Safety and Effectiveness of Tenofovir Alafenamide in Usual Clinical Practice Confirms Results of Clinical Trials: TARGET-HBV.

BACKGROUND: Nucleos(t)ide analogues, with a proven record of safety and efficacy, have been the therapy of choice for over a decade for the treatment of chronic hepatitis B. The approval of tenofovir alafenamide (TAF) in 2016 provided an additional treatment option. AIMS: The aim of this study was to evaluate the characteristics and clinical outcomes of patients treated with TAF in usual clinical practice. METHODS: Retrospective data from electronic health records was obtained from those enrolled in TARGET-HBV, a longitudinal observational cohort study of patients with chronic hepatitis B managed according to local practice standards at community and academic medical centers throughout the U.S. RESULTS: Of 500 patients enrolled, most were male (66%) and of Asian race (66%) with median age of 55 years. Cirrhosis was evident in 15%. Most patients (82%) had switched to TAF after treatment with other antivirals. The perceived safety profile of TAF was cited as the primary reason for changing therapy (32%). TAF was well tolerated and only 4 patients discontinued therapy due to adverse event during a median duration of TAF dosing of 74 weeks. Among those with paired laboratory data 12-18 months after switching to TAF, biochemical response and HBV DNA suppression was maintained. Most patients had normal renal function which was essentially unchanged throughout follow-up. CONCLUSIONS: TAF is frequently utilized in routine clinical practice due to the perception of its improved safety profile. The current study supports the growing body of evidence regarding the safety and effectiveness of TAF. Trial Registration ClinicalTrials.gov identifier: NCT03692897, https://clinicaltrials.gov/ct2/show/NCT03692897 .

Patient Characteristics and Outcomes of 11 721 Patients With Coronavirus Disease 2019 (COVID-19) Hospitalized Across the United States.

BACKGROUND: As coronavirus disease 2019 (COVID-19) disseminates throughout the United States, a better understanding of the patient characteristics associated with hospitalization, morbidity, and mortality in diverse geographic regions is essential. METHODS: Hospital chargemaster data on adult patients with COVID-19 admitted to 245 hospitals across 38 states between 15 February and 20 April 2020 were assessed. The clinical course from admission, through hospitalization, and to discharge or death was analyzed. RESULTS: A total of 11 721 patients were included (majority were >60 years of age [59.9%] and male [53.4%]). Comorbidities included hypertension (46.7%), diabetes (27.8%), cardiovascular disease (18.6%), obesity (16.1%), and chronic kidney disease (12.2%). Mechanical ventilation was required by 1967 patients (16.8%). Mortality among hospitalized patients was 21.4% and increased to 70.5% among those on mechanical ventilation. Male sex, older age, obesity, geographic region, and the presence of chronic kidney disease or a preexisting cardiovascular disease were associated with increased odds of mechanical ventilation. All aforementioned risk factors, with the exception of obesity, were associated with increased odds of death (all P values < .001). Many patients received investigational medications for treatment of COVID-19, including 48 patients on remdesivir and 4232 on hydroxychloroquine. CONCLUSIONS: This large observational cohort describes the clinical course and identifies factors associated with the outcomes of hospitalized patients with COVID-19 across the United States. These data can inform strategies to prioritize prevention and treatment for this disease.

Lean Americans With Nonalcoholic Fatty Liver Disease Have Lower Rates of Cirrhosis and Comorbid Diseases.

BACKGROUND & AIMS: Nonalcoholic fatty liver disease (NAFLD) is typically associated with obesity. Little is known about the prevalence of cirrhosis in patients with NAFLD and a normal body mass index (BMI). METHODS: We determined prevalence of cirrhosis, cardiovascular disease (CVD), and metabolic abnormalities among participants in all BMI categories in the TARGET-NASH study. A total of 3386 patients with NAFLD were enrolled from August 2016 through March 2019. The odds ratios of cirrhosis, CVD, and metabolic abnormalities were estimated by age and race, adjusting for sex and center type. RESULTS: Based on standard BMI cutoff values, 12.8% of study subjects were lean, 27.1% were overweight, 26.5% had class 1 obesity, and 33.7% had class 2 or 3 obesity. Asians accounted for 48.7% of lean participants, and proportions decreased as BMI categories increased (P < .0001). Lower proportions of lean participants had cirrhosis (22.6% vs 40.2% of non-lean participants), CVD history (9.0% vs 14.8% of nonlean participants), diabetes (32.6% vs 53.5% of non-lean participants), hypertension (47.8% vs 67.4% of non-lean participants), or dyslipidemia (54.0% vs 64.1% of non-lean participants). Asian participants had a lower prevalence of cirrhosis, history of CVD, cardiovascular events, and diabetes compared with non-Asians, independent of BMI category. After we adjusted for age, sex, and center type and site, the odds of NAFLD-associated cirrhosis in Asians who were lean was almost half the odds of NAFLD-associated cirrhosis in non-Asians who were lean (odds ratio, 0.47; 95% CI, 0.29-0.77). CONCLUSIONS: More than 10% participants in a cohort of persons with NAFLD in the United States are lean; Asians account for almost half of the lean persons with NAFLD. Lean participants had a lower prevalence of cirrhosis, CVD, and metabolic abnormalities than non-lean persons with NAFLD. Asian participants had a significantly lower prevalence of cirrhosis, CVD, and metabolic abnormalities than non-Asians in all BMI categories. ClinicalTrials.gov, Number: NCT02815891.

