A simple Cox approach to estimating risk ratios without sharing individual-level data in multi-site studies.

Epidemiologic studies frequently use risk ratios to quantify associations between exposures and binary outcomes. When the data are physically stored at multiple data partners, it can be challenging to perform individual-level analysis if data cannot be pooled centrally due to privacy constraints. Existing methods either require multiple file transfers between each data partner and an analysis center (e.g., distributed regression) or only provide approximate estimation of the risk ratio (e.g., meta-analysis). Here we develop a practical method that requires a single transfer of eight summary-level quantities from each data partner. Our approach leverages an existing risk-set method and software originally developed for Cox regression. Sharing only summary-level information, the proposed method provides risk ratio estimates and confidence intervals identical to those that would be provided - if individual-level data were pooled - by the modified Poisson regression. We justify the method theoretically, confirm its performance using simulated data, and implement it in a distributed analysis of COVID-19 data from the U.S. Food and Drug Administration's Sentinel System.

A prediction model of elderly hip fracture mortality including preoperative red cell distribution width constructed based on the random survival forest (RSF) and Cox risk ratio regression.

An independent correlation between pre-RDW and 1-year mortality after surgery in elderly hip fracture can be used to predict mortality in elderly hip fracture patients and has predictive significance in anemia patients. With further research, a treatment algorithm can be developed to potentially identify patients at high risk of preoperative mortality. INTRODUCTION: Red blood cell distribution width (RDW) is an independent predictor of various disease states in elderly individuals, but its association with the prognosis of elderly hip fracture patients is controversial. This study aimed to evaluate the prognostic value of RDW in such patients, construct a prediction model containing RDW using random survival forest (RSF) and Cox regression analysis, and compare RDW in patients with and without anemia. METHODS: We retrospectively analyzed the data of elderly patients who underwent hip fracture surgery, selected the best variables using RSF, stratified the independent variables by Cox regression analysis, constructed a 1-year mortality prediction model of elderly hip fracture with RDW, and conducted internal validation and external validation. RESULTS: Two thousand one hundred six patients were included in this study. The RSF algorithm selects 12 important influencing factors, and Cox regression analysis showed that eight variables including preoperative RDW (pre-RDW) were independent risk factors for death within 1-year after hip fracture surgery in elderly patients. Stratified analysis showed that pre-RDW was still independently associated with 1-year mortality in the non-anemia group and not in the anemia group. The nomogram prediction model had high differentiation and fit, and the prediction model constructed by the total cohort of patients was also used for validation of patients in the anemia patients and obtained good clinical benefits. CONCLUSION: An independent correlation between pre-RDW and 1-year mortality after surgery in elderly hip fracture can be used to predict mortality in elderly hip fracture patients and has predictive significance in anemia patients.

Relationship between participation in projects of incentives to promote walking and healthy aging among the older population: A four-year longitudinal study.

OBJECTIVE: This study aimed to evaluate the association between the Yokohama Walking Point Program, which promotes walking through feedback on step counts and incentives, and the extension of healthy life expectancy. METHODS: A total of 4298 individuals aged over 65 years who responded to the 2013 and 2016 surveys and who were not certified as needing long-term care in 2016 were included in this study. The participants were categorized into "non-participation," "participation without uploading," and "participation with uploading" groups based on their involvement and uploading of pedometer data. The objective variable was the occurrence of long-term care certification and deaths over the subsequent four years. A modified Poisson regression model was applied, adjusting for 15 variables before project initiation. RESULTS: A total of 440 participants (10.2 %) were included in the "participation with uploading" group and 206 (4.8 %) in the "participation without uploading" group. Compared with "non-participation," the risk ratio was 0.77 (95 % confidence interval (CI): 0.59-0.99) for "participation with uploading" and 1.02 (95 % CI: 0.75-1.38) for "participation without uploading". In the sensitivity analysis censoring death as an inapplicable outcome and considering functional decline, participation with uploading showed a risk ratio of 0.79 (95 % CI: 0.60-1.04) for the likelihood of functional decline. CONCLUSIONS: The use of pedometers and health point programs based on walking activity is associated with enhancing the health of older individuals participating in the program, representing a population-centric strategy targeting all citizens.

