Accuracy of p53 codon 72 polymorphism status determined by multiple laboratory methods: a latent class model analysis

INTRODUCTION: Studies on the association of a polymorphism in codon 72 of the p53 tumour suppressor gene (rs1042522) with cervical neoplasia have inconsistent results. While several methods for genotyping p53 exist, they vary in accuracy and are often discrepant. METHODS: We used latent class models (LCM) to examine the accuracy of six methods for p53 determination, all conducted by the same laboratory. We also examined the association of p53 with cytological cervical abnormalities, recognising potential test inaccuracy. RESULTS: Pairwise disagreement between laboratory methods occurred approximately 10% of the time. Given the estimated true p53 status of each woman, we found that each laboratory method is most likely to classify a woman to her correct status. Arg/Arg women had the highest risk of squamous intraepithelial lesions (SIL). Test accuracy was independent of cytology. There was no strong evidence for correlations of test errors. DISCUSSION: Empirical analyses ignore possible laboratory errors, and so are inherently biased, but test accuracy estimated by the LCM approach is unbiased when model assumptions are met. LCM analysis avoids ambiguities arising from empirical test discrepancies, obviating the need to regard any of the methods as a “gold” standard measurement. The methods we presented here to analyse the p53 data can be applied in many other situations where multiple tests exist, but where none of them is a gold standard

Informing randomized clinical trials of respiratory syncytial virus vaccination during pregnancy to prevent recurrent childhood wheezing::a sample size analysis

Background: Early RSV illness is associated with wheeze-associated disorders in childhood. Candidate respiratory syncytial virus (RSV) vaccines may prevent acute RSV illness in infants. We investigated the feasibility of maternal RSV vaccine trials to demonstrate reductions in recurrent childhood wheezing in general paediatric populations. Methods: We calculated vaccine trial effect sizes that depended on vaccine efficacy, allocation ratio, rate of early severe RSV illness, risk of recurrent wheezing at age 3, and increased risk of RSV infection on recurrent wheezing. Model inputs came from systematic reviews and meta-analyses. For each combination of inputs, we estimated the sample size required to detect the effect of vaccination on recurrent wheezing. Results: There were 81 scenarios with 1:1 allocation ratio. Risk ratios between vaccination and recurrent wheezing ranged from 0.9 to 1.0 for 70% of the scenarios. Among the 57 more plausible scenarios, the lowest sample size required to detect significant reductions in recurrent wheezing was 6196 mother-infant pairs per trial arm; however, 75% and 47% of plausible scenarios required >31,060 and >100,000 mother-infant pairs per trial arm, respectively. Studies with asthma endpoints at age 5 will likely need to be larger. Discussion: Clinical efficacy trials of candidate maternal RSV vaccines undertaken for licensure are unlikely to demonstrate an effect on recurrent wheezing illness due to the large sample sizes likely needed to demonstrate a significant effect. Further efforts are needed to plan for alternative study designs to estimate the impact of maternal RSV vaccine programs on recurrent childhood wheezing in general populations

Systemic hematogenous maintenance of memory inflation by MCMV infection.

Several low-grade persistent viral infections induce and sustain very large numbers of virus-specific effector T cells. This was first described as a response to cytomegalovirus (CMV), a herpesvirus that establishes a life-long persistent/latent infection, and sustains the largest known effector T cell populations in healthy people. These T cells remain functional and traffic systemically, which has led to the recent exploration of CMV as a persistent vaccine vector. However, the maintenance of this remarkable response is not understood. Current models propose that reservoirs of viral antigen and/or latently infected cells in lymph nodes stimulate T cell proliferation and effector differentiation, followed by migration of progeny to non-lymphoid tissues where they control CMV reactivation. We tested this model using murine CMV (MCMV), a natural mouse pathogen and homologue of human CMV (HCMV). While T cells within draining lymph nodes divided at a higher rate than cells elsewhere, antigen-dependent proliferation of MCMV-specific effector T cells was observed systemically. Strikingly, inhibition of T cell egress from lymph nodes failed to eliminate systemic T cell division, and did not prevent the maintenance of the inflationary populations. In fact, we found that the vast majority of inflationary cells, including most cells undergoing antigen-driven division, had not migrated into the parenchyma of non-lymphoid tissues but were instead exposed to the blood supply. Indeed, the immunodominance and effector phenotype of inflationary cells, both of which are primary hallmarks of memory inflation, were largely confined to blood-localized T cells. Together these results support a new model of MCMV-driven memory inflation in which most immune surveillance occurs in circulation, and in which most inflationary effector T cells are produced in response to viral antigen presented by cells that are accessible to the blood supply

Time to Switch to Second-line Antiretroviral Therapy in Children With Human Immunodeficiency Virus in Europe and Thailand.

