Death Risk Response of High-Altitude Resident Populations to COVID-19 Vaccine: A Retrospective Cohort Study.

Vásquez-Velásquez, Cinthya, Diego Fano-Sizgorich, and Gustavo F Gonzales. Death risk response of high-altitude resident populations to COVID-19 vaccine: Retrospective cohort study. High Alt Med Biol. 00:00-00, 2024. Background: Peru had one of the highest mortality rates caused by the coronavirus disease 2019 (COVID-19) pandemic worldwide. Vaccination significantly reduces mortality. However, the effectiveness of vaccination might differ at different altitudinal levels. The study aimed to evaluate the effect modification of altitude on the association between vaccination and COVID-19 mortality in Peru. Methodology: A retrospective cohort, using open access databases of deaths, COVID-19 cases, hospitalizations, and vaccination was obtained from the Peruvian Ministry of Health. Deaths due to COVID-19 were evaluated in vaccinated and nonvaccinated patients. Crude (RR) and adjusted relative risks (aRR) were calculated using generalized linear models of Poisson family with robust variances. Models were adjusted for age, sex, pandemic wave, and Human Development Index. To evaluate the interaction by altitude, a stratified analysis by this variable was performed. The variable altitude was categorized as, 0-499 m (828,298 cases), 500-1,499 m (64,735 cases), 1,500-2,499 m (106,572 cases), and ≥2,500 m (179,004 cases). The final sample studied included 1,362,350 cases. Results: The vaccine showed a considerable reduction of death risk with the second (aRR: 0.41, 95% confidence interval [CI]: 0.38-0.44) and third doses (aRR: 0.21, 95% CI: 0.20-0.23). In the adjusted and interaction model, it can be observed that medium and high altitude present a higher risk of death compared to sea level (aRR: 2.58 and 2.03, respectively). Likewise, the two doses' group presents an aRR:1.22 for medium altitude (1,500-2,499 m) and 1.6 for high altitude (≥2,500 m), compared with low-altitude population, suggesting that the action of vaccination at high altitude is altered by the effect of the altitude itself. Conclusions: Altitude might modify the protective effect of SARS-CoV-2 vaccine against COVID-19 death.

Frailty as an Effect Modifier in Randomized Controlled Trials: A Systematic Review.

BACKGROUND: The effect of clinical interventions may vary by patients' frailty status. Understanding treatment effect heterogeneity by frailty could lead to frailty-guided treatment strategies and reduce overtreatment and undertreatment. This systematic review aimed to examine the effect modification by frailty in randomized controlled trials (RCTs) that evaluate pharmacological, non-pharmacological, and multicomponent interventions. METHODS: We searched PubMed, Web of Science, EMBASE, and ClinicalTrial.gov, from their inception to 8 December 2023. Two reviewers independently extracted trial data and examined the study quality with senior authors. RESULTS: Sixty-one RCTs that evaluated the interaction between frailty and treatment effects in older adults were included. Frailty was evaluated using different tools such as the deficit accumulation frailty index, frailty phenotype, and other methods. The effect of several pharmacological interventions (e.g., edoxaban, sacubitril/valsartan, prasugrel, and chemotherapy) varied according to the degree of frailty, whereas other treatments (e.g., antihypertensives, vaccinations, osteoporosis medications, and androgen medications) demonstrated consistent benefits across different frailty levels. Some non-pharmacological interventions had greater benefits in patients with higher (e.g., chair yoga, functional walking, physical rehabilitation, and higher dose exercise program) or lower (e.g., intensive lifestyle intervention, psychosocial intervention) levels of frailty, while others (e.g., resistance-type exercise training, moderate-intensive physical activity, walking and nutrition or walking) produced similar intervention effects. Specific combined interventions (e.g., hospital-based disease management programs) demonstrated inconsistent effects across different frailty levels. DISCUSSION: The efficacy of clinical interventions often varied by frailty levels, suggesting that frailty is an important factor to consider in recommending clinical interventions in older adults. REGISTRATION: PROSPERO registration number CRD42021283051.

Role of individual deprivation and community-level deprivation on suicidal behaviors: Insights from the UK Biobank study.

