Active Postlicensure Safety Surveillance for Recombinant Zoster Vaccine Using Electronic Health Record Data.

Recombinant zoster vaccine (RZV) (Shingrix; GlaxoSmithKline, Brentford, United Kingdom) is an adjuvanted glycoprotein vaccine that was licensed in 2017 to prevent herpes zoster (shingles) and its complications in older adults. In this prospective, postlicensure Vaccine Safety Datalink study using electronic health records, we sequentially monitored a real-world population of adults aged ≥50 years who received care in multiple US Vaccine Safety Datalink health systems to identify potentially increased risks of 10 prespecified health outcomes, including stroke, anaphylaxis, and Guillain-Barré syndrome (GBS). Among 647,833 RZV doses administered from January 2018 through December 2019, we did not detect a sustained increased risk of any monitored outcome for RZV recipients relative to either historical (2013-2017) recipients of zoster vaccine live, a live attenuated virus vaccine (Zostavax; Merck & Co., Inc., Kenilworth, New Jersey), or contemporary non-RZV vaccine recipients who had an annual well-person visit during the 2018-2019 study period. We confirmed prelicensure trial findings of increased risks of systemic and local reactions following RZV. Our study provides additional reassurance about the overall safety of RZV. Despite a large sample, uncertainty remains regarding potential associations with GBS due to the limited number of confirmed GBS cases that were observed.

Effect of Mexico's vaccination program on Covid-19 cases, hospitalizations, and deaths among older adults in Mexico City.

OBJECTIVE: To characterize the impact of Mexico's Co-vid-19 vaccination campaign of older adults. MATERIALS AND METHODS: We estimated the absolute change in sympto-matic cases, hospitalizations and deaths for vaccine-eligible adults (aged >60 years) and the relative change compared to vaccine-ineligible groups since the campaign started. Re-sults. By May 3, 2021, the odds of Covid-19 cases among adults over 60 compared to 50-59 year olds decreased by 60.3% (95%CI: 53.1, 66.9), and 2 003 cases (95%CI: 1 156, 3 130) were avoided. Hospitalizations and deaths showed similar trends. CONCLUSIONS: Covid-19 events decreased after vaccine rollout among those eligible for vaccination.

Racial disparities in prostate cancer survival in a screened population: Reality versus artifact.

BACKGROUND: Racial disparities in prostate cancer survival (PCS) narrowed during the prostate-specific antigen (PSA) era, suggesting that screening may induce more equitable outcomes. However, the effects of lead time and overdiagnosis can inflate survival even without real screening benefit. METHODS: A simulation model of PCS in the early PSA era (1991-2000) was created. The modeled survival started with baseline survival in the pre-PSA era (1975-1990) and added lead times and overdiagnosis using estimates from published studies. The authors quantified 1) discrepancies between modeled and observed PCS in the PSA era and 2) residual period effects on PCS given specified values for screening benefit. RESULTS: Lead time and overdiagnosis explained more of the improvement in PCS for older ages at diagnosis (46% [95% confidence interval (CI), 44%-50%] for blacks and 51% [95% CI, 50%-52%] for all races ages 50-54 years vs 98% [95% CI, 97%-99%] for blacks and 100% for all races ages 75-79 years). They also explained more of the narrowing in PCS disparities for older ages (33% [95% CI, 31%-43%] for men ages 50-54 years vs 74% [95% CI, 71%-81%] for men ages 75-79 years). The period effects amounted to reductions of 27% to 40% among blacks and 26% to 38% among all races in the risk of prostate cancer death, depending on the screening benefit. CONCLUSIONS: Real improvements in survival disparities in the PSA era are smaller than those observed and reflect similar reductions in the risk of prostate cancer death among blacks and all races. Understanding screening artifacts is necessary for valid interpretation of observed survival trends. Cancer 2018;124:1752-9. © 2018 American Cancer Society.

Estimation of the Cost-Effectiveness of Breast Cancer Screening Using Mammography in Mexico Through a Simulation.

