Meta-analysis of breast cancer risk for individuals with PALB2 pathogenic variants.

Multigene panel testing now allows efficient testing of many cancer susceptibility genes leading to a larger number of mutation carriers being identified. They need to be counseled about their cancer risk conferred by the specific gene mutation. An important cancer susceptibility gene is PALB2. Multiple studies reported risk estimates for breast cancer (BC) conferred by pathogenic variants in PALB2. Due to the diverse modalities of reported risk estimates (age-specific risk, odds ratio, relative risk, and standardized incidence ratio) and effect sizes, a meta-analysis combining these estimates is necessary to accurately counsel patients with this mutation. However, this is not trivial due to heterogeneity of studies in terms of study design and risk measure. We utilized a recently proposed Bayesian random-effects meta-analysis method that can synthesize estimates from such heterogeneous studies. We applied this method to combine estimates from 12 studies on BC risk for carriers of pathogenic PALB2 mutations. The estimated overall (meta-analysis-based) risk of BC is 12.80% (6.11%-22.59%) by age 50 and 48.47% (36.05%-61.74%) by age 80. Pathogenic mutations in PALB2 makes women more susceptible to BC. Our risk estimates can help clinically manage patients carrying pathogenic variants in PALB2.

A Utilitarian Perspective on Risk Quantification for Clinical Significance in Binary Outcomes.

Null hypothesis significance testing (NHST) in medical research is increasingly being supplemented by estimation statistics, focusing on effect sizes (ESs) and confidence intervals (CIs). This study evaluates the expression of ESs and CIs for binary outcomes. A utilitarian framework is proposed, emphasizing the number of beneficiaries and the impact level. To evaluate clinical significance, minimal clinically important risk difference (MCIRD) is proposed based on event magnitude (EM). Within this framework, risk difference (RD) is introduced as the primary measure. To assess the performance of RD, we compared its statistical power against other measures (risk ratio, RR; odds ratio, OR; Cohen's h) in individual study scenarios, and visual information conveyance in meta-analysis scenarios. RDs maintain statistical power in comparison to other measures in individual studies. They provide clarity on the true impact of clinical interventions without compromising statistical integrity. Meta-analytic results indicate that using RDs directly enhances transparency, uncovers heterogeneity, and addresses misaligned assumptions. This approach, by quantifying clinical effectiveness under a utilitarian perspective, facilitates the applicability of research to patient care and encourages shared decision-making. The study advocates for reporting baseline risks (BRs) with RDs and recommends a standardized presentation of these statistics. In a utilitarian perspective, adopting RD as the preferred ES can foster a transparent, patient-focused research ethos. This aids in accurately presenting the magnitude and variability of treatment effects, offering a new direction in methodology.

The performance of marginal structural models for estimating risk differences and relative risks using weighted univariate generalized linear models.

We used Monte Carlo simulations to compare the performance of marginal structural models (MSMs) based on weighted univariate generalized linear models (GLMs) to estimate risk differences and relative risks for binary outcomes in observational studies. We considered four different sets of weights based on the propensity score: inverse probability of treatment weights with the average treatment effect as the target estimand, weights for estimating the average treatment effect in the treated, matching weights and overlap weights. We considered sample sizes ranging from 500 to 10,000 and allowed the prevalence of treatment to range from 0.1 to 0.9. We examined both the robust variance estimator when using generalized estimating equations with an independent working correlation matrix and a bootstrap variance estimator for estimating the standard error of the risk difference and the log-relative risk. The performance of these methods was compared with that of direct weighting. Both the direct weighting approach and MSMs based on weighted univariate GLMs resulted in the identical estimates of risk differences and relative risks. When sample sizes were small to moderate, the use of an MSM with a bootstrap variance estimator tended to result in the most accurate estimates of standard errors. When sample sizes were large, the direct weighting approach and an MSM with a bootstrap variance estimator tended to produce estimates of standard error with similar accuracy. When using a MSM to estimate risk differences and relative risks, in general it is preferable to use a bootstrap variance estimator than the robust variance estimator. We illustrate the application of the different methods for estimating risks differences and relative risks using an observational study on the effect on mortality of discharge prescribing of a beta-blocker in patients hospitalized with acute myocardial infarction.

