Epidemiology and excess mortality of antimicrobial resistance in bacteraemias among cancer patients: a cohort study using routinely collected health data from regional hospital trusts in Oxford and Oslo, 2008-2018.

OBJECTIVES

We investigated the epidemiology and impact on mortality of antimicrobial resistance (AMR) in cancer patients with bacteraemia at Oxford University Hospitals (OxUH), UK, and Oslo University Hospital (OsUH), Norway, during 2008-2018.

DESIGN

Historical cohort study.

SETTING

Regional hospital trusts with multiple sites in OxUH and OsUH.

METHODS

Patients with cancer and blood cultures positive for one of six pathogen groups during a hospital stay within 3 years following their first cancer diagnosis were followed for 30 days after their first bacteraemia episode. We determined the number of cases and the proportion of infections with an AMR phenotype. Excess mortality and the population-attributable fraction (PAF) due to AMR were estimated by contrasting observed mortality at the end of follow-up with an estimated counterfactual scenario where AMR was absent from all bacteraemias, using inverse probability weighting.

MAIN OUTCOME MEASURE

30-day all-cause mortality following the first bacteraemia episode.

MAIN EXPOSURE MEASURE

A resistant phenotype of the causative pathogen.

RESULTS

The study included 1929 patients at OxUH and 1640 patients at OsUH. The highest resistance proportions were found for vancomycin resistance in enterococci (85/314, 27.1%) and carbapenem-resistance in (63/260, 24.2%) at OxUH, and third-generation cephalosporin resistance in (62/743, 8.3%) and (14/223, 6.3%) at OsUH. Observed mortality for all infections was 26.4% at OxUH, with an estimated counterfactual mortality without AMR of 24.7%, yielding an excess mortality of 1.7% (95% CI: 0.8 to 2.5%). The PAF was 6.3% (95% CI: 2.9 to 9.6%), meaning an estimated 32 of 509 deaths could be attributed to AMR. Limited events at OsUH precluded a similar estimate.

CONCLUSIONS

Despite estimating modest excess mortality, the mortality attributable to resistance in these two high-income, low-prevalence settings highlights the potential for escalation if global resistance trends continue to worsen.