LS1 4AP, UK.
Sarah F MooreUniversity of Exeter Medical School, St Luke's Campus, Exeter EX1 2HZ, UK.ORCID 0000-0001-9815-5665
Sean McPhailNational Disease Registration Service, NHS England, Leeds LS1 4AP, UK.
Greg P RubinPopulation Health Sciences Institute, Newcastle University, Newcastle upon Tyne NE1 4LP, UK.
Georgios LyratzopoulosEpidemiology of Cancer Healthcare and Outcomes (ECHO) Research Group, Department of Behavioural Science and Health, University College London, 1-19 Torrington Place, London WC1E 6BT, UK.ORCID 0000-0002-2873-7421
NHS EnglandUniversity of Exeter · GBCancer Research UK · GBNewcastle University · GBUniversity College London · GB

Funding

Cancer Research UK 18180Cancer Research UK 29738Cancer Research UK C18081/A29738
6 · The paper itself

Abstract

backgroundBlood tests can support the diagnostic process in primary care. Understanding how symptomatic presentations are associated with blood test use in patients subsequently diagnosed with cancer can help to benchmark current practices and guide interventions.

methodsEnglish National Cancer Diagnosis Audit data on 39,751 patients with incident cancer in 2018 were analysed. The frequency of four generic (full blood count, urea and electrolytes, liver function tests, and inflammatory markers) and five organ-specific (cancer biomarkers (PSA or CA125), serum protein electrophoresis, ferritin, bone profile, and amylase) blood tests was described for a total of 83 presenting symptoms. The adjusted analysis explored variation in blood test use by the symptom-positive predictive value (PPV) group.

resultsThere was a large variation in generic blood test use by presenting symptoms, being higher in patients subsequently diagnosed with cancer who presented with nonspecific symptoms (e.g., fatigue 81% or loss of appetite 79%), and lower in those who presented with alarm symptoms (e.g., breast lump 3% or skin lesion 1%). Serum protein electrophoresis (reflecting suspicion of multiple myeloma) was most frequently used in cancer patients who presented with back pain (18%), and amylase measurement (reflecting suspicion of pancreatic cancer) was used in those who presented with upper abdominal pain (14%). Prostate-specific antigen (PSA) use was greatest in men with cancer who presented with lower urinary tract symptoms (88%), and CA125 in women with cancer who presented with abdominal distention (53%). Symptoms with PPV values between 2.00-2.99% were associated with greater test use (64%) compared with 52% and 51% in symptoms with PPVs in the 0.01-0.99 or 1.00-1.99% range and compared with 42% and 31% in symptoms with PPVs in either the 3.00-4.99 or ≥5% range (

conclusionsGeneric blood test use reflects the PPV of presenting symptoms, and the use of organ-specific tests is greater in patients with symptomatic presentations with known associations with certain cancer sites. There are opportunities for greater blood test use in patients presenting with symptoms that do not meet referral thresholds (i.e., <3% PPV for cancer) where information gain to support referral decisions is likely greatest. The findings benchmark blood test use in cancer patients, highlighting opportunities for increasing use.

Indexed as

blood testscancernational cancer diagnosis auditsymptoms

Identifiers

PMID37509248
PMCPMC10377509
OpenAlexW4384131094

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.