Structured benefit-risk assessment for enoxaparin, in the context of its label extension, for the extended treatment of deep vein thrombosis and pulmonary embolism, and prevention of its recurrence in patients with active cancer.

PURPOSE: Guidelines recommend low-molecular-weight heparins (LMWHs) for patients with cancer-associated thrombosis. However, until recently, only dalteparin and tinzaparin were approved in the European Economic Area (EEA) for these patients. This study compares the benefit-risk profile of enoxaparin with dalteparin and tinzaparin for the extended treatment of deep vein thrombosis (DVT) and pulmonary embolism (PE), and prevention of recurrence in adult patients with active cancer. METHODS: A semi-quantitative structured benefit-risk assessment was conducted for the label-extension application of enoxaparin based on the benefit-risk action team descriptive framework: define decision context; determine key benefit and risk outcomes; identify data sources; extract data; interpret results. RESULTS: The key benefits were defined as reduced all-cause mortality and venous thromboembolism (VTE) recurrence (including symptomatic DVT, fatal PE or non-fatal PE); the key risks were major and non-major bleeding of clinical significance, and heparin-induced thrombocytopenia (HIT). Enoxaparin demonstrated comparable effects for the reduction of VTE recurrence and all-cause mortality versus other EEA-approved LMWHs (dalteparin, tinzaparin). There was no evidence of a significant difference between enoxaparin and the comparator groups with regard to incidence of major and non-major bleeding. The data on HIT were too limited to assess the difference between the two groups. CONCLUSIONS: The assessment demonstrated a favourable benefit-risk profile for enoxaparin similar to that of other EEA-approved LMWHs for the treatment of DVT and PE and the prevention of recurrence in patients with active cancer and thus supported the label-extension approval.

Structured Benefit-Risk Assessment of a New Quadrivalent Meningococcal Conjugate Vaccine (MenACYW-TT) in Individuals Ages 12 Months and Older.

INTRODUCTION: A favorable benefit-risk balance is required to support licensure of biologics, in keeping with regulatory agencies' evolving recommendations, including the United States Food and Drugs Administration. We present a structured semi-quantitative benefit-risk analysis of MenACYW-TT, a quadrivalent meningococcal conjugate vaccine against Neisseria meningitidis serogroups, A, C, W and Y versus licensed comparators in individuals aged ≥ 12 months. METHODS: We used data from six MenACYW-TT clinical trials, stratified by age group, versus licensed vaccines: toddlers (12-23 months; Nimenrix® [MCV4-TT]), children (2-9 years; Menveo® [MCV4-CRM]), adolescents (10-17 years; MCV4-CRM or Menactra® [MCV4-DT]), adults (18-55 years; MCV4-DT) and older adults (≥ 56 years; Menomune®-A/C/Y/W-135 [MPSV4]). Eight benefit (seroresponse and seroprotection for A, C, W and Y) and five risk outcomes (any and grade 3 solicited injection site and systemic reactions, and serious adverse events) were measured at Day 30 after initial vaccination. Analyses were conducted by baseline vaccination status (meningococcal vaccine-naïve or vaccine-primed). RESULTS: MenACYW-TT showed favorable seroresponse and seroprotection among vaccine-naïve participants aged ≥ 2 years, against all serogroups, compared with MCV4-CRM, MCV4-DT and MPSV4. In vaccine-naïve toddlers, there was a favorable effect for serogroup C, but no difference between MenACYW-TT and MCV4-TT for serogroups A, Y and W. A favorable effect for MenACYW-TT against serogroup C was observed in all vaccine-naïve and combined vaccine-naïve and MenC conjugate vaccine-primed groups. For all risk criteria, there were no differences between MenACYW-TT and MCV4s in toddlers, children, adolescents and adults. Results for solicited injection site and systemic reactions favored MPSV4 in older adults. CONCLUSIONS: The benefit-risk profile for MenACYW-TT showed favorable seroresponse and seroprotection in individuals aged ≥ 2 years and no difference in risk criteria between MenACYW-TT and MCV4s. MenACYW-TT may provide an alternative to the standard-of-care for meningococcal disease prevention in those aged ≥ 12 months.

Structured benefit-risk evaluation for medicinal products: review of quantitative benefit-risk assessment findings in the literature.

