Blood test trend versus single threshold abnormality to discriminate cancer from non-cancer in patients with unexpected weight loss: A retrospective cohort study

BACKGROUND: Unexpected weight loss (UWL) is a non-specific cancer symptom. Abnormalities in the most recent blood test contribute to cancer referral decisions in primary care. Interpreting historical changes (trends) in blood tests could enhance discrimination for undiagnosed cancer. We aimed to assess the discrimination of blood test trend for undiagnosed cancer and compare this to that of blood test abnormality in patients presenting to primary care with UWL. METHODS AND FINDINGS: We conducted a retrospective cohort study of patients presenting to English primary care with UWL aged ≥18 years between 01/01/2000 and 31/12/2018 in the Clinical Practice Research Datalink. We extracted all quantitative results for 26 blood tests prior to the date of UWL. Overall and site-specific cancer diagnosis was ascertained using linked National Cancer Registrations Data. Cox models, unadjusted and adjusted for age and sex, estimated cancer risk based on blood test abnormalities (such as low albumin or raised platelets) co-occurring with UWL and joint models assessed trends in each blood test over 1-, 3-, 5-, and 10-year periods prior to UWL. The area under the curve (AUC) was used to assess discrimination, with 95% confidence intervals (CIs). Amongst 275,205 UWL patients, 5.0% (n = 13,798) with cancer, the median (interquartile range (IQR)) number of blood tests per person over the 10 years ranged from 2 (IQR [12-3]) for 3 types of tests to 4 (IQR [2-7]) for 12 types of tests. The median (IQR) time between the first and last blood test per person was 5.2 (IQR [1.5-8.2]) years cases and 4.3 (IQR [1.0-7.7]) years for those cancer-free. The median time between the last blood test and UWL per person was 0.1 (IQR [0.0-0.6]) years for cases and 0.3 (IQR [0.0-1.1]) years for those cancer-free. Adjusted blood test abnormalities and trends were more discriminative than the unadjusted equivalent. Adjustment resulted in higher AUCs for trend compared to the equivalent blood test abnormality on 34 occasions, with highest AUC of 0.82 (95% CI [0.81, 0.83]). This included 26 trends for cancer overall, mean cell volume trend for bowel cancer and lymphoma, white blood count and neutrophil trend for lung cancer, and aspartate aminotransferase, red blood cell count, haematocrit, and platelet-to-lymphocyte ratio trend for prostate cancer. A limitation of our modelling strategy is that it did not take into account the bias in who was tested and our trend analysis was also restricted to patients with 2 or more tests in each trend window. CONCLUSIONS: Blood test abnormalities should be interpreted after age and sex adjustment to improve triage for cancer investigation in patients attending primary care with UWL. Evaluating historical trend offers further discrimination after adjustment for some test-cancer combinations.