Structured Literature Review to Identify Human Papillomavirus's Natural History Parameters for Dynamic Population Models of Vaccine Impacts

Human papillomavirus (HPV) is a common sexually transmitted virus that can cause cervical cancer and other diseases. Dynamic transmission models (DTMs) have been developed to evaluate the health and economic impacts of HPV vaccination. These models typically include many parameters, such as natural history of the disease, transmission, demographic, behavioral, and screening. To ensure the accuracy of DTM projections, it is important to parameterize them with the best available evidence. This study aimed to identify and synthesize data needed to parametrize DTMs on the natural history of HPV infection and related diseases. Parameters describing data of interest were grouped by their anatomical location (genital warts, recurrent respiratory papillomatosis, and cervical, anal, vaginal, vulvar, head and neck, and penile cancers), and natural history (progression, regression, death, cure, recurrence, detection), and were identified through a systematic literature review (SLR) and complementary targeted literature reviews (TLRs). The extracted data were then synthesized by pooling parameter values across publications, and summarized using the range of values across studies reporting each parameter and the median value from the most relevant study. Data were extracted and synthesized from 223 studies identified in the SLR and TLRs. Parameters frequently reported pertained to cervical cancer outcomes, while data for other anatomical locations were less available. The synthesis of the data provides a large volume of parameter values to inform HPV DTMs, such as annual progression rates from cervical intraepithelial neoplasia (CIN) 1 to CIN 2+ (median of highest quality estimate 0.0836), CIN 2 to CIN 3+ (0.0418), carcinoma in situ (CIS) 2 to local cancer+ (0.0396), and regional to distant cancer (0.0474). Our findings suggest that while there is a large body of evidence on cervical cancer, parameter values featured substantial heterogeneity across studies, and further studies are needed to better parametrize the non-cervical components of HPV DTMs.

Impact of Differential Rates of Disease Progression in Amyloid-Positive Early Alzheimer's Disease: Findings from a Longitudinal Cohort Analysis

BACKGROUND

There is limited literature regarding the impact of differential rates of disease progression on longitudinal outcomes in individuals with early Alzheimer's disease (AD) and confirmed brain amyloid pathology.

OBJECTIVES

To describe the underlying characteristics and long-term outcomes associated with different rates of disease progression among amyloid-positive individuals with early symptomatic AD.

DESIGN

Retrospective observational study.

SETTING

Data from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) in the United States (06/2005-11/2021).

PARTICIPANTS

Individuals with a clinical assessment of mild cognitive impairment or dementia and Clinical Dementia Rating® Dementia Staging Instrument Sum of Boxes (CDR-SB) score 0.5-9.0 (inclusive; first visit defined as the index date) and confirmed amyloid positivity. Participants were stratified into No Progression (change ≤0), Slower Progression (0< change <2.0 points), Median Progression (2.0-point change), and Faster Progression (change >2.0 points) cohorts based on the observed distribution of changes in CDR-SB score between the index and first subsequent visit.

MEASUREMENTS

For each cohort, the functional and neuropsychiatric outcomes were described at index and each subsequent visit for up to five years, and least-square (LS) mean changes from baseline were estimated using linear mixed-effects models adjusting for baseline demographic and clinical characteristics.

RESULTS

Among 1,263 participants included in the analysis, the mean±standard deviation (SD) age at index was 72.7±9.7 years and 55.3% were males. Demographic characteristics and comorbidity profiles at index were similar across cohorts. However, at index, the Faster Progression (N=279) cohort had higher CDR-SB and Functional Assessment Questionnaire (FAQ) scores compared with the No Progression (N=474), Slower Progression (N=297), and Median Progression (N=213) cohorts. Adjusting for baseline characteristics, at year 5 after index the FAQ score increased by 23.6 points for Faster Progression cohort and 10.4, 15.8, and 19.2 points for the No, Slower, and Median Progression cohorts, respectively. The corresponding increases in Neuropsychiatric Inventory Questionnaire (NPI-Q) scores were 6.7 points for the Faster Progression cohort, and by 1.3, 3.1, and 8.3 points, for the No, Slower, and Median Progression cohorts, respectively.

