Re-evaluating the placebo response in recent canine dietary epilepsy trials.

The placebo response is a common phenomenon. Limited evidence is available about its magnitude in canine epilepsy trials, even though it can significantly influence the efficacy evaluation of new treatments. It was hypothesised that the placebo response is diminished when epilepsy trials are conducted in a prospective crossover design. Seizure data spanning six months from three previous multicenter epilepsy studies were analysed. The monthly seizure frequency of 60 dogs diagnosed with idiopathic epilepsy was calculated, comparing baseline data with placebo treatment. Furthermore, differentiation was made between dogs randomised to the placebo group early (Phase 1: first 3 months) or later during the study (Phase 2: second 3 months).The analysis did not reveal any placebo response in terms of monthly seizure frequency. Instead, an increase was noted during the placebo treatment period, with a mean of 2.95 seizures per month compared to 2.30 seizures per month before study entry (p = 0.0378). Additionally, a notable phase effect was observed. Dogs receiving the placebo in the second study phase exhibited a significant increase in monthly seizure frequency compared to baseline (p = 0.0036). Conversely, no significant difference from baseline was observed for dogs receiving the placebo in the first study phase. These findings underscore the considerable variability in placebo responses observed in trials for canine epilepsy, contrasting with previous limited data. The identified phase effect should be carefully considered in the design and evaluation of canine epilepsy trials to ensure a more accurate assessment of efficacy for new treatments.

Pregnancy health in a multi-state U.S. population of systemically underserved patients and their children: PROMISE cohort design and baseline characteristics.

BACKGROUND: Gestational weight gain (GWG) is a routinely monitored aspect of pregnancy health, yet critical gaps remain about optimal GWG in pregnant people from socially marginalized groups, or with pre-pregnancy body mass index (BMI) in the lower or upper extremes. The PROMISE study aims to determine overall and trimester-specific GWG associated with the lowest risk of adverse birth outcomes and detrimental infant and child growth in these underrepresented subgroups. This paper presents methods used to construct the PROMISE cohort using electronic health record data from a network of community-based healthcare organizations and characterize the cohort with respect to baseline characteristics, longitudinal data availability, and GWG. METHODS: We developed an algorithm to identify and date pregnancies based on outpatient clinical data for patients 15 years or older. The cohort included pregnancies delivered in 2005-2020 with gestational age between 20 weeks, 0 days and 42 weeks, 6 days; and with known height and adequate weight measures needed to examine GWG patterns. We linked offspring data from birth records and clinical records. We defined study variables with attention to timing relative to pregnancy and clinical data collection processes. Descriptive analyses characterize the sociodemographic, baseline, and longitudinal data characteristics of the cohort, overall and within BMI categories. RESULTS: The cohort includes 77,599 pregnancies: 53% had incomes below the federal poverty level, 82% had public insurance, and the largest race and ethnicity groups were Hispanic (56%), non-Hispanic White (23%) and non-Hispanic Black (12%). Pre-pregnancy BMI groups included 2% underweight, 34% normal weight, 31% overweight, and 19%, 8%, and 5% Class I, II, and III obesity. Longitudinal data enable the calculation of trimester-specific GWG; e.g., a median of 2, 4, and 6 valid weight measures were available in the first, second, and third trimesters, respectively. Weekly rate of GWG was 0.00, 0.46, and 0.51 kg per week in the first, second, and third trimesters; differences in GWG between BMI groups were greatest in the second trimester. CONCLUSIONS: The PROMISE cohort enables characterization of GWG patterns and estimation of effects on child growth in underrepresented subgroups, ultimately improving the representativeness of GWG evidence and corresponding guidelines.

Social Deprivation and Multimorbidity Among Community-Based Health Center Patients in the United States.

Introduction: Multimorbidity - having 2 or more chronic diseases - is a national public health concern that entails burdensome and costly care for patients, their families, and public health programs. Adults residing in socially deprived areas often have limited access to social and material resources. They also experience a greater multimorbidity burden. Methods: We conducted a retrospective cohort analysis of electronic health record (EHR) data from 678 community-based health centers (CHCs) in 27 states from the Accelerating Data Value Across a National Community Health Center (ADVANCE) Network, a clinical research network, from 2012-2019. We used mixed-effects Poisson regression to examine the relationship of area-level social deprivation (eg, educational attainment, household income, unemployment) to chronic disease accumulation among a sample of patients aged 45 years or older (N = 816,921) residing across 9,362 zip code tabulation areas and receiving care in safety-net health organizations. Results: We observed high rates of chronic disease among this national sample. Prevalence of multimorbidity varied considerably by geographic location, both within and between states. People in more socially deprived areas with Social Deprivation Index (SDI) scores in quartiles 2, 3, and 4 had greater initial chronic disease counts - 17.1%, 17.7%, and 18.0%, respectively - but a slower rate of accumulation compared with people in the least-deprived quartile. Our findings were consistent for models of the composite SDI and those evaluating disaggregated measures of area-level educational attainment, household income, and unemployment. Conclusion: Social factors play an important role in the development and progression of multimorbidity, which suggests that an assessment and understanding of area-level social deprivation is necessary for developing public health strategies to address multimorbidity.