Introduction: This study aimed to investigate the impact of individual- and community-level deprivation on suicidal behaviors among community members. Methods: Data from 350,884 UK Biobank participants were employed to construct an individual deprivation index. Absolute poverty was defined as a pre-tax annual household income below £18,000. Predictors for absolute poverty incorporated variables such as sex, ethnicity, type of accommodation, tenure status, number of vehicles owned, educational qualifications, current employment status, and subjective health rating. The individual deprivation index was constructed using a logistic regression model to predict absolute poverty. Townsend Deprivation Index (TDI) was employed to represent community-level deprivation. The associations between the individual deprivation index, TDI, and suicidal behaviors were examined through multivariate linear regression. Interaction analyses were conducted to investigate effect modification. Results: The logistic regression model demonstrated high predictive accuracy for absolute poverty (area under the receiver operating curve = 0.840). The associations between individual deprivation index and suicidal behaviors were observed to be more substantial than those between TDI and suicidal behaviors. A positive interaction between the individual deprivation index and TDI was detected, indicating an amplifying effect of community-level deprivation on the impact of individual-level deprivation on suicidal behaviors. Conclusion: Our study successfully constructed a comprehensive individual deprivation index that could be applied widely to measure individual-level deprivation. Our findings revealed that individual-level deprivation and community-level deprivation have a synergistic effect on suicidal behaviors, underscoring the importance of multilevel interventions in suicide prevention.

Factors associated with blood mercury concentrations and their interactions with three glutathione S-transferase genes (GSTT1, GSTM1, and GSTP1): an exposure assessment study of typically developing Jamaican children.

BACKGROUND: Jamaican soil is abundant in heavy metals including mercury (Hg). Due to availability and ease of access, fish is a traditional dietary component in Jamaica and a significant source of Hg exposure. Mercury is a xenobiotic and known neuro-toxicant that affects children's neurodevelopment. Human glutathione S-transferase (GST) genes, including GSTT1, GSTM1, and GSTP1, affect Hg conjugation and elimination mechanisms. METHODS: In this exposure assessment study we used data from 375 typically developing (TD) 2-8-year-old Jamaican children to explore the association between environmental Hg exposure, GST genes, and their interaction effects on blood Hg concentrations (BHgCs). We used multivariable general linear models (GLMs). RESULTS: We identified the child's age, consumption of saltwater fish, canned fish (sardine, mackerel), string beans, grain, and starches (pasta, macaroni, noodles) as the environmental factors significantly associated with BHgCs (all P < 0.05). A significant interaction between consumption of canned fish (sardine, mackerel) and GSTP1 in relation to BHgC using either a co-dominant or recessive genetic model (overall interaction P = 0.01 and P < 0.01, respectively) indicated that consumption of canned fish (sardine, mackerel) was significantly associated with higher mean BHgC only among children with the GSTP1 Ile105Val, Ile/Ile [Ratio of mean Hg (95% CI) = 1.59 (1.09, 2.32), P = 0.02] and Ile/Val [Ratio of mean Hg (95% CI) = 1.46 (1.12, 1.91), P = 0.01] genotypes. CONCLUSIONS: Since this is the first study from Jamaica to report these findings, replication in other populations is recommended.

Uncovering associations between gender nonconformity, psychosocial factors, and mental health in adolescents: a birth cohort study.

BACKGROUND: Little information is available on the association between gender nonconformity during adolescence and subsequent mental health. While the distress related to gender nonconformity may be socially produced rather than attributed to individual-level factors, further research is needed to better understand the role of psychosocial factors in this context. METHOD: We analyzed data from the Tokyo Teen Cohort, obtained through random sampling of adolescents born between 2002 and 2004. We used inverse probability weighting to examine the association of gender nonconformity at ages 12 and 14 as a time-varying variable with subsequent mental health at age 16, while accounting for time-fixed and time-varying confounders. Furthermore, we used a weighting approach to investigate the mediating role of modifiable psychosocial factors in this association, addressing exposure-mediator and mediator-mediator interactions. RESULTS: A total of 3171 participants were analyzed. Persistent gender nonconforming behavior at ages 12 and 14 was associated with subsequent depression (ß = 2.02, 95% confidence interval [CI] 0.85 to 3.19) and psychotic experiences (ß = 0.33, 95% CI 0.14 to 0.52) at age 16. The results remained robust in sensitivity analyses. Approximately 30% of the association between gender nonconformity and depression was consistently mediated by a set of psychosocial factors, namely loneliness, bullying victimization, and relationships with mother, father, and friends. CONCLUSIONS: Persistent gender nonconformity during adolescence is associated with subsequent mental health. Psychosocial factors play a vital mediating role in this association, highlighting the essential need for social intervention and change to reduce stigmatization and ameliorate mental health challenges.

Neighborhood greenness and participation in specific types of recreational physical activities in the Sister Study.

