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.

Role of pharmacoepidemiology studies in addressing pharmacovigilance questions: a case example of pancreatitis risk among ulcerative colitis patients using mesalazine.

PURPOSE: Well-designed pharmacoepidemiology studies address several limitations of postmarketing spontaneous reports in regard to signal evaluation. This study evaluated a signal of disproportionate reporting of acute pancreatitis cases observed in patients with ulcerative colitis (UC) treated with MMX Multi Matrix System® (MMX®) mesalazine and demonstrated how inherent limitations of postmarketing reports were overcome. METHODS: Adults with UC who were new users of MMX mesalazine or another branded mesalazine (controlled-release, delayed-release, or extended-release mesalazine; balsalazide disodium; olsalazine sodium; sulfasalazine; or sulfasalazine delayed-release) were identified from a large US administrative healthcare claims database. Acute pancreatitis incidence rates were compared between patients on MMX mesalazine versus comparator therapies. Propensity scores were used to match patients on MMX mesalazine with patients on comparator drugs to achieve a balance of baseline patient factors. RESULTS: Crude incidence rates [95 % confidence interval (CI)] of acute pancreatitis among patients on MMX mesalazine were similar to those of patients on comparator therapies [8.55 (5.54-13.21) vs 10.05 (7.54-13.41) per 1000 person-years]; the resulting incidence rate ratio (IRR) was [0.85 (0.48-1.47)]. Propensity score-matching had little influence on the IRR [0.84 (0.46-1.55)]; nor did further adjustment by demographic characteristics, daily dose, and causes of acute pancreatitis [0.76 (0.41-1.43)]. CONCLUSION: Findings of no increase in pancreatitis risk with MMX mesalazine demonstrate the value of pharmacoepidemiology studies for evaluating a drug's postmarket safety profile when confronted with spontaneous reporting data suggestive of a safety issue.

Development and Evaluation of the Algorithm CErtaInty Tool (ACE-IT) to Assess Electronic Medical Record and Claims-based Algorithms' Fit for Purpose for Safety Outcomes.

INTRODUCTION: Electronic health record (EHR) or medical claims-based algorithms (i.e., operational definitions) can be used to define safety outcomes using real-world data. However, existing tools do not allow researchers and decision-makers to adequately appraise whether a particular algorithm is fit for purpose (FFP) to support regulatory decisions on drug safety surveillance. Our objective was to develop a tool to enable regulatory decision-makers and other stakeholders to appraise whether a given algorithm is FFP for a specific decision context. METHODS: We drafted a set of 77 generic items informed by regulatory guidance documents, existing instruments, and publications. The outcome of ischemic stroke served as an exemplar to inform the development of draft items. The items were designed to be outcome independent. We conducted a three-round online Delphi panel to develop and refine the tool and achieve consensus on items (> 70% agreement) among panel participants composed of regulators, researchers from pharmaceutical organizations, academic clinicians, methodologists, pharmacoepidemiologists, and cardiologists. We conducted a qualitative analysis of panel responses. Five pairs of reviewers independently evaluated two ischemic stroke algorithm validation studies to test its application. We developed a user guide, with explanation and elaboration for each item, guidance on essential and additional elements for user responses, and an illustrative example of a complete assessment. Furthermore, we conducted a 2-h online stakeholder panel of 16 participants from regulatory agencies, academic institutions, and industry. We solicited input on key factors for an FFP assessment, their general reaction to the Algorithm CErtaInty Tool (ACE-IT), limitations of the tool, and its potential use. RESULTS: The expert panel reviewed and made changes to the initial list of 77 items. The panel achieved consensus on 38 items, and the final version of the ACE-IT includes 34 items after removal of duplicate items. Applying the tool to two ischemic stroke algorithms demonstrated challenges in its application and identified shared concepts addressed by more than one item. The ACE-IT was viewed positively by the majority of stakeholders. They identified that the tool could serve as an educational resource as well as an information-sharing platform. The time required to complete the assessment was identified as an important limitation. We consolidated items with shared concepts and added a preliminary screen section and a summary assessment box based on their input. The final version of the ACE-IT is a 34-item tool for assessing whether algorithm validation studies on safety outcomes are FFP. It comprises the domains of internal validity (24 items), external validity (seven items), and ethical conduct and reporting of the validation study (three items). The internal validity domain includes sections on objectives, data sources, population, outcomes, design and setting, statistical methods, reference standard, accuracy, and strengths and limitations. The external validity domain includes items that assess the generalizability to a proposed target study. The domain on ethics and transparency includes items on ethical conduct and reporting of the validation study. CONCLUSION: The ACE-IT supports a structured, transparent, and flexible approach for decision-makers to appraise whether electronic health record or medical claims-based algorithms for safety outcomes are FFP for a specific decision context. Reliability and validity testing using a larger sample of participants in other therapeutic areas and further modifications to reduce the time needed to complete the assessment are needed to fully evaluate its utility for regulatory decision-making.

