Triple challenges - Small sample size in both exposure and control groups to scan rare maternal outcomes in a signal identification approach: A simulation study.

There is a dearth of safety data on maternal outcomes after perinatal medication exposure. Data-mining for unexpected adverse event occurrence in existing datasets is a potentially useful approach. One method, the Poisson tree-based scan statistic (TBSS), assumes that the expected outcome counts, based on incidence of outcomes in the control group, are estimated without error. This assumption may be difficult to satisfy with a small control group. Our simulation study evaluated the effect of imprecise incidence proportions from the control group on TBSS' ability to identify maternal outcomes in pregnancy research. We simulated base case analyses with "true" expected incidence proportions and compared these to imprecise incidence proportions derived from sparse control samples. We varied parameters impacting Type I error and statistical power (exposure group size, outcome's incidence proportion, and effect size). We found that imprecise incidence proportions generated by a small control group resulted in inaccurate alerting, inflation of Type I error, and removal of very rare outcomes for TBSS analysis due to "zero" background counts. Ideally, the control size should be at least several times larger than the exposure size to limit the number of false positive alerts and retain statistical power for true alerts.

Detection of SARS-CoV-2 antibodies after confirmed Omicron BA.1 and presumed BA.4/5 infections using Abbott ARCHITECT and Panbio assays.

Background: Commercial severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests were developed before variants with spike protein mutations emerged, leading to concerns that these tests have reduced sensitivity for detecting antibody responses in individuals infected with Omicron subvariants. This study was performed to evaluate Abbott ARCHITECT serologic assays, AdviseDx SARS-CoV-2 IgG II, and SARS-CoV-2 IgG for the detection of spike (S) and nucleocapsid (N) IgG antibody increases in vaccinated healthcare workers infected with Omicron subvariants. Methods: During the BA.1/2 and BA.4/5 waves, 171 SARS-CoV-2-infected individuals (122 in the BA.1/2 wave, 49 in the BA.4/5 wave) were tested for S and N IgG post infection. Sequencing and SARS-CoV-2 variant confirmation were performed on nasal swab samples from individuals infected during the BA.1/2 wave. Results: Twenty-seven Omicron sequence confirmed individuals in the BA.1/2 wave and all 49 in the BA.4/5 wave had pre-infection antibody data. Compared to pre-infection levels, post-infection S IgG increased 6.6-fold from 1294 ± 302 BAU/ml (mean ± standard error measurement) to 9796 ± 1252 BAU/ml (P < 0.001) during the BA.1/2 wave, and 3.6-fold from 1771 ± 351 BAU/ml to 8224 ± 943 BAU/ml (P < 0.001) during the BA.4/5 wave. N IgG increased post infection 19.1-fold from 0.2 ± 0.1 to 3.7 ± 0.5 (P < 0.001) during the BA.1/2 wave and 13.5-fold from 0.22 ± 0.1 to 3.2 ± 0.3 (P < 0.001) during the BA.4/5 wave. Among 159 infection-naïve individuals, positive N IgG levels were detected with a sensitivity of 88% in the 87 individuals who were tested between 14 days and 60 days post infection. Conclusions: The large increases in post-infection S IgG along with the N IgG sensitivity that was comparable to previously reported N IgG sensitivity data in unvaccinated individuals after Omicron infection, support the use of Abbott SARS-CoV-2 assays for detecting increased S IgG and seroconversion of N IgG in vaccinated individuals post Omicron infection. Given that 68% of the United States population is fully vaccinated, these results are of current relevance.

Outcomes of the "BRCA Quality Improvement Dissemination Program": An initiative to improve patient receipt of cancer genetics services at five health systems.

OBJECTIVE: A quality improvement initiative (QII) was conducted with five community-based health systems' oncology care centers (sites A-E). The QII aimed to increase referrals, genetic counseling (GC), and germline genetic testing (GT) for patients with ovarian cancer (OC) and triple-negative breast cancer (TNBC). METHODS: QII activities occurred at sites over several years, all concluding by December 2020. Medical records of patients with OC and TNBC were reviewed, and rates of referral, GC, and GT of patients diagnosed during the 2 years before the QII were compared to those diagnosed during the QII. Outcomes were analyzed using descriptive statistics, two-sample t-test, chi-squared/Fisher's exact test, and logistic regression. RESULTS: For patients with OC, improvement was observed in the rate of referral (from 70% to 79%), GC (from 44% to 61%), GT (from 54% to 62%) and decreased time from diagnosis to GC and GT. For patients with TNBC, increased rates of referral (from 90% to 92%), GC (from 68% to 72%) and GT (81% to 86%) were observed. Effective interventions streamlined GC scheduling and standardized referral processes. CONCLUSION: A multi-year QII increased patient referral and uptake of recommended genetics services across five unique community-based oncology care settings.

Monitoring Drug Safety in Pregnancy with Scan Statistics: A Comparison of Two Study Designs.

BACKGROUND: Traditional surveillance of adverse infant outcomes following maternal medication exposures relies on pregnancy exposure registries, which are often underpowered. We characterize the statistical power of TreeScan, a data mining tool, to identify potential signals in the setting of perinatal medication exposures and infant outcomes. METHODS: We used empirical data to inform background incidence of major congenital malformations and other birth conditions. Statistical power was calculated using two probability models compatible with TreeScan, Bernoulli and Poisson, while varying the sample size, magnitude of the risk increase, and incidence of a specified outcome. We also simulated larger referent to exposure matching ratios when using the Bernoulli model in the setting of fixed N:1 propensity score matching. Finally, we assessed the impact of outcome misclassification on power. RESULTS: The Poisson model demonstrated greater power to detect signals than the Bernoulli model across all scenarios and suggested a sample size of 4,000 exposed pregnancies is needed to detect a twofold increase in risk of a common outcome (approximately 8 per 1,000) with 85% power. Increasing the fixed matching ratio with the Bernoulli model did not reliably increase power. An outcome definition with high sensitivity is expected to have somewhat greater power to detect signals than an outcome definition with high positive predictive value. CONCLUSIONS: Use of the Poisson model with an outcome definition that prioritizes sensitivity may be optimal for signal detection. TreeScan is a viable method for surveillance of adverse infant outcomes following maternal medication use.

