Association of Rosuvastatin Use with Risk of Hematuria and Proteinuria.

BACKGROUND: Despite reports of hematuria and proteinuria with rosuvastatin use at the time of its approval by the US Food and Drug Association (FDA), little postmarketing surveillance exists to assess real-world risk. Current labeling suggests dose reduction (maximum daily dose of 10 mg) for patients with severe CKD. METHODS: Using deidentified electronic health record data, we analyzed 152,101 and 795,799 new users of rosuvastatin and atorvastatin, respectively, from 2011 to 2019. We estimated inverse probability of treatment-weighted hazard ratios (HRs) of hematuria, proteinuria, and kidney failure with replacement therapy (KFRT) associated with rosuvastatin. We reported the initial rosuvastatin dose across eGFR categories and evaluated for a dose effect on hematuria and proteinuria. RESULTS: Overall, we identified 2.9% of patients with hematuria and 1.0% with proteinuria during a median follow-up of 3.1 years. Compared with atorvastatin, rosuvastatin was associated with increased risk of hematuria (HR, 1.08; 95% confidence interval [95% CI], 1.04 to 1.11), proteinuria (HR, 1.17; 95% CI, 1.10 to 1.25), and KFRT (HR, 1.15; 95% CI, 1.02 to 1.30). A substantial share (44%) of patients with eGFR <30 ml/min per 1.73 m2 was prescribed high-dose rosuvastatin (20 or 40 mg daily). Risk was higher with higher rosuvastatin dose. CONCLUSIONS: Compared with atorvastatin, rosuvastatin was associated with increased risk of hematuria, proteinuria, and KFRT. Among patients with eGFR <30 ml/min per 1.73 m2, 44% were prescribed a rosuvastatin daily dose exceeding the FDA's recommended 10 mg daily dose. Our findings suggest the need for greater care in prescribing and monitoring rosuvastatin, particularly in patients who receive high doses or who have severe CKD.

The FDA Metformin Label Change and Racial and Sex Disparities in Metformin Prescription among Patients with CKD.

BACKGROUND: In 2016, the Food and Drug Administration (FDA) changed labeling regarding metformin contraindications in patients with diabetes and CKD from using serum creatinine-based thresholds to using eGFR-based thresholds. Because race and sex affect serum creatinine levels independently of GFR, the earlier creatinine-based contraindication may have inadvertently caused racial and sex disparities in metformin prescription among patients with low eGFR. METHODS: In an analysis of 15,946 Black and White primary care patients with diabetes and eGFR≥30 ml/min per 1.73 m2 in a large health system (the primary cohort), we assessed the association of race and sex with metformin prescription across eGFR level before and after the FDA label change. For a replication cohort, we meta-analyzed data from 36 cohorts with 1,051,723 patients from OptumLabs Data Warehouse. RESULTS: In the primary cohort, before the label change, Black patients with eGFR of 30-44 ml/min per 1.73 m2 were prescribed metformin less often than White counterparts (adjusted prevalence ratio [aPR], 0.65; 95% confidence interval [95% CI], 0.52 to 0.82); this disparity was significantly attenuated after the label change (aPR, 0.90; 95% CI, 0.74 to 1.09; P value for interaction by period =0.04). Results were consistent in the replication cohorts. Men with eGFR of 30-44 ml/min per 1.73 m2 received metformin prescriptions less often than women counterparts before the label change; this was nonsignificantly attenuated after the label change, but we found significant attenuation in the replication cohorts (aPRpre-label change, 0.76; 95% CI, 0.73 to 0.79; aPRpost-label change, 0.85; 95% CI, 0.83 to 0.88; P value for interaction by period <0.001). CONCLUSIONS: The metformin label change to an eGFR-based contraindication may have reduced racial and sex disparities in metformin prescription in moderate kidney dysfunction.

Development of Risk Prediction Equations for Incident Chronic Kidney Disease.