Background: Data on durability of first-line antiretroviral therapy (ART) in children with human immunodeficiency virus (HIV) are limited. We assessed time to switch to second-line therapy in 16 European countries and Thailand. Methods: Children aged <18 years initiating combination ART (≥2 nucleoside reverse transcriptase inhibitors [NRTIs] plus nonnucleoside reverse transcriptase inhibitor [NNRTI] or boosted protease inhibitor [PI]) were included. Switch to second-line was defined as (i) change across drug class (PI to NNRTI or vice versa) or within PI class plus change of ≥1 NRTI; (ii) change from single to dual PI; or (iii) addition of a new drug class. Cumulative incidence of switch was calculated with death and loss to follow-up as competing risks. Results: Of 3668 children included, median age at ART initiation was 6.1 (interquartile range (IQR), 1.7-10.5) years. Initial regimens were 32% PI based, 34% nevirapine (NVP) based, and 33% efavirenz based. Median duration of follow-up was 5.4 (IQR, 2.9-8.3) years. Cumulative incidence of switch at 5 years was 21% (95% confidence interval, 20%-23%), with significant regional variations. Median time to switch was 30 (IQR, 16-58) months; two-thirds of switches were related to treatment failure. In multivariable analysis, older age, severe immunosuppression and higher viral load (VL) at ART start, and NVP-based initial regimens were associated with increased risk of switch. Conclusions: One in 5 children switched to a second-line regimen by 5 years of ART, with two-thirds failure related. Advanced HIV, older age, and NVP-based regimens were associated with increased risk of switch

US shelter in place policies and child abuse Google search volume during the COVID-19 pandemic.

The COVID-19 pandemic has led to unemployment, school closures, movement restrictions, and social isolation, all of which are child abuse risk factors. Our objective was to estimate the effect of COVID-19 shelter in place (SIP) policies on child abuse as captured by Google searches. We applied a differences-in-differences design to estimate the effect of SIP on child abuse search volume. We linked state-level SIP policies to outcome data from the Google Health Trends Application Programming Interface. The outcome was searches for child abuse-related phrases as a scaled proportion of total searches for each state-week between December 31, 2017 and June 14, 2020. Between 914 and 1512 phrases were included for each abuse subdomain (physical, sexual, and emotional). Eight states and DC were excluded because of suppressed outcome data. Of the remaining states, 38 introduced a SIP policy between March 19, 2020 and April 7, 2020 and 4 states did not. The introduction of SIP generally led to no change, except for a slight reduction in child abuse search volume in weeks 8-10 post-SIP introduction, net of changes experienced by states that did not introduce SIP at the same time. We did not find strong evidence for an effect of SIP on child abuse searches. However, an increase in total search volume during the pandemic that may be differential between states with and without SIP policies could have biased these findings. Future work should examine the effect of SIP at the individual and population level using other data sources

Harnessing Google Health Trends API Data for Epidemiologic Research

Interest in using internet search data, such as that from the Google Health Trends Application Programming Interface (GHT-API), to measure epidemiologically relevant exposures or health outcomes is growing due to their accessibility and timeliness. Researchers enter search term(s), geography, and time period, and the GHT-API returns a scaled probability of that search term, given all searches within the specified geographic-time period. In this study, we detailed a method for using these data to measure a construct of interest in 5 iterative steps: first, identify phrases the target population may use to search for the construct of interest; second, refine candidate search phrases with incognito Google searches to improve sensitivity and specificity; third, craft the GHT-API search term(s) by combining the refined phrases; fourth, test search volume and choose geographic and temporal scales; and fifth, retrieve and average multiple samples to stabilize estimates and address missingness. An optional sixth step involves accounting for changes in total search volume by normalizing. We present a case study examining weekly state-level child abuse searches in the United States during the coronavirus disease 2019 pandemic (January 2018 to August 2020) as an application of this method and describe limitations