Depression as a Risk Factor for Dementia: A Meta-Analysis.

Dementia is a syndrome characterized by the deterioration of cognitive function beyond what is expected. The increased risk of developing this syndrome resulting from established modifiable risk factors, such as depressive episodes, is currently a subject of interest. The aim of this study was to review the scientific evidence that addresses the relationship between depression and dementia. A bibliographic search of the PubMed and PsycInfo databases for articles published over the past 20 years was conducted with the following medical subject heading terms: depression or depressive, dementia, and incidence or cohort studies. After articles meeting the inclusion criteria were selected, relevant moderating variables were grouped as sample characteristics, methodological characteristics, extrinsic characteristics, and outcome variables. The 26 selected studies resulted in a sample comprising 1,760,262 individuals. Statistical analysis revealed a pooled relative risk for the development of dementia of 1.82 (95% CI=1.62-2.06). The primary variables evaluated were the diagnostic methods for depression and dementia and the presence of depression. Other variables, such as mean age, methodological quality of each study, follow-up time, and publication year, were also evaluated. Age was statistically but not clinically significant. No relevant publication bias or alterations in the results were found when accounting for the quality of the studies. It is recommended that new moderating variables be evaluated or that existing variables be reformulated in future studies.

Variance Estimation for Logistic Regression in Case-cohort Studies.

BACKGROUND: The logistic regression analysis proposed by Schouten et al (Stat Med. 1993;12:1733-1745) has been a standard method in current statistical analysis of case-cohort studies, and it enables effective estimation of risk ratios from selected subsamples, with adjustment of potential confounding factors. Schouten et al (1993) also proposed the standard error estimate of the risk ratio estimator can be calculated using the robust variance estimator, and this method has been widely adopted. METHODS AND RESULTS: The robust variance estimator does not account for the duplications of case and subcohort samples and generally has certain bias (ie, inaccurate confidence intervals and P-values are possibly obtained). To address the invalid statistical inference problem, we provide an alternative bootstrap-based valid variance estimator. Through simulation studies, the bootstrap method consistently provided more precise confidence intervals compared with those provided using the robust variance method, while retaining adequate coverage probabilities. CONCLUSION: The robust variance estimator has certain bias, and inadequate conclusions might be deduced from the resultant statistical analyses. The proposed bootstrap variance estimator can provide more accurate and precise interval estimates. The bootstrap method would be an alternative effective approach in practice to provide accurate evidence.

An update of the severe trauma scoring system using the Korean National Emergency Department Information System (NEDIS) database.

BACKGROUND: Various scoring systems are utilized to assess severe trauma patients, with one of the most commonly used tools being the International Classification of Diseases Injury Severity Score (ICISS) criteria derived from the Survival Risk Ratio (SRR) calculated using diagnostic codes. This study aimed to redefine the severe trauma scoring system in Korea based on the SRR for diagnostic codes, and subsequently evaluate its performance in predicting survival outcomes for trauma patients. METHODS: This study included trauma patients who visited Level 1 and 2 emergency departments (EDs) between January 2016 and December 2019, utilizing the Korean National Emergency Department Information System (NEDIS) database. The primary outcome of this study was in-hospital mortality. The new SRR-2020 value was calculated for each of the 865 trauma diagnosis codes (Korean Standard Classification of Diseases [KCD-7] codes, 4-digit format), and the patient-specific ICISS-2020 value was derived by multiplying the corresponding SRR-2020 value based on patient diagnosis. We compared the predictive performance for in-hospital mortality between severe trauma patients with an ICISS <0.9 based on the newly developed ICISS-2020 version and those defined by the previously used ICISS-2015 version. RESULTS: A total of 3,841,122 patients were enrolled, with an in-hospital mortality rate of 0.5 %. Severe trauma patients with ICISS-2020 < 0.9 accounted for 5.3 % (204,897 cases) that was lower than ICISS-2015 < 0.9 accounting for 15.3 % (587,801 cases). Among the 20,619 in-hospital mortality cases, 81.4 % had ICISS-2020 < 0.9, and 88.6 % had ICISS-2015 < 0.9. When comparing predictive performance for in-hospital mortality between the two ICISS versions, ICISS-2020 showed higher accuracy (0.95), specificity (0.95), positive predictive value (PPV) (0.08), positive likelihood ratio (LR+) (16.53), and area under the receiver operating characteristic curve (AUROC) (0.96) than ICISS-2015 for accuracy (0.85), sensitivity (0.88), specificity (0.85), PPV (0.03), LR+ (5.94), and AUROC (0.94). However, regarding sensitivity, ICISS-2020 < 0.9 showed a lower value of 0.81 compared to ICISS-2015 < 0.9, which was 0.88. The negative predictive value (NPV) was 1.00 for both versions. CONCLUSIONS: The newly developed ICISS-2020, utilizing a nationwide emergency patient database, demonstrated relatively good performance (accuracy, specificity, PPV, LR+, and AUROC) in predicting survival outcomes for patients with trauma.