Understanding the influence of individual variables contributing to multivariate outliers in assessments of data quality.

Mahalanobis distance is often recommended to identify patients or clinical sites that are considered unusual in clinical trials. Patients extreme in one or more covariates may be considered outliers in that they reside some distance from the multivariate mean, which can be thought of as the center of the data cloud. Less often discussed, patients whose data are believed to be "too good to be true" are located near the centroid as inliers. In order to efficiently investigate these anomalies for potential lapses in data quality, it is important to understand how the individual variables contribute to each multivariate outlier. There is a lack of literature describing a reasonable workflow for identification of outliers and their subsequent investigation to understand how each variable contributes to an observation being considered extreme. We describe how to identify multivariate inliers and outliers, classify outliers according to varying levels of severity, and summarize the contributions of variables using principal components in a manner that is accessible to a wide audience with straightforward interpretation. We illustrate how numerous data visualizations, including Pareto plots, can facilitate further review even in studies containing numerous observations and variables. We illustrate these methodologies using data from a multicenter clinical trial.

Aggregate IND Safety Reporting for Smaller Companies and Programs.

The United States (US) Food and Drug Administration (FDA) Investigational New Drug (IND) Final Rule (US FDA, Final rule: Investigational new drug safety reporting requirements for human drug and biological products and safety reporting requirements for bioavailability and bioequivalence studies in humans, 2010) applies to all human drugs and biological products being studied under an IND. The Final Rule specifies that a sponsor must file an IND safety report for any Suspected Unexpected Serious Adverse Reaction (SUSAR) of a medicinal product being investigated. To make a proper SUSAR classification, sponsors need to go beyond conventional Data Monitoring Committees (DMCs) with an interdisciplinary effort, using all relevant data (including data outside clinical trials), to make judgments on the possibility of serious adverse events being caused by the study drug-rather than the underlying condition of the patient or a concomitant therapy. Ball et al. (Ball et al. in Ther Innov Regul Sci 55:705-716, 2021) have reported on how the Final Rule has been implemented by large pharmaceutical companies. This paper explores the experiences of small sponsor companies regarding the Final Rule, to understand the current challenges that they have been facing to meet aggregate IND safety reporting requirements.

Summarizing the incidence of adverse events using volcano plots and time intervals.

BACKGROUND: Adverse event incidence analyses are a critical component for describing the safety profile of any new intervention. The results typically are presented in lengthy summary tables. For therapeutic areas where patients have frequent adverse events, analysis and interpretation are made more difficult by the sheer number and variety of events that occur. Understanding the risk in these instances becomes even more crucial. PURPOSE: We describe a space-saving graphical summary that overcomes the limitations of traditional presentations of adverse events and improves interpretability of the safety profile. METHODS: We present incidence analyses of adverse events graphically using volcano plots to highlight treatment differences. Data from a clinical trial of patients experiencing an aneurysmal subarachnoid hemorrhage are used for illustration. Adjustments for multiplicity are illustrated. RESULTS: Color is used to indicate the treatment with higher incidence; bubble size represents the total number of events that occur in the treatment arms combined. Adjustments for multiple comparisons are displayed in a manner to indicate clearly those events for which the difference between treatment arms is statistically significant. Furthermore, adverse events can be displayed by time intervals, with multiple volcano plots or animation to appreciate changes in adverse event risk over time. Such presentations can emphasize early differences across treatments that may resolve later or highlight events for which treatment differences may become more substantial with longer follow-up. LIMITATIONS: Treatment arms are compared in a pairwise fashion. CONCLUSIONS: Volcano plots are space-saving tools that emphasize important differences between the adverse event profiles of two treatment arms. They can incorporate multiplicity adjustments in a manner that is straightforward to interpret and, by using time intervals, can illustrate how adverse event risk changes over the course of a clinical trial.