Health Care Disparities, Social Determinants of Health, and Emotional Impacts in Patients with Ulcerative Colitis: Results from a Global Ulcerative Colitis Narrative Patient Survey.

BACKGROUND: The Ulcerative Colitis (UC) Narrative global survey assessed aspects of living with UC. This analysis aimed to identify health care disparities, social determinants of health, and emotional impacts related to UC disease management, patient experience, and quality of life. METHODS: The survey was conducted by The Harris Poll from August 2017 to February 2018 among adults with UC. Responses from 1000 patients in the United States, Canada, Japan, France, and Finland were analyzed based on patient income, employment status, educational level, age, sex, and psychological comorbidities. Odds ratios (ORs) with significant P values (P < .05) from multivariate logistic regression models are reported. RESULTS: Low-income vs high-income patients were less likely to have participated in a peer mentoring (OR, 0.30) or UC education program (OR, 0.51). Patients not employed were less likely to report being in "good/excellent" health (OR, 0.58) than patients employed full time. Patients with low vs high educational levels were less likely to have reached out to patient associations/organizations (OR, 0.59). Patients aged younger than 50 years vs those aged 50 years and older were less likely to have visited an office within an inflammatory bowel disease center/clinic in the past 12 months (OR, 0.53). Males were less likely to be currently seeing their gastroenterologist than females (OR, 0.66). Patients with vs without depression were less likely to agree that UC had made them more resilient (OR, 0.51). CONCLUSIONS: Substantial differences in disease management and health care experience were identified, based on categories pertaining to patient demographics and psychological comorbidities, which may help health care providers better understand and advance health equity to improve patient care.

Patient-reported survey results revealed substantial differences in disease management and health care experience in patients with ulcerative colitis, based on categories pertaining to patient demographics and diagnosed psychological comorbidities, including income level, employment status, educational level, age, sex, depression, and anxiety.

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.

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.

Disease-Specific Health Disparities: A Targeted Review Focusing on Race and Ethnicity.

BACKGROUND: Wide disparities in health status exist in the United States across race and ethnicity, broadly driven by social determinants of health-most notably race and ethnic group differences in income, education, and occupational status. However, disparities in disease frequency or severity remain underappreciated for many individual diseases whose distribution in the population varies. Such information is not readily accessible, nor emphasized in treatment guidelines or reviews used by practitioners. Specifically, a summary on disease-specific evidence of disparities from population-based studies is lacking. Our goal was to summarize the published evidence for specific disease disparities in the United States so that this knowledge becomes more widely available "at the bedside". We hope this summary stimulates health equity research at the disease level so that these disparities can be addressed effectively. METHODS: A targeted literature review of disorders in Pfizer's current pipeline was conducted. The 38 diseases included metabolic disorders, cancers, inflammatory conditions, dermatologic disorders, rare diseases, and infectious targets of vaccines under development. Online searches in Ovid and Google were performed to identify sources focused on differences in disease rates and severity between non-Hispanic Whites and Black/African Americans, and between non-Hispanic Whites and Hispanics. As a model for how this might be accomplished for all disorders, disparities in disease rates and disease severity were scored to make the results of our review most readily accessible. After primary review of each condition by one author, another undertook an independent review. Differences between reviewers were resolved through discussion. RESULTS: For Black/African Americans, 29 of the 38 disorders revealed a robust excess in incidence, prevalence, or severity. After sickle cell anemia, the largest excesses in frequency were identified for multiple myeloma and hidradenitis suppurativa. For Hispanics, there was evidence of disparity in 19 diseases. Most notable were metabolic disorders, including non-alcoholic steatohepatitis (NASH). CONCLUSIONS: This review summarized recent disease-specific evidence of disparities based on race and ethnicity across multiple diseases, to inform clinicians and health equity research. Our findings may be well known to researchers and specialists in their respective fields but may not be common knowledge to health care providers or public health and policy institutions. Our hope is that this effort spurs research into the causes of the many disease disparities that exist in the United States.