A favorable benefit-risk profile remains an essential requirement for marketing authorization of medicinal drugs and devices. Furthermore, prior subjective, implicit and inconsistent ad hoc benefit-risk assessment methods have rightly evolved towards more systematic, explicit or "structured" approaches. Contemporary structured benefit-risk evaluation aims at providing an objective assessment of the benefit-risk profile of medicinal products and a higher transparency for decision making purposes. The use of a descriptive framework should be the preferred starting point for a structured benefit-risk assessment. In support of more precise assessments, quantitative and semi-quantitative methodologies have been developed and utilized to complement descriptive or qualitative frameworks in order to facilitate the structured evaluation of the benefit-risk profile of medicinal products. In addition, quantitative structured benefit-risk analysis allows integration of patient preference data. Collecting patient perspectives throughout the medical product development process has become increasingly important and key to the regulatory decision-making process. Both industry and regulatory authorities increasingly rely on descriptive structured benefit-risk evaluation and frameworks in drug, vaccine and device evaluation and comparison. Although varied qualitative methods are more commonplace, quantitative approaches have recently been emphasized. However, it is unclear how frequently these quantitative frameworks have been used by pharmaceutical companies to support submission dossiers for drug approvals or to respond to the health authorities' requests. The objective of this study has been to identify and review, for the first time, currently available, published, structured, quantitative benefit-risk evaluations which may have informed health care professionals and/or payor as well as contributed to decision making purposes in the regulatory setting for drug, vaccine and/or device approval. PLAIN LANGUAGE SUMMARY: Quantitative evaluation of the benefit-risk balance for medicinal products The review of the benefits and the risks associated with a medicinal product is called benefit-risk assessment. One of the conditions for a medicinal product to receive marketing authorization is to demonstrate a positive benefit-risk balance in which the benefits outweigh the risks. In order to enhance the transparency and consistency in the assessment of benefit-risk balance, frameworks and quantitative methods have been developed for decision making purposes and regulatory approvals of medicinal products. This article considers published quantitative benefit-risk evaluations which may have informed health care professionals and/or payor as well as contributed to decision making purposes in the regulatory setting for drug, vaccine and/or device approval.

Evaluating the "return on patient engagement initiatives" in medicines research and development: A literature review.

BACKGROUND: Showing how engagement adds value for all stakeholders can be an effective motivator for broader implementation of patient engagement. However, it is unclear what methods can best be used to evaluate patient engagement. This paper is focused on ways to evaluate patient engagement at three decision-making points in the medicines research and development process: research priority setting, clinical trial design and early dialogues with regulators and health technology assessment bodies. OBJECTIVE: Our aim was to review the literature on monitoring and evaluation of patient engagement, with a focus on indicators and methods. SEARCH STRATEGY AND INCLUSION CRITERIA: We undertook a scoping literature review using a systematic search, including academic and grey literature with a focus on evaluation approaches or outcomes associated with patient engagement. No date limits were applied other than a cut-off of publications after July 2018. DATA EXTRACTION AND SYNTHESIS: Data were extracted from 91 publications, coded and thematically analysed. MAIN RESULTS: A total of 18 benefits and 5 costs of patient engagement were identified, mapped with 28 possible indicators for their evaluation. Several quantitative and qualitative methods were found for the evaluation of benefits and costs of patient engagement. DISCUSSION AND CONCLUSIONS: Currently available indicators and methods are of some use in measuring impact but are not sufficient to understand the pathway to impact, nor whether interaction between researchers and patients leads to change. We suggest that the impacts of patient engagement can best be determined not by applying single indicators, but a coherent set of measures.

Comparison of text processing methods in social media-based signal detection.

