Long-term Safety in Epstein-Barr Virus-Seropositive Kidney-only Transplant Recipients Treated With Belatacept in Clinical Practice: Final Study Results From the ENLiST Registry.

Background: Belatacept, a selective T-cell costimulation blocker, was associated with improved survival and renal function but also with a risk of posttransplant lymphoproliferative disorder (PTLD) in adult kidney transplant recipients in phase 3 trials. This registry examined long-term safety in Epstein-Barr virus (EBV)-seropositive kidney transplant recipients treated with belatacept. Methods: This US-based, prospective, voluntary, multicenter registry (Evaluating Nulojix Long-Term Safety in Transplant [ENLiST]) included adult EBV-seropositive kidney-only transplant recipients treated de novo (within 14 d of transplantation) with belatacept. Primary objectives were to estimate incidence rates of confirmed PTLD, central nervous system (CNS) PTLD, and progressive multifocal encephalopathy (PML). The minimum follow-up was 2 y. Results: Of 985 enrolled transplant recipients, 933 EBV-seropositive patients received belatacept, with 523 (56.1%) receiving concomitant tacrolimus at transplant (for up to 12 mo). By study end, 3 cases of non-CNS PTLD (incidence rate, 0.08/100 person-years), 1 case of CNS PTLD (0.03/100 person-years), and no cases of PML had been reported. Two patients with non-CNS PTLD received concomitant belatacept and tacrolimus and 1 received belatacept and lymphocyte-depleting therapy. Incidence rates were comparable between patients who received concomitant belatacept and tacrolimus and those who did not receive tacrolimus (0.09/100 person-years and 0.07/100 person-years, respectively; P = 0.96). Two of 4 patients with PTLD died, and 2 were alive at the end of the study. Cumulatively, 131 graft losses or deaths were reported by study end. Conclusions: Our results from the ENLiST registry, a large, prospective real-world study, showed that the incidence rates of PTLD and CNS PTLD in belatacept-treated EBV-seropositive transplant recipients were consistent with findings from previous phase 3 trials.

Adverse events in patients with liver cancer.

This study aimed to further the understanding of the incidence of adverse events (AEs) in a population-based representative liver cancer population where there is currently a lack of knowledge. We carried out a retrospective cohort study using data from an administrative claims database between 1 January 2004 and 31 December 2010. Patients were included in the study if they had at least one primary liver cancer diagnosis [International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM): 155.0] and a metastatic diagnosis [ICD-9-CM: 196.x, 197.x (except 197.7), 198.x or 199.0]. We estimated the incidence rate (IR) and 95% confidence interval (CI) for each AE under study. Of the patients identified, 1292 fulfilled the inclusion and exclusion criteria. The most common AEs were nausea and vomiting (IR=878.5/1000 person-years; 95% CI=799.5-963.1). Other common AEs were hypertension (IR=648.7/1000 person-years; 95% CI=569.2-736.1) and hemorrhage (IR=580.0/1000 person-years; 95% CI=518.6-646.6). The least common AEs were rare dermatologic diseases such as Stevens-Johnson syndrome and toxic epidermal necrolysis where no cases were observed. The rates detailed in this analysis are helpful in understanding the benefit risk of treating patients with liver cancer in the real world. Although no formal comparisons were performed, the increased risk of certain events observed in sorafenib-treated patients from this analysis mirrors the risks reported on the label for sorafenib. Therefore, this analysis provided a reasonable assessment of the AEs that patients with liver cancer experience in the real world.

Delta-8, a Cannabis-Derived Tetrahydrocannabinol Isomer: Evaluating Case Report Data in the Food and Drug Administration Adverse Event Reporting System (FAERS) Database.

Purpose: The aim of this study was to characterize the frequency of adverse effects where delta-8 tetrahydrocannabinol (D8-THC) was identified as a possible suspect drug in the FDA Adverse Event Reporting System (FAERS) database. Methods: A case-series design was used. Results: A total of 183 cases listed D8-THC as a suspect drug in FAERS as of June 30, 2021. The most common events included dyspnea, respiratory disorder, and seizure. The reporting odds ratios were consistently and significantly greater than 2, a 2-fold increase from 2019 to 2021, indicating a potential safety signal. Conclusion: The first report of D8-THC, in the FAERS database, as a suspect drug appears to be in 2011. Overall, there are 183 total cases listing D8-THC as a suspect drug in the FAERS database as of June 30, 2021. Of the 183 cases, most were respiratory in nature.

Neural Net Modeling of Checkpoint Inhibitor Related Myocarditis and Steroid Response.

