title: Symptoms and risk factors to identify men with suspected cancer in primary care: derivation and validation of an algorithm.
abstract: BACKGROUND
  Early diagnosis of cancer could improve survival so better tools are needed.
  
  
  OBJECTIVE
  To derive an algorithm to estimate absolute risks of different types of cancer in men incorporating multiple symptoms and risk factors.
  
  
  METHODS
  Cohort study using data from 452 UK QResearch® general practices for development and 224 for validation.
  
  
  METHODS
  Included patients were males aged 25-89 years. The primary outcome was incident diagnosis of cancer over the next 2 years (lung, colorectal, gastro-oesophageal,  pancreatic, renal, blood, prostate, testicular, other cancer). Factors examined were: 'red flag' symptoms such as weight loss, abdominal distension, abdominal pain, indigestion, dysphagia, abnormal bleeding, lumps; general symptoms such as tiredness, constipation; and risk factors  including age, family history, smoking, alcohol intake, deprivation score and medical conditions. Multinomial logistic regression was used to develop a risk equation to predict cancer type. Performance was tested on a separate validation cohort.
  
  
  RESULTS
  There were 22 521  cancers from 1 263 071 males in the derivation cohort. The final model included risk factors (age, BMI, chronic pancreatitis, COPD, diabetes, family history, alcohol, smoking, deprivation); 22 symptoms, anaemia and venous thrombo-embolism. The model was well calibrated with good discrimination.  The receiver operator curve statistics values were: lung (0.92), colorectal (0.92), gastro-oesophageal (0.93), pancreas (0.89), renal (0.94), prostate (0.90) blood (0.83, testis (0.82); other cancers (0.86). The 10% of males with the highest risks contained 59% of all cancers diagnosed over  2 years.
  
  
  CONCLUSIONS
  The algorithm has good discrimination and could be used to identify those at highest risk of cancer to facilitate more timely referral and investigation.
authors: Division of Primary Care, Tower Building, University Park, Nottingham NG2 7RD, UK. julia.hippisley-cox@nottingham.ac.uk
authors: Julia
authors: J
authors: Hippisley-Cox
authors: Carol
authors: C
authors: Coupland
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D015331:Cohort Studies; D015897:Comorbidity; D003362:Cost-Benefit Analysis; D055088:Early Detection of Cancer / Q000191:economics / Q000379:methods; D004739:England / Q000453:epidemiology; D058006:General Practice; D006801:Humans; D008297:Male; D008875:Middle Aged; D009369:Neoplasms / Q000175:diagnosis* / Q000401:mortality / Q000517:prevention & control; D011237:Predictive Value of Tests; D011320:Primary Health Care / Q000379:methods; D011379:Prognosis; D011446:Prospective Studies; D012307:Risk Factors; D014852:Wales / Q000453:epidemiology