Validation of a Modified National Eye Institute Grading Scale for Corneal Fluorescein Staining.

Purpose: Validation of the novel Lexitas modified NEI scale for use in assessment of corneal fluorescein staining. Patients and Methods: A series of 18 illustrations and 14 clinical photographs depicting varying severity levels of corneal fluorescein staining were assessed by 3 independent examiners. Regions of the cornea were graded for staining severity based on 3 different grading scales: the original NEI staining scale (density-based scoring; 0-3 scale), a structured version of the NEI scale (dot-count scoring; 0-3 scale), and the Lexitas modified NEI staining scale (0-4 scale with half-point increments). Kappa statistics (simple and weighted) were computed to determine intra-examiner image grading repeatability for each examiner over 2 separate assessments. Inter-examiner assessment reliability utilized the scores from the first read of each examiner, and pairs of examiners to compute kappa statistics. Results: Data was analyzed from the scores provided by the examiners from each gradable corneal region on 32 images (18 illustrations and 14 photographs) for a total of 154 corneal regions across the 3 grading scales for each validation run. The mean intra-examiner simple/weighted kappa values using the NEI density, NEI dot count, and the Lexitas modified NEI staining scales were 0.67/0.72, 0.91/0.94, 0.80/0.92 for the graded illustrations, and 0.83/0.88, 0.76/0.85, 0.77/0.88 for the graded photographs, respectively. The mean inter-examiner simple/weighted kappa values using the NEI density, NEI dot count, and the Lexitas modified NEI staining scales were 0.59/0.65, 0.86/0.90, and 0.78/0.91 for the graded illustrations, and 0.80/0.88, 0.84/0.89, 0.69/0.88 for the graded photographs, respectively. Conclusion: The expanded scale of the Lexitas modified NEI staining scale demonstrated a high degree of reliability and repeatability of grading assessments within and across individual examiners, comparing favorably with the original NEI staining scale. A future investigation into the in-office utility of the Lexitas modified NEI staining scale is warranted.

Safety and efficacy of topical azithromycin ophthalmic solution 1.0% in the treatment of contact lens-related dry eye.

PURPOSE: The purpose of this pilot study was to evaluate the safety and efficacy of azithromycin ophthalmic solution 1% in patients with contact lens-related dry eye (CLDE). METHODS: This was a 4-week, single-center, open-label clinical trial in patients diagnosed with CLDE using the Contact Lens Dry Eye Questionnaire (CLDEQ). Fifty patients were enrolled in this study. The patients were randomized to 1 of 2 treatment groups: azithromycin ophthalmic solution administered bid on days 1 and 2 and on days 3 to 29±1 or Visine for Contacts rewetting drops administered qid on days 1 to 29±1. The patient diaries were used daily to collect data on comfortable and total contact lens wear time and ocular dryness throughout the treatment period. Tear osmolarity, fluorescein corneal staining, and visual acuity were also assessed during clinic visits. RESULTS: Fifty patients were enrolled, and 44 completed the study. One patient discontinued in the azithromycin group, and five patients discontinued in the rewetting drops group because of adverse events. A statistically significant increase in mean comfortable contact lens wear time from baseline was observed for the subjects treated with azithromycin ophthalmic solution as compared with the subjects treated with rewetting drops at week 4 (P=0.004; primary endpoint), in addition to weeks 2 and 3. The improvement in the mean comfortable wear time for the patients in the azithromycin treatment group exceeded 2 hrs throughout the treatment period (weeks 1-4). No significant differences were observed between the groups for total wear time, low contrast visual acuity, or tear osmolarity. Subject-rated ocular dryness (PM time assessments) was significantly improved from baseline in the subjects treated with azithromycin ophthalmic solution as compared with those treated with rewetting drops at weeks 2 and 3 endpoints (P=0.015 for each week). Additionally, a statistical difference was observed in favor of the azithromycin treatment group at week 2 for the subjects reclassifying as nondry eye as determined by the CLDEQ (P=0.05). CONCLUSIONS: Treatment with topical azithromycin ophthalmic solution was well tolerated and resulted in a significant improvement in comfortable contact lens wear time in the patients with CLDE.

GEECORR: A SAS macro for regression models of correlated binary responses and within-cluster correlation using generalized estimating equations.