Importance: Early identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions. Objective: To develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR). Design, Setting, and Participants: Individual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5 222 711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n = 2 253 540). Exposures: Demographic and clinical factors. Main Outcomes and Measures: Incident eGFR of less than 60 mL/min/1.73 m2. Results: Among 4 441 084 participants without diabetes (mean age, 54 years, 38% women), 660 856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781 627 participants with diabetes (mean age, 62 years, 13% women), 313 646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. Conclusions and Relevance: Equations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.

Estimating Kidney Failure Risk Using Electronic Medical Records.

Background: The four-variable kidney failure risk equation (KFRE) is a well-validated tool for patients with GFR <60 ml/min per 1.73 m2 and incorporates age, sex, GFR, and urine albumin-creatinine ratio (ACR) to forecast individual risk of kidney failure. Implementing the KFRE in electronic medical records is challenging, however, due to low ACR testing in clinical practice. The aim of this study was to determine, when ACR is missing, whether to impute ACR from protein-to-creatinine ratio (PCR) or dipstick protein for use in the four-variable KFRE, or to use the three-variable KFRE, which does not require ACR. Methods: Using electronic health records from OptumLabs Data Warehouse, patients with eGFR <60 ml/min per 1.73 m2 were categorized on the basis of the availability of ACR testing within the previous 3 years. For patients missing ACR, we extracted urine PCR and dipstick protein results, comparing the discrimination of the three-variable KFRE (age, sex, GFR) with the four-variable KFRE estimated using imputed ACR from PCR and dipstick protein levels. Results: There were 976,299 patients in 39 health care organizations; 59% were women, the mean age was 72 years, and mean eGFR was 47 ml/min per 1.73 m2. The proportion with ACR testing was 19% within the previous 3 years. An additional 2% had an available PCR and 36% had a dipstick protein; the remaining 43% had no form of albuminuria testing. The four-variable KFRE had significantly better discrimination than the three-variable KFRE among patients with ACR testing, PCR testing, and urine dipstick protein levels, even with imputed ACR for the latter two groups. Calibration of the four-variable KFRE was acceptable in each group, but the three-variable equation showed systematic bias in the groups that lacked ACR or PCR testing. Conclusions: Implementation of the KFRE in electronic medical records should incorporate ACR, even if only imputed from PCR or urine dipstick protein levels.

The Serious Illness Population: Ascertainment via Electronic Health Record or Claims Data.

CONTEXT: Palliative care can improve the lives of people with serious illness, yet clear operational definitions of this population do not exist. Prior efforts to identify this population have not focused on Medicare Advantage (MA) and commercial health plan enrollees. OBJECTIVES: We aimed to operationalize our conceptual definition of serious illness to identify those with serious medical conditions (SMC) among commercial insurance and MA enrollees, and to compare the populations identified through electronic health record (EHR) or claims data sources. METHODS: We used de-identified claims and EHR data from the OptumLabs Data Warehouse (2016-2017), to identify adults age ≥18 with SMC and examine their utilization and mortality. Within the subset found in both data sources, we compared the performance of claims and EHR data. RESULTS: Within claims, SMC was identified among 10% of those aged ≥18 (5.4% ages 18-64, 27% age ≥65). Within EHR, SMC was identified among 9% of those aged ≥18 (5.6% ages 18-64, 21% ages ≥65). Hospital, emergency department and mortality rates were similar between the EHR and claims-based groups. Only 50% of people identified as having SMC were recognized by both data sources. CONCLUSION: These results demonstrate the feasibility of identifying adults with SMC in a commercially insured population, including MA enrollees; yet separate use of EHR or claims result in populations that differ. Future research should examine methods to combine these data sources to optimize identification and support population management, quality measurement, and research to improve the care of those living with serious illness.

Trends in patient characteristics and first-year medical costs of older incident hemodialysis patients, 1995-2005.