Identifying Valid Algorithms for Number of Lines of Anti-Neoplastic Therapy in the Danish National Patient Registry Among Patients with Advanced Ovarian, Gastric, Renal Cell, Urothelial, and Non-Small Cell Lung Cancer Attending a Danish University Hospital.

PURPOSE: To develop algorithms to identify number of lines of anti-neoplastic therapy per patient based on the Danish National Patient Registry (DNPR) and identify which algorithm has the highest percentage agreement with a reference standard of documentation in medical records. PATIENTS AND METHODS: We included 179 patients diagnosed between January 1, 2012, and December 31, 2016, with stage II, III, or IV urothelial cell carcinoma or stage III or IV epithelial ovarian cancer, gastric adenocarcinoma, renal cell carcinoma, or non-small cell lung cancer (NSCLC). We developed two algorithms for number of lines of anti-neoplastic therapy based on dates and treatment codes (eg, "treatment with cisplatin" or "cytostatic treatment") in the DNPR. First, to denote a change in line of therapy the "Time-based algorithm" used the number of days between consecutive administrations. Second, the "Drug-based algorithm" used information on drug names if available or the number of days between consecutive administrations if no drug names were specified. We calculated the percentage agreement between the algorithms setting the number of allowed days between consecutive administrations from 28 to 50 and the reference standard - information on anti-neoplastic therapy drugs abstracted from medical records and subsequently coded according to lines of anti-neoplastic therapy. RESULTS: For the "Time-based algorithm", the highest percentage agreement with the reference standard was found when using <45 days between consecutive administrations (67.6%; 95% CI: 60.1-73.8%). However, the percentage agreement was higher for the "Drug-based algorithm" using <45 days between consecutive administrations for registrations where the drug name was unspecified (90.5%; 95% CI: 85.0-93.7%). CONCLUSION: The algorithm for number of lines of anti-neoplastic therapy that had the highest percentage agreement with the reference standard (medical records) incorporated both registration of specific drug names and <45 days between consecutive administrations if the drug name was unspecified in routinely recorded data from DNPR.

Exploring patient preference heterogeneity for pharmacological treatments for chronic pain: A latent class analysis.

BACKGROUND: Several pharmaceutical treatments for chronic pain caused by osteoarthritis (OA) and chronic low back pain (CLBP) are available or currently under development, each associated with different adverse events (AEs) and efficacy profiles. It is therefore important to understand what trade-offs patients are willing to make when choosing between treatments. METHODS: A discrete-choice experiment (DCE) was conducted with 437 adults with chronic pain caused by OA and/or CLBP. Respondents were presented with a series of scenarios and asked to choose between pairs of hypothetical treatments, each defined by six attributes: level of symptom control; risks of heart attack, rapidly progressive osteoarthritis and dependency; frequency and mode of administration and cost. Attributes were based on known profiles of oral nonsteroidal anti-inflammatory drugs, opioids and injected nerve growth factor inhibitors, the last of which were under clinical development at the time of the study. Data were analysed using a latent class (LC) model to explore preference heterogeneity. RESULTS: Overall, respondents considered improving symptom control and reducing risk of physical dependency to be the most important attributes. The LC analysis identified four participant classes: an 'efficacy-focused' class (33.7%), a 'cost-averse' class (29.4%), a 'physical-dependence-averse' class (19.6%) and a 'needle-averse' class (17.3%). Subgroup membership was incompletely predicted by participant age and their responses to comprehension questions. CONCLUSIONS: Preference heterogeneity across respondents indicates a need for a personalized approach to offering treatment options. Symptom improvement, cost, physical dependence and route of administration might be important to different patients. SIGNIFICANCE: Multiple treatment options that differ substantially in terms of efficacy and adverse events are available for the management of chronic pain. With a growing emphasis on a patient-centred care model that incorporates patients' priorities and values into treatment decisions, there is a need to understand how individuals with chronic musculoskeletal pain balance the benefits and risks of treatment and how treatment priorities vary among individuals. This study was designed to identify patient preferences for different characteristics of treatments for the management of chronic pain and to investigate how preferences differ among respondents.

The effects of latent variables in the development of comorbidity among common mental disorders.