Background: Serious but rare side effects associated with immunotherapy pose a difficult problem for regulators and practitioners. Immune checkpoint inhibitors (ICIs) have come into widespread use in oncology in recent years and are associated with rare cardiotoxicity, including potentially fatal myocarditis. To date, no comprehensive model of myocarditis progression and outcomes integrating time-series based laboratory and clinical signals has been constructed. In this paper, we describe a time-series neural net (NN) model of ICI-related myocarditis derived using supervised machine learning. Methods: We extracted and modeled data from electronic medical records of ICI-treated patients who had an elevation in their troponin. All data collection was performed using an electronic case report form, with approximately 300 variables collected on as many occasions as available, yielding 6000 data elements per patient over their clinical course. Key variables were scored 0-5 and sequential assessments were used to construct the model. The NN model was developed in MatLab and applied to analyze the time course and outcomes of treatments. Results: We identified 23 patients who had troponin elevations related to their ICI therapy, 15 of whom had ICI-related myocarditis, while the remaining 8 patients on ICIs had other causes for troponin elevation, such as myocardial infarction. Our model showed that troponin was the most predictive biomarker of myocarditis, in line with prior studies. Our model also identified early and aggressive use of steroid treatment as a major determinant of survival for cases of grade 3 or 4 ICI-related myocarditis. Conclusion: Our study shows that a supervised learning NN can be used to model rare events such as ICI-related myocarditis and thus provide clinical insight into drivers of progression and treatment outcomes. These findings direct attention to early detection biomarkers and clinical symptoms as the best means of implementing early and potentially life-saving steroid treatment.

Predicting cardiac adverse events in patients receiving immune checkpoint inhibitors: a machine learning approach.

BACKGROUND: Treatment with immune checkpoint inhibitors (ICIs) has been associated with an increased rate of cardiac events. There are limited data on the risk factors that predict cardiac events in patients treated with ICIs. Therefore, we created a machine learning (ML) model to predict cardiac events in this at-risk population. METHODS: We leveraged the CancerLinQ database curated by the American Society of Clinical Oncology and applied an XGBoosted decision tree to predict cardiac events in patients taking programmed death receptor-1 (PD-1) or programmed death ligand-1 (PD-L1) therapy. All curated data from patients with non-small cell lung cancer, melanoma, and renal cell carcinoma, and who were prescribed PD-1/PD-L1 therapy between 2013 and 2019, were used for training, feature interpretation, and model performance evaluation. A total of 356 potential risk factors were included in the model, including elements of patient medical history, social history, vital signs, common laboratory tests, oncological history, medication history and PD-1/PD-L1-specific factors like PD-L1 tumor expression. RESULTS: Our study population consisted of 4960 patients treated with PD-1/PD-L1 therapy, of whom 418 had a cardiac event. The following were key predictors of cardiac events: increased age, corticosteroids, laboratory abnormalities and medications suggestive of a history of heart disease, the extremes of weight, a lower baseline or on-treatment percentage of lymphocytes, and a higher percentage of neutrophils. The final model predicted cardiac events with an area under the curve-receiver operating characteristic of 0.65 (95% CI 0.58 to 0.75). Using our model, we divided patients into low-risk and high-risk subgroups. At 100 days, the cumulative incidence of cardiac events was 3.3% in the low-risk group and 6.1% in the high-risk group (p<0.001). CONCLUSIONS: ML can be used to predict cardiac events in patients taking PD-1/PD-L1 therapy. Cardiac risk was driven by immunological factors (eg, percentage of lymphocytes), oncological factors (eg, low weight), and a cardiac history.

Realizing the Potential of the Patient Perspective.

Assessing a patient's perspective on their treatment is part of an increasingly integrated approach to pharmacovigilance and treatment optimization. New tools and methods developed in partnership with patients can capture and quantify cognitive and behavioral aspects of the treatment experience. These treatment insights have the potential to shape the drug development process, as well as supplement patient-reported outcome data in a way that is meaningful to the patient. We highlight examples of tools developed to assess the impact of treatment on the aspects of disease that are of utmost concern to the patient in their daily life.

Comparative risk of malignancies and infections in patients with rheumatoid arthritis initiating abatacept versus other biologics: a multi-database real-world study.