Multimorbidity analysis with low condition counts: a robust Bayesian approach for small but important subgroups.

BACKGROUND: Robustly examining associations between long-term conditions may be important in identifying opportunities for intervention in multimorbidity but is challenging when evidence is limited. We have developed a Bayesian inference framework that is robust to sparse data and used it to quantify morbidity associations in the oldest old, a population with limited available data. METHODS: We conducted a retrospective cross-sectional study of a representative dataset of primary care patients in Scotland as of March 2007. We included 40 long-term conditions and studied their associations in 12,009 individuals aged 90 and older, stratified by sex (3039 men, 8970 women). We analysed associations obtained with Relative Risk (RR), a standard measure in the literature, and compared them with our proposed measure, Associations Beyond Chance (ABC). To enable a broad exploration of interactions between long-term conditions, we built networks of association and assessed differences in their analysis when associations are estimated by RR or ABC. FINDINGS: Our Bayesian framework was appropriately more cautious in attributing association when evidence is lacking, particularly in uncommon conditions. This caution in reporting association was also present in reporting differences in associations between sex and affected the aggregated measures of multimorbidity and network representations. INTERPRETATION: Incorporating uncertainty into multimorbidity research is crucial to avoid misleading findings when evidence is limited, a problem that particularly affects small but important subgroups. Our proposed framework improves the reliability of estimations of associations and, more in general, of research into disease mechanisms and multimorbidity. FUNDING: National Institute for Health and Care Research.

A new method for vascular age estimation based on relative risk difference in vascular aging.

OBJECTIVE: The current models of estimating vascular age (VA) primarily rely on the regression label expressed with chronological age (CA), which does not account individual differences in vascular aging (IDVA) that are difficult to describe by CA. This may lead to inaccuracies in assessing the risk of cardiovascular disease based on VA. To address this limitation, this work aims to develop a new method for estimating VA by considering IDVA. This method will provide a more accurate assessment of cardiovascular disease risk. METHODS: Relative risk difference in vascular aging (RRDVA) is proposed to replace IDVA, which is represented as the numerical difference between individual predicted age (PA) and the corresponding mean PA of healthy population. RRDVA and CA are regard as the influence factors to acquire VA. In order to acquire PA of all samples, this work takes CA as the dependent variable, and mines the two most representative indicators from arteriosclerosis data as the independent variables, to establish a regression model for obtaining PA. RESULTS: The proposed VA based on RRDVA is significantly correlated with 27 indirect indicators for vascular aging evaluation. Moreover, VA is better than CA by comparing the correlation coefficients between VA, CA and 27 indirect indicators, and RRDVA greater than zero presents a higher risk of disease. CONCLUSION: The proposed VA overcomes the limitation of CA in characterizing IDVA, which may help young groups with high disease risk to promote healthy behaviors.

Post stroke pain: Is there under-diagnosis in Black versus White patients?

Stroke incidence is higher and stroke outcomes are poorer in Black patients compared to White patients. Poststroke pain, however, is not a well understood stroke outcome. Using the National Institutes of Health All of Us Research Program database, we hypothesized that the dataset would demonstrate proportionately higher relative risk of poststroke pain in the Black poststroke patient population compared to the White poststroke patient population. However, our analysis showed that Black stroke patients were diagnosed with poststroke pain at a similar rate as White stroke patients. As our results are not consistent with other poststroke outcomes in the literature, this study identifies a potentially underdiagnosed patient population, highlighting the need for further research.

Visceral adiposity index as a predictor of type 2 diabetes mellitus risk: A systematic review and dose-response meta-analysis.

