The effect of comorbidities on diagnostic interval for lung cancer in England: a cohort study using electronic health record data.

Background: Comorbid conditions may delay lung cancer diagnosis by placing demand on clinician’s time reducing the possibility of prompt cancer investigation (“competing demand conditions”), or by offering a plausible non-cancer explanation for signs/symptoms (“alternative explanation conditions”).

Method: Patients in England born before 1955 and diagnosed with incident lung cancer between 1990 and 2019 were identified in the Clinical Practice Research Datalink and linked hospital admission and cancer registry data. Diagnostic interval was defined as time from first presentation in primary care with a relevant sign/symptom to the diagnosis date. 14 comorbidities were classified as ten “competing demand“ and four “alternative explanation” conditions. Associations with diagnostic interval were investigated using multivariate linear regression models.

Results: Complete data were available for 11870 lung cancer patients. In adjusted analyses diagnostic interval was longer for patients with “alternative explanation” conditions, by 31 and 74 days in patients with one and ≥2 conditions respectively compared to those with none. Number of “competing demand” conditions did not remain in the final adjusted regression model for diagnostic interval.

Conclusions: Conditions offering alternative explanations for lung cancer symptoms are associated with increased diagnostic intervals. Clinical guidelines should incorporate the impact of alternative and competing causes upon delayed diagnosis.