BACKGROUND: Urban green spaces have been consistently shown to have important human health benefits across a range of outcomes. These benefits are thought to be achieved, in part, because urban greenness provides opportunities for participation in recreational activity. However, the findings from studies that have assessed links between exposure to greenness and physical activity have been mixed. To date, few studies have examined association between greenness and specific types of recreational physical activities. OBJECTIVE: We evaluated associations between measures of greenness and specific types of recreational physical activities. Moreover, we explored the extent to which these associations were modified by socioeconomic conditions, and regionally. METHODS: We analyzed cross-sectional data from 49,649 women in the Sister Study and assigned three residentially-based measures of greenness based on national land cover data at buffer distances of 250 m and 500 m. Data on participation in up to ten specific recreational physical activities, including time spent in each activity were collected. Logistic regression was used to estimate odds ratios (OR) and their 95% confidence intervals (CI) controlling for confounders. RESULTS: Compared to those in the lowest tertile of greenness, participants in the upper tertile of greenness within a 500 m buffer, were more likely to garden (OR = 1.46, 95% CI = 1.25,1.69), participate in sports (OR = 1.28, 95% CI = 1.19,1.38), run (OR = 1.15, 95% CI = 1.04,1.27), walk (OR = 1.11, 95% CI = 1.06,1.16), and engage in conditioning exercises (OR = 1.10, 95% CI = 1.05,1.16) at least once a week for at least one month over the past year. These associations were modified by household income and US region. DISCUSSION: Our findings suggest a beneficial effect of greenness on physical activity and provide additional information to inform planning of green environments that contribute to better health and wellbeing.

Increasing transparency in indirect treatment comparisons: is selecting effect modifiers the missing part of the puzzle? A review of methodological approaches and critical considerations.

Failure to adjust for effect modifiers (EMs) in indirect treatment comparisons (ITCs) can produce biased and uncertain effect estimates. This is particularly important for health technology assessments (HTAs), where the availability of new treatments is based on comparative effectiveness results. Much emphasis has been placed on advancing ITC methods to adjust for EMs, yet whether EMs are appropriately identified for the conduct of ITCs in the first place is unclear. To understand the extent of guidance and requirements for the selection of EMs for ITCs currently available and if and how this guidance is applied in practice, a series of pragmatic reviews of guidance documents from HTA and non-payer organizations, primary published ITC analyses, and prior HTA submissions in two indications (non-small cell lung cancer and psoriasis) was conducted. The reviews showed that current ITC guidance mainly focused on developing analytical methods to adjust for EMs. Some organizations, such as HTA bodies in the UK, France and Germany, recommended the use of literature reviews, expert opinion and statistical methods to identify EMs. No detailed guidance on the selection process or the appropriate literature review approach was found. Similar trends were identified through the database search and review of prior HTA submissions; only few published ITCs and submissions included information on the EM selection process which was either based on findings from the literature, trial subgroup analyses, or clinical input. No reference to a systematic selection approach was found. There is an urgent need to fill the guidance gap identified across the reviews by including a step in ITC guidelines on how EMs should be identified through systematic reviews, formal expert elicitation, and a quantitative assessment of the EM distribution. Researchers and manufacturers are also encouraged to improve transparent reporting and justification of their selection of EMs to allow for an independent review of the set of factors being considered for adjustment. Both will contribute toward reducing bias in the ITC results and ultimately increase confidence in decision-making.

Potential effect modifiers for treatment with chiropractic manipulation versus sham manipulation for recurrent headaches in children aged 7-14 years: development of and results from a secondary analysis of a randomised clinical trial.