AIMS: Considering the positive association between visceral adiposity index (VAI) and type 2 diabetes mellitus (T2DM), no comprehensive assessment on the summarized and dose-response relationship between VAI and T2DM has yet been reported. Therefore, we performed a meta-analysis, including dose-response analysis, to quantitively elucidate this association. DATA SYNTHESIS: MEDLINE via PubMed and Embase databases were searched for relevant articles up to December 14, 2021. Random-effects generalized least squares regression models were used to assess the quantitative association between VAI and T2DM risk across studies. Restricted cubic splines were used to model the dose-response association. A total of 9 prospective cohort studies and 5 cross sectional studies were included in our review. Based on the meta-analysis, the pooled RR of T2DM was 2.05 (95% CI 1.74-2.41) for the highest versus reference VAI category. We found that the risk of T2DM was increased by 44% (RR, 1.44; 95% CI, 1.23-1.68) with each 1-unit increment of VAI. While, we found no evidence of a nonlinear dose-response association of VAI and T2DM (Pnon-linearity = 0.428). With the linear cubic spline model, when compared to population with VAI at 0.6, for those with VAI at 2.0, the risk of T2DM was increased by 81% (RR, 1.81; 95% CI 1.55-2.12). CONCLUSIONS: Our meta-analysis provides quantitative data suggesting that VAI is associated with an increased risk of T2DM. Public health strategies focusing on weight loss among obesity, especially the people characterized by the thin-on-the-outside--fat-on-the-inside phenotype could possibly reduce a substantial risk of T2DM. SYSTEMATIC REVIEW REGISTRATION: PROSPERO CRD42022372666.

Assessing heatwave effects on disabled persons in South Korea.

This study investigated the risk of heatwaves for people with disabilities and other socioeconomic attributes using Health Care Bigdata in South Korea. The Health Care Bigdata provides detailed information on heat-related illness (HRI) patients in 2011-2020 from seven major cities. We employed the Distributed Lag Nonlinear Model (DLNM) to measure heat waves' relative risk. Our findings are four-fold. First, the relative risk (RR) of disabled people was 5.075 (95% confidence interval 4.476-5.674), significantly surpassing that of non-disabled people, 3.296 (2.517-4.075). Second, among various personal characteristics studied, disability influenced RR the most, exceeding impacts from elderly (4.457: 3.748-5.166), low-income (3.909: 3.004-4.813), and outdoor (4.052: 2.940-5.164). Third, the disabled young group (5.305: 4.414-6.195) was more vulnerable than the non-disabled elderly group (4.287: 3.576-4.999). Lastly, no significant difference in relative risk was observed between the mild (4.413: 3.855-4.971) and severe disabled groups (4.013: 3.121-4.905).

Psychosis prevalence in London neighbourhoods; A case study in spatial confounding.

Analysis of impacts of neighbourhood risk factors on mental health outcomes frequently adopts a disease mapping approach, with unknown neighbourhood influences summarised by random effects. However, such effects may show confounding with observed predictors, especially when such predictors have a clear spatial pattern. Here, the standard disease mapping model is compared to methods which account and adjust for spatial confounding in an analysis of psychosis prevalence in London neighbourhoods. Established area risk factors such as area deprivation, non-white ethnicity, greenspace access and social fragmentation are considered as influences on psychosis. The results show evidence of spatial confounding in the standard disease mapping model. Impacts expected on substantive grounds and available evidence are either nullified or reversed in direction. It is argued that the potential for spatial confounding to affect inferences about geographic disease patterns and risk factors should be routinely considered in ecological studies of health based on disease mapping.

Miettinen and Nurminen score statistics revisited.

It is commonly necessary to perform inferences on the difference, ratio, and odds ratio of two proportions p1 and p2 based on two independent samples. For this purpose, the most common asymptotic statistics are based on the score statistics (S-type statistics). As these do not correct the bias of the estimator of the product pi (1-pi), Miettinen and Nurminen proposed the MN-type statistics, which consist of multiplying the statistics S by (N-1)/N, where N is the sum of the two sample sizes. This paper demonstrates that the factor (N-1)/N is only correct in the case of the test of equality of two proportions, providing the estimation of the correct factor (AU-type statistics) and the minimum value of the same (AUM-type statistics). Moreover, this paper assesses the performance of the four-type statistics mentioned (S, MN, AU and AUM) in one and two-tailed tests, and for each of the three parameters cited (d, R and OR). We found that the AUM-type statistics are the best, followed by the MN type (whose performance was most similar to that of AU-type). Finally, this paper also provides the correct factors when the data are from a multinomial distribution, with the novelty that the MN and AU statistics are similar in the case of the test for the odds ratio.

