A framework for setting enrollment goals to ensure participant diversity in sponsored clinical trials in the United States.

BACKGROUND: Diversity in clinical trials (CTs) has the potential to improve health equity and close health disparities. Underrepresentation of historically underserved groups compromises the generalizability of trial findings to the target population, hinders innovation, and contributes to low accrual. The aim of this study was to establish a transparent and reproducible process for setting trial diversity enrollment goals informed by the disease epidemiology. METHOD: An advisory board of epidemiologists with expertise in health disparities, equity, diversity, and social determinants of health was convened to evaluate and strengthen the initial goal-setting framework. Data sources used were the epidemiologic literature, US Census, and real-world data (RWD); limitations were considered and addressed where appropriate. A framework was designed to safeguard against the underrepresentation of historically medically underserved groups. A stepwise approach was created with Y/N decisions based on empirical data. RESULTS: We compared race and ethnicity distributions in the RWD of six diseases from Pfizer's portfolio chosen to represent different therapeutic areas (multiple myeloma, fungal infections, Crohn's disease, Gaucher disease, COVID-19, and Lyme disease) to the distributions in the US Census and established trial enrollment goals. Enrollment goals for potential CTs were based on RWD for multiple myeloma, Gaucher disease, and COVID-19; enrollment goals were based on the Census for fungal infections, Crohn's disease, and Lyme disease. CONCLUSIONS: We developed a transparent and reproducible framework for setting CT diversity enrollment goals. We note how limitations due to data sources can be mitigated and consider several ethical decisions in setting equitable enrollment goals.

Multimethod quantitative benefit-risk assessment of treatments for moderate-to-severe osteoarthritis.

OBJECTIVE: Demonstrate how benefit-risk profiles of systemic treatments for moderate-to-severe osteoarthritis (OA) can be compared using a quantitative approach accounting for patient preference. STUDY DESIGN AND SETTING: This study used a multimethod benefit-risk modelling approach to quantifiably compare treatments of moderate-to-severe OA. In total four treatments and placebo were compared. Comparisons were based on four attributes identified as most important to patients. Patient Global Assessment of Osteoarthritis was included as a favourable effect. Unfavourable effects, or risks, included opioid dependence, nonfatal myocardial infarction and rapidly progressive OA leading to total joint replacement. Clinical data from randomized clinical trials, a meta-analysis of opioid dependence and a long-term study of celecoxib were mapped into value functions and weighted with patient preferences from a discrete choice experiment. RESULTS: Lower-dose NGFi had the highest weighted net benefit-risk score (0.901), followed by higher-dose NGFi (0.889) and NSAIDs (0.852), and the lowest score was for opioids (0.762). Lower-dose NGFi was the highest-ranked treatment option even when assuming a low incidence (0.34% instead of 4.7%) of opioid dependence (ie, opioid benefit-risk score 808) and accounting for both the uncertainty in clinical effect estimates (first rank probability 46% vs 20% for NSAIDs) and imprecision in patient preference estimates (predicted choice probability 0.26, 95% confidence interval [CI] 0.25-0.28 vs 0.21, 95% CI 0.19-0.23 for NSAIDs). CONCLUSION: The multimethod approach to quantitative benefit-risk modelling allowed the interpretation of clinical data from the patient perspective while accounting for uncertainties in the clinical effect estimates and imprecision in patient preferences.

Use of Real-World Evidence to Drive Drug Development Strategy and Inform Clinical Trial Design.

Interest in real-world data (RWD) and real-world evidence (RWE) to expedite and enrich the development of new biopharmaceutical products has proliferated in recent years, spurred by the 21st Century Cures Act in the United States and similar policy efforts in other countries, willingness by regulators to consider RWE in their decisions, demands from third-party payers, and growing concerns about the limitations of traditional clinical trials. Although much of the recent literature on RWE has focused on potential regulatory uses (e.g., product approvals in oncology or rare diseases based on single-arm trials with external control arms), this article reviews how biopharmaceutical companies can leverage RWE to inform internal decisions made throughout the product development process. Specifically, this article will review use of RWD to guide pipeline and portfolio strategy; use of novel sources of RWD to inform product development, use of RWD to inform clinical development, use of advanced analytics to harness "big" RWD, and considerations when using RWD to inform internal decisions. Topics discussed will include the use of molecular, clinicogenomic, medical imaging, radiomic, and patient-derived xenograft data to augment traditional sources of RWE, the use of RWD to inform clinical trial eligibility criteria, enrich trial population based on predicted response, select endpoints, estimate sample size, understand disease progression, and enhance diversity of participants, the growing use of data tokenization and advanced analytical techniques based on artificial intelligence in RWE, as well as the importance of data quality and methodological transparency in RWE.