BACKGROUND: A recent randomized controlled trial (RCT) investigating the effect of chiropractic manipulation in 199 children aged 7-14 years with recurrent headaches demonstrated a significant reduction of number of days with headache and a better global perceived effect (GPE) in the chiropractic manipulation group compared to a sham manipulation group. However, potential modifiers for the effectiveness of chiropractic manipulation of children with recurrent headaches have never been identified. The present study is a secondary analysis of data from that RCT and will investigate potential effect modifiers for the benefit of chiropractic manipulation for children with headache. METHODS: Sixteen potential effect modifiers were identified from the literature and a summary index was prespecified based on clinical experience. Relevant variables were extracted from baseline questionnaires, and outcomes were obtained by means of short text messages. The modifying effect of the candidate variables was assessed by fitting interaction models to the data of the RCT. In addition, an attempt to define a new summary index was made. RESULTS: The prespecified index showed no modifying effect. Four single variables demonstrated a treatment effect difference of more than 1 day with headache per week between the lower and the upper end of the spectrum: intensity of headache (p = 0.122), Frequency of headache (p = 0.031), sleep duration (p = 0.243), and Socioeconomic status (p = 0.082). Five variables had a treatment effect difference of more than 0.7 points on the GPE scale between the lower and the upper end of the spectrum: Frequency of headache (p = 0.056), Sport activity (p = 0.110), Sleep duration (p = 0.080), History of neck pain (p = 0.011), and Headache in the family (0.050). A new summary index could be constructed giving highest weight to History of neck pain and Headache in the family and Frequency of headache. The index suggests a difference of about 1 point in GPE between low and high values of the index. CONCLUSION: Chiropractic manipulation offers a moderate benefit for a broad spectrum of children. However, it cannot be excluded that specific headache characteristics, family factors, or a history of neck pain may modify the effect. This question must be addressed in future studies. TRIAL REGISTRATION: ClinicalTrials.gov (Albers et al in Curr Pain Headache Rep 19:3-4, 2015), identifier NCT02684916, registered 02/18/2016-retrospectively registered.

Sex and age do not modify the association between glucocorticoids and bone mineral density in patients with rheumatoid arthritis: a cross-sectional study.

BACKGROUND: It is unclear whether sex or age modify the association of glucocorticoid (GC) use with reduced bone mineral density (BMD) in patients with rheumatoid arthritis (RA). METHODS: We studied cross-sectional data of RA patients with current or previous GC treatment in a single center cohort study (Rh-GIOP cohort). Our primary outcome was the minimum T-score (measured by DXA) of either lumbar spine, total femur, or femoral neck. Current GC dose was the main exposure; cumulative GC dose and cumulative duration of GC use were also assessed. Following a predefined statistical analysis plan, linear regression analyses with adjustment for confounders assessed whether the association of GC use with BMD was modified by sex (men versus women) or age (≥ 65 versus < 65 years). RESULTS: Four hundred eighty-three patients with RA (mean age 64 ± 12 years, 80% women) were included. 33% were not currently taking GCs, 32% were treated with a dose of 5 mg/d prednisone equivalent and 11% with more than 7.5 mg/d. 23% of patients had osteoporosis by DXA (minimum T-score ≤ -2.5). The slope, i.e., the association between changes in minimum T-scores with 1 mg/d change in current GC dose, was similar in men and women (-0.07 and -0.04, respectively; difference -0.03 [-0.11 to 0.04]; p for interaction = 0.41). Slopes were also similar for elderly and non-elderly patients (-0.03 and -0.04, respectively; difference -0.01 [-0.06 to 0.05]; p for interaction = 0.77). Using cumulative dose and duration of use as exposures did not lead to substantial changes of these results. CONCLUSIONS: In our sample, the association of GC use with reduced BMD in RA was not modified by sex or age.

Does Periodontitis Affect the Association of Biological Aging with Mortality?

The prevalence of periodontitis is increasing with the aging of the global population. Periodontitis has been suggested to accelerate aging and increase mortality. The present nationwide prospective cohort study aimed to determine whether periodontitis could modify the association of biological aging with all-cause and cause-specific mortality in middle-aged and older adults. Participants ≥40 y of age from the Third National Health and Nutrition Examination Survey (NHANES III) were included (n = 6,272). Phenotypic age acceleration (PhenoAgeAccel) was used to evaluate the biological aging process. Moderate/severe periodontitis was defined using a half-reduced Centers for Disease Control and Prevention and American Academy of Periodontology case definition. Multivariable Cox proportional hazard regression was conducted to estimate the association between PhenoAgeAccel and mortality risk, followed by effect modification analysis to test whether periodontitis modified the association. During a median follow-up of 24.5 y, 3,600 (57.4%) deaths occurred. The positive relationships between PhenoAgeAccel and all-cause and cause-specific mortality were nonlinear. After adjusting for potential confounders, the highest quartile of PhenoAgeAccel was associated with increased all-cause mortality in individuals with no/mild periodontitis (hazard ratio for Q4 vs. Q1 [HRQ4vs.Q1] = 1.789; 95% confidence interval [CI], 1.541-2.076). In contrast, the association was enhanced in patients with moderate/severe periodontitis (HRQ4vs.Q1 = 2.446 [2.100-2.850]). Periodontal status significantly modified the association between PhenoAgeAccel and all-cause mortality (P for interaction = 0.012). In subgroup analyses, the modifying effect of periodontitis was observed in middle-aged adults (40-59 y), females, and non-Hispanic Whites. Although cause-specific mortality showed a similar trend, the PhenoAgeAccel × periodontitis interaction did not reach statistical significance. In conclusion, periodontitis might enhance the association of biological aging with all-cause mortality in middle-aged and older adults. Hence, maintaining and enhancing periodontal health is expected to become an intervention to slow aging and extend life span.