BACKGROUND AND OBJECTIVES: Generalized estimating equations (GEE) provide population-averaged model inference for longitudinal and clustered outcomes via a generalized linear model for the effect of explanatory variables on the marginal mean, while intra-cluster correlations are ordinarily treated as nuisance parameters. Software to richly parameterize and conduct inference for complex correlation structures in the marginal modeling framework is scarce. METHODS: A SAS macro, GEECORR, has been developed for the analysis of clustered binary data based on GEE to include additional estimating equations for modeling pairwise correlation between binary variates as a function of covariates. RESULTS: We illustrate the macro in a surveillance study with repeated measures, a longitudinal study, and a study with biological clustering. CONCLUSIONS: This article provides an overview of the GEE method consisting of a pair of estimating equations, describes the features and capabilities of the GEECORR macro including regression diagnostics and finite-sample bias-corrected covariance estimators, and demonstrates the macro usage for three studies.

A Real-World Observational Cohort of Patients with Hepatocellular Carcinoma: Design and Rationale for TARGET-HCC.

This study describes the design of the TARGET-hepatocellular carcinoma (HCC) cohort and descriptive characteristics of the patient population at diagnosis among those who were enrolled in the cohort across academic and community clinical centers. TARGET-HCC is a 5-year, longitudinal, observational cohort of patients with HCC receiving care in usual clinical practice. Redacted clinical information, obtained from medical records, captures the natural history and management of the disease, including the safety and efficacy of treatment interventions used in usual clinical practice. Patients can complete patient-reported outcome measures and provide biological specimens for future translational studies. The TARGET-HCC study includes adults with histologic, cytologic, or radiologic diagnosis of HCC from academic and community centers in both the United States and Europe. A total of 1,841 participants were enrolled between January 9, 2017, and July 23, 2019, at 67 sites in the United States and Europe. To date, the most common liver disease etiology in the cohort continues to be hepatitis C, although nearly half had a nonviral etiology, including alcohol-related liver disease or nonalcoholic steatohepatitis. Most included patients were diagnosed at an early stage (Barcelona Clinic Liver Cancer Stage [BCLC] 0/A), but only approximately one third underwent curative treatment. Systemic therapy has been used in 7.3% of enrolled patients, including 45.7% of those with BCLC stage C tumors. Conclusion: Overall, the TARGET-HCC cohort allows for the assessment of patient characteristics and investigation of new treatment paradigms and sequencing with existing agents as well as novel regimens for HCC.

Entecavir versus lamivudine for patients with HBeAg-negative chronic hepatitis B.

BACKGROUND: Entecavir is a potent and selective antiviral agent that has demonstrated efficacy in phase 2 studies in patients with hepatitis B e antigen (HBeAg)-negative chronic hepatitis B. METHODS: In this phase 3, double-blind trial, we randomly assigned 648 patients with HBeAg-negative chronic hepatitis B who had not previously been treated with a nucleoside analogue to receive 0.5 mg of entecavir or 100 mg of lamivudine once daily for a minimum of 52 weeks. The primary efficacy end point was histologic improvement (a decrease by at least two points in the Knodell necroinflammatory score, without worsening of fibrosis). RESULTS: Histologic improvement after 48 weeks of treatment occurred in 208 of 296 patients in the entecavir group who had adequate baseline liver-biopsy specimens that could be evaluated (70 percent), as compared with 174 of 287 such patients in the lamivudine group (61 percent, P=0.01). More patients in the entecavir group than in the lamivudine group had undetectable serum hepatitis B virus (HBV) DNA levels according to a polymerase-chain-reaction assay (90 percent vs. 72 percent, P<0.001) and normalization of alanine aminotransferase levels (78 percent vs. 71 percent, P=0.045). The mean reduction in serum HBV DNA levels from baseline to week 48 was greater with entecavir than with lamivudine (5.0 vs. 4.5 log [on a base-10 scale] copies per milliliter, P<0.001). There was no evidence of resistance to entecavir. Safety and adverse-event profiles were similar in the two groups. CONCLUSIONS: Among patients with HBeAg-negative chronic hepatitis B who had not previously been treated with a nucleoside analogue, the rates of histologic improvement, virologic response, and normalization of alanine aminotransferase levels were significantly higher at 48 weeks with entecavir than with lamivudine. The safety profile of the two agents was similar, and there was no evidence of viral resistance to entecavir. (ClinicalTrials.gov number, NCT00035789.).

Rethinking the Clinically Based Thresholds of TransCelerate BioPharma for Risk-Based Monitoring.