CONCLUSIONS

Despite similar demographic and clinical profiles at baseline, amyloid-positive individuals with greater deterioration based on CDR-SB early in the AD trajectory continue to experience worse functional and behavioral outcomes over time than those with more gradual deterioration in this metric.

Potential Implications of Slowing Disease Progression in Amyloid-Positive Early Alzheimer's Disease: Estimates from Real-World Data

BACKGROUND

Emerging therapies have shown promising results for slowing the progression of Alzheimer's disease (AD). However, the potential impact of these therapies on real-world outcomes remains to be explored.

OBJECTIVE

To examine the impact of slowing AD progression on functional abilities and behavioral symptoms.

DESIGN

Retrospective observational study.

SETTING

Data from the National Alzheimer's Coordinating Center (NACC) Uniform Data Set (UDS) in the United States (06/2005-11/2021, primary analysis) and the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (09/2005-03/2022, sensitivity analysis) were used.

PARTICIPANTS

Individuals with mild cognitive impairment (MCI) or mild dementia, Clinical Dementia Rating Scale Sum of Boxes (CDR-SB) score 0.5-9.0 (inclusive; first visit defined as the index date), and confirmed amyloid positivity were identified in NACC. In ADNI, individuals with at least one clinical center visit with a clinical assessment of MCI or mild dementia and confirmed amyloid positivity were identified.

MEASUREMENTS

Hypothetical effects of slowing disease progression as assessed by CDR-SB on functional and behavioral outcomes including the Functional Activities Questionnaire (FAQ) score, Neuropsychiatric Inventory Questionnaire (NPI-Q) score, and the probability of complete dependence over five years were evaluated using multivariable regression among NACC participants, separately for the subgroups with MCI and mild dementia at baseline, respectively. For the ADNI sensitivity analysis, the hypothetical effects of slowing disease progression were evaluated for FAQ score using multivariable regression among the MCI participants only.

RESULTS

Compared with natural disease progression, slowing progression by 20% over five years for NACC participants with MCI and mild dementia, respectively, would result in 1.7-point (10.8%) and 1.6-point (12.9%) less deterioration based on FAQ; 0.5-point (20.3%) and 0.5-point (19.3%) less deterioration based on NPI-Q; 4.7 percentage-point (22.2%) and 10.1 percentage-point (21.6%) lower probability of complete dependence. Among ADNI participants, delaying disease progression by 20% or 30% over 4 years would avert deterioration based on FAQ of 1.1 points (20.4%) and 1.6 points (29.6%), respectively, compared to natural disease progression.

CONCLUSIONS

Slowing early AD progression could result in preservation of functional and behavioral attributes and functional autonomy for longer.

Comparative efficacy and safety of ozanimod and ponesimod for relapsing multiple sclerosis: A matching-adjusted indirect comparison

BACKGROUND

Ozanimod and ponesimod are sphingosine 1-phosphate receptor modulators approved by the U.S. Food and Drug Administration for treatment of relapsing forms of multiple sclerosis (MS). Given that no head-to-head trials have assessed these two treatments, we performed a matching-adjusted indirect comparison (MAIC) to compare efficacy and safety outcomes between ozanimod and ponesimod for MS.

METHODS

A MAIC compared efficacy and safety of ozanimod and ponesimod at 2 years. Outcomes included annualized relapse rate (ARR) and percentage change from baseline in brain volume loss (BVL) as well as rates of any treatment-emergent adverse events (TEAEs), serious adverse events (AEs), AEs leading to discontinuation, and other safety outcomes. Individual patient-level data were obtained for ozanimod from the RADIANCE-B trial, while aggregate-level patient data were obtained for ponesimod from the OPTIMUM trial. The MAIC was not anchored owing to lack of a common comparator across the two trials. The following characteristics were matched between the trials' populations: age, sex, time since MS symptom onset, relapses in prior year, Expanded Disability Status Scale score, disease-modifying therapies received in the prior 2 years, absence of gadolinium-enhancing T1 lesions, and percentage of patients from Eastern Europe.