Modifiers of COVID-19 vaccine efficacy: Results from four COVID-19 prevention network efficacy trials.

Questions remain regarding the effect of baseline host and exposure factors on vaccine efficacy (VE) across pathogens and vaccine platforms. We report placebo-controlled data from four Phase 3 COVID-19 trials during the early period of the pandemic. This was a cross-protocol analysis of four randomized, placebo-controlled efficacy trials (Moderna/mRNA1273, AstraZeneca/AZD1222, Janssen/Ad26.COV2.S, and Novavax/NVX-CoV2373) using a harmonized design. Trials were conducted in the United States and international sites in adults ≥ 18 years of age. VE was assessed for symptomatic and severe COVID-19. We analyzed 114,480 participants from both placebo and vaccine arms, enrolled July 2020 to February 2021, with follow up through July 2021. VE against symptomatic COVID-19 showed little heterogeneity across baseline socio-demographic, clinical or exposure characteristics, in either univariate or multivariate analysis, regardless of vaccine platform. Similarly, VE against severe COVID-19 in the single trial (Janssen) with sufficient endpoints for analysis showed little evidence of heterogeneity. COVID-19 VE is not influenced by baseline host or exposure characteristics across efficacy trials of different vaccine platforms and countries when well matched to circulating virus strains. This supports use of these vaccines, regardless of platform type, as effective tools in the near term for reducing symptomatic and severe COVID-19, particularly for older individuals and those with common co-morbidities during major variant shifts. Clinical trial registration numbers: NCT04470427, NCT04516746, NCT04505722, and NCT04611802.

Finding the (biomarker-defined) subgroup of patients who benefit from a novel therapy: No time for a game of hide and seek.

An important element of precision medicine is the ability to identify, for a specific therapy, those patients for whom benefits of that therapy meaningfully exceed the risks. To achieve this goal, treatment effect usually is examined across subgroups defined by a variety of factors, including demographic, clinical, or pathologic characteristics or by molecular attributes of patients or their disease. Frequently such subgroups are defined by the measurement of biomarkers. Even though such examination is necessary when pursuing this goal, the evaluation of treatment effect across a variety of subgroups is statistically fraught due to both the danger of inflated false-positive error rate from multiple testing and the inherent insensitivity to how treatment effects differ across subgroups.Pre-specification of subgroup analyses with appropriate control of false-positive (i.e. type I) error is recommended when possible. However, when subgroups are specified by biomarkers, which could be measured by different assays and might lack established interpretation criteria, such as cut-offs, it might not be possible to fully specify those subgroups at the time a new therapy is ready for definitive evaluation in a Phase 3 trial. In these situations, further refinement and evaluation of treatment effect in biomarker-defined subgroups might have to take place within the trial. A common scenario is that evidence suggests that treatment effect is a monotone function of a biomarker value, but optimal cut-offs for therapy decisions are not known. In this setting, hierarchical testing strategies are widely used, where testing is first conducted in a particular biomarker-positive subgroup and then is conducted in the expanded pool of biomarker-positive and biomarker-negative patients, with control for multiple testing. A serious limitation of this approach is the logical inconsistency of excluding the biomarker-negatives when evaluating effects in the biomarker-positives, yet allowing the biomarker-positives to drive the assessment of whether a conclusion of benefit could be extrapolated to the biomarker-negative subgroup.Examples from oncology and cardiology are described to illustrate the challenges and pitfalls. Recommendations are provided for statistically valid and logically consistent subgroup testing in these scenarios as alternatives to reliance on hierarchical testing alone, and approaches for exploratory assessment of continuous biomarkers as treatment effect modifiers are discussed.

Effect of important modifiers on harmful effects in evidence synthesis practice of adverse events were insufficiently investigated: an empirical investigation.