Risk of acute kidney injury following contrast-enhanced CT or MRI in a cohort of 3061 hospitalized children in China.

OBJECTIVES: To compare the risk of acute kidney injury (AKI) between hospitalized children who received intravenous contrast media for imaging examinations and those who did not. METHODS: This retrospective cohort study enrolled patients aged 0-18 years with serum creatinine levels before and after imaging examinations from 2015 to 2020 at Beijing Children's Hospital. Participants were classified into an exposure group or a control group. Log-binomial regression analysis was used to estimate the adjusted risk ratio (aRR) value for the association between exposure to contrast media and consequential AKI. After which, inverse probability treatment weighting was used to reduce systematic differences in baseline characteristics among the groups. Moreover, subgroup and sensitivity analyses were performed. Finally, multivariate logistic regression analysis was performed to identify risk factors for pediatric AKI. RESULTS: In total, 3061 pediatric patients were included in the analyses (median age, 4.5 [IQR, 1.3-8.9] years, 1760 males). According the KDIGO definition of AKI, the incidence of AKI in the exposure group, and the control group were 7.4% and 6.5%, respectively; furthermore, the aRR was 1.35 (95% CI: 1.31-1.39). In patients underwent CT, the risk of AKI in the exposure group of contrast media increased compared with the control group and the aRR was 1.39 (95% CI: 1.09-1.78). However, it is not observed in patients underwent MRI (aRR: 1.36; 95% CI: 0.96-1.95). According to our subgroup analysis of pediatric patients aged ≥ 2 years (aRR: 1.38; 95% CI: 1.05-1.82) and sensitivity analysis (aRR: 1.32, 95% CI: 1.08-1.61), the risk of AKI in the exposure group was greater than that in the control group. An increased risk to exposure to contrast media was seen in females (aRR: 1.41, 95% CI: 1.05-1.89) rather than males (aRR: 1.30, 95% CI: 0.99-1.70). According to the multivariate logistic regression analyses, the baseline eGFR (OR: 1.02; 95% CI: 1.01-1.03) and comorbidities (OR: 2.97; 95% CI: 1.89-4.65) were risk factors, while age (OR: 0.87; 95% CI: 0.84-0.91) was a protective factor against AKI. CONCLUSION: The evidence from the present study suggested that the increased risk of AKI in hospitalized children induced by intravascular contrast should not be ignored.

Incident diabetes in adolescents using antidepressant: a systematic review and meta-analysis.

