Does the Primary Tumor Site Drive Biology for Patients With Synovial Sarcoma?

OBJECTIVE: We evaluated survival outcomes by primary tumor site in synovial sarcoma (SS) patients with localized and metastatic disease at diagnosis. METHODS: We conducted a retrospective review of 504 SS patients diagnosed from 1974 to 2020. Kaplan-Meier method, log-rank test, and Cox-proportional hazards regression were used. RESULTS: Among 504 patients, 401 (79.6%) presented with localized disease, and 103 (20.4%) with metastases. For patients with localized disease, (1) 5-year OS by tumor site was as follows: 80% (95% CI, 67%-89%) for head/neck, 30% (95% CI, 18%-42%) for intrathoracic, 51% (95% CI, 35%-65%) for abdomen/pelvis, 71% (95% CI, 62%-79%) for proximal-extremity, and 83% (71%, 91%) for distal-extremity. (2) On multivariable analysis, tumor site (compared with proximal-extremity: intrathoracic tumors [HR: 1.95; 95% CI, 1.22-3.16]; hand/foot [HR: 0.52; 95% CI, 0.28-0.97]), tumor size (compared with <5 cm, 5-10 cm [HR: 1.80; 95% CI, 1.14-2.85]; ≥10 cm [HR: 4.37; 95% CI, 2.69-7.11]), and use of neo/adjuvant radiation (HR: 0.54; 95% CI, 0.37-0.79) remained significantly associated with OS. For patients with metastatic disease, (1) 5-year OS was 12% (95% CI, 6%-21%) and (2) the only factor that remained significantly associated with OS on multivariable analysis was surgical resection for the primary tumor (HR: 0.14; 95% CI, 0.08-0.26). CONCLUSIONS: The primary tumor location plays a significant role in predicting outcomes for patients with localized SS. Even though patients present with metastatic disease, surgical resection of the primary tumor improves their survival. These findings are critical for patient counseling and designing a personalized treatment plan that reflects the corresponding outcomes.

Epidemiological trends of synovial sarcoma by primary tumor sites in the US from 2000 to 2020.

BACKGROUND: Synovial sarcoma (SS) is a rare soft-tissue cancer. Existing literature encompasses Surveillance, Epidemiology, and End Results (SEER) data-based research on SS explaining the incidence-prevalence in general, by subtypes, and by age at diagnosis. Therefore, this study aimed to fill in the gap of knowledge about measures of disease occurrence and burden of SS by tumor site using the SEER database. METHODS: In this cross-sectional study, primary SS patients were selected from SEER 17 Registries, Nov. 2021 (2000-2020) using ICD-O-3 codes 9040, 9041, 9042, and 9043. Patients with additional cancers were excluded. The primary tumor site was categorized into (1) head/neck, (2) internal thorax, (3) abdomen/pelvis, (4) upper extremity, and (5) lower extremity using ICD-10CM codes. Five outcomes were analyzed: age-adjusted incidence rate, 5-year limited-duration prevalence rate, incidence-based mortality, case-fatality rate, and overall survival. RESULTS: From 2000-2020, the overall age-adjusted incidence rate was 0.15 per 100,000; the 5-year limited duration prevalence rate was 0.56 per 100,000; and the incidence-based mortality rate was 0.06 per 100,000 people. The case-fatality and 5-year OS rates were 39.2 % and 62.9 %, respectively. Lower extremity had the highest incidence of 0.07 (estimated 1166 cases), prevalence of 0.36 (estimated 224 cases), and mortality rate of 0.025 (estimated 429 deaths) per 100,000. The other four locations had much closer rates with each other. Intrathoracic SS had the highest case-fatality rate of 71.5 % (148/207) and lowest 5-year OS of 26.0 % (95 % CI: 19.6 %, 32.9 %) than other sites. CONCLUSION: Based on the measures of disease frequency, the most common primary tumor site is the lower extremity, followed by the upper extremity, abdomen/pelvis, internal thorax, and head/neck. The least favorable primary location is the internal thorax. Those with a primary location of the upper extremity have the longest overall survival, followed by the head/neck, lower extremity, abdomen/pelvis, and internal thorax.