PURPOSE: Adverse event (AE) identification in social media (SM) can be performed using various types of natural language processing (NLP) and machine learning (ML). These methods can be categorized by complexity and precision level. Co-occurrence-based ML methods are rather basic, as they identify simultaneous appearance of drugs and clinical events in a single post. In contrast, statistical learning methods involve more complex NLP and identify drugs, events, and associations between them. We aimed to compare the ability of co-occurrence and NLP to identify AEs and signals of disproportionate reporting (SDR) in patient-generated SM. We also examined the performance of lift in SM-based signal detection (SD). METHODS: Our examination was performed in a corpus of SM posts crawled from open online patient forums and communities, using the spontaneously reported VigiBase data as reference data set. RESULTS: We found that co-occurrence and NLP produce AEs, which are 57% and 93% consistent with VigiBase AEs, respectively. Among the SDRs identified both in SM and in VigiBase, up to 55.3% were identified earlier in co-occurrence, and up to 32.1% were identified earlier in NLP-processed SM. Using lift in SM SD provided performance similar to frequentist methods, both in co-occurrence and in NLP-processed AEs. CONCLUSION: Our results indicate that using SM as a data source complementary to traditional pharmacovigilance sources should be considered further. Various levels of SM processing may be considered, depending on the preferred policies and tolerance for false-positive to false-negative balance in routine pharmacovigilance processes.

Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis.

BACKGROUND: While traditional signal detection methods in pharmacovigilance are based on spontaneous reports, the use of social media is emerging. The potential strength of Web-based data relies on their volume and real-time availability, allowing early detection of signals of disproportionate reporting (SDRs). OBJECTIVE: This study aimed (1) to assess the consistency of SDRs detected from patients' medical forums in France compared with those detected from the traditional reporting systems and (2) to assess the ability of SDRs in identifying earlier than the traditional reporting systems. METHODS: Messages posted on patients' forums between 2005 and 2015 were used. We retained 8 disproportionality definitions. Comparison of SDRs from the forums with SDRs detected in VigiBase was done by describing the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, receiver operating characteristics curve, and the area under the curve (AUC). The time difference in months between the detection dates of SDRs from the forums and VigiBase was provided. RESULTS: The comparison analysis showed that the sensitivity ranged from 29% to 50.6%, the specificity from 86.1% to 95.5%, the PPV from 51.2% to 75.4%, the NPV from 68.5% to 91.6%, and the accuracy from 68% to 87.7%. The AUC reached 0.85 when using the metric empirical Bayes geometric mean. Up to 38% (12/32) of the SDRs were detected earlier in the forums than that in VigiBase. CONCLUSIONS: The specificity, PPV, and NPV were high. The overall performance was good, showing that data from medical forums may be a valuable source for signal detection. In total, up to 38% (12/32) of the SDRs could have been detected earlier, thus, ensuring the increased safety of patients. Further enhancements are needed to investigate the reliability and validation of patients' medical forums worldwide, the extension of this analysis to all possible drugs or at least to a wider selection of drugs, as well as to further assess performance against established signals.

Assessment of the Utility of Social Media for Broad-Ranging Statistical Signal Detection in Pharmacovigilance: Results from the WEB-RADR Project.

INTRODUCTION AND OBJECTIVE: Social media has been proposed as a possibly useful data source for pharmacovigilance signal detection. This study primarily aimed to evaluate the performance of established statistical signal detection algorithms in Twitter/Facebook for a broad range of drugs and adverse events. METHODS: Performance was assessed using a reference set by Harpaz et al., consisting of 62 US Food and Drug Administration labelling changes, and an internal WEB-RADR reference set consisting of 200 validated safety signals. In total, 75 drugs were studied. Twitter/Facebook posts were retrieved for the period March 2012 to March 2015, and drugs/events were extracted from the posts. We retrieved 4.3 million and 2.0 million posts for the WEB-RADR and Harpaz drugs, respectively. Individual case reports were extracted from VigiBase for the same period. Disproportionality algorithms based on the Information Component or the Proportional Reporting Ratio and crude post/report counting were applied in Twitter/Facebook and VigiBase. Receiver operating characteristic curves were generated, and the relative timing of alerting was analysed. RESULTS: Across all algorithms, the area under the receiver operating characteristic curve for Twitter/Facebook varied between 0.47 and 0.53 for the WEB-RADR reference set and between 0.48 and 0.53 for the Harpaz reference set. For VigiBase, the ranges were 0.64-0.69 and 0.55-0.67, respectively. In Twitter/Facebook, at best, 31 (16%) and four (6%) positive controls were detected prior to their index dates in the WEB-RADR and Harpaz references, respectively. In VigiBase, the corresponding numbers were 66 (33%) and 17 (27%). CONCLUSIONS: Our results clearly suggest that broad-ranging statistical signal detection in Twitter and Facebook, using currently available methods for adverse event recognition, performs poorly and cannot be recommended at the expense of other pharmacovigilance activities.

