Non-visible versus visible haematuria and bladder cancer risk: a study of electronic records in primary care

Background

Diagnosis of bladder cancer relies on investigation of symptoms presented to primary care, notably visible haematuria. The importance of non-visible haematuria has never been estimated.

Aim

To estimate the risk of bladder cancer with non-visible haematuria.

Design and setting

A case–control study using UK electronic primary care medical records, including uncoded data to supplement coded records.

Method

A total of 4915 patients (aged ≥40 years) diagnosed with bladder cancer between January 2000 and December 2009 were selected from the Clinical Practice Research Datalink and matched to 21 718 controls for age, sex, and practice. Variables for visible and non-visible haematuria were derived from coded and uncoded data. Analyses used multivariable conditional logistic regression, followed by estimation of positive predictive values (PPVs) for bladder cancer using Bayes’ theorem.

Results

Non-visible haematuria (coded/uncoded data) was independently associated with bladder cancer: odds ratio (OR) 20 (95% confidence interval [CI] =12 to 33). The PPV of non-visible haematuria was 1.6% (95% CI = 1.2 to 2.1) in those aged ≥60 years and 0.8% (95% CI = 0.1 to 5.6) in 40–59-year-olds. The PPV of visible haematuria was 2.8% (95% CI = 2.5 to 3.1) and 1.2% (95% CI = 0.6 to 2.3) for the same age groups respectively, lower than those calculated using coded data alone. The proportion of records of visible haematuria in coded, rather than uncoded, format was higher in cases than in controls (P<0.002, χ² test). There was no evidence for such differential recording of non-visible haematuria by case/control status (P = 0.78), although, overall, the uncoded format was preferred (P<0.001).

Conclusion

Both non-visible and visible haematuria are associated with bladder cancer, although the visible form confers nearly twice the risk of cancer compared with the non-visible form. GPs’ style of record keeping varies by symptom and possible diagnosis.