Xuechen Wang

Background: To systematically analyze differences in atherosclerotic cardiovascular disease (ASCVD) burden between young and older adults. Methods: We estimated the prevalence, mortality, and disability-adjusted life years (DALYs) of ASCVD, including ischemic heart disease (IHD), ischemic stroke (IS), and peripheral artery disease (PAD), in individuals aged 20–54 and > 55 years from 1990–2019, utilizing data from the 2019 Global Burden of Disease Study. The annual percentage changes (EAPCs) for age-specific prevalence, mortality, or DALY rates were calculated to quantify the temporal trends of ASCVD burden. We also analyzed population attribution fractions (PAF) of premature ASCVD mortality and DALYs for different risk factors and compared the burden of extremely premature, premature, and non-premature ASCVD cases based on clinical classifications. Results: From 1990–2019, the global prevalence rates of IHD, IS, and PAD in the 20–54 years age group increased by 20.55% (from 694.74 to 837.49 per 100,000 population), 11.50% (from 439.48 to 490.03 per 100,000 population), and 7.38% (from 384.24 to 412.59 per 100,000 population), respectively. Conversely, the ASCVD prevalence in > 55years age group decreased. Adverse outcome burdens, including mortality and DALYs, varied among ASCVD subtypes. The decrease in the mortality/DALY burden of IHD and IS was lower in the 20–54 years group than in the > 55 years group. For PAD, DALYs among those aged 20–54 increased but decreased among those aged > 55 years. When grouped according to socio-demographic index (SDI) values, lower SDI regions exhibited a higher proportion of young ASCVD burden. The prevalence of young IHD, IS, and PAD in low SDI regions reached 20.70%, 40.05%, and 19.31% in 2019, respectively, compared with 12.14%, 16.32%, and 9.54%, respectively, in high SDI regions. Metabolic risks were the primary contributors to the ASCVD burden in both age groups. Increased susceptibility to ambient particulate matter pollution and inadequate control of high body-mass index and high fasting plasma glucose in young individuals may partially explain the differing temporal trends between young and older individuals. Conclusions: The ASCVD burden in young individuals may become a growing global health concern, especially in areas with lower socioeconomic development levels that require more effective primary prevention strategies.

Observational data (e.g. electronic health records) has become increasingly important in evidence-based research on dynamic treatment regimes, which tailor treatments over time to patients based on their characteristics and evolving clinical history. It is of great interest for clinicians and statisticians to identify an optimal dynamic treatment regime that can produce the best expected clinical outcome for each individual and thus maximize the treatment benefit over the population. Observational data impose various challenges for using statistical tools to estimate optimal dynamic treatment regimes. Notably, the task becomes more sophisticated when the clinical outcome of primary interest is time-to-event. Here, we propose a matching-based machine learning method to identify the optimal dynamic treatment regime with time-to-event outcomes subject to right-censoring using electronic health record data. In contrast to the established inverse probability weighting-based dynamic treatment regime methods, our proposed approach provides better protection against model misspecification and extreme weights in the context of treatment sequences, effectively addressing a prevalent challenge in the longitudinal analysis of electronic health record data. In simulations, the proposed method demonstrates robust performance across a range of scenarios. In addition, we illustrate the method with an application to estimate optimal dynamic treatment regimes for patients with advanced non-small cell lung cancer using a real-world, nationwide electronic health record database from Flatiron Health.

Skin cancer has become increasingly common among young adults; however, this population does not consistently adhere to recommended methods for preventing the disease. Interventions in college settings have relied on appearance-focused appeals and have not been able to examine the cumulative effect of multiple behavior change and skin cancer risk communication strategies. The goal of the current study was to examine the unique and combined impacts of personalized ultraviolet (UV) radiation photographs, genetic testing for skin cancer risk, and general skin cancer prevention education. Participants were randomly assigned to one of four conditions: (1) skin cancer prevention education, (2) education + UV photo, (3) education + genetic testing, and (4) education + UV photo + genetic testing. Self-reported sun protection, tanning, and sunburn were assessed at baseline, immediately post-intervention, and 1 month post-intervention. The findings indicated benefits of the interventions to skin cancer prevention behaviors in the overall sample; however, the combined (UV photo + genetic testing) intervention had the most consistent positive effects on behaviors. Intervention effects were distinct across seasons. These results suggest that interventions containing multiple skin cancer risk communication strategies hold promise in benefitting health-promoting behavior changes in an at-risk, young adult population. Trial Registration Number: NCT03979872; Registered 6/5/2019.

Response to Letter in regards to Berberine: Best Alternative Medicine Insight Abating Global Challenges for Treatment of MRSA Infections [Letter]

Patients with terminal cancers commonly receive aggressive and sub-optimal treatment near the end of life, which may not be beneficial in terms of duration or quality of life. To improve end-of-life care, it is essential to develop methods that can accurately predict the short-term risk of death. However, most prediction models for patients with cancer are static in the sense that they only use patient features at a fixed time. We proposed a dynamic prediction model (DPM) that can incorporate time-dependent predictors. We apply this method to patients with advanced non-small-cell lung cancer from a real-world database. Inverse probability of censoring weighted AUC with bootstrap inference was used to compare predictions among models. We found that increasing ECOG performance status and decreasing albumin had negative prognostic associations with overall survival (OS). Moreover, the negative prognostic implications strengthened over the patient disease course. DPMs using both time-independent and time-dependent predictors substantially improved short-term prediction accuracy compared to Cox models using only predictors at a fixed time. The proposed model can be broadly applied for prediction based on longitudinal data, including an estimation of the dynamic effects of time-dependent features on OS and updating predictions at any follow-up time.

Purpose To examine patterns of radiotherapy (RT) and endocrine therapy (ET) use, associations between RT omission and ET adherence, and associations among ET and RT use and disease recurrence in older women with early-stage, estrogen receptor-positive breast cancer. Methods Women age 65 and older diagnosed with hormone receptor-positive, clinically node-negative breast cancer between 2005 and 2018 and who did not undergo mastectomy were included. Multinomial logistic regression was used to examine the trends in practice patterns over time and by age. Kaplan–Meier estimates were used to estimate the probability of ET discontinuation. Cox proportional hazards models were constructed to assess associations between recurrence and ET/RT. Results Of the 484 enrolled patients, 47.9% patients underwent RT and initiated ET, 27.4% received ET alone, 10.2% received RT alone, and 13.8% patients received neither. Older patients had a higher probability of receiving ET alone or neither ET nor RT (both p < 0.001). The probability of initiating ET was greater among patients who underwent RT than those who omitted RT (p < 0.001). Regardless of RT status (RT or no RT), initiation and continuation of ET may be associated with reduced risk of recurrence. Conclusion Patients who opt for no adjuvant therapy, or who do not tolerate ET, are at increased risk of disease recurrence if they omit RT. Clinicians should consider the likelihood a patient will adhere to ET prior to recommending omission of RT.