A six-month prospective, randomised, double-blinded, placebo-controlled, crossover, dietary trial design to investigate the potential of psychobiotics on seizure semiology and comorbidities in canine epilepsy: study protocol.

BACKGROUND: Epilepsy is the most common chronic neurological disease in dogs. More than two-thirds of these patients suffer from associated behavioural comorbidities. The latter could have their origin in partially overlapping pathomechanisms, with the intestinal microbiome as a potential key link between them. The current arsenal of drugs for epilepsy management remains limited. Most canine patients continue to have seizures despite treatment and the occurrence of comorbidities is not sufficiently addressed, limiting quality of life of affected dogs and owners. Therefore, novel additional epilepsy management options are urgently needed. The microbiome-gut-brain axis may serve as a new target for the development of innovative multimodal therapeutic approaches to overcome current shortcomings in epilepsy management. METHODS: A six-month prospective, randomised, double-blinded, placebo-controlled, crossover, dietary trial was designed to investigate the potential of the psychobiotic Bifidobacterium longum on behavioural comorbidities in canine epilepsy. Seizure semiology will be evaluated as a secondary outcome measure. Thirty-four privately owned dogs are planned to be included in the ongoing study meeting the following inclusion criteria: Dogs displaying increased anxiety/fear behaviour since the start of the idiopathic epilepsy. Tier II confidence level of the International Veterinary Epilepsy Task Force for the diagnosis of idiopathic epilepsy, with a maximum seizure interval of 3 month and a minimum of three generalised seizures within that period and chronically treated with at least one antiseizure drug without improvement in seizure frequency Each dog will receive the allocated supplement (probiotic vs. placebo) alongside its normal diet for a 3-month period. After a three-week wash out period, the second phase starts by administering the respective other supplement for another 3 months. DISCUSSION: The current study considers modern high-quality standards for epilepsy medication trials. Common biasing effects should be limited to a possible minimum (regression-to-the mean effect, placebo effect, observer effect), ensuring a high validity and accuracy of the acquired results, thus enabling a representative nature of the efficacy of Bifidobacterium longum as add-on supplement for dogs suffering from epilepsy and its comorbidities. This publication should provide a description of the study procedure and data acquisition methods, including prognosed statistical analysis.

Prevalent Multimorbidity Combinations Among Middle-Aged and Older Adults Seen in Community Health Centers.

BACKGROUND: Multimorbidity (≥ 2 chronic diseases) is associated with greater disability and higher treatment burden, as well as difficulty coordinating self-management tasks for adults with complex multimorbidity patterns. Comparatively little work has focused on assessing multimorbidity patterns among patients seeking care in community health centers (CHCs). OBJECTIVE: To identify and characterize prevalent multimorbidity patterns in a multi-state network of CHCs over a 5-year period. DESIGN: A cohort study of the 2014-2019 ADVANCE multi-state CHC clinical data network. We identified the most prevalent multimorbidity combination patterns and assessed the frequency of patterns throughout a 5-year period as well as the demographic characteristics of patient panels by prevalent patterns. PARTICIPANTS: The study included data from 838,642 patients aged ≥ 45 years who were seen in 337 CHCs across 22 states between 2014 and 2019. MAIN MEASURES: Prevalent multimorbidity patterns of somatic, mental health, and mental-somatic combinations of 22 chronic diseases based on the U.S. Department of Health and Human Services Multiple Chronic Conditions framework: anxiety, arthritis, asthma, autism, cancer, cardiac arrhythmia, chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), congestive heart failure, coronary artery disease, dementia, depression, diabetes, hepatitis, human immunodeficiency virus (HIV), hyperlipidemia, hypertension, osteoporosis, post-traumatic stress disorder (PTSD), schizophrenia, substance use disorder, and stroke. KEY RESULTS: Multimorbidity is common among middle-aged and older patients seen in CHCs: 40% have somatic, 6% have mental health, and 24% have mental-somatic multimorbidity patterns. The most frequently occurring pattern across all years is hyperlipidemia-hypertension. The three most frequent patterns are various iterations of hyperlipidemia, hypertension, and diabetes and are consistent in rank of occurrence across all years. CKD-hyperlipidemia-hypertension and anxiety-depression are both more frequent in later study years. CONCLUSIONS: CHCs are increasingly seeing more complex multimorbidity patterns over time; these most often involve mental health morbidity and advanced cardiometabolic-renal morbidity.

Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography.

INTRODUCTION: This study aimed to test the diagnostic significance of FET-PET imaging combined with machine learning for the differentiation between multiple sclerosis (MS) and glioma II°-IV°. METHODS: Our database was screened for patients in whom FET-PET imaging was performed for the diagnostic workup of newly diagnosed lesions evident on MRI and suggestive of glioma. Among those, we identified patients with histologically confirmed glioma II°-IV°, and those who later turned out to have MS. For each group, tumor-to-brain ratio (TBR) derived features of FET were determined. A support vector machine (SVM) based machine learning algorithm was constructed to enhance classification ability, and Receiver Operating Characteristic (ROC) analysis with area under the curve (AUC) metric served to ascertain model performance. RESULTS: A total of 41 patients met selection criteria, including seven patients with MS and 34 patients with glioma. TBR values were significantly higher in the glioma group (TBRmax glioma vs. MS: p = 0.002; TBRmean glioma vs. MS: p = 0.014). In a subgroup analysis, TBR values significantly differentiated between MS and glioblastoma (TBRmax glioblastoma vs. MS: p = 0.0003, TBRmean glioblastoma vs. MS: p = 0.0003) and between MS and oligodendroglioma (ODG) (TBRmax ODG vs. MS: p = 0.003; TBRmean ODG vs. MS: p = 0.01). The ability to differentiate between MS and glioma II°-IV° increased from 0.79 using standard TBR analysis to 0.94 using a SVM based machine learning algorithm. CONCLUSIONS: FET-PET imaging may help differentiate MS from glioma II°-IV° and SVM based machine learning approaches can enhance classification performance.

Dosimetric impact of the positioning variation of tumor treating field electrodes in the PriCoTTF-phase I/II trial.

PURPOSE: The aim of the present study based on the PriCoTTF-phase I/II trial is the quantification of skin-normal tissue complication probabilities of patients with newly diagnosed glioblastoma multiforme treated with Tumor Treating Field (TTField) electrodes, concurrent radiotherapy, and temozolomide. Furthermore, the skin-sparing effect by the clinically applied strategy of repetitive transducer array fixation around their center position shall be examined. MATERIAL AND METHODS: Low-dose cone-beam computed tomography (CBCT) scans of all fractions of the first seven patients of the PriCoTTF-phase I/II trial, used for image guidance, were applied for the dosimetric analysis, for precise TTField transducer array positioning and contour delineation. Within this trial, array positioning was varied from fixation-to-fixation period with a standard deviation of 1.1 cm in the direction of the largest variation of positioning and 0.7 cm in the perpendicular direction. Physical TTField electrode composition was examined and a respective Hounsfield Unit attributed to the TTField electrodes. Dose distributions in the planning CT with TTField electrodes in place, as derived from prefraction CBCTs, were calculated and accumulated with the algorithm Acuros XB. Dose-volume histograms were obtained for the first and second 2 mm scalp layer with and without migrating electrodes and compared with those with fixed electrodes in an average position. Skin toxicity was quantified according to Lyman's model. Minimum doses in hot-spots of 0.05 cm2 and 25 cm2 ( Δ D0.05cm 2 , Δ D25cm 2 ) size in the superficial skin layers were analyzed. RESULTS: Normal tissue complication probabilities (NTCPs) for skin necrosis ranged from 0.005% to 1.474% (median 0.111%) for the different patients without electrodes. NTCP logarithms were significantly dependent on patient (P < 0.0001) and scenario (P < 0.0001) as classification variables. Fixed positioning of TTField arrays increased skin-NTCP by a factor of 5.50 (95%, CI: 3.66-8.27). The variation of array positioning increased skin-NTCP by a factor of only 3.54 (95%, CI: 2.36-5.32) (P < 0.0001, comparison to irradiation without electrodes; P = 0.036, comparison to irradiation with fixed electrodes). NTCP showed a significant rank correlation with D25cm2 over all patients and scenarios (rs  = 0.76; P < 0.0001). CONCLUSION: Skin-NTCP calculation uncovers significant interpatient heterogeneity and may be used to stratify patients into high- and low-risk groups of skin toxicity. Array position variation may mitigate about one-third of the increase in surface dose and skin-NTCP by the TTField electrodes.