BACKGROUND: Currently, breast cancer is the most prevalent tumor among Mexican women. Screening methods such as mammography could potentially reduce the health and economic burden of breast cancer; however, its risk-benefit balance is still unclear. OBJECTIVE: To estimate the cost-effectiveness of different breast cancer screening programs using mammography in Mexico and to contribute to the decision-making process on this preventive measure. METHODS: A simulation study was performed using population data and incidence rates. Several screening programs were assessed using the cost-effectiveness methodology recommended by the World Health Organization. RESULTS: The feasible recommended screening program has an examination schedule periodicity of every three years, with a population coverage of 0, 15, 18, 20, 25, 20, 18, and 0% for the age groups of 25-40, 40-45, 45-50, 50-55, 55-60, 60-65, 65-70, and 70-75 years, respectively. CONCLUSIONS: Given the present coverage in Mexico, it is necessary to optimize our resource allocation to improve the country's breast cancer prevention policy.

Causal isotonic calibration for heterogeneous treatment effects.

We propose causal isotonic calibration, a novel nonparametric method for calibrating predictors of heterogeneous treatment effects. In addition, we introduce a novel data-efficient variant of calibration that avoids the need for hold-out calibration sets, which we refer to as cross-calibration. Causal isotonic cross-calibration takes cross-fitted predictors and outputs a single calibrated predictor obtained using all available data. We establish under weak conditions that causal isotonic calibration and cross-calibration both achieve fast doubly-robust calibration rates so long as either the propensity score or outcome regression is estimated well in an appropriate sense. The proposed causal isotonic calibrator can be wrapped around any black-box learning algorithm to provide strong distribution-free calibration guarantees while preserving predictive performance.

Pragmatic Randomized Study of Targeted Text Message Reminders to Reduce Missed Clinic Visits.

INTRODUCTION: Missed clinic appointments ("no-shows") waste health system resources, decrease physician availability, and may worsen patient outcomes. Appointment reminders reduce no-shows, though evidence on the optimal number of reminders is limited and sending multiple reminders for every visit is costly. Risk prediction models can be used to target reminders for visits that are likely to be missed. METHODS: We conducted a randomized quality improvement project at Kaiser Permanente Washington among patients with primary care and mental health visits with a high no-show risk comparing the effect of one text message reminder (sent 2 business days prior to the appointment) with 2 text message reminders (sent 2 and 3 days prior) on no-shows and same-day cancellations. We estimated the relative risk (RR) of an additional reminder using G-computation with logistic regression adjusted for no-show risk. RESULTS: Between February 27, 2019 and September 23, 2019, a total of 125,076 primary care visits and 33,593 mental health visits were randomized to either 1 or 2 text message reminders. For primary care visits, an additional text message reduced the chance of no-show by 7% (RR = 0.93, 95% CI: 0.89-0.96) and same-day cancellations by 6% (RR = 0.94, 95% CI: 0.90-0.98). In mental health visits, an additional text message reduced the chance of no-show by 11% (RR = 0.89, 95% CI: 0.86-0.93) but did not impact same-day cancellations (RR = 1.02, 95% CI: 0.96-1.11). We did not find effect modification among subgroups defined by visit or patient characteristics. CONCLUSION: Study findings indicate that using a prediction model to target reminders may reduce no-shows and spend health care resources more efficiently.

Leveraging the entire cohort in drug safety monitoring: part 1 methods for sequential surveillance that use regression adjustment or weighting to control confounding in a multisite, rare event, distributed data setting.

OBJECTIVE: Study designs involving self-controlled or exposure-matched samples are commonly used to monitor postmarket vaccine and drug safety, and they use a subset of the available larger cohort. This article overviews group sequential methods designed for observational data safety monitoring that use the whole exposed and unexposed cohorts by implementing regression adjustment or weighting to control confounding. METHODS: We summarize what is known about the performance of "whole cohort" methods in multisite health plan data networks such as the Sentinel System of the Food and Drug Administration, where outcomes are rare, individual-level patient data cannot be pooled across sites, site heterogeneity is large, and data are dynamically updated over time. RESULTS: Group sequential estimation and testing methods that use regression or weighting can flexibly handle electronic health care data's unpredictability, including an uncertain rate of new product uptake, variable composition of the population over time, and data changes due to dynamic administrative updates. Regression and weighting methods generally have higher power, faster signal detection, and fewer practical challenges compared with some design-based confounder adjustment methods. CONCLUSION: Group sequential regression adjustment and weighting approaches are feasible and underused in practice. They leverage more information than designs that involved sampling and increase power to detect rare adverse effects without increasing bias.