Sleep duration, its change, and risk of dementia among Japanese: The Japan Public Health Center-based Prospective Study.

OBJECTIVE: Previous findings on the association between sleep duration, changes in sleep duration, and long-term dementia risk were mixed. Thus, we aimed to investigate the association between midlife sleep duration, its change, and dementia. METHODS: We recruited 41,731 Japanese (40-71 years) and documented their habitual sleep duration at baseline (1990-1994) and a 5-year follow-up survey. Changes in sleep duration were calculated as differences between baseline and 5-year measurements. We identified dementia using the Long-Term Care Insurance system (2007-2016). Hazard ratios (HRs) and 95% confidence intervals (CIs) of dementia were calculated using the area-stratified Cox model. RESULTS: During 360,389 person-years, 4621 participants exhibited dementia. The multivariable HRs of dementia compared with 7 h of sleep were 1.13 (95% CI: 0.98-1.30) for 3-5 h, 0.93 (0.85-1.02) for 6 h, 1.06 (0.99-1.14) for 8 h, 1.13 (1.01-1.27) for 9 h, and 1.40 (1.21-1.63) for 10-12 h with a J-shaped fashion (p for linear < 0.001 and quadratic < 0.001). For its change, the HRs compared with no change were 1.02 (0.90-1.16) for decreased ≥2 h, 0.95 (0.88-1.03) for decreased 1 h, 1.00 (0.91-1.09) for increased 1 h, and 1.37 (1.20-1.58) for increased ≥2 h. The positive association for decreased sleep duration was observed in individuals with an initial sleep duration of ≤7 h, but not in those with ≥8 h (p for interaction = 0.007). CONCLUSIONS: Long and increased sleep duration was associated with a higher risk of dementia.

Time-series analysis of meteorological factors and emergency department visits due to dog/cat bites in Jinshan area, China.

Background: Meteorological factors play an important role in human health. Clarifying the occurrence of dog and cat bites (DCBs) under different meteorological conditions can provide key insights into the prevention of DCBs. Therefore, the objective of the study was to explore the relationship between meteorological factors and DCBs and to provide caution to avoid the incidents that may occur by DCBs. Methods: In this study, data on meteorological factors and cases of DCBs were retrospectively collected at the Shanghai Climate Center and Jinshan Hospital of Fudan University, respectively, in 2016-2020. The distributed lag non-linear and time series model (DLNM) were used to examine the effect of meteorological elements on daily hospital visits due to DCBs. Results: A total of 26,857 DCBs were collected ranging from 1 to 39 cases per day. The relationship between ambient temperature and DCBs was J-shaped. DCBs were positively correlated with daily mean temperature (rs = 0.588, P < 0.01). The relative risk (RR) of DCBs was associated with high temperature (RR = 1.450; 95% CI [1.220-1.722]). Female was more susceptible to high temperature than male. High temperature increased the risk of DCBs. Conclusions: The extremely high temperature increased the risk of injuries caused by DCBs, particularly for females. These data may help to develop public health strategies for potentially avoiding the occurrence of DCBs.

Interval estimation of relative risks for combined unilateral and bilateral correlated data.