Caregiving and all-cause mortality in postmenopausal women: Findings from the Women's Health Initiative.

BACKGROUND: Caregiving is commonly undertaken by older women. Research is mixed, however, about the impact of prolonged caregiving on their health, well-being, and mortality risk. Using a prospective study design, we examined the association of caregiving with mortality in a cohort of older women. METHODS: Participants were 158,987 postmenopausal women aged 50-79 years at enrollment into the Women's Health Initiative (WHI) who provided information on current caregiving status and caregiving frequency at baseline (1993-1998) and follow-up (2004-2005). Mortality was ascertained from baseline through March of 2019. Cox regression with caregiving status defined as a time-varying exposure was used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for mortality, adjusting for sociodemographic factors, smoking, and history of diabetes, hypertension, cardiovascular disease (CVD), and cancer. Stratified analyses explored whether age, race-ethnicity, depressive symptoms, frequency of caregiving, optimism, and living status modified the association between caregiver status and mortality. RESULTS: At baseline, 40.7% of women (mean age 63.3 years) self-identified as caregivers. During a mean 17.5-year follow-up, all-cause mortality (50,526 deaths) was 9% lower (multivariable-adjusted HR = 0.91, 95% CI: 0.89-0.93) in caregivers compared to non-caregivers. The inverse association between caregiving and all-cause mortality did not differ according to caregiving frequency or when stratified by age, race-ethnicity, depressive symptoms, optimism, or living status (interaction p > 0.05, all). Caregiving was inversely associated with CVD and cancer mortality. CONCLUSION: Among postmenopausal women residing across the United States, caregiving was associated with lower mortality. Studies detailing the type and amount of caregiving are needed to further determine its impact on older women.

The Prevalence and Perceived Utility of Mobile Health Technology Among Recently Incarcerated Homeless Adults.

Mobile technologies can deliver physical and mental health services for recently incarcerated homeless adults (RIHAs). The purpose of this study was to examine the prevalence and perceived utility of mobile technology to support health behavior change among RIHAs. Participants (n = 324) from an ongoing clinical trial at a homeless shelter in Texas were included in the current descriptive cross-sectional analyses. Over one fourth (28.4%) of participants had an active cell phone. Nearly 90 percent (88.6%) of participants reported at least weekly use of the internet, 77 percent used email (77.2%), and more than half used Facebook (55.2%). Although most participants (82.8%) believed that smartphone applications (apps) could help change their behavior, only a quarter (25.1%) had used an app for this purpose. These findings highlight the potential for smartphone-based intervention technologies, and future studies should examine whether smartphone apps that address mental health and health behaviors are feasible among RIHAs.

Popularity of Delta-8 THC on the Internet Across US States, 2021.

Objectives. To assess the popularity of an emergent drug, delta-8 tetrahydrocannabinol (THC), and compare interest levels between US states with or without legalized recreational cannabis. Methods. We used Google Trends to assess the growth of interest among delta-8 THC-related search terms from May 17, 2020, to May 9, 2021. We examined differences between states with or without legalized cannabis using state-level Google Trends data from February 13 to May 13, 2021, and policy data from the National Conference of State Legislatures. Results. Interest in delta-8 THC increased starting in mid-June 2020, with search volumes for delta-8 THC queries currently at 35% of the "marijuana" query. States where recreational cannabis is illegal had higher relative queries than did states with legalized recreational cannabis (52.3 vs 14.8; t = 40.9; P < .001). Conclusions. There has been rapid growth in interest in delta-8 THC. Findings between state policy contexts likely indicate delta-8 THC's role as a substitute good for delta-9 THC. Public Health Implications. Digital signals such as search volumes may point to an emergent use trend in the substance delta-8 THC. Further studies are needed to assess potential harms and correlates of delta-8 THC use. (Am J Public Health. 2022;112(2):296-299. https://doi.org/10.2105/AJPH.2021.306586).