A real-world study on characteristics, treatments and outcomes in US patients with advanced stage ovarian cancer.

BACKGROUND: Detailed epidemiologic descriptions of large populations of advanced stage ovarian cancer patients have been lacking to date. This study aimed to describe the patient characteristics, treatment patterns, survival, and incidence rates of health outcomes of interest (HOI) in a large cohort of advanced stage ovarian cancer patients in the United States (US). METHODS: This cohort study identified incident advanced stage (III/IV) ovarian cancer patients in the US diagnosed from 2010 to 2018 in the HealthCore Integrated Research Database (HIRD) using a validated predictive model algorithm. Descriptive characteristics were presented overall and by treatment line. The incidence rates and 95% confidence intervals for pre-specified HOIs were evaluated after advanced stage diagnosis. Overall survival, time to treatment discontinuation or death (TTD), and time to next treatment or death (TTNT) were defined using treatment information in claims and linkage with the National Death Index. RESULTS: We identified 12,659 patients with incident advanced stage ovarian cancer during the study period. Most patients undergoing treatment received platinum agents (75%) and/or taxanes (70%). The most common HOIs (> 24 per 100 person-years) included abdominal pain, nausea and vomiting, anemia, and serious infections. The median overall survival from diagnosis was 4.5 years, while approximately half of the treated cohort had a first-line time to treatment discontinuation or death (TTD) within the first 4 months, and a time to next treatment or death (TTNT) from first to second-line of about 6 months. CONCLUSIONS: This study describes commercially insured US patients with advanced stage ovarian cancer from 2010 to 2018, and observed diverse treatment patterns, incidence of numerous HOIs, and limited survival in this population.

Development of predictive models to identify advanced-stage cancer patients in a US healthcare claims database.

BACKGROUND: Although healthcare databases are a valuable source for real-world oncology data, cancer stage is often lacking. We developed predictive models using claims data to identify metastatic/advanced-stage patients with ovarian cancer, urothelial carcinoma, gastric adenocarcinoma, Merkel cell carcinoma (MCC), and non-small cell lung cancer (NSCLC). METHODS: Patients with ≥1 diagnosis of a cancer of interest were identified in the HealthCore Integrated Research Database (HIRD), a United States (US) healthcare database (2010-2016). Data were linked to three US state cancer registries and the HealthCore Integrated Research Environment Oncology database to identify cancer stage. Predictive models were constructed to estimate the probability of metastatic/advanced stage. Predictors available in the HIRD were identified and coefficients estimated by Least Absolute Shrinkage and Selection Operator (LASSO) regression with cross-validation to control overfitting. Classification error rates and receiver operating characteristic curves were used to select probability thresholds for classifying patients as cases of metastatic/advanced cancer. RESULTS: We used 2723 ovarian cancer, 6522 urothelial carcinoma, 1441 gastric adenocarcinoma, 109 MCC, and 12,373 NSCLC cases of early and metastatic/advanced cancer to develop predictive models. All models had high discrimination (C > 0.85). At thresholds selected for each model, PPVs were all >0.75: ovarian cancer = 0.95 (95% confidence interval [95% CI]: 0.94-0.96), urothelial carcinoma = 0.78 (95% CI: 0.70-0.86), gastric adenocarcinoma = 0.86 (95% CI: 0.83-0.88), MCC = 0.77 (95% CI 0.68-0.89), and NSCLC = 0.91 (95% CI 0.90 - 0.92). CONCLUSION: Predictive modeling was used to identify five types of metastatic/advanced cancer in a healthcare claims database with greater accuracy than previous methods.

Prevalence, Patient Characteristics, and Pharmacological Treatment of Children, Adolescents, and Adults Diagnosed With ADHD in Sweden.