BACKGROUND: The quality of data from clinical trials has received a great deal of attention in recent years. Of central importance is the need to protect the well-being of study participants and maintain the integrity of final analysis results. However, traditional approaches to assess data quality have come under increased scrutiny as providing little benefit for the substantial cost. Numerous regulatory guidance documents and industry position papers have described risk-based approaches to identify quality and safety issues. In particular, the position paper of TransCelerate BioPharma recommends defining risk thresholds to assess safety and quality risks based on past clinical experience. This exercise can be extremely time-consuming, and the resulting thresholds may only be relevant to a particular therapeutic area, patient or clinical site population. In addition, predefined thresholds cannot account for safety or quality issues where the underlying rate of observing a particular problem may change over the course of a clinical trial, and often do not consider varying patient exposure. METHODS: In this manuscript, we appropriate rules commonly utilized for funnel plots to define a traffic-light system for risk indicators based on statistical criteria that consider the duration of patient follow-up. Further, we describe how these methods can be adapted to assess changing risk over time. Finally, we illustrate numerous graphical approaches to summarize and communicate risk, and discuss hybrid clinical-statistical approaches to allow for the assessment of risk at sites with low patient enrollment. RESULTS: We illustrate the aforementioned methodologies for a clinical trial in patients with schizophrenia. CONCLUSIONS: Funnel plots are a flexible graphical technique that can form the basis for a risk-based strategy to assess data integrity, while considering site sample size, patient exposure, and changing risk across time.

Sources of Safety Data and Statistical Strategies for Design and Analysis: Clinical Trials.

BACKGROUND: There has been an increased emphasis on the proactive and comprehensive evaluation of safety endpoints to ensure patient well-being throughout the medical product life cycle. In fact, depending on the severity of the underlying disease, it is important to plan for a comprehensive safety evaluation at the start of any development program. Statisticians should be intimately involved in this process and contribute their expertise to study design, safety data collection, analysis, reporting (including data visualization), and interpretation. METHODS: In this manuscript, we review the challenges associated with the analysis of safety endpoints and describe the safety data that are available to influence the design and analysis of premarket clinical trials. RESULTS: We share our recommendations for the statistical and graphical methodologies necessary to appropriately analyze, report, and interpret safety outcomes, and we discuss the advantages and disadvantages of safety data obtained from clinical trials compared to other sources. CONCLUSIONS: Clinical trials are an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. This work is a result of the efforts of the American Statistical Association Biopharmaceutical Section Safety Working Group.

Sources of Safety Data and Statistical Strategies for Design and Analysis: Real World Insights.

BACKGROUND: Although randomized controlled clinical trials provide necessary information and serve as the basis for regulatory decision making, a significant gap exists between the evidence these trials provide and what the biomedical community needs. It is recognized that a wealth of data are routinely collected outside clinical trials. Such real-world data (RWD) are not of comparable quality, it does not have similar immunity from bias and confounding as data collected in randomized clinical trials, but it might offer additional understanding of the benefit-risk, provide new insights to different stakeholders, and aid in regulatory decision making. This can be especially true when rare but serious adverse events are considered because randomized clinical trials are often not large enough and have insufficient duration to address safety concerns fully. Also, the passage of the 21st Century Cures bill passed by Congress in 2016 means that several data sources outside traditional clinical trials will play a greater role in regulatory decision making. This manuscript is third in a series of articles from the American Statistical Association Biopharmaceutical Section Safety Working Group. METHODS: In this manuscript, authors reviewed some RWD sources and shared considerations for statistical strategies and methodologies needed to design and analyze observational safety studies and pragmatic trials. RESULTS: Authors presented case studies and shared recommendations for statistical methods necessary to design and analyze safety trials using RWD. CONCLUSIONS: RWD is an important source of safety data that contribute to the totality of safety information available to generate evidence for regulators, sponsors, payers, physicians, and patients. However, it is important to determine if such data are fit for purpose.

Using Contour Plots to Assess the Sensitivity of Clinical Trial Design Assumptions.