BACKGROUND: Characteristics of patients with chronic kidney disease who survive to end-stage renal disease may change over time, affecting subsequent outcomes and costs. We examined trends in older incident hemodialysis patient characteristics and analyzed first-year post-dialysis therapy initiation medical costs. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: All US incident hemodialysis patients aged > or =67 years at dialysis therapy initiation from January 1, 1995, to December 31, 2005, with Medicare Part A and Part B in the prior 2 years. PREDICTOR: Year of dialysis therapy initiation. OUTCOMES: Changes in patient characteristics and first-year costs. MEASUREMENTS: Mean and median values for continuous variables and percentages of categorical variables; first-year total medical costs measured per person per year. Observed costs were adjusted using Medicare Price Indices and patient case-mix. RESULTS: Median age at dialysis therapy initiation increased from 74.9 to 77.0 years from 1995 (n = 19,044) to 2005 (n = 31,796; P < 0.001). Diabetes prevalence increased from 54.2% to 64.1% (P < 0.001). Median estimated glomerular filtration rate increased from 8.0 to 11.2 mL/min/1.73 m(2), and median hemoglobin level increased from 9.4 to 10.2 g/dL. Obesity increased from 8.9% to 22.9% (P < 0.001). First-year observed costs increased by 37.9%; however, inflation-adjusted and case-mix-inflation-adjusted costs were stable. Important adjusters for costs are inability to ambulate/transfer, baseline serum albumin level, primary end-stage renal disease cause, comorbid peripheral vascular disease, and baseline hospital days. LIMITATIONS: Population aged > or =67 years at dialysis therapy initiation and results may not generalize to the overall hemodialysis population. CONCLUSIONS: From 1995 to 2005, incident hemodialysis patients aged > or =67 years became older, sicker, and more obese with significantly increased estimated glomerular filtration rates and hemoglobin levels at dialysis therapy initiation. Increased first-year post-dialysis therapy initiation costs became stable over time after adjustment for price inflation; case-mix-inflation-adjusted costs remained constant, possibly because of mixed changes in patient characteristics.

High Costs of Dialysis Transportation in the United States: Exploring Approaches to a More Cost-effective Delivery System.

Background: The costs of transporting end-stage renal disease (ESRD) patients to dialysis centers are high and growing rapidly. Research has suggested that substantial cost savings could be achieved if medically appropriate transport was made available and covered by Medicare. Objectives: To estimate US dialysis transportation costs from a purchaser's perspective, and to estimate cost savings that could be achieved if less expensive means of transport were utilized. Methods: Costs were estimated using an actuarial model. Travel distance estimates were calculated using GIS software from patient ZIP codes and dialysis facility addresses. Cost and utilization estimates were derived from fee schedules, government reports, transportation websites and peer-reviewed literature. Results: The estimated annual cost of dialysis transportation in the United States is $3.0 billion, half of which is for ambulances. Most other costs are due to transport via ambulettes, wheelchair vans and taxis. Approximately 5% of costs incurred are for private vehicle or public transportation use. If ambulance use dropped to 1% of trips from the current 5%, costs could be reduced by one-third. Conclusions: Decision-makers should consider policies to reduce ambulance use, while providing appropriate levels of care.

Geographic disparities in patient travel for dialysis in the United States.

PURPOSE: To estimate travel distance and time for US hemodialysis patients and to compare travel of rural versus urban patients. METHODS: Dialysis patient residences were estimated from ZIP code-level patient counts as of February 2011 allocated within the ZIP code proportional to census tract-level population, obtained from the 2010 U.S. Census. Dialysis facility addresses were obtained from Medicare public-use files. Patients were assigned to an "original" and "replacement" facility, assuming patients used the facility closest to home and would select the next closest facility as a replacement, if a replacement facility was required. Driving distances and times were calculated between patient residences and facility locations using GIS software. FINDINGS: The mean one-way driving distance to the original facility was 7.9 miles; for rural patients average distances were 2.5 times farther than for urban patients (15.9 vs. 6.2 miles). Mean driving distance to a replacement facility was 10.6 miles, with rural patients traveling on average 4 times farther than urban patients to a replacement facility (28.8 vs. 6.8 miles). CONCLUSION: Rural patients travel much longer distances for dialysis than urban patients. Accessing alternative facilities, if required, would greatly increase rural patient travel, while having little impact on urban patients. Increased travel could have clinical implications as longer travel is associated with increased mortality and decreased quality of life.