BACKGROUND: Safety is important in the assessment of health interventions, while the results of adverse events are often susceptive to potential effect modifiers since the event risk tends to be rare. In this study, we investigated whether the potential impact of the important effect modifiers on harmful effects was analyzed in meta-analyses of adverse events. METHODS: Systematic reviews of healthcare interventions, had adverse events as the exclusive outcomes, had at least one meta-analysis, and published between 1st January 2015, and 1st January 2020 were collected. An adverse event was defined as any untoward medical occurrence in a patient or subject in healthcare practice. Six effect modifiers that are the most important for harmful effects were identified by a group discussion. The proportions of eligible systematic reviews that investigated the potential impact of the six effect modifiers on harmful effects were summarized. RESULTS: We identified 279 systematic reviews eligible for this study. Except for the modifier of interventions/controls (70.61%, 197/279), most of the systematic reviews failed to investigate the potential impact of treatment duration (21.15%, 59/279), dosage (24.73%, 69/279), age (11.47%, 32/279), risk of bias (6.45%, 18/279), and source of funding (1.08%, 3/279) on harmful effects. Systematic reviews with meta-analyses containing more studies were more likely to investigate the potential impacts of these modifiers on the effects, but the proportion was still low (2.3% to 33.3%). Systematic reviews that developed a protocol were significantly more likely to investigate the potential impact of all these effect modifiers (e.g. treatment duration: odds ratio = 5.08, 95% CI: 2.76 to 9.35) on the results. CONCLUSIONS: Current systematic reviews rarely investigated the potential impact of the important effect modifiers on harmful effects. Methodological guidelines for meta-analysis of adverse events should consider "effect modifier" as one of the domains to help systematic review authors better investigate harmful effects.

Association Between Mortality Due to Nasopharyngeal Carcinoma and Race in the United States From 2007 to 2016.

BACKGROUND: Asians and Pacific Islanders (API) exhibit increased incidence of nasopharyngeal carcinoma (NPC). However, they are often excluded when the disease is studied. Risk-factors and incidence are well-researched while cancer-specific mortality trends remain unclear. We aimed to determine whether insurance status modifies the association between race and cancer-specific mortality in NPC patients. METHODS: This retrospective cohort study used secondary data analysis from the Surveillance, Epidemiology, and End Results Program database. Patients ≥18 years with histologically confirmed primary NPC from 2007 - 2016 were included. The main outcome assessed was 5-year survival and the main exposure variable was race (API, white, black). Insurance status was classified into uninsured, any Medicaid, and insured (with any insurance). Potential confounders included age, sex, marital status, stage at diagnosis, and surgical treatment. Adjusted Cox regression analysis was used to calculate hazard ratios (HR) and corresponding 95% confidence intervals (CI). RESULTS: 1610 patients were included (72.98% male, 27.02% female). 49.8% were API, 40.5% were Whites, and 9.8% Blacks. Maximum follow-up was 5-years. The adjusted hazards of 5-year cancer-specific death for API and Blacks compared with Whites were 0.77 (95% CI 0.62 - 0.96) and 0.92 (95% CI 0.65 - 1.31), respectively. Cases decreased with age in API and Blacks. 8.2% of cases had localized disease, 45.3% had local spread, and 44.6% had distant metastasis. Insurance status did not modify the association between race and mortality. CONCLUSION: Race is an important prognostic factor to account for in NPC patients. Investigating risk-factors and subtypes stratified by race may explain our findings.

Understanding the differential effect of local socio-economic conditions on the relation between prescription opioid supply and drug overdose deaths in US counties.

BACKGROUND AND AIMS: Both local socio-economic conditions and prescription opioid supply are associated with drug overdose deaths, which exhibit substantial geographical heterogeneity across the United States. We measured whether the associations of prescription opioid supply with drug overdose deaths vary by local socio-economic conditions. DESIGN: Ecological county-level study, including 3109 US counties between 2006 and 2019 (n = 43 526 county-years) using annual mortality data. SETTING: United States. CASES: A total of 711 447 drug overdose deaths. MEASUREMENTS: We modeled overdose counts using Bayesian hierarchical Poisson models, estimating associations between four types of drug overdose deaths (deaths involving any drugs, any opioid, prescription opioids only and heroin), prescription opioid supply and five socio-economic indicators: unemployment, poverty rate, income inequality, Rey index (components include mean household income, % high school graduates, % blue-collar workers and unemployment rate), and American human development index (HDI; an indicator of community wellbeing). FINDINGS: Drug overdose deaths and all substance-specific overdose deaths were higher in counties with higher income inequality [adjusted odds ratios (aORs) = 1.09-1.13], Rey index (aORs = 1.15-1.21) and prescription opioid supply (aORs = 1.14-1.21), and lower in counties with higher HDI scores (aORs = 0.75-0.92). Poverty rate, income inequality and HDI scores were found to modify the effect of prescription opioid supply on heroin overdose deaths. The plot of the interactions showed that when disadvantage is high, increasing prescription opioid supply does not increase heroin overdose deaths. The less disadvantage there is, indicated by lower poverty rates, higher HDI scores and lower income inequality, the greater the effect of increasing prescription opioid supply relative to population size on heroin overdose deaths in US counties. CONCLUSIONS: In the United States, prescription opioid supply is associated with higher drug overdose deaths; associations are stronger in counties with less disadvantage and less income inequality, but only for heroin overdose deaths.