Measurements are generally collected as unilateral or bilateral data in clinical trials, epidemiology, or observational studies. For example, in ophthalmology studies, the primary outcome is often obtained from one eye or both eyes of an individual. In medical studies, the relative risk is usually the parameter of interest and is commonly used. In this article, we develop three confidence intervals for the relative risk for combined unilateral and bilateral correlated data under the equal dependence assumption. The proposed confidence intervals are based on maximum likelihood estimates of parameters derived using the Fisher scoring method. Simulation studies are conducted to evaluate the performance of proposed confidence intervals with respect to the empirical coverage probability, the mean interval width, and the ratio of mesial non-coverage probability to the distal non-coverage probability. We also compare the proposed methods with the confidence interval based on the method of variance estimates recovery and the confidence interval obtained from the modified Poisson regression model with correlated binary data. We recommend the score confidence interval for general applications because it best controls converge probabilities at the 95% level with reasonable mean interval width. We illustrate the methods with a real-world example.

Risk of central nervous system tumour incidence in a cohort of workers chronically exposed to ionising radiation.

The aim of the present study was to assess the risk of primary central nervous system (CNS) tumour incidence in a cohort of 22,377 Mayak Production Association workers chronically exposed to ionising radiation. There were 96 primary CNS tumours, including 42 cases of glioma and 44 cases of meningioma, registered during the whole follow-up period (1948-2018). The study demonstrated that the risk of primary CNS tumour incidence was associated with sex, attained age, calendar period, tall body height, age at the beginning of exposure, and facility type. There was no association found between risk of CNS tumour incidence and body mass index, smoking (males) and alcohol consumption status. The study did not find an effect of the total external gamma radiation dose absorbed in the brain on risk of CNS tumour incidence irrespective of whether an adjustment for the total external neutron dose absorbed in the brain was included or not. Excess relative risk per 1 Gy of external gamma brain dose was 0.05 (95% confidence interval (CI) -0.30; 0.70) for all CNS tumours, -0.18 (95% CI -; 0.44) for gliomas, and 0.38 (95% CI -0.32; 2.08) for meningiomas without adjustment for total neutron brain dose. There was no effect modification by sex, attained age, age at hire or facility.

Distributed lag effects and vulnerable groups of PM and active pulmonary TB in Qingdao, China.

There has been a gap regarding current knowledge of the effect of PM on pulmonary TB, such as the exposure-time-response between them. This study aimed to explore the distributed lag effects of particulate matter (PM) on active pulmonary tuberculosis (TB) and identify the vulnerable groups. A generalized additive mixed model combined with a distributed lag non-linear model was applied to quantify the association between PM and active pulmonary TB with adjustment for potential confounders. Relative risk (RR) and cumulative RR with 95% confidence interval (CI) were calculated to quantify the exposure-time-response. A total of 16,486 cases of active pulmonary TB were notified. Results suggested that a unit 10 µg/m3 increase of daily PM2.5 concentration was positively associated with active pulmonary TB morbidity at 36-115 lag day and RR reached maximum at 66 lag day (1.0076; 95%CI, 1.0031-1.0122), and the cumulative RR was 2.1940 (95%CI, 1.2292-3.9161). For PM10, this association was significantly positive at 73-117 lag day, and RR reached maximum at 100 lag day (1.0036; 95%CI, 1.0003-1.0067), and the cumulative RR was not significant. This study provides evidence that PM significantly associate with active pulmonary TB. Vulnerability to PM2.5 was identified in male, female, 0-18 ages, 19-64 ages, workers, and students. Our findings have significant implications for developing local strategies to prevent and reduce health impact in PM polluted areas.

Hematopoietic cell transplantation and cellular therapies in Switzerland. Evolution over 25 years. A report from the stem cell transplantation and cellular therapies working groups of the SBST 1997-2021.