BACKGROUND: The use of antidepressants has been on the rise among adolescents and young adults, populations also increasingly at risk for type 2 diabetes. However, the relationship between antidepressant uses and diabetes incidence in these age groups remains poorly understood. METHODS: Adhering to PRISMA guidelines and the Cochrane Handbook, we conducted a comprehensive search in PubMed, Scopus, Embase, and Web of Science up to 21 February 2024, registering our protocol on PROSPERO (CRD42024516272). RESULTS: Six studies, ranging from 16, 470 to 1, 582, 914 participants and spanning 2010 to 2023 across North America, Europe, and Asia, were included. The meta-analysis revealed a significant association between antidepressant use and diabetes onset, with 10 cases per 1, 000 observations (p < 0.01; I2 = 100%). Adolescents using high doses of antidepressants showed a 62% increased risk of developing diabetes compared to non-users or those on low doses (Risk ratio = 1.67; 95% CI 1.19-2.35; I2 = 87%; p < 0.01). The overall quality of the studies was high, with an average Newcastle-Ottawa Scale score of 7.66. Sensitivity analysis highlighted the robustness of these findings, except when removing specific studies, indicating potential sources of heterogeneity. CONCLUSION: Antidepressant use in adolescents is associated with a significantly increased risk of diabetes onset, particularly at higher doses. This finding underscores the necessity for vigilant monitoring of glucose levels in this population and warrants further investigation into the underlying mechanisms and long-term outcomes.

Firth-Type Penalized Methods of the Modified Poisson and Least-Squares Regression Analyses for Binary Outcomes.

The modified Poisson and least-squares regression analyses for binary outcomes have been widely used as effective multivariable analysis methods to provide risk ratio and risk difference estimates in clinical and epidemiological studies. However, there is no certain evidence that assessed their operating characteristics under small and sparse data settings and no effective methods have been proposed for these regression analyses to address this issue. In this article, we show that the modified Poisson regression provides seriously biased estimates under small and sparse data settings. In addition, the modified least-squares regression provides unbiased estimates under these settings. We further show that the ordinary robust variance estimators for both of the methods have certain biases under situations that involve small or moderate sample sizes. To address these issues, we propose the Firth-type penalized methods for the modified Poisson and least-squares regressions. The adjustment methods lead to a more accurate and stable risk ratio estimator under small and sparse data settings, although the risk difference estimator is not invariant. In addition, to improve the inferences of the effect measures, we provide an improved robust variance estimator for these regression analyses. We conducted extensive simulation studies to assess the performances of the proposed methods under real-world conditions and found that the accuracies of the point and interval estimations were markedly improved by the proposed methods. We illustrate the effectiveness of these methods by applying them to a clinical study of epilepsy.

Misuse of multinomial logistic regression in stroke related health research: A systematic review of methodology.

Multinomial logistic regression (MLR) is often used to model the association between a nominal outcome variable and one or more covariates. The results of MLR are interpreted as relative risk ratios (RRR) and warrant a more coherent interpretation than ordinary logistic regression. Some authors compare the results of MLR to ordinal logistic regression (OLR), irrespective of the fact that these estimate different quantities. We aim to investigate the time trends in the use and misuse of MLR in studies including stroke patients, specifically the extent to which (1) the results are denoted as anything other than RRR, (2) comparisons are made of results with results of OLR and (3) results have been interpreted coherently. Secondarily, we examine the use of model validation techniques in studies with predictive aims. We searched EMBASE and PubMed for articles using MLR on populations of stroke patients. Identified studies were screened, and information pertaining to our aims was extracted. A total of 285 articles were identified through a systematic literature search, and 68 of these were included in the review. Of these, 60 articles (88%) did not denote exponentiated coefficients of MLR as relative risk ratios but rather some other measure. Additionally, 63 articles (93%) interpreted the results of MLR in a non-coherent manner. Two articles attempted to compare MLR results with those of OLR. Nine studies attempted to use MLR for predictive means, and three used relevant validation techniques. From these findings, it is clear that the interpretation of MLR is often suboptimal.

Comparative analysis of inflight transmission of SARS-CoV-2, influenza, and SARS-CoV-1.