Novel methods for pregnancy drug safety surveillance in the FDA Sentinel System.

PURPOSE: It is a priority of the US Food and Drug Administration (FDA) to monitor the safety of medications used during pregnancy. Pregnancy exposure registries and cohort studies utilizing electronic health record data are primary sources of information but are limited by small sample sizes and limited outcome assessment. TreeScan™, a statistical data mining tool, can be applied within the FDA Sentinel System to simultaneously identify multiple potential adverse neonatal and infant outcomes after maternal medication exposure. METHODS: We implemented TreeScan using the Sentinel analytic tools in a cohort of linked live birth deliveries and infants nested in the IBM MarketScan® Research Database. As a case study, we compared first trimester fluoroquinolone use and cephalosporin use. We used the Bernoulli and Poisson TreeScan statistics with compatible propensity score-based study designs for confounding control (matching and stratification) and used multiple propensity score models with various strategies for confounding control to inform best practices. We developed a hierarchical outcome tree including major congenital malformations and outcomes of gestational length and birth weight. RESULTS: A total of 1791 fluoroquinolone-exposed and 8739 cephalosporin-exposed mother-infant pairs were eligible for analysis. Both TreeScan analysis methods resulted in single alerts that were deemed to be due to uncontrolled confounding or otherwise not warranting follow-up. CONCLUSIONS: In this implementation of TreeScan using Sentinel analytic tools, we did not observe any new safety signals for fluoroquinolone use in the first trimester. TreeScan, with tailored or high-dimensional propensity scores for confounding control, is a valuable tool in addition to current safety surveillance methods for medications used during pregnancy.

Building Blocks for the Long-acting and Permanent Contraceptives Coordinated Registry Network.

Objectives: A multistakeholder expert group under the Women's Health Technology Coordinated Registry Network (WHT-CRN) was organized to develop the foundation for national infrastructure capturing the performance of long-acting and permanent contraceptives. The group, consisting of representatives from professional societies, the US Food and Drug Administration, academia, industry and the patient community, was assembled to discuss the role and feasibility of the CRN and to identify the core data elements needed to assess contraceptive medical product technologies. Design: We applied a Delphi survey method approach to achieve consensus on a core minimum data set for the future CRN. A series of surveys were sent to the panel and answered by each expert anonymously and individually. Results from the surveys were collected, collated and analyzed by a study design team from Weill Cornell Medicine. After the first survey, questions for subsequent surveys were based on the analysis process and conference call discussions with group members. This process was repeated two times over a 6-month time period until consensus was achieved. Results: Twenty-three experts participated in the Delphi process. Participation rates in the first and second round of the Delphi survey were 83% and 100%, respectively. The working group reached final consensus on 121 core data elements capturing reproductive/gynecological history, surgical history, general medical history, encounter information, long-acting/permanent contraceptive index procedures and follow-up, procedures performed in conjunction with the index procedure, product removal, medications, complications related to the long-acting and/or permanent contraceptive procedure, pregnancy and evaluation of safety and effectiveness outcomes. Conclusions: The WHT-CRN expert group produced a consensus-based core set of data elements that allow the study of current and future contraceptives. These data elements influence patient and provider decisions about treatments and include important outcomes related to safety and effectiveness of these medical devices, which may benefit other women's health stakeholders.

Risk of Severe Abnormal Uterine Bleeding Associated with Rivaroxaban Compared with Apixaban, Dabigatran and Warfarin.

INTRODUCTION: There have been reports of clinically relevant uterine bleeding events among women of reproductive age exposed to rivaroxaban. OBJECTIVE: The aim of this study was to compare the risk of severe abnormal uterine bleeding (SAUB) resulting in transfusion or surgical intervention among women on rivaroxaban versus apixaban, dabigatran and warfarin. METHODS: We conducted a retrospective cohort study in the FDA's Sentinel System (10/2010-09/2015) among females aged 18+ years with venous thromboembolism (VTE), or atrial flutter/fibrillation (AF) who newly initiated a direct oral anticoagulant (DOAC; rivaroxaban, apixaban, dabigatran) or warfarin. We followed women from dispensing date until the earliest of transfusion or surgery following vaginal bleeding, disenrollment, exposure or study end date, or recorded death. We estimated hazard ratios (HRs) using Cox proportional hazards regression via propensity score stratification. Four pairwise comparisons were conducted for each intervention. RESULTS: Overall, there was an increased risk of surgical intervention with rivaroxaban when compared with dabigatran (HR 1.19; 95% CI 1.03-1.38), apixaban (1.23; 1.04-1.47), and warfarin (1.34; 1.22-1.47). No difference in risk for surgical intervention was observed for dabigatran-apixaban comparisons. Increased risk of transfusion was observed for rivaroxaban compared with dabigatran (1.49; 1.03-2.17) only. For patients with no gynecological history, rivaroxaban was associated with risk of surgical intervention compared with dabigatran (1.22; 1.05-1.42), apixaban (1.25; 1.04-1.49), and warfarin (1.36; 1.23-1.50). CONCLUSION: Our study found increased SAUB risk with rivaroxaban use compared with other DOACs or warfarin. Increased risk with rivaroxaban was present among women without underlying gynecological conditions. Women on anticoagulant therapy should be aware of a risk of SAUB.