The Swiss Blood Stem Cell Transplantation and Cellular Therapy Group (SBST) leads a mandatory national registry for all hematopoietic stem cell transplants (HCT) and cellular therapies. After 25 years, information was available for 11,226 patients receiving an HCT (4031 allogeneic and 7195 autologous), including 925 pediatric patients. We compared patient characteristics and outcome by quinquennia 1997-2001, 2002-2006, 2007-2011, 2012-2016, and 2017-2021. There were numerous changes over time. Allogeneic transplant recipients became older (median age 33.7 vs. 54.3) and had more frequently unrelated donors and reduced intensity conditioning in later quinquennia. Similarly, age increased for recipients of autologous HCT (median 48.3 vs. 59.9). We did not see a significant drop in transplant activity during the SARS-CoV-2 pandemic. Analysis of outcome showed overall survival (relative risk (RR) of death 0.664 (0.529-0.832) and progression free survival (RR 0.708 (0.577-0.870) being improved over time comparing the latest to the first quinquennium adjusting for risk factors. Non-relapse mortality decreased in recipients of allogeneic HCT (RR: 0.371 (0.270-0.509)) over time but relapse risks did not. Outcome of autologous HCT improved as well across quinquennia, this improvement was mainly due to decreased relapse risks (RR 0.681 (0.597-0.777)), possibly related to maintenance treatment or rescue treatment for relapse mainly in myeloma patients. Cellular therapies other than allogeneic or autologous HCT, particularly chimeric antigen receptor T-cells (CAR-T) treatment have started to increase after 2019, year of approval of the first commercial CAR-T product in Switzerland. Data on chimeric antigen receptor T-cell treatment are too early for comparative analyses. Detailed analyses of changes over time are presented. This study includes all HCTs, and cellular therapies, data useful for quality assurance programs, health care cost estimation and benchmarking. Between 50% and 60% of patients are long-term survivors after both types of HCT, indicating growing populations of surviving patients requiring long-term care.

Receipt of opioid use disorder treatments prior to fatal overdoses and comparison to no treatment in Connecticut, 2016-17.

OBJECTIVE: To determine the relative risk of death following exposure to treatments for OUD compared to no treatment. METHODS: In this retrospective cohort study we compiled and merged state agency data on accidental and undetermined opioid overdose deaths in 2017 and exposures to OUD treatment in the prior six months to determine incidence rates following exposure to different treatment modalities. These rates were compared to the estimated incidence among those exposed to no treatment to determine relative risk of death for each treatment exposure. RESULTS: Incidence rates for opioid poisoning deaths for those exposed to treatment ranged from 6.06±1.40 per 1000 persons exposed to methadone to 17.36±3.22 per 1000 persons exposed to any non-medication treatment. The estimated incidence rate for those not exposed to treatment was 9.80±0.72 per 1000 persons. With no exposure to treatment as referent, exposure to methadone or buprenorphine reduced the relative risk by 38% or 34%, respectively; the relative risk of non-medication treatments was equal to or worse than no exposure to treatment (RR = 1.27-1.77). PRINCIPAL CONCLUSIONS: Exposure to non-MOUD treatments provided no protection against fatal opioid poisoning whereas the relative risk was reduced following exposures to MOUD treatment, even if treatment was not continued. Population level efforts to reduce opioid overdose deaths need to focus on expanding access to agonist-based MOUD treatments and are unlikely to succeed if access to non-MOUD treatments is made more available.

Pediculosis capitis risk factors in schoolchildren: hair thickness and hair length.

The human head lice is a cosmopolitan ectoparasite that causes pediculosis. The main way of spreading lice is through direct head-to-head contact. It is popular knowledge that some individuals are more susceptible to contracting head lice than others. Reports of individuals who have never been affected by the disease are common, even living in the same environment and under the same conditions as people who regularly have lice infestations. Previous research has been carried out on the risk of this infection associated with different human factors like gender or age. However, studies on the influence of the individual hair characteristics are scarce. The objective of the study was to analyze the pediculosis risk using geographical location, gender, age and individual hair characteristics as variables. Pediculosis was diagnosed through the detection of living lice in the hair. This cross-sectional school-based epidemiological study was conducted in 310 schoolchildren aged 1 to 13 years of schools in 4 municipalities situated in the State of Paraná, Brazil. The prevalence of head louse infection in primary school students was 49.35 %. The Odds Ratio of presence of pediculosis (OR) was estimated using multivariate logistic regression analysis. The results obtained indicate that hair length and thickness increase the risk of infection. Furthermore, the inclusion of hair color, hair shape, kind of hair-scale as covariates increases the risk of pediculosis, indicating that these variables partly explain this susceptibility and that pediculosis is independent of gender. A smaller hair diameter may favor insect fixation to the hair in the nymphal phases. These results may explain why girls are a greater risk as they let their hair grow for cultural reasons, i.e., being of female gender is an agglutinating variable. The conclusions drawn may explain the discrepancies obtained in previous analyses.