The aim of this study is to evaluate the infection risk of aircraft passengers seated within and beyond two rows of the index case(s) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), influenza A(H1N1)pdm09 virus, and SARS-CoV-1. PubMed databases were searched for articles containing information on air travel-related transmission of SARS-CoV-2, influenza A(H1N1)pdm09 virus, and SARS-CoV-1 infections. We performed a meta-analysis of inflight infection data. In the eight flights where the attack rate could be calculated, the inflight SARS-CoV-2 attack rates ranged from 2.6% to 16.1%. The risk ratios of infection for passengers seated within and outside the two rows of the index cases were 5.64 (95% confidence interval (CI):1.94-16.40) in SARS-CoV-2 outbreaks, 4.26 (95% CI:1.08-16.81) in the influenza A(H1N1)pdm09 virus outbreaks, and 1.91 (95% CI:0.80-4.55) in SARS-CoV-1 outbreaks. Furthermore, we found no significant difference between the attack rates of SARS-CoV-2 in flights where the passengers were wearing masks and those where they were not (p = 0.22). The spatial distribution of inflight SARS-CoV-2 outbreaks was more similar to that of the influenza A(H1N1)pdm09 virus outbreaks than to that of SARS-CoV-1. Given the high proportion of asymptomatic or pre-symptomatic infection in SARS-CoV-2 transmission, we hypothesised that the proximity transmission, especially short-range airborne route, might play an important role in the inflight SARS-CoV-2 transmission.

Recommendations for risk minimization when using Janus kinase inhibitors for the treatment of chronic inflammatory skin diseases.

In accordance with article 20 of Regulation (EC) No 726/2004, the Pharmacovigilance Risk Assessment Committee (PRAC) of the European Medicines Agency (EMA) has re-evaluated the safety of Janus kinase inhibitors for the treatment of inflammatory diseases and formulated safety information deviating from the previous indications in the respective summary of product characteristics of the products concerned. These refer to the consideration of a possibly increased risk of venous thromboembolic or severe cardiovascular events, an increased infection rate and an increase in the prevalence of skin cancer across drugs and indications. Therefore, in patients with independent risk factors (age 65 years and older, smokers or former smokers, patients with oral contraception or hormone replacement therapy and other risk factors), it is recommended to use Janus kinase inhibitors therapeutically only if there are no suitable treatment alternatives. To facilitate a pragmatic and thorough detection of high-risk patients in everyday clinical practice, an interdisciplinary checklist was developed that is suitable as a working tool from the perspective of the dermatologist.

Controversies in rheumatology: maintenance therapy with low-dose glucocorticoids in rheumatoid arthritis.

Since the beginning of the use of glucocorticoids in clinical medicine, the risk-benefit ratio of these still very important drugs has been debated. There is no doubt that they produce many desirable therapeutic effects quickly and reliably. However, their potential to cause adverse effects, especially with prolonged use in high doses, limits their applicability. We discuss the arguments against and in favour of maintenance therapy with low-dose glucocorticoids in patients with RA, and present recent studies, assessments and conclusions on this question.

Effects of prenatal exposure to maternal COVID-19 and perinatal care on neonatal outcome: results from the INTERCOVID Multinational Cohort Study.

