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dc.contributor.authorShephard, EA
dc.contributor.authorNeal, RD
dc.contributor.authorRose, P
dc.contributor.authorWalter, FM
dc.contributor.authorLitt, EJ
dc.contributor.authorHamilton, W
dc.date.accessioned2016-06-30T14:08:34Z
dc.date.issued2015-02
dc.description.abstractBACKGROUND: Patients with myeloma experience the longest diagnostic delays compared with patients with other cancers in the UK; 37% are diagnosed through emergency presentations. AIM: To identify and quantify the risk of myeloma from specific clinical features reported by primary care patients. DESIGN AND SETTING: Matched case-control study using General Practice Research Database primary care electronic records. METHOD: Putative clinical features of myeloma were identified and analysed using conditional logistic regression. Positive predictive values (PPVs) were calculated for the consulting population. RESULTS: A total of 2703 patients aged ≥40 years, diagnosed with myeloma between 2000 and 2009, and 12 157 age, sex, and general practice-matched controls were identified. Sixteen features were independently associated with myeloma: hypercalcaemia, odds ratio 11.4 (95% confidence interval [CI] = 7.1 to 18), cytopenia 5.4 (95% CI = 4.6 to 6.4), raised inflammatory markers 4.9 (95% CI = 4.2 to 5.8), fracture 3.1 (95% CI = 2.3 to 4.2), raised mean corpuscular volume 3.1 (95% CI = 2.4 to 4.1), weight loss 3.0 (95% CI = 2.0 to 4.5), nosebleeds 3.0 (95% CI = 1.9 to 4.7), rib pain 2.5 (95% CI = 1.5 to 4.4), back pain 2.2 (95% CI = 2.0 to 2.4), other bone pain 2.1 (95% CI = 1.4 to 3.1), raised creatinine 1.8 (95% CI = 1.5 to 2.2), chest pain 1.6 (95% CI = 1.4 to 1.8), joint pain 1.6 (95% CI = 1.2 to 2.2), nausea 1.5 (95% CI = 1.1 to 2.1), chest infection 1.4 (95% CI = 1.2 to 1.6), and shortness of breath 1.3 (95% CI = 1.1 to 1.5). Individual symptom PPVs were generally <1%, although were >10% for some symptoms when combined with leucopenia or hypercalcaemia. CONCLUSION: Individual symptoms of myeloma in primary care are generally low risk, probably explaining diagnostic delays. Once simple primary care blood tests are taken, risk estimates change. Hypercalcaemia and leucopenia are particularly important abnormalities, and coupled with symptoms, strongly suggest myeloma.en_GB
dc.description.sponsorshipThis article presents independent research funded by the National Institute for Health Research (NIHR) under its Programme Grants for Applied Research Programme (Grant Reference Number RP-PG-0608- 10045). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. Fiona M Walter is part-funded by a NIHR Clinician Scientist award. Richard D Neal is part funded by Public Health Wales and Betsi Cadwaladr University Health Board.en_GB
dc.identifier.citationVol. 65, e106 - e113en_GB
dc.identifier.doi10.3399/bjgp15X683545
dc.identifier.urihttp://hdl.handle.net/10871/22340
dc.language.isoenen_GB
dc.publisherRoyal College of General Practitionersen_GB
dc.relation.urlhttp://www.ncbi.nlm.nih.gov/pubmed/25624306en_GB
dc.subjectblood testsen_GB
dc.subjectdiagnosisen_GB
dc.subjecthypercalcaemiaen_GB
dc.subjectleucopeniaen_GB
dc.subjectmultiple myelomaen_GB
dc.subjectprimary health careen_GB
dc.titleQuantifying the risk of multiple myeloma from symptoms reported in primary care patients: a large case-control study using electronic recordsen_GB
dc.typeArticleen_GB
exeter.place-of-publicationEnglanden_GB
dc.descriptionThis is the author accepted manuscript. The final version is available from Royal College of General Practitioners via the DOI in this record.en_GB
dc.identifier.journalBritish Journal of General Practiceen_GB


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