Effective primary care attenuates the association between frailty and hospital admission in old age: the ELSI-Brazil.

BACKGROUND: Frailty is a multidimensional syndrome leading to a higher hospitalization. However, few studies explicitly analyze whether measures of effective primary care modify the relationship between frailty and hospital admission. METHODS: This cross-sectional study included data from the second wave of the Brazilian Longitudinal Study of Aging (ELSI-Brazil), a representative community-based study with older adults aged 50 years and over, conducted in 2019-2021. Self-reported hospital admission in the past 12 months was the outcome. Frailty included the 5 phenotypic criteria: weight loss, exhaustion, low physical activity, weakness, and slowness. The effective primary care index included 12 attributes indicators, continuously. Statistical analyzes comprised logistic regression. RESULTS: Among the 7,436 study participants, frailty (odds ratio [OR] 2.17; 95% confidence intervals [95% CI] 1.31-3.62) and effective primary care index (OR 1.10; 95% CI 1.03-1.16) were positively associated with higher hospitalization. Interaction revealed that while effective primary care was positively associated with hospitalization, this association was different among frail older adults (OR 0.80; 95% CI 0.65-0.99). After stratification by frailty status, positive association with hospitalization remained only among prefrail and nonfrail individuals. The predicted probability of hospitalization tended to decrease along with higher primary care index values among frail older adults and became similar to prefrail/nonfrail at the highest end of the scale. CONCLUSIONS: Effective primary care decreases the likelihood of hospital admission among frail older adults. Interventions for delaying frailty should be initiated in primary care along with policies to strengthen primary care's organizational and provider/team-level attributes.

Frailty is a multidimensional syndrome leading to a higher hospitalization. However, few studies explicitly analyze whether measures of effective primary care modify the relationship between frailty and hospital admission. Using data from the Brazilian Longitudinal Study of Aging (ELSI-Brazil), a representative community-based study with older adults aged 50 years and over, we evaluated self-reported hospital admission in the past 12 months, frailty according to 5 phenotypic criteria, and an effective primary care index with 12 attributes indicators. According to data of 7,436 study participants, we revealed that while effective primary care index was positively associated with hospital admission, this association was different among frail older adults. After stratification by frailty status, positive association with hospitalization remained only among prefrail and nonfrail individuals. Therefore, effective primary care decreases the likelihood of hospital admission among frail older adults. Interventions for delaying frailty should be initiated in primary care along with policies to strengthen primary care's organizational and provider/team-level attributes.

Who are likely to benefit from the Good Life with osteoArthritis in Denmark (GLAD) exercise and education program? An effect modifier analysis of a randomised controlled trial.

OBJECTIVE: To identify contextual factors that modify the treatment effect of the 'Good Life with osteoArthritis in Denmark' (GLAD) exercise and education programme compared to open-label placebo (OLP) on knee pain in individuals with knee osteoarthritis (OA). METHODS: Secondary effect modifier analysis of a randomised controlled trial. 206 participants with symptomatic and radiographic knee OA were randomised to either the 8-week GLAD programme (n = 102) or OLP given as 4 intra-articular saline injections over 8 weeks (n = 104). The primary outcome was change from baseline to week 9 in the Knee injury and Osteoarthritis Outcome Score questionnaire (KOOS) pain subscale (range 0 (worst) to 100 (best)). Subgroups were created based on baseline information: BMI, swollen study knee, bilateral radiographic knee OA, sports participation as a young adult, sex, median age, a priori treatment preference, regular use of analgesics (NSAIDs or paracetamol), radiographic disease severity, and presence of constant or intermittent pain. RESULTS: Participants who reported use of analgesics at baseline seem to benefit from the GLAD programme over OLP (subgroup contrast: 10.3 KOOS pain points (95% CI 3.0 to 17.6)). Participants with constant pain at baseline also seem to benefit from GLAD over OLP (subgroup contrast: 10.0 points (95% CI 2.8 to 17.2)). CONCLUSIONS: These results imply that patients who take analgesics or report constant knee pain, GLAD seems to yield clinically relevant benefits on knee pain when compared to OLP. The results support a stratified recommendation of GLAD as management of knee OA. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03843931. EudraCT number 2019-000809-71.