BACKGROUND: The effect of COVID-19 in pregnancy on maternal outcomes and its association with preeclampsia and gestational diabetes mellitus have been reported; however, a detailed understanding of the effects of maternal positivity, delivery mode, and perinatal practices on fetal and neonatal outcomes is urgently needed. OBJECTIVE: To evaluate the impact of COVID-19 on fetal and neonatal outcomes and the role of mode of delivery, breastfeeding, and early neonatal care practices on the risk of mother-to-child transmission. STUDY DESIGN: In this cohort study that took place from March 2020 to March 2021, involving 43 institutions in 18 countries, 2 unmatched, consecutive, unexposed women were concomitantly enrolled immediately after each infected woman was identified, at any stage of pregnancy or delivery, and at the same level of care to minimize bias. Women and neonates were followed up until hospital discharge. COVID-19 in pregnancy was determined by laboratory confirmation and/or radiological pulmonary findings or ≥2 predefined COVID-19 symptoms. The outcome measures were indices of neonatal and perinatal morbidity and mortality, neonatal positivity and its correlation with mode of delivery, breastfeeding, and hospital neonatal care practices. RESULTS: A total of 586 neonates born to women with COVID-19 diagnosis and 1535 neonates born to women without COVID-19 diagnosis were enrolled. Women with COVID-19 diagnosis had a higher rate of cesarean delivery (52.8% vs 38.5% for those without COVID-19 diagnosis, P<.01) and pregnancy-related complications, such as hypertensive disorders of pregnancy and fetal distress (all with P<.001), than women without COVID-19 diagnosis. Maternal diagnosis of COVID-19 carried an increased rate of preterm birth (P≤.001) and lower neonatal weight (P≤.001), length, and head circumference at birth. In mothers with COVID-19 diagnosis, the length of in utero exposure was significantly correlated to the risk of the neonate testing positive (odds ratio, 4.5; 95% confidence interval, 2.2-9.4 for length of in utero exposure >14 days). Among neonates born to mothers with COVID-19 diagnosis, birth via cesarean delivery was a risk factor for testing positive for COVID-19 (odds ratio, 2.4; 95% confidence interval, 1.2-4.7), even when severity of maternal conditions was considered and after multivariable logistic analysis. In the subgroup of neonates born to women with COVID-19 diagnosis, the outcomes worsened when the neonate also tested positive, with higher rates of neonatal intensive care unit admission, fever, gastrointestinal and respiratory symptoms, and death, even after adjusting for prematurity. Breastfeeding by mothers with COVID-19 diagnosis and hospital neonatal care practices, including immediate skin-to-skin contact and rooming-in, were not associated with an increased risk of newborn positivity. CONCLUSION: In this multinational cohort study, COVID-19 in pregnancy was associated with increased maternal and neonatal complications. Cesarean delivery was significantly associated with newborn COVID-19 diagnosis. Vaginal delivery should be considered the safest mode of delivery if obstetrical and health conditions allow it. Mother-to-child skin-to-skin contact, rooming-in, and direct breastfeeding were not risk factors for newborn COVID-19 diagnosis, thus well-established best practices can be continued among women with COVID-19 diagnosis.

Roles and outcomes of stereotactic biopsy for adult patients with brainstem lesion.

PURPOSE: This study aimed to assess the benefit-risk ratio by determining diagnostic yield and safety of brainstem biopsies in adult patients. The secondary objectives were (i) to compare brainstem biopsy safety and postbiopsy patients' outcomes and survival with those of patients biopsied for a brain or cerebellar lesion, and (ii) to assess the impact of brainstem biopsy on final diagnosis and further therapeutic management. METHODS: Among 1784 stereotactic biopsies performed in adult patients at a tertiary center between April 2009 and October 2020, we retrospectively examined 50 consecutive brainstem biopsies. We compared variables regarding diagnostic yield, safety and post-biopsy outcomes between brainstem biopsy patients and brain/cerebellum biopsy patients. RESULTS: Brainstem biopsy led to a diagnosis in 86% of patients (94.6% in patients with suspected tumor). Lesion contrast enhancement on imaging was the sole predictor of obtaining a diagnosis. Rates of symptomatic complications and mortality were significantly higher in brainstem biopsy patients compared to brain/cerebellum biopsy patients (20% vs 0%; p < 0.001 and 6% vs 0%; p = 0.01, respectively). Transfrontal trajectory and prebiopsy swallowing disorders were predictors of brainstem biopsy-related symptomatic complications. Brainstem biopsy findings led to diagnostic change in 22% of patients. CONCLUSIONS: Stereotactic biopsy in adult patients with brainstem lesion has a high diagnostic yield. Although stereotactic brainstem biopsy is associated with more functional and fatal complications than biopsies targeting the brain/cerebellum, its safety profile appears acceptable. Thus, the benefit-risk ratio of stereotactic biopsy in patients with brainstem lesion is favorable but should nevertheless be carefully weighted on a case-by-case basis.

Bayesian spatio-temporal modelling and mapping of malaria and anaemia among children between 0 and 59 months in Nigeria.

