Empagliflozin and Risk of Incident Gout: Analysis from the EMPagliflozin Comparative Effectiveness and SafEty (EMPRISE) Cohort Study

BACKGROUND

Hyperuricemia is frequently observed in patients with type 2 diabetes (T2D) and is associated with increased risk of gout and cardiovascular disease (CVD). Empagliflozin lowers serum urate levels by enhancing its urinary excretion.

OBJECTIVE

To compare initiators of empagliflozin vs dipeptidyl peptidase-4 inhibitor (DPP4i) and initiators of empagliflozin vs glucagon-like peptide-1 receptor agonist (GLP-1RA) with respect to the risk of incident gout events.

DESIGN AND PARTICIPANTS

Using three claims-based datasets from 08/2014 to 09/2019, we generated two cohorts (cohort 1: empagliflozin vs DPP4i; cohort 2: empagliflozin vs GLP-1RA) of adult patients with T2D and without prior history of gout or gout-specific medication dispensing separately in each dataset. To assess the risk of incident gout, we estimated hazard ratios (HR) and rate differences (RD) per 1000 person-years (PY) with their 95% confidence intervals (CI) before and after 1:1 propensity score (PS) matching adjusting for 141 baseline covariates.

KEY RESULTS

We identified 102,262 pairs of 1:1 propensity score-matched adults in cohort 1 and 131,216 pairs in cohort 2. Over a mean follow-up period of 8 months on treatment, the risk of gout was lower in patients initiating empagliflozin compared to DPP4i (HR = 0.69: 95% CI (0.60-0.79); RD =  - 2.27: 95% CI (- 3.08, 1.46)) or GLP-1RA (HR = 0.83: 95% CI (0.73-0.94); RD =  - 0.99: 95% CI (- 1.66, - 0.32)). Results were consistent across subgroups (sex, age, body mass index, chronic kidney disease, heart failure, cardiovascular disease, and concurrent diuretic use) and sensitivity analyses.

CONCLUSIONS

Among adults with T2D, the initiation of empagliflozin vs a DPP4i or GLP-1RA was associated with lower risk of incident gout, complementing results from a post hoc analysis of the EMPA-REG OUTCOME trial and previously published observational research focusing on the sodium-glucose co-transporter-2 inhibitor class in more narrowly defined study populations.

Improving the accuracy of automated gout flare ascertainment using natural language processing of electronic health records and linked Medicare claims data

BACKGROUND

We aimed to determine whether integrating concepts from the notes from the electronic health record (EHR) data using natural language processing (NLP) could improve the identification of gout flares.

METHODS

Using Medicare claims linked with EHR, we selected gout patients who initiated the urate-lowering therapy (ULT). Patients' 12-month baseline period and on-treatment follow-up were segmented into 1-month units. We retrieved EHR notes for months with gout diagnosis codes and processed notes for NLP concepts. We selected a random sample of 500 patients and reviewed each of their notes for the presence of a physician-documented gout flare. Months containing at least 1 note mentioning gout flares were considered months with events. We used 60% of patients to train predictive models with LASSO. We evaluated the models by the area under the curve (AUC) in the validation data and examined positive/negative predictive values (P/NPV).

RESULTS

We extracted and labeled 839 months of follow-up (280 with gout flares). The claims-only model selected 20 variables (AUC = 0.69). The NLP concept-only model selected 15 (AUC = 0.69). The combined model selected 32 claims variables and 13 NLP concepts (AUC = 0.73). The claims-only model had a PPV of 0.64 [0.50, 0.77] and an NPV of 0.71 [0.65, 0.76], whereas the combined model had a PPV of 0.76 [0.61, 0.88] and an NPV of 0.71 [0.65, 0.76].

CONCLUSION

Adding NLP concept variables to claims variables resulted in a small improvement in the identification of gout flares. Our data-driven claims-only model and our combined claims/NLP-concept model outperformed existing rule-based claims algorithms reliant on medication use, diagnosis, and procedure codes.

Gastrointestinal prophylaxis for COVID-19: an illustration of severe bias arising from inappropriate comparators in observational studies

OBJECTIVES

We aimed to use setting-appropriate comparisons to estimate the effects of different gastrointestinal (GI) prophylaxis pharmacotherapies for patients hospitalized with COVID-19 and setting-inappropriate comparisons to illustrate how improper design choices could result in biased results.

STUDY DESIGN AND SETTING

We identified 3,804 hospitalized patients aged ≥ 18 years with COVID-19 from March to November 2020. We compared the effects of different gastroprotective agents on clinical improvement of COVID-19, as measured by a published severity scale. We used propensity score-based fine-stratification for confounding adjustment. Based on guidelines, we prespecified comparisons between agents with clinical equipoise and inappropriate comparisons of users vs. nonusers of GI prophylaxis in the intensive care unit (ICU).

RESULTS

No benefit was detected when comparing oral famotidine to omeprazole in patients treated in the general ward or ICUs. We also found no associations when comparing intravenous famotidine to intravenous pantoprazole. For inappropriate comparisons of users vs. nonusers in the ICU, the probability of improvement was reduced by 32%-45% in famotidine users and 21%-48% in omeprazole or pantoprazole users.

CONCLUSION

We found no evidence that GI prophylaxis improved outcomes for patients hospitalized with COVID-19 in setting-appropriate comparisons. An improper comparator choice can lead to spurious associations in critically ill patients.

Real-World Evidence Prediction of a Phase IV Oncology Trial: Comparative Degarelix vs Leuprolide Safety

BACKGROUND

Medical and regulatory communities are increasingly interested in the utility of real-world evidence (RWE) for answering questions pertaining to drug safety and effectiveness but concerns about validity remain. A principled approach to conducting RWE studies may alleviate concerns and increase confidence in findings. This study sought to predict the findings from the PRONOUNCE trial using a principled approach to generating RWE.

METHODS

This propensity-score (PS) matched observational cohort study utilized 3 claims databases to compare the occurrence of major adverse cardiovascular events (MACE) among initiators of degarelix vs. leuprolide. Patients were included if they had history of prostate cancer and atherosclerotic cardiovascular disease. Subjects were excluded if they didn't have continuous database enrollment in the year prior to treatment initiation, were exposed to androgen deprivation therapy or experienced an acute cardiovascular event within 30 days prior to treatment initiation, or had a history or risk factors of QT prolongation.

RESULTS

There were 12,448 leuprolide and 1,969 degarelix study-eligible patients before matching, with 1,887 in each arm after PS-matching. The results for MACE comparing degarelix to leuprolide in the observational analysis (hazard ratio= 1.35; 95% confidence interval = 0.94-1.93) was consistent with the subsequently released PRONOUNCE result (hazard ratio = 1.28; 95% confidence interval = 0.59-2.79).

CONCLUSIONS

This study successfully predicted the result of a comparative cardiovascular safety trial in the oncology setting. Although the findings are encouraging, limitations of measuring cancer stage and tumor progression are representative of challenges in attempting to generalize whether claims-based RWE can be used as actionable evidence.