BACKGROUND: Patients with rheumatoid arthritis (RA) are at an increased risk of developing certain cancers and infections compared with the general population. Biologic and targeted synthetic disease-modifying antirheumatic drugs (b/tsDMARDs) are effective treatment options for RA, but limited evidence is available on the comparative risks among b/tsDMARDs. We assessed the risk of malignancies and infections in patients with RA who initiated abatacept versus other b/tsDMARDs in a real-world setting. METHODS: This retrospective, observational study used administrative data from three large US healthcare databases (MarketScan, PharMetrics, and Optum) to identify patients treated with abatacept or other b/tsDMARDs. In both groups, age-stratified incidence rates (IRs) with 95% confidence intervals (CIs) were calculated for total malignancy and hospitalized infections; propensity score matching and Cox proportional hazards regression models were used to estimate hazard ratios (HRs) with 95% CIs for total malignancy, lung cancer, lymphoma, breast cancer, non-melanoma skin cancer (NMSC), hospitalized infections, opportunistic infections, and tuberculosis (TB), both within individual databases and in meta-analyses across the three databases. RESULTS: A rounded total of 19.2, 13.6, and 4.2 thousand patients initiating abatacept and 55.3, 40.8, and 13.8 thousand initiating other b/tsDMARDs were identified in the MarketScan, PharMetrics, and Optum databases, respectively. The IRs for total malignancy and hospitalized infections were similar between the two groups in each age stratum. In meta-analyses, total malignancy risk (HR [95% CI] 1.09 [1.02-1.16]) of abatacept versus other b/tsDMARDs was slightly but statistically significantly increased; small, but not statistically significant, increases were seen for lung cancer (1.10 [0.62-1.96]), lymphoma (1.27 [0.94-1.72]), breast cancer (1.15 [0.92-1.45]), and NMSC (1.10 [0.93-1.30]). No significant increase in hospitalized infections (0.96 [0.84-1.09]) or opportunistic infections (1.06 [0.96-1.17]) was seen. For TB, low event counts precluded meta-analysis. CONCLUSIONS: In this real-world multi-database study, the risks for specific cancers and infections did not differ significantly between patients in the abatacept and other b/tsDMARDs groups. The slight increase in total malignancy risk associated with abatacept needs further investigation. These results are consistent with the established safety profile of abatacept.

An integrated epidemiological and neural net model of the warfarin effect in managed care patients.

INTRODUCTION: Risk assessment tools are utilized to estimate the risk for stroke and need of anticoagulation therapy for patients with atrial fibrillation (AF). These risk stratification scores are limited by the information inputted into them and a reliance on time-independent variables. The objective of this study was to develop a time-dependent neural net model to identify AF populations at high risk of poor clinical outcomes and evaluate the discriminatory ability of the model in a managed care population. METHODS: We performed a longitudinal, cohort study within a health-maintenance organization from 1997 to 2008. Participants were identified with incident AF irrespective of warfarin status and followed through their duration within the database. Three clinical outcome measures were evaluated including stroke, myocardial infarction, and hemorrhage. A neural net model was developed to identify patients at high risk of clinical events and defined to be an "enriched" patient. The model defines the enrichment based on the top 10 minimum mean square error output parameters that describe the three clinical outcomes. Cox proportional hazard models were utilized to evaluate the outcome measures. RESULTS: Among 285 patients, the mean age was 74±12 years with a mean follow-up of 4.3±2.6 years, and 154 (54%) were treated with warfarin. After propensity score adjustment, warfarin use was associated with a slightly increased risk of adverse outcomes (including stroke, myocardial infarction, and hemorrhage), though it did not attain statistical significance (adjusted hazard ratio [aHR] =1.22; 95% confidence interval [CI] 0.75-1.97; p=0.42). Within the neural net model, subjects at high risk of adverse outcomes were identified and labeled as "enriched." Following propensity score adjustment, enriched subjects were associated with an 81% higher risk of adverse outcomes as compared to nonenriched subjects (aHR=1.81; 95% CI, 1.15-2.88; p=0.01). CONCLUSION: Enrichment methodology improves the statistical discrimination of meaningful endpoints when used in a health records-based analysis.

Does panic disorder increase the risk of coronary heart disease? A cohort study of a national managed care database.

OBJECTIVE: The association between panic disorder (PD) and coronary heart disease (CHD) was examined in a large national managed care database. METHODS: The Integrated Health Care Information Services managed care database is a fully de-identified, Health Insurance Portability and Accountability Act-compliant database and includes complete medical history for more than 17 million managed care lives; data from more than 30 United States health plans covering 7 census regions and from patient demographics, including morbidity, age, and gender. A cohort study was designed with a total of 39,920 PD patients and an equal number of patients without PD. The Cox proportional hazards regression models were used to assess the risk of CHD adjusted for age at entry into the cohort, tobacco use, obesity, depression, and use of medications including angiotensin converting enzyme inhibitors, beta blockers, and statins. RESULTS: Patients with PD were observed to have nearly a 2-fold increased risk for CHD (HR = 1.87, 95% CI = 1.80-1.91) after adjusting for these factors. There was some evidence of a possible trend toward increased risk in a subgroup of patients diagnosed with depression. After controlling for the aforementioned covariates and comparing these patients with those who did not have a diagnosis of depression, it was noted that patients with a comorbid diagnosis of depression were almost 3 times more likely to develop CHD (HR = 2.60, 95% CI = 2.30-3.01). CONCLUSIONS: The risk of CHD associated with a diagnosis of PD suggests the need for cardiologists and internists to monitor panic disorder to ensure a reduction in the risk of CHD.