The Affordable Care Act improved health insurance coverage and cardiovascular-related screening rates for cancer survivors seen in community health centers.

BACKGROUND: This study assessed the impact of Affordable Care Act (ACA) Medicaid expansion on health insurance rates and receipt of cardiovascular-related preventive screenings (body mass index, glycated hemoglobin [HbA1c], low-density lipoproteins, and blood pressure) for cancer survivors seen in community health centers (CHCs). METHODS: This study identified cancer survivors aged 19 to 64 years with at least 3 CHC visits in 13 states from the Accelerating Data Value Across a National Community Health Center Network (ADVANCE). Via inverse probability of treatment weighting multilevel multinomial modeling, insurance rates before and after the ACA were estimated by whether a patient lived in a state that expanded Medicaid, and changes between a pre-ACA time period and 2 post-ACA time periods were assessed. RESULTS: The weighted estimated sample size included 409 cancer survivors in nonexpansion states and 2650 in expansion states. In expansion states, the proportion of uninsured cancer survivors decreased significantly from 20.3% in 2012-2013 to 4.5%in 2016-2017, and the proportion of those with Medicaid coverage increased significantly from 38.8% to 55.6%. In nonexpansion states, there was a small decrease in uninsurance rates (from 33.6% in 2012-2013 to 22.5% in 2016-2017). Cardiovascular-related preventive screening rates increased over time in both expansion and nonexpansion states: HbA1c rates nearly doubled from the pre-ACA period (2012-2013) to the post-ACA period (2016-2017) in expansion states (from 7.2% to 12.8%) and nonexpansion states (from 9.3% to 16.8%). CONCLUSIONS: This study found a substantial decline in uninsured visits among cancer survivors in Medicaid expansion states. Yet, 1 in 5 cancer survivors living in a state that did not expand Medicaid remained uninsured. Several ACA provisions likely worked together to increase cardiovascular-related preventive screening rates for cancer survivors seen in CHCs.

Smoking Assessment and Current Smoking Status Among Adolescents in Primary Care Settings.

INTRODUCTION: Initiating tobacco use in adolescence increases the risk of nicotine dependence and continued use into adulthood. Primary care visits provide opportunities for the assessment and treatment of tobacco use; however, little is known about prevalence and correlates of assessing smoking status and current use among adolescents in these settings. AIMS AND METHODS: Using electronic health record data from the OCHIN network, we identified adolescents with greater than or equal to one primary care visit to a study clinic (n = 366 clinics from 15 US states) during January 1, 2016 to December 31, 2017. We estimated odds ratios of smoking assessment and current smoking status by patient covariates. RESULTS: Of 140 887 patients, 87.4% were assessed for smoking. Being Latino or Black (adjusted odds ratio = 1.22, 95% confidence interval: 1.13-1.32; adjusted odds ratio = 1.17, 95% confidence interval: 1.07-1.29, respectively, vs. non-Hispanic White), publicly insured, having more visits, and having an asthma diagnosis or other respiratory symptoms were associated with higher odds of assessment. Odds were lower if the patient was male and uninsured. Of those assessed, 1.6% identified as current smokers. Being older, having more visits, an asthma diagnosis, other respiratory symptoms, and lower household income was associated with higher odds of being a current smoker. Latinos and Blacks had lower odds than non-Hispanic Whites. CONCLUSIONS: Although some commonly reported tobacco-related disparities were not present, smoking assessment and current smoking status differed significantly by most patient demographics. Implementation of adolescent tobacco assessment protocols and the development of interventions to target subpopulations of adolescents with higher rates of smoking could mitigate disparate rates of assessment and smoking, respectively. IMPLICATIONS: Clinical guidelines recommend screening adolescents for tobacco use in primary care settings. We found that most adolescents seen in US safety-net primary care clinics were assessed for smoking. We also found that smoking assessment and current smoking status differed significantly by most patient demographics. Implementing tobacco assessment protocols specific to adolescents could mitigate disparate rates of assessment and ensure accurate documentation of all forms of tobacco use, given the evolution of alternative tobacco products and poly use among adolescents. Interventions to target subpopulations of adolescents with higher smoking rates are needed to prevent the negative health effects of continued smoking.