RESULTS

After matching, key baseline characteristics were balanced between patients receiving ozanimod and ponesimod. Compared with ponesimod, ozanimod had a numerically lower ARR (rate ratio: 0.80 [95% CI: 0.57, 1.10]) and was associated with a significant reduction in BVL (% change difference: 0.20 [95% CI: 0.05, 0.36]). Additionally, ozanimod was associated with a significantly lower risk of TEAEs (risk difference: -11.9% [95% CI: -16.8%, -7.0%]), AEs leading to discontinuation (-6.1% [95% CI: -8.9%, -3.4%]), and lymphocyte count <0.2 K/μL (-2.3% [95% CI: -4.2%, -0.5%]). There were no statistically significant differences in the other safety outcomes.

CONCLUSION

The MAIC results suggest that, compared with ponesimod, ozanimod is more effective in preserving brain volume, is comparable in terms of reducing relapse rates, and has a favorable safety profile.

Modeling the health and economic implications of adopting a 1-dose 9-valent human papillomavirus vaccination regimen in a high-income country setting: An analysis in the United Kingdom

Although no human papillomavirus (HPV) vaccine is indicated for single-dose administration, some observational evidence suggests that a 1-dose regimen might reduce HPV infection risk to that achieved with 2 doses. This study estimated the potential health and economic outcomes associated with switching from a 2-dose HPV vaccination program for girls and boys aged 13-14 years to an off-label 9-valent (9vHPV), 1-dose regimen, accounting for the uncertainty of the effectiveness and durability of a single dose. A dynamic HPV transmission infection and disease model was adapted to the United Kingdom and included a probabilistic sensitivity analysis using estimated distributions for duration of protection of 1-dose and degree of protection of 1 relative to 2 doses. One-way sensitivity analyses of key inputs were performed. Outcomes included additional cancer and disease cases and the difference in net monetary benefit (NMB). The 1-dose program was predicted to result in 81,738 additional HPV-related cancer cases in males and females over 100 years compared to the 2-dose program, ranging from 36,673 to 134,347 additional cases (2.5% and 97.5% quantiles, respectively), and had a 7.8% probability of being cost-effective at the £20,000/quality-adjusted life years willingness-to-pay (WTP) threshold. In one-way sensitivity analyses, the number of additional cancer cases was sensitive to the median of the duration of protection distribution and coverage rates. The differences in NMBs were sensitive to the median of the duration of protection distribution, dose price and discount rate, but not coverage variations. Across sensitivity analyses, the probability of 1 dose being cost-effective vs 2 doses was < 50% at the standard WTP threshold. Adoption of a 1-dose 9vHPV vaccination program resulted in more vaccine-preventable HPV-related cancer and disease cases in males and females, introduced substantial uncertainty in health and economic outcomes, and had a low probability of being cost-effective compared to the 2-dose program.

Impact of the COVID-19 pandemic on adolescent vaccinations: projected time to reverse deficits in routine adolescent vaccination in the United States

OBJECTIVE

The COVID-19 pandemic has led to significant reductions in the administration of routinely recommended vaccines among adolescents in the US including tetanus, diphtheria, and acellular pertussis (Tdap); meningococcal (ACWY); and human papillomavirus (HPV) vaccines. The extent to which these deficits could persist in 2021 and beyond is unclear. To address this knowledge gap, this study estimated the cumulative deficits of routine vaccine doses among US adolescents during the COVID-19 pandemic and estimated the time and effort needed to recover from those deficits.

METHODS

Monthly reductions in Tdap, meningococcal, and HPV doses administered to US adolescents during the COVID-19 pandemic were quantified using MarketScan Commercial Claims and Encounters data. The time and effort required to reverse the vaccination deficit under various catch-up scenarios were estimated.