Estimating interactions and subgroup-specific treatment effects in meta-analysis without aggregation bias: A within-trial framework.

Estimation of within-trial interactions in meta-analysis is crucial for reliable assessment of how treatment effects vary across participant subgroups. However, current methods have various limitations. Patients, clinicians and policy-makers need reliable estimates of treatment effects within specific covariate subgroups, on relative and absolute scales, in order to target treatments appropriately-which estimation of an interaction effect does not in itself provide. Also, the focus has been on covariates with only two subgroups, and may exclude relevant data if only a single subgroup is reported. Therefore, in this article we further develop the "within-trial" framework by providing practical methods to (1) estimate within-trial interactions across two or more subgroups; (2) estimate subgroup-specific ("floating") treatment effects that are compatible with the within-trial interactions and make maximum use of available data; and (3) clearly present this data using novel implementation of forest plots. We described the steps involved and apply the methods to two examples taken from previously published meta-analyses, and demonstrate a straightforward implementation in Stata based upon existing code for multivariate meta-analysis. We discuss how the within-trial framework and plots can be utilised with aggregate (or "published") source data, as well as with individual participant data, to effectively demonstrate how treatment effects differ across participant subgroups.

Impact of Alcohol and Smoking on Outcomes of HPV-Related Oropharyngeal Cancer.

BACKGROUND: The aim of this study was to evaluate the impact of adverse lifestyle factors on outcomes in patients with human papillomavirus (HPV)-related oropharyngeal squamous cell carcinoma (OPSCC). METHODS: From 2010 to 2019, 150 consecutive non-metastatic OPSCC patients receiving curative treatment in our institution were retrospectively enrolled. HPV positivity was defined as p16 expression ≥75%. The effects of adverse lifestyle factors on overall survival (OS) and disease-free survival (DFS) on OPSCC patients were determined. RESULTS: The median follow-up duration was 3.6 years. Of the 150 OPSCCs, 51 (34%) patients were HPV-positive and 99 (66%) were HPV-negative. The adverse lifestyle exposure rates were 74.7% (n = 112) alcohol use, 57.3% (n = 86) betel grid chewing, and 78% (n = 117) cigarette smoking. Alcohol use strongly interacted with HPV positivity (HR, 6.00; 95% CI, 1.03-35.01), leading to an average 26.1% increased risk of disease relapse in patients with HPV-positive OPSCC. Heavy smoking age ≥30 pack-years was associated with increased risk of death (HR, 2.05; 95% CI, 1.05-4.00) and disease relapse (HR, 1.99; 95% CI, 1.06-3.75) in OPSCC patients. In stratified analyses, the 3-year absolute risk of disease relapse in HPV-positive OPSCC patients reached up to 50% when alcohol use and heavy smoking for ≥30 pack-years were combined. CONCLUSIONS: Alcohol acted as a significant treatment-effect modifier for DFS in HPV-positive OPSCC patients, diluting the favorable prognostic effect of HPV positivity. Heavy smoking age ≥30 pack-years was an independent adverse prognostic factor of OS and DFS in OPSCC patients. De-intensification treatment for HPV-related OPSCC may be avoided when these adverse lifestyle factors are present.

[The Moderating Effect of Organizational Justice on the Relationship between Self-Efficacy and Nursing Performance in Clinical Nurses].

PURPOSE: This study aimed to examine the moderating effect of organizational justice on the relationship between self-efficacy and nursing performance among clinical nurses. METHODS: In January 2021, a cross-sectional survey was conducted with 224 clinical nurses recruited from a university-affiliated hospital in Suwon, South Korea. Participants completed online-based, self-report structured questionnaires. Collected data were analyzed using multiple regression and a simple model of PROCESS macro with a 95% bias-corrected bootstrap confidence interval. RESULTS: Self-efficacy and organizational justice were found to be significant predictors of nursing performance. These two predictors explained the additional 34.8% variance of nursing performance in the hierarchical regression model, after adjusting the other covariates. In addition, organizational justice moderated the relationship between self-efficacy and nursing performance among the clinical nurses. In particular, at low self-efficacy level, participants with high organizational justice had higher nursing performance compared to those with low organizational justice. CONCLUSION: Enhancing organizational justice can be used as an organizational strategy for improving the organizational culture in terms of distribution, procedure, and interaction. Ultimately, these efforts will contribute to the improvement of nursing performance through a synergistic effect on organizational justice beyond nurses' individual competency and self-efficacy.