Tobacco Cessation in Affordable Care Act Medicaid Expansion States Versus Non-expansion States.

INTRODUCTION: Community health centers (CHCs) care for vulnerable patients who use tobacco at higher than national rates. States that expanded Medicaid eligibility under the Affordable Care Act (ACA) provided insurance coverage to tobacco users not previously Medicaid-eligible, thereby potentially increasing their odds of receiving cessation assistance. We examined if tobacco users in Medicaid expansion states had increased quit rates, cessation medications ordered, and greater health care utilization compared to patients in non-expansion states. METHODS: Using electronic health record (EHR) data from 219 CHCs in 10 states that expanded Medicaid as of January 1, 2014, we identified patients aged 19-64 with tobacco use status documented in the EHR within 6 months prior to ACA Medicaid expansion and ≥1 visit with tobacco use status assessed within 24 months post-expansion (January 1, 2014 to December 31, 2015). We propensity score matched these patients to tobacco users from 108 CHCs in six non-expansion states (n = 27 670 matched pairs; 55 340 patients). Using a retrospective observational cohort study design, we compared odds of having a quit status, cessation medication ordered, and ≥6 visits within the post-expansion period among patients in expansion versus non-expansion states. RESULTS: Patients in expansion states had increased adjusted odds of quitting (adjusted odds ratio [aOR] = 1.35, 95% confidence interval [CI]: 1.28-1.43), having a medication ordered (aOR = 1.53, 95% CI: 1.44-1.62), and having ≥6 follow-up visits (aOR = 1.34, 95% CI: 1.28-1.41) compared to patients from non-expansion states. CONCLUSIONS: Increased access to insurance via the ACA Medicaid expansion likely led to increased quit rates within this vulnerable population. IMPLICATIONS: CHCs care for vulnerable patients at higher risk of tobacco use than the general population. Medicaid expansion via the ACA provided insurance coverage to a large number of tobacco users not previously Medicaid-eligible. We found that expanded insurance coverage was associated with increased cessation assistance and higher odds of tobacco cessation. Continued provision of insurance coverage could lead to increased quit rates among high-risk populations, resulting in improvements in population health outcomes and reduced total health care costs.

Identifying and characterizing cancer survivors in the US primary care safety net.

BACKGROUND: Primary care providers must understand the use patterns, clinical complexity, and primary care needs of cancer survivors to provide quality health care services. However, to the authors' knowledge, little is known regarding the prevalence and health care needs of this growing population, particularly in safety net settings. METHODS: The authors identified adults with a history of cancer documented in primary care electronic health records within a network of community health centers (CHCs) in 19 states. The authors estimated cancer history prevalence among >1.2 million patients and compared sex-specific site distributions with national estimates. Each survivor was matched to 3 patients without cancer from the same set of clinics. The demographic characteristics, primary care use, and comorbidity burden then were compared between the 2 groups, assessing differences with absolute standardized mean differences (ASMDs). ASMD values >0.1 denote meaningful differences between groups. Generalized estimating equations yielded adjusted odds ratios (aORs) for select indicators. RESULTS: A total of 40,266 cancer survivors were identified (prevalence of 3.0% of adult CHC patients). Compared with matched cancer-free patients, a higher percentage of survivors had ≥6 primary care visits across 3 years (62% vs 48%) and were insured (83% vs 74%) (ASMD, >0.1 for both). Cancer survivors had excess medical complexity, including a higher prevalence of depression, asthma/chronic obstructive pulmonary disease, and liver disease (ASMD, >0.1 for all). Survivors had higher odds of any opioid prescription (aOR, 1.23; 95% CI, 1.19-1.27) and chronic opioid therapy (aOR, 1.27; 95% CI, 1.23-1.32) compared with matched controls (P < .001 for all). CONCLUSIONS: Identifying cancer survivors and understanding their patterns of utilization and physical and mental comorbidities present an opportunity to tailor primary health care services to this population.

Simultaneous primary cancer occurrence of melanoma and pulmonary adenocarcinoma in leptomeningeal metastases: a case report.

BACKGROUND: Leptomeningeal metastasis (LM) is a predominantly late stage, devastating complication of a variety of malignant solid tumors. Diagnosis relies predominantly on neurological, radiographic, and cerebrospinal fluid (CSF) assessments. Recently, liquid biopsy tests derived from CSF has shown to be a feasible, noninvasive promising approach to tumor molecular profiling for proper brain cancer diagnostic treatment, thereby providing an opportunity for CSF-based personalized medicine. However, LM is typically misleadingly assumed to originate from only one primary tumor type. CASE PRESENTATION: In this case report, we provide first evidence of the co-occurrence of LM originating from more than one primary tumor types. DISCUSSION AND CONCLUSIONS: Based on this patient case profile, the co-occurrence of LM from two or more primary tumor types should be accounted for when deriving diagnostic conclusions from liquid biopsy tests.