OBJECTIVE: The objective of this study was to describe the epidemiology of diagnosed ADHD and the pharmacological treatment of patients with ADHD in Sweden. Specifically, this study estimates the prevalence of patients with a newly registered diagnosis of ADHD over a 5-year period, and the prevalence of all patients with a registered ADHD diagnoses over a 6-year period in Sweden. METHOD: Two population-based registries were used as data sources for this study; the National Patient Register (NPR) and the Prescribed Drug Register (PDR). The international Classification of Diseases 10th Revison (ICD-10) was used to identify patients with ADHD. RESULTS: The annual prevalence of ADHD in the general population of Sweden was found to be 1.1 per 1,000 persons in the year 2006 increasing to 4.8 per 1,000 persons in 2011. The corresponding prevalence for newly diagnosed patients increased from 0.6 per 1,000 persons in 2007 to 1.3 per 1,000 persons in 2011. The majority of diagnosed patients received pharmacological treatment, with methylphenidate being the most common dispensed drug. Comorbidities in the autism spectrum were most common for younger patients, while substance abuse, anxiety, and personality disorder were the most common comorbidities in older patients. CONCLUSION: From 2006 to 2011, the number of patients diagnosed with ADHD has increased in Sweden over all ages. The majority of patients diagnosed with ADHD in Sweden received a pharmacological treatment regardless of age. An ADHD diagnosis was often accompanied with psychiatric comorbidity.

Descriptive comparison of drug treatment-persistent, -nonpersistent, and nondrug treatment patients with newly diagnosed attention deficit/hyperactivity disorder in Germany.

BACKGROUND: Attention deficit/hyperactivity disorder (ADHD) is a heterogeneous behavioral disorder commonly found in children, with serious lifetime health and social consequences for both children and their parents. Public awareness of ADHD in Germany has increased in the past decade, but little is known about the costs of treating newly diagnosed patients in clinical practice. OBJECTIVE: This study aimed to describe the resource utilization and treatment costs of patients aged 6 to 17 years with newly diagnosed ADHD, using patient data from a German sickness fund, and to quantify resource utilization by drug treatment and treatment persistence. METHODS: To identify patients with newly diagnosed ADHD, the second largest German sickness fund was utilized. Complete claims data of all de-identified patients meeting eligibility criteria for 2007 and 2008 were extracted. Patients were divided into 1 of 3 treatment groups: drug treatment-persistent, drug treatment-nonpersistent, and nondrug treatment. The differences in costs and resource utilization are reported in a descriptive manner, with paired and unpaired 2-sample Wilcoxon tests used. RESULTS: Of 3407 newly diagnosed patients with ADHD, 1105 (32%) received an ADHD-specific drug following diagnosis; the remaining 2302 comprised the nondrug treatment group. Of the total number of drug-treated patients, 1-year observational data were available for only 786 methylphenidate users (71%). Of these, 503 patients (64%) comprised the drug treatment-persistent group (those having at least 1 prescription every 3 months during the 12 months following their first ADHD prescription) and 283 (36%) comprised the drug treatment-nonpersistent group. After excluding those patients with <12 months of follow-up, 1779 patients (52%) were included in the nondrug-treatment group. Outpatient visits and the number of drug prescriptions and associated costs were highest in the drug treatment-persistent group (P = 0.05); however, the number of hospital admissions and days spent in-hospital were lowest in this group. Significant average savings of €347/y in overall costs(P » 0.05) were noted for the drug treatment­persistent group compared with the drug treatment­non persistent group. Nondrug-treated patients had €181/y lower costs (P » 0.05) comparedtodrugtreatment-persistentgroup.Drugtreatment-nonpersistentpatientswerethemost expensive group [corrected]. These mean savings were €739/y and €552/y (drug treatment-persistent group and drug treatment-nonpersistent group, respectively) compared with nondrug-treated patients. CONCLUSIONS: There are potential cost-savings benefits when patients are treatment persistent compared to nonpersistent [corrected]. Therefore, future disease-management programs might consider treatment persistence as potentially reducing overall payer costs. Additionally, the clinical and psychosocial situations of patients and their families should be taken into account.

Adult ADHD: prevalence of diagnosis in a US population with employer health insurance.