BACKGROUND: Although numerous studies have examined the role of latent predispositions to internalizing and externalizing disorders in the structure of comorbidity among common mental disorders, none examined latent predispositions in predicting development of comorbidity. METHODS: A novel method was used to study the role of latent variables in the development of comorbidity among lifetime DSM-IV disorders in the National Comorbidity Surveys. Broad preliminary findings are briefly presented to describe the method. The method used survival analysis to estimate time-lagged associations among 18 lifetime DSM-IV anxiety, mood, behavior, and substance disorders. A novel estimation approach examined the extent to which these predictive associations could be explained by latent canonical variables representing internalizing and externalizing disorders. RESULTS: Consistently significant positive associations were found between temporally primary and secondary disorders. Within-domain time-lagged associations were generally stronger than between-domain associations. The vast majority of associations were explained by a model that assumed mediating effects of latent internalizing and externalizing variables, although the complexity of this model differed across samples. A number of intriguing residual associations emerged that warrant further investigation. CONCLUSIONS: The good fit of the canonical model suggests that common causal pathways account for most comorbidity among the disorders considered. These common pathways should be the focus of future research on the development of comorbidity. However, the existence of several important residual associations shows that more is involved than simple mediation. The method developed to carry out these analyses provides a unique way to pinpoint these significant residual associations for subsequent focused study.

High-dose corticosteroid use and risk of hospitalization for infection in patients treated with immune checkpoint inhibitors--A nationwide register-based cohort study.

High-dose corticosteroids have been associated with increased risk of serious infection in patients with metastatic melanoma treated with immune checkpoint inhibitors targeting cytotoxic T-lymphocyte antigen 4. This potential association needs to be examined further among patients with other cancer types and for other immune checkpoint inhibitors. We examined whether receipt of high-dose corticosteroids was associated with increased rates of hospitalization for infection among 981 Danish renal, urothelial, and lung cancer patients followed from first administration of programmed death receptor 1 (PD-1)/programmed death ligand 1 (PD-L1) immune checkpoint inhibitors. Our cohort analysis was based on the information from national medical registries. During follow-up, 522 patients (53.2%) initiated treatment with high-dose corticosteroids and 317 patients (32.3%) experienced at least one hospitalization for infection. In analyses adjusted for age, sex, and previous use of chemotherapy/targeted therapy, initiation of high-dose systemic corticosteroids was associated with increased rate of hospitalization for infections (hazard ratio (HR) = 2.96, 95% confidence interval (CI) = 2.41-3.65) even in patients not receiving any chemotherapy/targeted therapy (HR = 3.66, 95% CI = 2.25-5.96). Our findings showed that high-dose corticosteroid initiation is associated with hospitalization for infection in patients treated with PD-1/PD-L1 immune checkpoint inhibitors. Clinicians and patients should be aware of this risk of infection when initiating treatment with high-dose corticosteroids.

Treatment and Survival in Advanced Non-Small Cell Lung Cancer, Urothelial, Ovarian, Gastric and Kidney Cancer: A Nationwide Comprehensive Evaluation.

PURPOSE: Few studies have described real-world treatment patterns and survival before the widespread use of immune checkpoint inhibitors (ICIs). We aimed to describe anti-cancer treatment including the use of programmed cell death-1 and ligand-1 (PD-1/PD-L1) ICIs and overall survival (OS) in advanced cancer patients as a benchmarking real-world standard before widespread use of ICIs. PATIENTS AND METHODS: Using nationwide Danish medical registries, we assembled cohorts of Danish patients with advanced non-small cell lung cancer (NSCLC) (n=12,283), urothelial carcinoma (n=2504), epithelial ovarian cancer (n=1466), gastric adenocarcinoma (n=1457), and renal cell carcinoma (RCC) (n=1261) diagnosed between 1/1/2013 and 31/12/2017. We describe anti-cancer treatment and OS using proportions, medians, and Kaplan-Meier methods. RESULTS: Between 9% (ovarian cancer) and 25% (gastric adenocarcinoma) of patients did not receive anti-cancer treatment. The remaining patients received surgery, radiation therapy, and/or medical therapy. Chemotherapy was the most frequent medical therapy in all cohorts except for RCC (tyrosine kinase inhibitors). PD-L1/PD-1 ICIs were used in 7-8% of the NSCLC and RCC cohorts-mainly as second or higher line treatments. OS was longest in patients starting treatment with surgery (eg 25.6 months [95%-confidence interval (CI)=21.9-29.4] for NSCLC and 21.4 months [95%-CI=19.8-23.5] for urothelial carcinoma) and shortest for radiation therapy (eg 3.9 months [95%-CI=3.6-4.2] for NSCLC and 12.6 months [95%-CI=9.2-17.5] for urothelial carcinoma). NSCLC patients starting with medical therapy had OS between these limits. Median OS for NSCLC patients starting treatment with PD-L1/PD-1 ICIs was 21.4 months (95%-CI=13.9-not estimable). CONCLUSION: Most patients with advanced NSCLC, urothelial carcinoma, epithelial ovarian cancer, gastric adenocarcinoma and RCC had poor OS in an era where only a minority received PD-L1/PD-1 ICIs. This information on treatment patterns and survival is important as a benchmarking real-world standard before widespread use of ICIs.