The "Network Effect" on Interfacility Transfers Among Regional Stroke Certified Hospitals.

INTRODUCTION AND PURPOSE: Timely inter-facility transfer of thrombectomy-eligible patients is a mainstay of Stroke Systems of Care. We investigated transfer patterns among stroke certified hospitals in the Dallas-Fort Worth (DFW) Metroplex (19 counties, 9,286 sq mi, > 7.7 million people), by hospital network and stroke center status. METHODS: We conducted a North Central Texas Trauma Regional Advisory Council (NCTTRAC) Stroke Regional Care Survey at all 44 centers involved in the treatment of MT-eligible ischemic stroke patients between June-September 2019, with a response rate of 100%. All hospitals identified network status, stroke designation - Acute Stroke Ready Hospital (ASRH), Primary Stroke Center (PSC), Comprehensive Stroke Center (CSC) - and geographic location. Stroke Assessment and Large Vessel Occlusion (LVO) screening tool use was evaluated. The distance between the sending and receiving facility was calculated using GPS coordinates. If the closest CSC was not used, the average distance between the selected and the closest CSC was geospatially mapped via R statistical analysis software (Vienna, Austria) gmapsdistance package. RESULTS: Of the 44 facilities, 6 were ASRHs, 27 were PSCs, 11 were CSCs. Seventy-seven percent (n=34) belonged to one of four hospital networks. All facilities used stroke assessment tools; 57% completed LVO screening. There was significant heterogeneity in inter-facility transfer patterns with no regional standardization. Seventeen percent of ASRHs (n=1) and 56% of PSCs (n=15) conducted inter-facility transfers using ground transportation via EMS. Sixty percent of non-network facilities transferred to the closest CSC. Of the remaining 40%, the average distance between the closest and the selected CSC was 1.5 miles (min max 0.2-2.9 miles). Seventeen percent of network facilities transferred to the closest CSC. Among the remaining 83%, the average distance between the closest and the selected CSC was 4.1 miles (min-max 1-8 miles). CONCLUSIONS: Non-network facility status increased the likelihood of transfer to the closest Comprehensive Stroke Center. Transfer distance variability among network facilities may contribute to delays in reperfusion therapy.

U.S. population estimates and correlates of sexual abuse of community-dwelling older adults.

We describe the annual prevalence of sexual abuse among community-dwelling older adults in the United States. We also describe factors associated with experiencing sexual abuse. We used data from 24,343 older adults from the 2005 Behavioral Risk Factor Surveillance System pooled across 18 states. We estimated prevalence of sexual abuse, bivariate distributions, and odds ratio associations across demographic, health, and contextual factors. Our results show that 0.9% of older adults reported experiencing sexual abuse in the previous year. This represents approximately 90,289 community-dwelling older adults. We also report on factors associated with experiencing recent sexual abuse. There was a significant gender by binge drinking interaction, with a stronger association among women. There is a need for health promotion efforts targeted specifically toward older adults, encouraging them to seek services, if possible, after exposure to sexual abuse.

Doubly robust testing and estimation of model-adjusted effect-measure modification with complex survey data.

Model-based standardization enables adjustment for confounding of a population-averaged exposure effect on an outcome. It requires either a model for the probability of the exposure conditional on the confounders (an exposure model) or a model for the expectation of the outcome conditional on the exposure and the confounders (an outcome model). The methodology can also be applied to estimate averaged exposure effects within categories of an effect modifier and to test whether these effects differ or not. Recently, we extended that methodology for use with complex survey data, to estimate the effects of disability status on cost barriers to health care within three age categories and to test for differences. We applied the methodology to data from the 2007 Florida Behavioral Risk Factor Surveillance System Survey (BRFSS). The exposure modeling and outcome modeling approaches yielded two contrasting sets of results. In the present paper, we develop and apply to the BRFSS example two doubly robust approaches to testing and estimating effect modification with complex survey data; these approaches require that only one of these two models be correctly specified. Furthermore, assuming that at least one of the models is correctly specified, we can use the doubly robust approaches to develop and apply goodness-of-fit tests for the exposure and outcome models. We compare the exposure modeling, outcome modeling, and doubly robust approaches in terms of a simulation study and the BRFSS example.

