title: Quantifying the risk of multiple myeloma from symptoms reported in primary care patients: a large case-control study using electronic records.
abstract: BACKGROUND
  Patients with myeloma experience the longest diagnostic delays compared with patients with other cancers in the UK; 37% are diagnosed through emergency presentations.
  
  
  OBJECTIVE
  To identify and quantify the risk of myeloma from specific clinical features reported by primary care patients.
  
  
  METHODS
  Matched case-control study using General Practice Research Database primary care electronic records.
  
  
  METHODS
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: University of Exeter Medical School, Exeter.
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Shephard
authors.affiliation: North Wales Centre for Primary Care Research, Bangor University, Wrexham.
authors.forename: Richard D
authors.initials: RD
authors.lastname: Neal
authors.affiliation: Department of Primary Care Health Sciences, University of Oxford.
authors.forename: Peter
authors.initials: P
authors.lastname: Rose
authors.affiliation: Department of Public Health and Primary Care, University of Cambridge, Cambridge.
authors.forename: Fiona M
authors.initials: FM
authors.lastname: Walter
authors.affiliation: Glyndwr University, Wrexham.
authors.forename: Emma J
authors.initials: EJ
authors.lastname: Litt
authors.affiliation: University of Exeter Medical School, Exeter.
authors.forename: William T
authors.initials: WT
authors.lastname: Hamilton
mesh_terms: D000328:Adult; D000368:Aged; D057286:Electronic Health Records; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009017:Morbidity / Q000639:trends; D009101:Multiple Myeloma / Q000175:diagnosis / Q000453:epidemiology*; D016017:Odds Ratio; D011320:Primary Health Care; D012017:Referral and Consultation / Q000706:statistics & numerical data*; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods*; D012307:Risk Factors; D015996:Survival Rate / Q000639:trends; D006113:United Kingdom / Q000453:epidemiology
keywords: blood tests; diagnosis; hypercalcaemia; leucopenia; multiple myeloma; primary health care