Insurance coverage and discontinuity during pregnancy: Frequency and associations documented in the PROMISE cohort.

OBJECTIVE: To describe insurance patterns and discontinuity during pregnancy, which may affect the experiences of the pregnant person: their timely access to care, continuity of care, and health outcomes. DATA SOURCES AND STUDY SETTING: Data are from the PROMISE study, which utilizes data from community-based health care organizations (CHCOs) (e.g., federally qualified health centers that serve patients regardless of insurance status or ability to pay) in the United States from 2005 to 2021. STUDY DESIGN: This descriptive study was a cohort utilizing longitudinal electronic health record data. DATA COLLECTION/EXTRACTION METHODS: Insurance type at each encounter was recorded in the clinical database and coded as Private, Public, and Uninsured. Pregnant people were categorized into one of several insurance patterns. We analyzed the frequency and timing of insurance changes and care utilization within each group. PRINCIPAL FINDINGS: Continuous public insurance was the most common insurance pattern (69.2%), followed by uninsured/public discontinuity (11.8%), with 6.4% experiencing uninsurance throughout the entirety of pregnancy. Insurance discontinuity was experienced by 16.6% of pregnant people; a majority of these reflect people transitioning to public insurance. Those with continuous public insurance had the highest frequency of inadequate prenatal care (19.5%), while those with all three types of insurance during pregnancy had the highest percentage of intensive prenatal care (16.5%). The majority (71.7%-81.2%) of those with a discontinuous pattern experienced a single insurance change. CONCLUSIONS: Insurance discontinuity and uninsurance are common within our population of pregnant people seeking care at CHCOs. Our findings suggest that insurance status should be regarded as a dynamic rather than a static characteristic during pregnancy and should be measured accordingly. Future research is needed to assess the drivers of perinatal insurance discontinuity and if and how these discontinuities may affect health care access, utilization, and birth outcomes.

Disparities in COVID-19 vaccination receipt by race, ethnicity, and social determinants of health among a large patient population in a network of community-based healthcare centers.

BACKGROUND: There are known disparities in U.S. COVID-19 vaccination but there is limited information on national vaccine uptake in a large, racially diverse, all-age population. Here, we describe COVID-19 vaccination coverage in a large U.S. population accessing care in OCHIN (not an acronym), a national network of community-based healthcare organizations. METHODS: Within OCHIN, we identified patients aged 6 months and older with ≥1 completed clinical encounter since becoming age-eligible for the COVID-19 vaccine between December 13, 2020 and December 31, 2022. Patients' COVID-19 vaccination status was assessed from OCHIN's Epic® electronic health record which includes data from state immunization information systems. Patients were considered vaccinated if they received ≥1 dose of a monovalent vaccine product; coverage was categorized by age groups (6 months-4 years; 5-11 years, 12-15 years, 16+ years). Multivariate analyses assessed factors associated with COVID-19 vaccination across age groups. RESULTS: The cohort included 3.3 million Hispanic (37 %), non-Hispanic (NH) White (31 %), NH Black (15 %), and NH Asian (7 %) patients; 45 % of whom were Medicaid-enrolled, 19 % uninsured, and 53 % with a household income below 100 % of the federal poverty level. The proportion with ≥1 COVID-19 vaccine dose increased with age, from 11.7 % (6 months through 4 years) to 72.3 % (65 years and older). The only factors associated with significantly higher COVID-19 vaccine coverage across age groups were prior receipt of an influenza vaccine and having private insurance. In adjusted modeling, when compared to NH whites, COVID-19 vaccine coverage was significantly higher among Hispanic, NH Asian, and NH multiple-race patients aged ≥5 years and significantly lower among NH Black and NH Native Hawaiian/Other Pacific Islander patients aged 6 months-4 years old. CONCLUSIONS: We identified disparities in primary series COVID-19 vaccine coverage by age, race and ethnicity, household income, insurance status, and prior influenza vaccination within this large, diverse population accessing care in community-based healthcare organizations.

Trimester-specific rate of gestational weight loss or gain and birth size: differences by prepregnancy BMI.