Validation of New Signal Detection Methods for Web Query Log Data Compared to Signal Detection Algorithms Used With FAERS.

INTRODUCTION: Post-marketing drug surveillance is largely based on signals found in spontaneous reports from patients and healthcare providers. Rare adverse drug reactions and adverse events (AEs) that may develop after long-term exposure to a drug or from drug interactions may be missed. The US FDA and others have proposed that web-based data could be mined as a resource to detect latent signals associated with adverse drug reactions. METHODS: Recently, a web-based search query method called a query log reaction score (QLRS) was developed to detect whether AEs associated with certain drugs could be found from search engine query data. In this study, we compare the performance of two other algorithms, the proportional query ratio (PQR) and the proportional query rate ratio (Q-PRR) against that of two reference signal-detection algorithms (SDAs) commonly used with the FDA AE Reporting System (FAERS) database. RESULTS: In summary, the web query methods have moderate sensitivity (80%) in detecting signals in web query data compared with reference SDAs in FAERS when the web query data are filtered, but the query metrics generate many false-positives and have low specificity compared with reference SDAs in FAERS. CONCLUSION: Future research is needed to find better refinements of query data and/or the metrics to improve the specificity of these web query log algorithms.

Effectiveness and safety of phentolamine mesylate in routine dental care.

BACKGROUND: Phentolamine mesylate (PM) is widely used to reverse local anesthesia after dental procedures. Limited knowledge is available regarding effectiveness and safety in routine dental practice. METHODS: The authors conducted 2 national, prospective, noninterventional, postauthorization effectiveness studies (OraVerse Post-Authorization Efficacy Study [ORAPAES] controlled, OraVerse Non-Interventional Study [ORANIS] uncontrolled) in patients receiving a local anesthetic as part of their dental treatment. They investigated time to recovery of normal sensation and function and the frequency of adverse events (AEs). The authors used Kaplan-Meier methods to analyze times to recovery; in ORAPAES, they used hazard ratios based on Cox models using the control group as a reference. RESULTS: In ORAPAES (n = 856), PM reduced the time to recovery of normal sensation and function with a difference in the median time of 70 and 79 minutes, respectively, with similar results observed in ORANIS (n = 445). In ORAPAES, patients in the PM group had, at any time point, a 2.77-fold higher chance of recovery to normal sensation (hazard ratio, 2.77; 95% confidence interval [CI], 2.35-3.26; P < .001) and for normal function 2.94-fold higher chance of recovery to normal sensation (95% CI, 2.49-3.47; P < .001) than in the control group. The observed incidence of AEs with PM treatment was 8.4% in ORAPAES (95% CI, 6.2-10.9) and 9.7% (95% CI, 7.1-12.7) in ORANIS. No serious AEs occurred. CONCLUSIONS: PM substantially reduced the time to recovery of normal sensation and function after local anesthesia in routine dental treatment. The results confirm the effectiveness, safety, and tolerability of PM used in patients with routine dental conditions in Germany, and that PM augments the safety of dental treatments. PRACTICAL IMPLICATIONS: The authors determined that PM is well suited to reverse local anesthesia after routine dental procedures.

A pilot study on the incidence of severe photosensitivity reactions leading to hospitalization linked to topical ketoprofen and other medications in selected European regions.

The aim of this study was to assess the prevalence of exposure to topical nonsteroidal anti-inflammatory drugs (NSAIDs), particularly ketoprofen, in a convenience sample of the population, to obtain estimates of the incidence of severe photosensitivity leading to hospitalization, and to assess causative factors in three catchment areas: the Paris metropolitan area, the Lombardy region (Italy) and the Prague area. All cases of severe photosensitivity not explained by underlying conditions and admitted to hospitals in the selected areas were included in the study. Controls were patients consecutively admitted to hospitals, in the same areas, for an acute condition or for an elective procedure not suspected of being related to medication use. From October 2012 to September 2013, 920 controls were recruited (median age 44 years, 50.8% females); 8 severe photosensitivity cases were reported in the population aged 18-74 years of the 3 geographical areas during the 1-year surveillance period, corresponding to an incidence rate of 4.81 cases per 10 million person-years (95% confidence interval - CI, 2.07-9.48). Six controls reported 1-month exposure to topical ketoprofen, with an estimated prevalence of 0.65% (95% CI, 0.24-1.42). The population attributable risk for severe photosensitivity reactions linked to ketoprofen was 11.92% (95% CI, -0.12-52.99). This study was conducted in selected European areas and showed that the incidence of severe photosensitivity reactions leading to hospitalization as well as the exposure rate to topical ketoprofen were low. Among topical NSAIDs, topical ketoprofen was the leading cause of photosensitivity reactions but accounted for a limited number of hospitalized cases. Probably most of the relevant reactions were managed in the outpatient setting and a community based case-control study is advisable.