Patients' and caregivers' maximum acceptable risk of death for non-curative gene therapy to treat Duchenne muscular dystrophy.

BACKGROUND: Gene therapy offers an etiologically targeted treatment for genetic disorders. Little is known about the acceptance of mortality risk among patients with progressive, fatal conditions. We assessed patients' and caregivers' maximum acceptable risk (MAR) of mortality for gene therapy when used to treat Duchenne muscular dystrophy (DMD). METHODS: The threshold technique was used to assess tolerance for mortality risks using a hypothetical vignette. Gene therapy was described as non-curative and resulting in a slowing of progression and with a 10-year benefit duration. MAR was analyzed using interval regression for gene therapy initiated "now"; in the last year of walking well; in the last year of being able to bring arms to mouth; and in newborns (for caregivers only). RESULTS: Two hundred eighty-five caregivers and 35 patients reported the greatest MAR for gene therapy initiated in last year of being able to lift arms (mean MAR 6.3%), followed by last year of walking well (mean MAR 4.4%), when used "now" (mean MAR 3.5%), and when used in the newborn period (mean MAR 2.1%, caregivers only). About 35% would accept ≥200/2000 risk in the last year of being able to lift arms. Non-ambulatory status predicted accepting 1.8 additional points in MAR "now" compared with ambulatory status (p = 0.010). Respondent type (caregiver or patient) did not predict MAR. CONCLUSION: In this first quantitative study to assess MAR associated with first-generation DMD gene therapy, we find relatively high tolerance for mortality risk in response to a non-curative treatment scenario. Risk tolerance increased with disease progression. Patients and caregivers did not have significantly different MAR. These results have implications for protocol development and shared decision making.

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.

Priorities when deciding on participation in early-phase gene therapy trials for Duchenne muscular dystrophy: a best-worst scaling experiment in caregivers and adult patients.

PURPOSE: Several gene therapy trials for Duchenne muscular dystrophy initiated in 2018. Trial decision making is complicated by non-curative, time-limited benefits; the progressive, fatal course; and high unmet needs. Here, caregivers and patients prioritize factors influencing decision making regarding participation in early-phase gene therapy trials. METHODS: We conducted a best-worst scaling experiment among U.S. caregivers and adults with Duchenne (N = 274). Participants completed 11 choice sets, choosing features they cared about most and least when deciding whether to participate in a hypothetical gene therapy trial. We analyzed the data using sequential conditional logistic regression. RESULTS: Participants prioritized improved muscle function in trial decision making. Concerns about participation limiting later use of gene transfer and editing were also important, as were improved lung and heart function. Low risk of death fell near the middle. Participants cared least about muscle biopsies and potential for randomization to placebo. Adults with Duchenne and caregivers of non-ambulatory children significantly prioritized improved lung function compared to caregivers of ambulatory children. CONCLUSION: Our data demonstrate prioritization of anticipated benefits and opportunity costs relative to potential harms and procedures in gene therapy trial decision making. Such data inform protocol development, education and advocacy efforts, and informed consent.

A model for decision support in signal triage.

Spontaneous reporting of suspected adverse drug reactions (ADRs) has long been a cornerstone of pharmacovigilance. With the increasingly large volume of ADRs, regulatory agencies, scientific/academic organizations and marketing authorization holders have applied statistical tools to assist in signal detection by identifying disproportionate reporting relationships in spontaneous reporting databases. These tools have generated large numbers of signals defined as drug-ADR reporting associations that meet specified statistical criteria. The challenge is to identify which signals are most likely to be medically important and therefore warrant priority for further investigation. Decisions related to signal triage are often complex and are based on a combination of clinical, epidemiological, pharmacological and regulatory criteria. There are no specific regulations, guidelines or standards that provide an objective basis for these decisions. This paper describes preliminary work to identify and quantify the specific factors that contribute to a decision to prioritize a specific drug-ADR combination for further in-depth review. We applied a tool from the discipline of decision analysis to systematically assess the important attributes of spontaneously reported ADRs. A model was created that integrates these assessments and produces rankings for the signals generated from quantitative signalling methods. Although more research is necessary to evaluate the performance of this model fully, preliminary results suggest that the use of formal decision analysis approaches to support signal triage can provide potential benefit and will help meet an important need.

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.

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.