OBJECTIVE: The objective of this study was to estimate the effects of trimester-specific gestational weight gain (GWG) on small and large (compared with appropriate) for gestational age (i.e., SGA, LGA, and AGA) by prepregnancy BMI classifications. METHODS: We conducted a cohort study of pregnancies in a national network of community health care organizations, stratifying by prepregnancy BMI (n = 20,676 with normal weight; 19,156 with overweight; 11,647 with obesity class I; 5124 with obesity class II; and 3197 with obesity class III). SGA and LGA (vs. AGA) were modeled as a function of trimester 1, 2, or 3 GWG rate, previous trimester(s) GWG rate, and maternal characteristics using modified Poisson regression. RESULTS: GWG rates ranged from weight loss to substantial gains. GWG-LGA associations were strongest in trimester 1 (risk ratio [RR] range for 10th vs. 50th percentile GWG, across BMI categories: 0.60-0.73). GWG-SGA associations were strongest in lower BMI categories and in trimester 2; RRs were 1.62, 1.40, and 1.17 for prepregnancy normal weight, obesity class I, and obesity class III, respectively, with curvilinear associations for class II and III. CONCLUSIONS: Among people with prepregnancy obesity class II or III, GWG rate is associated with higher LGA risk in a dose-dependent manner, including understudied ranges of weight loss, but with weak associations with SGA.

Treatment Strategies for Glioblastoma in the Elderly: What Should We Focus on Compared to Younger Patients.

(1) Background: Although the incidence of glioblastoma (GB) has a peak in patients aged 75-84 years, no standard treatment regimen for elderly patients has been established so far. The goal of this study was to analyze the outcome of GB patients ≥ 65 years to detect predictors with relevant impacts on overall survival (OS) and progression-free survival (PFS). (2) Methods: Medical records referred to our institution from 2006 to 2020 were analyzed. Adult GB patients with clinical data, postoperative MRI data, and ≥1 follow-up investigation after surgical resection were included. The complete cohort was divided into a younger (<65) and an elderly group (≥65 years). Multiple factors regarding OS and PFS were scanned using univariate and multivariable regression with p < 0.05. (3) Results: 1004 patients were included with 322 (61.0%) male individuals in the younger and 267 (56.1%) males in the older cohort. The most common tumor localization was frontal in both groups. Gross total resection (GTR) was the most common surgical procedure in both groups, followed by subtotal resection (STR) (145; 27.5%) in the younger group, and biopsy (156; 32.8%) in the elderly group. Multivariate analyses detected that in the younger cohort, MGMT promoter methylation and GTR were predictors for a longer OS, while MGMT methylation, GTR, and hypofractionated radiation were significantly associated with a longer OS in the elderly group. (4) Conclusions: Elderly patients benefit from surgical resection of GB when they show MGMT promoter methylation, undergo GTR, and receive hypofractionated radiation. Furthermore, MGMT methylation seems to be associated with a longer PFS in elderly patients. Further investigations are required to confirm these findings, especially within prospective radiation therapy studies and molecular examinations.

The Role of Fibroblast Activation Protein in Glioblastoma and Gliosarcoma: A Comparison of Tissue, 68Ga-FAPI-46 PET Data, and Survival Data.

Despite their unique histologic features, gliosarcomas belong to the group of glioblastomas and are treated according to the same standards. Fibroblast activation protein (FAP) is a component of a tumor-specific subpopulation of fibroblasts that plays a critical role in tumor growth and invasion. Some case studies suggest an elevated expression of FAP in glioblastoma and a particularly strong expression in gliosarcoma attributed to traits of predominant mesenchymal differentiation. However, the prognostic impact of FAP and its diagnostic and therapeutic potential remain unclear. Here, we investigate the clinical relevance of FAP expression in gliosarcoma and glioblastoma and how it correlates with 68Ga-FAP inhibitor (FAPI)-46 PET uptake. Methods: Patients diagnosed with gliosarcoma or glioblastoma without sarcomatous differentiation with an overall survival of less than 2.5 y were enrolled. Histologic examination included immunohistochemistry and semiquantitative scoring of FAP (0-3, with higher values indicating stronger expression). Additionally, 68Ga-FAPI-46 PET scans were performed in a subset of glioblastomas without sarcomatous differentiation patients. The clinical SUVs were correlated with FAP expression levels in surgically derived tumor tissue and relevant prognostic factors. Results: Of the 61 patients who were enrolled, 13 of them had gliosarcoma. Immunohistochemistry revealed significantly more FAP in gliosarcomas than in glioblastomas without sarcomatous differentiation of tumor tissue (P < 0.0001). In the latter, FAP expression was confined to the perivascular space, whereas neoplastic cells additionally expressed FAP in gliosarcoma. A significant correlation of immunohistochemical FAP with SUVmean and SUVpeak of 68Ga-FAPI-46 PET indicates that clinical tracer uptake represents FAP expression of the tumor. Although gliosarcomas express higher levels of FAP than do glioblastomas without sarcomatous differentiation, overall survival does not significantly differ between the groups. Conclusion: The analysis reveals a significant correlation between SUVmean and SUVpeak in 68Ga-FAPI-46 PET and immunohistochemical FAP expression. This study indicates that FAP expression is much more abundant in the gliosarcoma subgroup of glioblastomas. This could open not only a diagnostic but also a therapeutic gap, since FAP could be explored as a theranostic target to enhance survival in a distinct subgroup of high-risk brain tumor patients with poor survival prognosis.

