Cost-effectiveness of screening for chronic kidney disease using a cumulative eGFR-based statistic.

OBJECTIVES: Routine screening for chronic kidney disease (CKD) could enable timely interventions to slow down disease progression, but currently there are no clinical guidelines for screening. We aim to evaluate the cost-effectiveness of screening for CKD using a novel analytical tool based on a cumulative sum statistic of estimated glomerular filtration rate (CUSUMGFR). METHODS: We developed a microsimulation model that captured CKD disease progression, major complications, patients' awareness, and treatment adherence for a nationally representative synthetic cohort of age ≥ 30 years in the United States. In addition to the status quo with no screening, we considered four CUSUMGFR-based universal screening policies by frequency (annual or biennial) and starting age (30 or 60 years), and two targeted annual screening policies for patients with hypertension and diabetes, respectively. For each policy, we evaluated the total discounted disability-adjusted life years (DALYs) and direct health costs over a lifetime horizon and estimated the incremental cost-effectiveness ratio (ICER). We further performed one-way and probabilistic sensitivity analyses to assess the impact of parameter uncertainty. RESULTS: Compared with the status quo, all the CUSUMGFR-based screening policies were cost-effective under the willingness-to-pay (WTP) range of $50,000 -$100,000, with the estimated incremental cost-effectiveness ratios (ICERs) ranging from $15,614/DALYs averted to $54,373/DALYs averted. Universal annual screening with starting age of 30 was the non-dominated policy on the cost-effectiveness frontier under the WTP of approximately $25,000. Adding more recent treatment option of sodium-glucose cotransporter-2 (SGLT2) inhibitors to the treatment regimen was found to be cost-saving. Among the most influential model parameters, variation in the CKD progression rate, adherence, and testing cost resulted in the highest variability in model outcomes. CONCLUSIONS: CUSUMGFR-based screening policies for CKD are highly cost-effective in identifying patients at risk of end stage kidney disease in early stages of CKD. Given its simple requirement of a basic blood test, the CUSUMGFR-based screening can be easily incorporated into clinical workflow for disease monitoring and prevention.

Using CUSUM in real time to signal clinically relevant decreases in estimated glomerular filtration rate.

BACKGROUND: The electronic health record (EHR), utilized to apply statistical methodology, assists provider decision-making, including during the care of chronic kidney disease (CKD) patients. When estimated glomerular filtration (eGFR) decreases, the rate of that change adds meaning to a patient's single eGFR and may represent severity of renal injury. Since the cumulative sum chart technique (CUSUM), often used in quality control and surveillance, continuously checks for change in a series of measurements, we selected this statistical tool to detect clinically relevant eGFR decreases and developed CUSUMGFR. METHODS: In a retrospective analysis we applied an age adjusted CUSUMGFR, to signal identification of eventual ESKD patients prior to diagnosis date. When the patient signaled by reaching a specified threshold value, days from CUSUM signal date to ESKD diagnosis date (earliness days) were measured, along with the corresponding eGFR measurement at the signal. RESULTS: Signaling occurred by CUSUMGFR on average 791 days (se = 12 days) prior to ESKD diagnosis date with sensitivity = 0.897, specificity = 0.877, and accuracy = .878. Mean days prior to ESKD diagnosis were significantly greater in Black patients (905 days) and patients with hypertension (852 days), diabetes (940 days), cardiovascular disease (1027 days), and hypercholesterolemia (971 days). Sensitivity and specificity did not vary by sociodemographic and clinical risk factors. CONCLUSIONS: CUSUMGFR correctly identified 30.6% of CKD patients destined for ESKD when eGFR was > 60 ml/min/1.73 m2 and signaled 12.3% of patients that did not go on to ESKD (though almost all went on to later-stage CKD). If utilized in an EHR, signaling patients could focus providers' efforts to slow or prevent progression to later stage CKD and ESKD.

Assessing school-based policy actions for COVID-19: An agent-based analysis of incremental infection risk.

Many schools and universities have seen a significant increase in the spread of COVID-19. As such, a number of non-pharmaceutical interventions have been proposed including distancing requirements, surveillance testing, and updating ventilation systems. Unfortunately, there is limited guidance for which policy or set of policies are most effective for a specific school system. We develop a novel approach to model the spread of SARS-CoV-2 quanta in a closed classroom environment that extends traditional transmission models that assume uniform mixing through air recirculation by including the local spread of quanta from a contagious source. In addition, the behavior of students with respect to guideline compliance was modeled through an agent-based simulation. Estimated infection rates were on average lower using traditional transmission models compared to our approach. Further, we found that although ventilation changes were effective at reducing mean transmission risk, it had much less impact than distancing practices. Duration of the class was an important factor in determining the transmission risk. For the same total number of semester hours for a class, delivering lectures more frequently for shorter durations was preferable to less frequently with longer durations. Finally, as expected, as the contact tracing level increased, more infectious students were identified and removed from the environment and the spread slowed, though there were diminishing returns. These findings can help provide guidance as to which school-based policies would be most effective at reducing risk and can be used in a cost/comparative effectiveness estimation study given local costs and constraints.