Data driven approach to characterize rapid decline in autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is a genetic kidney disease with high phenotypic variability. Furthering insights into patients' ADPKD progression could lead to earlier detection, management, and alter the course to end stage kidney disease (ESKD). We sought to identify patients with rapid decline (RD) in kidney function and to determine clinical factors associated with RD using a data-driven approach. A retrospective cohort study was performed among patients with incident ADPKD (1/1/2002-12/31/2018). Latent class mixed models were used to identify RD patients using differences in eGFR trajectories over time. Predictors of RD were selected based on agreements among feature selection methods, including logistic, regularized, and random forest modeling. The final model was built on the selected predictors and clinically relevant covariates. Among 1,744 patients with incident ADPKD, 125 (7%) were identified as RD. Feature selection included 42 clinical measurements for adaptation with multiple imputations; mean (SD) eGFR was 85.2 (47.3) and 72.9 (34.4) in the RD and non-RD groups, respectively. Multiple imputed datasets identified variables as important features to distinguish RD and non-RD groups with the final prediction model determined as a balance between area under the curve (AUC) and clinical relevance which included 6 predictors: age, sex, hypertension, cerebrovascular disease, hemoglobin, and proteinuria. Results showed 72%-sensitivity, 70%-specificity, 70%-accuracy, and 0.77-AUC in identifying RD. 5-year ESKD rates were 38% and 7% among RD and non-RD groups, respectively. Using real-world routine clinical data among patients with incident ADPKD, we observed that six variables highly predicted RD in kidney function.

Health Disparities in Kidney Failure Among Patients With Autosomal Dominant Polycystic Kidney Disease: A Cross-Sectional Study.

Rationale & Objective: Understanding potential differences in patterns of kidney failure among patients with autosomal dominant polycystic kidney disease (ADPKD) may provide insights into improving disease management. We sought to characterize patients with ADPKD and kidney failure across different race/ethnicities. Study Design: Cross-sectional study. Setting & Participants: Kaiser Permanente Southern California members diagnosed with ADPKD between January1, 2002, and December 31, 2018. Exposure: ADPKD. Outcome: Kidney failure, dialysis, or receipt of kidney transplant. Analytical Approach: Differences in characteristics by race/ethnicity were assessed using analysis of variance F test and χ2 test. To compare the range and distribution of the average age at onset of kidney failure by race/ethnicity and sex, we used box plots and confidence intervals. Multivariable logistic regression was used to estimate OR for kidney transplant. Results: Among 3,677 ADPKD patients, 1,027 (27.3%) had kidney failure. The kidney failure cohort was comprised of Black (n=138; 30.7%), White (n=496; 30.6%), Hispanic (n=306; 24.7%), and Asian (n=87; 23.6%) patients. Hispanic patients had the youngest mean age of kidney failure onset (50 years) compared to Black (56 years) and White (57 years) patients. Black (44.2%; OR, 0.72) and Hispanic (49.7%; OR, 0.65) patients had lower rates of kidney transplantation compared to White (53.8%) patients. Preemptive kidney transplantations occurred in 15.0% of patients. Limitations: Retrospective study design and possible misclassification of ADPKD cases. Kidney function calculations were based on equations incorporating race, potentially overestimating kidney function in African Americans. The study was conducted within a single, integrated health care system in 1 geographic region and may not be generalizable to all ADPKD patients. Conclusions: Among a large diverse ADPKD population, we observed racial/ethnic differences in rates of kidney failure, age of kidney failure onset, and rates of kidney transplantation. Our real-world ADPKD cohort provides insight into racial/ethnic variation in clinical features of disease and potential disparities in care, which may affect ADPKD outcomes.

Prevalence and incidence of microvascular and macrovascular complications over 15 years among patients with incident type 2 diabetes.

INTRODUCTION: Type 2 diabetes (T2D) is a common condition that, if left untreated or poorly managed, can lead to adverse microvascular and macrovascular complications. We estimated the prevalence and incidence of microvascular and macrovascular complications among patients newly diagnosed with T2D within a US integrated healthcare system. RESEARCH DESIGN AND METHODS: We conducted a retrospective cohort study among patients newly diagnosed with T2D between 2003 and 2014. We evaluated 13 complications, including chronic kidney disease (CKD), cardiovascular disease (CVD), and all-cause mortality through 2018. Multivariable Cox proportional hazards models were used to study factors associated with complications. RESULTS: We identified 135 199 patients with incident T2D. The mean age was 58 years, and 48% were women. The prevalence of CKD was the highest of the complications at the time of T2D diagnosis (prevalence=12.3%, 95% CI 12.2% to 12.5%), while the prevalence of CVD was among the lowest at 3.3% (95% CI 3.2% to 3.3%). The median time to incidence of a T2D complication ranged from 3.0 to 5.2 years. High incidence rates (95% CI) of T2D complications included peripheral neuropathy (26.9, 95% CI 26.5 to 27.3 per 1000 person-years (PY)), CKD (21.2, 95% CI 20.9 to 21.6 per 1000 PY), and CVD (11.9, 95% CI 11.7 to 12.2 per 1000 PY). The trend of 5-year incidence rates of T2D complications by diagnosis year decreased over time (p value<0.001). Older age, non-Hispanic white race/ethnicity, sex, higher A1C, smoking, and hypertension were associated with increased CKD and CVD incidence. CONCLUSION: Though incidence rates of T2D complications were lower in more recent years (2010-2014), a significant proportion of patients had complications at T2D diagnosis. Earlier preventive therapies as well as managing modifiable factors may help delay the development and progression of T2D complications.

Time in suboptimal glycemic control over 10 years for patients newly diagnosed with type 2 diabetes.

OBJECTIVE: To estimate time in suboptimal glycemic control among patients with incident type 2 diabetes (T2D) over 10 years. METHODS: We calculated percent of time in suboptimal glycemic control using three A1C thresholds (8%, 7.5%, 7%) following T2D diagnosis. Stratified analyses were conducted based on age and A1C levels at T2D diagnosis. RESULTS: We identified 28,315 patients with incident T2D. Percent of time in suboptimal glycemic control increased with T2D duration. Mean percent time in suboptimal A1C control in the first 2 years following diagnosis was 30%, 34% and 40% for the 8%, 7.5%, and 7% thresholds, respectively. In the 6-10 years following T2D diagnosis, the percent time in suboptimal A1C control increased to 39%, 48% and 61%, for the 8%, 7.5%, and 7% thresholds, respectively. Time in suboptimal glycemic control was longer among younger patients aged 20-44 versus ≥65 years and those with higher A1C (>8%) versus lower A1C (<7%) at diagnosis. CONCLUSIONS: Over 10 years following diagnosis, T2D patients spent one-third to over one-half of their time in suboptimal glycemic control. Reducing time spent above desired A1C targets could lower risk of microvascular and macrovascular complications.