Urinary neurotransmitter analysis and canine behavior assessment.

Behavioral problems are highly prevalent in domestic dogs, negatively affecting the quality of life of dogs and their owners. In humans and dogs, neuropsychological or neurobehavioral disorders can be associated with deviations in various neurotransmitter systems. Previous evidence has revealed correlations between urinary neurotransmitters and various behavioral disorders; however, a causal relationship has not yet been conclusively demonstrated. Non-invasive urinary neurotransmitter analysis may identify specific biomarkers, which enable a more differentiated assessment of canine behavioral disorders in the future and contribute to more effective neuromodulatory treatment decisions and monitoring. This approach could offer new insights into underlying pathomechanisms of canine neurobehavioral disorders. This study assessed urinary neurotransmitter levels and the descriptive behavior profile of 100 dogs using established rating scales (Canine Behavioral Assessment and Research Questionnaire, Attention Deficit Hyperactivity Disorder Rating Scale, Dog Personality Questionnaire, Canine Cognitive Dysfunction Rating Scale), and explored relationships between these variables. No correlation was found between urinary neurotransmitters and the assessed behavior profiles; however, age-, sex- and neuter-related influences were identified. The lack of correlation could be explained by the many confounding factors influencing both behavior and urinary neurotransmitter excretion, including age, sex and neuter status effects, and methodological issues e.g., low discriminatory power between anxiety and aggression in the descriptive behavior evaluation. Urinary neurotransmitter testing could not be validated as a tool for canine behavior evaluation in this study. However, reliable assessment methods with low susceptibility to human biases could be valuable in the future to support behavioral-phenotype diagnoses.

Are we providing best-available care to newly diagnosed glioblastoma patients? Systematic review of phase III trials in newly diagnosed glioblastoma 2005-2022.

Background: Glioblastoma is the most aggressive primary brain cancer with a poor prognosis. Despite numerous studies in the past 17 years, effective treatment options for glioblastoma remain limited. In this study, we aimed to identify and compare phase III clinical trials for glioblastoma in terms of efficacy and baseline characteristics. Methods: A systematic literature search was conducted using PubMed and ClinicalTrials.gov to identify phase III clinical trials for glioblastoma in adult patients. The target population included adult patients aged 18 years and above (younger cohort) and patients ≥60 years of age (elderly cohort). The search results were screened based on predefined inclusion criteria, and the included trials were analyzed for their study design, baseline characteristics, and survival results. Results: Eleven trials met the inclusion criteria in the younger cohort. Of these, three reported a statistically significant improvement in overall survival (OS), including the EORTC/NCIC study (NCT00006353), EF-14 (NCT00916409), and CeTeG (NCT01149109). Of the 11 trials, eight were open-label randomized trials, including all of the positive ones, while three negative trials employed treatment blinding and a placebo control. The baseline characteristics of the trials [such as extent of resection, age, gender, and O(6)-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status] did not significantly differ between positive and negative trials. Isocitrate dehydrogenase (IDH) mutation status was analyzed in only two trials, with a small percentage of IDH-mutated tumors in each. Additionally, three more trials in the elderly cohort showed a statistically significant improvement of OS, the NOA-08 trial, the ISRCTN81470623-trial by Malmström et al. and NCT00482677-trial by Perry et al. Their baseline characteristics and implications are also analyzed. Conclusion: This analysis of phase III clinical trials for glioblastoma conducted since 2005 showed that the majority of trials did not result in a significant improvement in OS. Among the trials included in this analysis, only the EORTC/NCIC, EF-14, and CeTeG studies demonstrated a positive OS outcome in the younger cohort.