OBJECTIVE: The burden of attention-deficit/hyperactivity disorder (ADHD) in adults is increasingly recognized. This retrospective analysis was designed to estimate the prevalence of diagnosed ADHD in a population of insured, employed individuals and their dependents in the United States. METHODS: Health care claims data obtained from the MarketScan Commercial Claims and Encounters Database were analyzed. Patients with ADHD were identified by at least two diagnostic claims per calendar year. Once identified, patient records were examined for evidence of continuing ADHD. RESULTS: Between 2002 and 2007, the MarketScan database identified 342,284 patients with more than one claim for ADHD. Of these, 79,368 patients met the eligibility for the prevalence estimates. During the study period, the prevalence of diagnosed ADHD among adults increased more than three-fold: 1.24 to 4.02 cases per 1000 covered members. The largest proportion of cases was in the 18-24 years age group (42.8%-45.8% per year). Most cases were males; however, the ratio of females-to-males diagnosed increased over time. ADHD with hyperactivity was prevalent across all age groups analyzed, although more common in the 18-24 years group. Pharmacy claims showed patients receiving medical treatment for ADHD increased from 78% to 88.5%. A limitation of this study is that it is restricted to employed persons and their dependents. Thus, the results from this database may underestimate the true prevalence of diagnosed ADHD in the US population. CONCLUSIONS: While the claims database used included employed insured persons and dependents only, study results highlight the rising prevalence of diagnosed ADHD in a US adult population. The prevalence increased more than three-fold from 2002 to 2007 with the largest increase in the 18-24 years age group. These findings on ADHD prevalence highlight the need for greater attention to the medical treatment of this disorder in different age groups, particularly in young adults.

Evaluating the postmarketing experience of risperidone use during pregnancy: pregnancy and neonatal outcomes.

BACKGROUND: A significant number of women of childbearing age have schizophrenia or other psychoses. This means that there is a considerable risk of in utero exposure to risperidone due to maternal use. OBJECTIVE: To determine whether in utero exposure to the atypical antipsychotic risperidone is associated with poor pregnancy and fetal/neonatal outcomes. METHODS: A search of the Benefit Risk Management Worldwide Safety database, using a selection of preferred terms from the Medical Dictionary of Regulatory Activities, was performed to identify all cases of pregnancy or fetal/neonatal outcomes reported in association with risperidone treatment from its first market launch (international birth date, 1 June 1993) to 31 December 2004. The main measures were the patterns and reporting rates of pregnancy (stillbirth and spontaneous and induced abortion) and fetal/neonatal outcomes (congenital abnormalities, perinatal syndromes and withdrawal symptoms) for women administered risperidone during pregnancy. RESULTS: Overall, 713 pregnancies were identified in women who were receiving risperidone. Data were considered prospective in 516 of these, and retrospective in the remaining 197 cases. The majority of the known adverse pregnancy and fetal/neonatal outcomes were retrospectively reported. Of the 68 prospectively reported pregnancies with a known outcome, organ malformations and spontaneous abortions occurred 3.8% and 16.9% (when the 15 induced abortions were excluded from the denominator, as they were predominantly undertaken for nonmedical reasons), respectively, a finding consistent with background rates of the general population. There were 12 retrospectively reported pregnancies involving major organ malformations, the most frequently reported of which affected the heart, brain, lip and/or palate. There were 37 retrospectively reported pregnancies involving perinatal syndromes, of which 21 cases involved behavioural or motor disorders. In particular, there was a cluster of cases reporting tremor, jitteriness, irritability, feeding problems and somnolence, which may represent a withdrawal-emergent syndrome. CONCLUSION: This comprehensive review of the Benefit Risk Management Worldwide Safety database for case reports of risperidone exposure during pregnancy represents the largest ever published dataset documenting pregnancy outcomes for women taking the atypical antipsychotic risperidone. It indicates that in utero exposure to risperidone does not appear to increase the risk of spontaneous abortions, structural malformations and fetal teratogenic risk above that of the general population. Self-limited extrapyramidal effects in neonates were observed after maternal exposure to risperidone during the third trimester of pregnancy. Risperidone should only be used during pregnancy if the benefits outweigh the potential risks.

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.