BACKGROUND/M&M: A vital aspect of disease management and policy making lies in the understanding of the universal distribution of diseases. Nevertheless, due to differences all-over host groups and space-time outbreak activities, data are subject to intricacies. Herein, Bayesian spatio-temporal models were proposed to model and map malaria and anaemia risk ratio in space and time as well as to ascertain risk factors related to these diseases and the most endemic states in Nigeria. Parameter estimation was performed by employing the R-integrated nested Laplace approximation (INLA) package and Deviance Information Criteria were applied to select the best model. RESULTS: In malaria, model 7 which basically suggests that previous trend of an event cannot account for future trend i.e., Interaction with one random time effect (random walk) has the least deviance. On the other hand, model 6 assumes that previous event can be used to predict future event i.e., (Interaction with one random time effect (ar1)) gave the least deviance in anaemia. DISCUSSION: For malaria and anaemia, models 7 and 6 were selected to model and map these diseases in Nigeria, because these models have the capacity to receive strength from adjacent states, in a manner that neighbouring states have the same risk. Changes in risk and clustering with a high record of these diseases among states in Nigeria was observed. However, despite these changes, the total risk of malaria and anaemia for 2010 and 2015 was unaffected. CONCLUSION: Notwithstanding the methods applied, this study will be valuable to the advancement of a spatio-temporal approach for analyzing malaria and anaemia risk in Nigeria.

Choosing and changing the analysis scale in non-inferiority trials with a binary outcome.

BACKGROUND: The size of the margin strongly influences the required sample size in non-inferiority and equivalence trials. What is sometimes ignored, however, is that for trials with binary outcomes, the scale of the margin - risk difference, risk ratio or odds ratio - also has a large impact on power and thus on sample size requirement. When considering several scales at the design stage of a trial, these sample size consequences should be taken into account. Sometimes, changing the scale may be needed at a later stage of a trial, for example, when the event proportion in the control arm turns out different from expected. Also after completion of a trial, a switch to another scale is sometimes made, for example, when using a regression model in a secondary analysis or when combining study results in a meta-analysis that requires unifying scales. The exact consequences of such switches are currently unknown. METHODS AND RESULTS: This article first outlines sample size consequences for different choices of analysis scale at the design stage of a trial. We add a new result on sample size requirement comparing the risk difference scale with the risk ratio scale. Then, we study two different approaches to changing the analysis scale after the trial has commenced: (1) mapping the original non-inferiority margin using the event proportion in the control arm that was anticipated at the design stage or (2) mapping the original non-inferiority margin using the observed event proportion in the control arm. We use simulations to illustrate consequences on type I and type II error rates. Methods are illustrated on the INES trial, a non-inferiority trial that compared single birth rates in subfertile couples after different fertility treatments. Our results demonstrate large differences in required sample size when choosing between risk difference, risk ratio and odds ratio scales at the design stage of non-inferiority trials. In some cases, the sample size requirement is twice as large on one scale compared with another. Changing the scale after commencing the trial using anticipated proportions mainly impacts type II error rate, whereas switching using observed proportions is not advised due to not maintaining type I error rate. Differences were more pronounced with larger margins. CONCLUSIONS: Trialists should be aware that the analysis scale can have large impact on type I and type II error rates in non-inferiority trials.

Use of diagnostic likelihood ratio of outcome to evaluate misclassification bias in the planning of database studies.

BACKGROUND: The diagnostic likelihood ratio (DLR) and its utility are well-known in the field of medical diagnostic testing. However, its use has been limited in the context of an outcome validation study. We considered that wider recognition of the utility of DLR would enhance the practices surrounding database studies. This is particularly timely and important since the use of healthcare-related databases for pharmacoepidemiology research has greatly expanded in recent years. In this paper, we aimed to advance the use of DLR, focusing on the planning of a new database study. METHODS: Theoretical frameworks were developed for an outcome validation study and a comparative cohort database study; these two were combined to form the overall relationship. Graphical presentations based on these relationships were used to examine the implications of validation study results on the planning of a database study. Additionally, novel uses of graphical presentations were explored using some examples. RESULTS: Positive DLR was identified as a pivotal parameter that connects the expected positive-predictive value (PPV) with the disease prevalence in the planned database study, where the positive DLR is equal to sensitivity/(1-specificity). Moreover, positive DLR emerged as a pivotal parameter that links the expected risk ratio with the disease risk of the control group in the planned database study. In one example, graphical presentations based on these relationships provided a transparent and informative summary of multiple validation study results. In another example, the potential use of a graphical presentation was demonstrated in selecting a range of positive DLR values that best represented the relevant validation studies. CONCLUSIONS: Inclusion of the DLR in the results section of a validation study would benefit potential users of the study results. Furthermore, investigators planning a database study can utilize the DLR to their benefit. Wider recognition of the full utility of the DLR in the context of a validation study would contribute meaningfully to the promotion of good practice in planning, conducting, analyzing, and interpreting database studies.

