Background Patients undergoing treatment for cancer are at increased risk of acute kidney injury (AKI). There are few data on AKI incidence and risk factors in the current era of cancer treatment. Methods We conducted a population-based study of all patients initiating systemic therapy (chemotherapy or targeted agents) for a new cancer diagnosis in Ontario, Canada (2007–2014). The primary outcome was hospitalization with AKI or acute dialysis. We estimated the cumulative incidence of AKI and fitted Fine and Gray models, adjusting for demographics, cancer characteristics, comorbidities, and coprescriptions. We modeled exposure to systemic therapy (the 90-day period following treatments) as a time-varying covariate. We also assessed temporal trends in annual AKI incidence. Results We identified 163 071 patients initiating systemic therapy of whom 10 880 experienced AKI. The rate of AKI was 27 per 1000 person-years, with overall cumulative incidence of 9.3% (95% CI = 9.1% to 9.6%). Malignancies with the highest 5-year AKI incidence were myeloma (26.0%, 95% CI = 24.4% to 27.7%), bladder (19.0%, 95% CI = 17.6% to 20.5%), and leukemia (15.4%, 95% CI = 14.3% to 16.5%). Advanced cancer stage, chronic kidney disease, and diabetes were associated with increased risk of AKI (adjusted hazard ratios [aHR] = 1.41, 95% CI = 1.28 to 1.54; 1.80, 95% CI = 1.67 to 1.93; and 1.43, 95% CI = 1.37 to 1.50, respectively). In patients aged 66 years or older with universal drug benefits, diuretic, and angiotensin-converting enzyme inhibitor/angiotensin receptor blocker coprescription was associated with higher AKI risk (aHR = 1.20, 95% CI = 1.14 to 1.28; 1.30, 95% CI = 1.23 to 1.38). AKI risk was further accentuated during the 90-day period following systemic therapy (aHR = 2.34, 95% CI = 2.24 to 2.45). The annual incidence of AKI increased from 18 to 52 per 1000 person-years between 2007 and 2014. Conclusion Cancer-related AKI is common and associated with advanced stage, chronic kidney disease, diabetes, and concomitant receipt of diuretics or angiotensin-converting enzyme inhibitors/angiotensin receptor blockers. Risk is heightened in the 90 days after systemic therapy. Preventive strategies are needed to address the increasing burden of AKI in this population.

Childhood transplant recipients have a 30-times greater cancer incidence versus the general population. Further investigation is needed to guide screening strategies in this at-risk population.

BackgroundAdministrative data are increasingly being used to assess outcomes in kidney transplant recipients.ObjectiveTo assess the validity of transplant data in healthcare administrative databases compared to the reference standard of information collected directly from transplant centres.DesignRetrospective cohort study.SettingOne of three major transplant centres in Ontario (Toronto General Hospital, University Hospital – London, and Ottawa Hospital).PatientsRecipients who received a kidney-only transplant between 2008 and 2011.MeasurementsFor each data source, we identified kidney transplants performed. We calculated the sensitivity and positive predictive value (PPV) of the administrative data for the reference standard data.MethodsThe data collected from transplant centres were compared with data from the Canadian Organ Replacement Register (CORR) database, a hospital procedural code from the Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD), and provincial physician billing claims from the Ontario Health Insurance Plan (OHIP) database.ResultsDuring the study period, the three centres reported a total of 1112 kidney transplants performed. The probability of identifying kidney transplant recipients in CORR, CIHI, and OHIP, given they were identified by the transplant centres (sensitivity), was 96%, 98%, and 98% respectively. The probability that the database code correctly identified a transplant recipient (positive predictive value) in CORR, CIHI, and OHIP was 98%, 98%, and 96% respectively.LimitationsWe validated the information from 2008 to 2011 and cannot attest to the reliability of the data beyond the study period. Specifically, we would not regard this as evidence that applies to the earlier years, shortly after the inception of the databases. Secondly, we were unable to distinguish between first and repeat transplantation.ConclusionsCodes in CORR, CIHI, and OHIP each operate well in the detection of kidney transplant recipients. These data sources can be used to efficiently identify and follow kidney transplant recipients for post-transplant outcomes.