RESULTS

Annual doses administered of Tdap, meningococcus, and HPV vaccines decreased by 21.2%, 20.8%, and 24.0%, respectively, in 2020 compared to 2019. For 2021, the reduction in doses administered is projected to be 6%-21% compared to 2019 under different scenarios. The projected deficit of missed doses is expected to be cleared between winter 2023 and fall 2031.

CONCLUSIONS

Administration rates of routine vaccines decreased significantly among US adolescents during COVID-19. Reversing these deficits to mitigate long-term health and economic consequences will require a sustained increase in vaccination rates over multiple years.

Estimating the drivers of urban economic complexity and their connection to economic performance

Estimating the capabilities, or inputs of production, that drive and constrain the economic development of urban areas has remained a challenging goal. We posit that capabilities are instantiated in the complexity and sophistication of urban activities, the know-how of individual workers, and the city-wide collective know-how. We derive a model that indicates how the value of these three quantities can be inferred from the probability that an individual in a city is employed in a given urban activity. We illustrate how to estimate empirically these variables using data on employment across industries and metropolitan statistical areas in the USA. We then show how the functional form of the probability function derived from our theory is statistically superior when compared with competing alternative models, and that it explains well-known results in the urban scaling and economic complexity literature. Finally, we show how the quantities are associated with metrics of economic performance, suggesting our theory can provide testable implications for why some cities are more prosperous than others.

Contagion in Mass Killings and School Shootings

Background

Several past studies have found that media reports of suicides and homicides appear to subsequently increase the incidence of similar events in the community, apparently due to the coverage planting the seeds of ideation in at-risk individuals to commit similar acts.

Methods

Here we explore whether or not contagion is evident in more high-profile incidents, such as school shootings and mass killings (incidents with four or more people killed). We fit a contagion model to recent data sets related to such incidents in the US, with terms that take into account the fact that a school shooting or mass murder may temporarily increase the probability of a similar event in the immediate future, by assuming an exponential decay in contagiousness after an event.

Conclusions

We find significant evidence that mass killings involving firearms are incented by similar events in the immediate past. On average, this temporary increase in probability lasts 13 days, and each incident incites at least 0.30 new incidents (p = 0.0015). We also find significant evidence of contagion in school shootings, for which an incident is contagious for an average of 13 days, and incites an average of at least 0.22 new incidents (p = 0.0001). All p-values are assessed based on a likelihood ratio test comparing the likelihood of a contagion model to that of a null model with no contagion. On average, mass killings involving firearms occur approximately every two weeks in the US, while school shootings occur on average monthly. We find that state prevalence of firearm ownership is significantly associated with the state incidence of mass killings with firearms, school shootings, and mass shootings.

The statistics of urban scaling and their connection to Zipf's law

Urban scaling relations characterizing how diverse properties of cities vary on average with their population size have recently been shown to be a general quantitative property of many urban systems around the world. However, in previous studies the statistics of urban indicators were not analyzed in detail, raising important questions about the full characterization of urban properties and how scaling relations may emerge in these larger contexts. Here, we build a self-consistent statistical framework that characterizes the joint probability distributions of urban indicators and city population sizes across an urban system. To develop this framework empirically we use one of the most granular and stochastic urban indicators available, specifically measuring homicides in cities of Brazil, Colombia and Mexico, three nations with high and fast changing rates of violent crime. We use these data to derive the conditional probability of the number of homicides per year given the population size of a city. To do this we use Bayes’ rule together with the estimated conditional probability of city size given their number of homicides and the distribution of total homicides. We then show that scaling laws emerge as expectation values of these conditional statistics. Knowledge of these distributions implies, in turn, a relationship between scaling and population size distribution exponents that can be used to predict Zipf’s exponent from urban indicator statistics. Our results also suggest how a general statistical theory of urban indicators may be constructed from the stochastic dynamics of social interaction processes in cities.