BACKGROUND: Sample size calculations are an important part of the design of any clinical trial. These calculations ensure a sufficient number of patients to detect a clinically meaningful difference between 2 treatments with high probability (ie, power). Perhaps less-often discussed, the sample size exercise is important so that resources are not wasted studying too many observations to test a particular hypothesis. Since patients may be randomized to doses of a novel treatment with a limited safety profile, or a placebo which provides no therapeutic benefit, sample size calculations in clinical trials come with an ethical burden not experienced in many subject-matter areas. METHODS: The sample size of a clinical trial should be determined using as much data as is available, over a range of assumptions, and with input from clinical colleagues. Graphical techniques are often utilized to summarize power and sample size calculations. In this manuscript, we propose the use of contour plots to better assess, report, and communicate the sensitivity of clinical trial design assumptions. RESULTS: Through several examples, we illustrate that contour plots are applicable to binary, continuous, and time-to-event endpoints for a variety of study design scenarios. CONCLUSIONS: Contour plots are a useful tool for the study team in designing clinical trials, and they can be included in study documents to better communicate the rationale for sample size for clinicians and regulators. Contour plots provide greater transparency as to the uncertainty of the currently available information, and can be useful in deciding whether to consider adaptive designs.

Effect of person-centered showering and the towel bath on bathing-associated aggression, agitation, and discomfort in nursing home residents with dementia: a randomized, controlled trial.

OBJECTIVES: To evaluate the efficacy of two nonpharmacological techniques in reducing agitation, aggression, and discomfort in nursing home residents with dementia. The techniques evaluated were person-centered showering and the towel bath (a person-centered, in-bed bag-bath with no-rinse soap). DESIGN: A randomized, controlled trial, with a usual-care control group and two experimental groups, with crossover. SETTING: Nine skilled nursing facilities in Oregon and six in North Carolina. PARTICIPANTS: Seventy-three residents with agitation during bathing (69 completed the trial) and 37 nursing assistants who bathed them. MEASUREMENTS: Agitation and aggression were measured using the Care Recipient Behavior Assessment; discomfort was measured using a modification of the Discomfort Scale for Dementia of the Alzheimer Type. Raters who were blinded to subject status coded both from videotaped baths. Secondary measures of effect included bath duration, bath completeness, skin condition, and skin microbial flora. RESULTS: All measures of agitation and aggression declined significantly in both treatment groups but not in the control group, with aggressive incidents declining 53% in the person-centered shower group (P<.001) and 60% in the towel-bath group (P<.001). Discomfort scores also declined significantly in both intervention groups (P<.001) but not in the control group. The two interventions did not differ in agitation/aggression reduction, but discomfort was less with the towel bath (P=.003). Average bath duration increased significantly (by a mean of 3.3 minutes) with person-centered showering but not with the towel bath. Neither intervention resulted in fewer body parts being bathed; both improved skin condition; and neither increased colonization with potentially pathogenic bacteria, corynebacteria, or Candida albicans. CONCLUSION: Person-centered showering and the towel bath constitute safe, effective methods of reducing agitation, aggression, and discomfort during bathing of persons with dementia.

ORTH: R and SAS software for regression models of correlated binary data based on orthogonalized residuals and alternating logistic regressions.

This article describes a new software for modeling correlated binary data based on orthogonalized residuals, a recently developed estimating equations approach that includes, as a special case, alternating logistic regressions. The software is flexible with respect to fitting in that the user can choose estimating equations for association models based on alternating logistic regressions or orthogonalized residuals, the latter choice providing a non-diagonal working covariance matrix for second moment parameters providing potentially greater efficiency. Regression diagnostics based on this method are also implemented in the software. The mathematical background is briefly reviewed and the software is applied to medical data sets.

Statistical and graphical approaches for disproportionality analysis of spontaneously-reported adverse events in pharmacovigilance.

AIM: Combine disproportionality analysis with dynamically interactive graphics to understand spontaneously-reported adverse events in pharmacovigilance. METHODS: Four statistical methods, including Reporting Odds Ratio, Proportional Reporting Ratio, Multi-Item Gamma Poisson Shrinker and Bayesian Confidence Propagation Neural Network that are used for computing disproportionality are described. Tree maps and other graphical techniques are used to display the disproportionality results. RESULTS: Spontaneously-reported adverse events in pharmacovigilance are collected from physicians, patients, or the medical literature by regulatory agencies, pharmaceutical companies and device manufacturers to monitor the safety of a product once it reaches the market. In order to identify potential safety-signals, disproportionality analysis methods compare the rate at which a particular event of interest co-occurs with a given drug with the rate this event occurs without the drug in the event database. Tree maps are employed to interactively display the adverse events for particular drugs and compare the adverse events among the drugs. CONCLUSION: Interactive graphical displays of disproportionality allow the analyst to quickly identify safety signals and perform additional follow-up analyses. Combining statistical methods with dynamically interactive graphics affords insights into the data inaccessible by traditional analysis methods.