Association of blood cotinine level with cognitive and physical performance in non-smoking older adults.

UNLABELLED: Background Studies show that active smoking may be associated with cognitive decline. However, the consequence of secondhand smoke on cognitive and physical performance remains unclear. The purpose of this study was to assess the association of secondhand smoke with cognitive performance and physical function using a population-based sample. METHODS: Data of 2,542 non-smoking participants from the 1999-2002 National Health and Nutrition Examination Survey were analyzed. Secondhand smoke exposure level was estimated using blood cotinine concentrations. Cognitive performance was assessed with the Digit Symbol Substitution Test and self-reported confusion/memory problems. Physical performance was analyzed using visual gait speed (m/s) and self-reported physical function. Multivariate linear and logistic regression models were used to assess the association. RESULTS: In never smokers, cognitive performance score decreased by 2.03 points (95% confidence interval (CI): -3.00, -1.05) per one unit increase in log-transformed blood cotinine level. After adjusting for potential confounders, including diabetes, hypertension, body mass index, alcohol, and blood lead level, change in cognitive performance score was still statistically significant (-1.17 95% CI: -2.32, -0.02). Similar trends were observed in former smokers. Gait speed decreased by 0.02m/s for one unit increase in log-transformed blood cotinine level. This was evident in both never and former smokers. The relationship remained significant after adjusting for potential confounders in former smokers. CONCLUSIONS: Our study suggests that secondhand smoke may contribute to cognitive decline in never and former smokers. Considering the cross-sectional design and the limitations of this study, the relationship warrants further assessment.

Age group differences in healthcare access for people with disabilities: are young adults at increased risk?

PURPOSE: The purpose of this study was to quantify and describe the population of young adults with disability in Florida and to assess correlates of healthcare access in this population in contrast with adults belonging to middle and older age groups. METHODS: This study analyzed data of 36,704 respondents obtained from the 2007 Florida Behavioral Risk Factor Surveillance System. A test for homogeneity of the risk difference across the three age groups was conducted using inverse weighting to adjust for confounding and selection bias. RESULTS: The adjusted model for risk difference of not being able to see a doctor in the past 12 months because of cost was significantly heterogeneous across age groups (χ(2)(2df)F value = 12.40, p < .01). The risk difference between population of young adults with disability and their age peers decreased significantly across the groups. The risk difference was 15.5% for those aged 18-29, 11.9% for those aged 30-64, and 2.1% for those aged ≥65. CONCLUSIONS: This article quantifies the differences in risk and access to health care between young adults with and without disability, using population-based data. It provides indirect evidence of the widely held belief that there is a problem in healthcare transition in the United States warranting continued investigation and intervention.

Testing and estimating model-adjusted effect-measure modification using marginal structural models and complex survey data.

Recently, it has been shown how to estimate model-adjusted risks, risk differences, and risk ratios from complex survey data based on risk averaging and SUDAAN (Research Triangle Institute, Research Triangle Park, North Carolina). The authors present an alternative approach based on marginal structural models (MSMs) and SAS (SAS Institute, Inc., Cary, North Carolina). The authors estimate the parameters of the MSM using inverse weights that are the product of 2 terms. The first term is a survey weight that adjusts the sample to represent the unstandardized population. The second term is an inverse-probability-of-exposure weight that standardizes the population in order to adjust for confounding; it must be estimated using the survey weights. The authors show how to use the MSM parameter estimates and contrasts to test and estimate effect-measure modification; SAS code is provided. They also explain how to program the previous risk-averaging approach in SAS. The 2 methods are applied and compared using data from the 2007 Florida Behavioral Risk Factor Surveillance System Survey to assess effect modification by age of the difference in risk of cost barriers to health care between persons with disability and persons without disability.