Immune checkpoint inhibitors and potential risk of thromboembolic events: Analysis of the WHO global database of individual case safety reports.

Introduction: Thromboembolic events with the use of immune checkpoint inhibitors (ICIs) in patients with cancer have been reported in few studies. However, the detailed profile of these cases remains mostly uncertain. Method: A descriptive analysis of Thromboembolic events associated with ICIs retrieved from the VigiBase, between 1967 to November 2020. We extracted the data using the terms of 'pulmonary embolism' OR 'deep vein thrombosis' OR 'acute coronary syndrome' OR 'myocardial infarction' OR 'ischemic stroke' (preferred term (PT) (MedDRA). Results: We included 161 cases from 26 countries in our descriptive analysis. Patients' ages were reported in 141 (87.6%) cases, with a median of 68 years (interquartile range 61-74), and 63.4% of the patients were male. Indications for ICIs were reported in 151 (93.8%) cases, as follows: lung cancer (n = 85, 52.8%), renal cell carcinoma (n = 24, 14.9%), melanoma (n = 20, 12.4%), urethral carcinoma (n = 12, 7.45%), breast cancer (n = 4, 2.48%), adenocarcinoma of the gastroesophageal junction (n = 3, 1.9%), gastric cancer (n = 2, 1.24%), and skin cancer (n = 1, 0.62%). Nivolumab was reported as a suspected drug in 76 cases (47%), pembrolizumab in 46 cases (28.5%), atezolizumab in 21 cases (13%), durvalumab in 14 cases (8.6%), and avelumab in four cases (2.4%).The time to onset of thromboembolic events was reported in 127 (78.8%) cases. Most of these patients (n = 109, 85.8%) reported thromboembolic events within the first six months. The causality assessment of included cases showed that 50.3% of reported thromboembolic events were possibly related to the suspected reported medication, 13.7% were probably related, 13% were unlikely to be related, and 23% were not assessable due to insufficient information. Conclusion: This study demonstrates a possible association between the use of ICIs and thromboembolic events. Further epidemiological studies are needed to assess this association and to elucidate the underlying mechanism.

Phosphodiesterase inhibitor for heart failure with preserved ejection fraction: A systematic review and meta-analysis.

Background: Although heart failure with preserved ejection fraction (HFpEF) is a serious disease, only limited options are available for its treatment. Recent studies have analyzed the effects of phosphodiesterase (PDE) inhibitors, especially PDE5 and PDE3 inhibitors, in patients with HFpEF, with mixed outcomes. Methods: We searched PUBMED and EMBASE databases up to August 2021. Randomized controlled trials (RCTs) and clinical trials that tested the effects of PDE inhibitors on patients with HFpEF were included as eligible studies. Indicators of left ventricular (LV) function, pulmonary arterial pressure (PAP), right ventricular (RV) function, exercise capacity, and quality of life (QOL) were used to evaluate the efficacy of PDE inhibitors in HFpEF. Results: Six RCTs that reported in 7 studies were included to evaluate the efficiency of PDE inhibitors on HFpEF patients. In the pooled analysis, PDE inhibitors showed insignificant changes in the ratio of early diastolic mitral inflow to annular velocities, left atrial volume index, pulmonary artery systolic pressure (PASP), pulmonary vascular resistance (PVR), peak oxygen uptake, 6-minute walking test distance, as well as Kansas City Cardiomyopathy Questionnaire score. However, substantial improvement was observed in the tricuspid annular plane systolic excursion (TAPSE). Additionally, the regression analysis showed that PDE inhibitor administration time is a critical factor for the decrease in PASP. Conclusions: PDE inhibitors did not effectively improve LV function, PAP, exercise capacity, and QOL in patients with HFpEF. However, they improved RV function with significant difference, suggesting that PDE inhibitors might be a promising option for HFpEF patients with RV dysfunction.