Excess Mortality Risk Due to Heat Stress in Different Climatic Zones of India.

India is at a high risk of heat stress-induced health impacts and economic losses owing to its tropical climate, high population density, and inadequate adaptive planning. The health impacts of heat stress across climate zones in India have not been adequately explored. Here, we examine and report the vulnerability to heat stress in India using 42 years (1979-2020) of meteorological data from ERA-5 and developed climate-zone-specific percentile-based human comfort class thresholds. We found that the heat stress is usually 1-4 °C higher on heatwave (HW) days than on nonheatwave (NHW) days. However, the stress on NHW days remains considerable and cannot be neglected. We then showed the association of a newly formulated India heat index (IHI) with daily all-cause mortality in three cities - Delhi (semiarid), Varanasi (humid subtropical), and Chennai (tropical wet and dry), using a semiparametric quasi-Poisson regression model, adjusted for nonlinear confounding effects of time and PM2.5. The all-cause mortality risk was enhanced by 8.1% (95% confidence interval, CI: 6.0-10.3), 5.9% (4.6-7.2), and 8.0% (1.7-14.2) during "sweltering" days in Varanasi, Delhi, and Chennai, respectively, relative to "comfortable" days. Across four age groups, the impact was more severe in Varanasi (ranging from a 3.2 to 7.5% increase in mortality risk for a unit rise in IHI) than in Delhi (2.6-4.2% higher risk) and Chennai (0.9-5.7% higher risk). We observed a 3-6 days lag effect of heat stress on mortality in these cities. Our results reveal heterogeneity in heat stress impact across diverse climate zones in India and call for developing an early warning system keeping in mind these regional variations.

Risk of infections in psoriatic arthritis or axial spondyloarthritis patients treated with targeted therapies: A meta-analysis of randomized controlled trials.

OBJECTIVE: To evaluate the risk of global infections in patients with psoriatic arthritis (PsA) and axial spondyloarthritis encompassing ankylosing spondylitis (AS) and non-radiographic axial spondyloarthritis (nr-axSpA) treated with targeted therapies. METHODS: Medline and Cochrane databases were systematically searched up to March 2021 for randomized controlled trials (RCTs) performed in patients with PsA or axial spondyloarthritis treated with biologic or targeted synthetic disease-modifying anti-rheumatic drugs (b/tsDMARDs). Global infections (any infections reported, including bacterial, viral and fungal infections, except serious infections) were the primary outcome. Secondary outcomes included serious infections defined as life-threatening infections or any infection requiring intravenous antibiotics or hospitalization. The relative risk of infections was determined by meta-analysis of RCTs. RESULTS: A total of 60 RCTs were included (20,418 patients), encompassing 17 b/tsDMARDs, compared with placebo, conventional synthetic drugs (csDMARDs) or non-steroidal anti-inflammatory drugs (NSAIDs). An increased risk of any infection for patients exposed to these drugs was found (RR 1.15, 95% CI [1.06-1.25]), mainly with high doses and longer duration of treatment. Most infections were respiratory tract or ear, nose, and throat (ENT) infections. Subgroup analyses showed a statistically significant increased risk of infections for axial spondyloarthritis patients (RR 1.32, 95% CI [1.14-1.52]), but not for PsA patients (RR 1.05, 95% CI [0.97-1.14]). Infection risk was highest with TNF inhibitors (RR 1.23, 95% CI [1.11-1.37]) and IL-17 inhibitors (RR 1.30, 95% CI [1.07-1.59]). No increased risk of serious infections was shown. CONCLUSION: In contrast to serious infections, the risk of global infections is moderately increased with b/tsDMARDs in spondyloarthritis, and is associated in particular with use of TNF and IL-17 inhibitors.