Modeling and predicting the long-term effects of various strategies and objectives of varicella-zoster vaccination campaigns.

BACKGROUND: Susceptible, exposed, infected, and recovered (SEIR) models are increasingly developed and used, but their simplicity contrasts with the wide variety of scenarios before launching vaccination campaigns. METHODS: We investigated the effects of some model-building choices (targets, pace, coverage rate) on the results of SEIR models in the case of vaccination against varicella and herpes zoster. RESULTS: The analysis demonstrated the need for a progressive unvaccinated to vaccinated transition and a dynamic system-equilibrium before vaccination onset. When several doses are considered, new compartments are needed to account for vaccination histories. For varicella, the delay to reach the expected coverage rate and the pace until reaching this rate have significant impacts, especially on the short-term incidence. The impact of vaccination through herd immunity should be systematically investigated. CONCLUSIONS: Graphs help understanding the progress of instantaneous incidence; however, tables of cumulative average incidence over decades should be preferred because of higher stability.

Intranasal triamcinolone use during pregnancy and the risk of adverse pregnancy outcomes.

BACKGROUND: Intranasal corticosteroid use during pregnancy has increased over the past decade. OBJECTIVE: We aim to estimate the safety of intranasal triamcinolone use during pregnancy, which was introduced for over-the-counter use in October 2013. METHODS: We designed a population-based prospective cohort study. From a cohort of 289,723 pregnancies in Montreal, Quebec, Canada, from 1998-2008, intranasal triamcinolone-exposed, other intranasal corticosteroid-exposed, and nonexposed women during the first trimester were studied for major congenital malformations (overall and organ specific) and spontaneous abortions and during the second/third trimesters for small-for-gestational age (SGA) newborns. The first trimester is the time window of interest for malformations and spontaneous abortion (organogenesis), and the second/third trimesters are the time windows of interest for SGA (fetal growth). Logistic regression model-based generalized estimating equations were used. RESULTS: Adjusting for potential confounders, use of intranasal triamcinolone during the first trimester of pregnancy was not significantly associated with the risk of overall congenital malformations (odds ratio [OR], 0.88; 95% CI, 0.60-1.28; 31 exposed cases) compared with nonexposure; however, it was associated with the risk of respiratory defects (OR, 2.71; 95% CI, 1.11-6.64; 5 exposed cases). Pregnancy exposure to intranasal triamcinolone was not significantly associated with the risk of spontaneous abortion (OR, 1.04; 95% CI, 0.76-1.43; 50 exposed cases). No association was found between second- or third-trimester exposure to intranasal triamcinolone and the risk of SGA (OR, 1.06; 95% CI, 0.79-1.43; 50 exposed cases). CONCLUSIONS: Maternal exposure to intranasal triamcinolone during pregnancy was not associated with the risk of SGA/spontaneous abortions/overall malformations. However, it has been shown to increase the risk of respiratory system defects. Chance finding cannot be ruled out.

Methodology of the sensitivity analysis used for modeling an infectious disease.

Mathematical models may be used to help clarify dynamics of several infectious diseases. Because of the complexity of some models and the high degree of uncertainty in estimating many parameters, the present study proposes a rigorous framework for sensitivity analyses of mathematical models using as example a model to assess varicella and herpes zoster incidence. Its main steps are to assess the uncertainty of the factors to be studied, to evaluate qualitatively and quantitatively the impacts of these factors on model results, and to conduct an univariate and multivariate sensitivity analysis. The application of this technique may have considerable utility in the analysis of a wide variety of complex biological and epidemiological models.