Incidence of genital infection among patients with type 2 diabetes in the UK General Practice Research Database.

The objective of this population-based study was to evaluate the incidence of vaginitis (females) and balanitis (males) among a cohort of type 2 diabetes patients and compare this risk to patients without diabetes. The study population included 125,237 female patients and 146,603 males identified from GPRD. All patients were followed for 1-year from their study index date for the first record of an infection or a censored event. Among patients with diabetes the incidence of vaginitis was 21.0/1000PY (95% CI 19.8-22.1) with the risk being 1.81 (95% CI 1.64-2.00) greater that patients without diabetes. The incidence of balanitis among diabetes patients was 8.4/1000PY (95% CI 7.8-9.1) with a relative risk of 2.85 (2.39-3.39) compared to patients without diabetes. Additional analyses were performed by HbA1c level. Results from this large population-based study indicate that patients with diabetes are at an increased risk of being diagnosed with infections of the genital tract and patients with poorly controlled diabetes have higher risks.

Incidence of urinary tract infection among patients with type 2 diabetes in the UK General Practice Research Database (GPRD).

The objective of this observational study was to quantify the incidence of urinary tract infections (UTI) among diabetes patients and compare this risk to patients without diabetes. Type 2 diabetes patients and a matched sample of patients without diabetes were identified from GPRD. Patients were followed for 1-year from their study index date until the first record of a UTI or a censored event. The incidence of UTI was 46.9 per 1000 person-years (95% confidence interval (CI) 45.8-48.1) among diabetes patients and 29.9 (95% CI 28.9-30.8) for patients without diabetes. Compared to the non-diabetes patients, the risk of UTI was 1.53 (95% CI 1.46-1.59) for all diabetes patients; and 2.08 (95% CI 1.93-2.24) for patients with previously diagnosed diabetes. In general practice, across gender and age, the risk of developing a UTI is higher for patients with type 2 diabetes compared to patients without diabetes.

Differential associations of beta-blockers with hemorrhagic events for chronic heart failure patients on warfarin.

PURPOSE: Beta-blockers have many different physiologic effects that could potentially influence the risk of hemorrhagic events in chronic heart failure patients (CHF) on warfarin. We examined how different beta-blockers vary in their associated risk of a hemorrhagic event. METHODS: We used databases from the Department of Veterans Affairs (VA) that contain information on medications prescribed, diagnoses, and hospitalizations. We identified patients with CHF on warfarin and either metoprolol, carvedilol, atenolol, or no beta-blocker during 1999-2001. We modeled time to first hemorrhagic event using a Cox proportional hazards model, adjusting for age, ethnicity, comorbidities, and other factors. INR levels were examined in a subsample of 3546 patients. RESULTS: We identified 66,988 CHF patients on warfarin. Hemorrhagic events occurred in 15.3% of the sample and, in 3.8% of the sample, the hemorrhage was considered severe. Compared to patients on carvedilol, the hazards ratio for a new hemorrhagic event was 1.25 (1.17, 1.34) for no beta-blocker, 1.27 (1.18, 1.38) for atenolol, and 1.38 (1.28, 1.48) for metoprolol. No differences in INR levels were evident among the four groups. CONCLUSIONS: The risk for a hemorrhagic event among CHF patients on warfarin may be affected by beta-blocker use and varies depending on which beta-blocker is prescribed.

Air pollution and distributions of lymphocyte immunophenotypes in cord and maternal blood at delivery.

A cross-sectional study of deliveries in two districts in the Czech Republic, 1994-1996, assessed the relation between air pollution and lymphocyte immunophenotype distributions. Maternal and cord blood samples were assayed by flow cytometry within 24 hours of delivery for 303 deliveries from Teplice, a polluted district, and 215 from Prachatice, a less polluted district. Analyses focused on: CD3(+) T-lymphocytes, CD3(-) CD19(+) B-lymphocytes, and CD3(-) CD16(+)56(+) natural killer (NK) lymphocytes, as well as the subsets CD3(+)CD4(+) ("T-helper") and CD3(+)CD8(+) ("T cytotoxic/suppressor") and the ratio of these two lymphocytes. We collected reproductive, occupational, and life-style information by questionnaire, and abstracted data on labor and delivery from medical records. After adjustment for numerous risk factors in multivariate linear regression models fit for each lymphocyte subset, mothers from Teplice had lower percentages of total T-cells and of CD4(+) cells, and a lower ratio of CD4(+):CD8(+) cells. Cord bloods from Teplice had a higher percentage of NK cells and a less precise lower percentage of T-cells. Stronger differences in maternal lymphocytes were seen when analyses were limited to the central hospital in each district. Heavy air pollution may affect the immune system in pregnant women and/or fetuses, reflecting an acute and/or chronic effect, although unmeasured confounders could also play a role.