Causal diagrams for disease latency bias.

BACKGROUND: Disease latency is defined as the time from disease initiation to disease diagnosis. Disease latency bias (DLB) can arise in epidemiological studies that examine latent outcomes, since the exact timing of the disease inception is unknown and might occur before exposure initiation, potentially leading to bias. Although DLB can affect epidemiological studies that examine different types of chronic disease (e.g. Alzheimer's disease, cancer etc), the manner by which DLB can introduce bias into these studies has not been previously elucidated. Information on the specific types of bias, and their structure, that can arise secondary to DLB is critical for researchers, to enable better understanding and control for DLB. DEVELOPMENT: Here we describe four scenarios by which DLB can introduce bias (through different structures) into epidemiological studies that address latent outcomes, using directed acyclic graphs (DAGs). We also discuss potential strategies to better understand, examine and control for DLB in these studies. APPLICATION: Using causal diagrams, we show that disease latency bias can affect results of epidemiological studies through: (i) unmeasured confounding; (ii) reverse causality; (iii) selection bias; (iv) bias through a mediator. CONCLUSION: Disease latency bias is an important bias that can affect a number of epidemiological studies that address latent outcomes. Causal diagrams can assist researchers better identify and control for this bias.

Using Causal Diagrams for Biomedical Research.

Causal diagrams are used in biomedical research to develop and portray conceptual models that accurately and concisely convey assumptions about putative causal relations. Specifically, causal diagrams can be used for both observational studies and clinical trials to provide a scientific basis for some aspects of multivariable model selection. This methodology also provides an explicit framework for classifying potential sources of bias and enabling the identification of confounder, collider, and mediator variables for statistical analyses. We illustrate the potential serious miscalculation of effect estimates resulting from incorrect selection of variables for multivariable modeling without regard to their type and causal ordering as demonstrated by causal diagrams. Our objective is to improve researchers' understanding of the critical variable selection process to enhance their communication with collaborating statisticians regarding the scientific basis for intended study designs and multivariable statistical analyses. We introduce the concept of causal diagrams and their development as directed acyclic graphs to illustrate the usefulness of this methodology. We present numeric examples of effect estimate calculations and miscalculations based on analyses of the well-known Framingham Heart Study. Clinical researchers can use causal diagrams to improve their understanding of complex causation relations to determine accurate and valid multivariable models for statistical analyses. The Framingham Heart Study dataset and software codes for our analyses are provided in Appendix E1 (available online at http://www.annemergmed.com) to allow readers the opportunity to conduct their analyses.

Introduction to computational causal inference using reproducible Stata, R, and Python code: A tutorial.

The main purpose of many medical studies is to estimate the effects of a treatment or exposure on an outcome. However, it is not always possible to randomize the study participants to a particular treatment, therefore observational study designs may be used. There are major challenges with observational studies; one of which is confounding. Controlling for confounding is commonly performed by direct adjustment of measured confounders; although, sometimes this approach is suboptimal due to modeling assumptions and misspecification. Recent advances in the field of causal inference have dealt with confounding by building on classical standardization methods. However, these recent advances have progressed quickly with a relative paucity of computational-oriented applied tutorials contributing to some confusion in the use of these methods among applied researchers. In this tutorial, we show the computational implementation of different causal inference estimators from a historical perspective where new estimators were developed to overcome the limitations of the previous estimators (ie, nonparametric and parametric g-formula, inverse probability weighting, double-robust, and data-adaptive estimators). We illustrate the implementation of different methods using an empirical example from the Connors study based on intensive care medicine, and most importantly, we provide reproducible and commented code in Stata, R, and Python for researchers to adapt in their own observational study. The code can be accessed at https://github.com/migariane/Tutorial_Computational_Causal_Inference_Estimators.

Nanocellulose-based Delivery Systems and Cervical Cancer: Review of the Literature.

It has become clear that targeted therapy is one of the best options for decreasing the unpleasant side effects of existing common methods and reducing the number of deaths occurred due to many types of cancer. Biocompatible and non-toxic delivery systems are provided by nanomedicine for aiding targeted therapy in many diseases containing cancer. Cervical cancer (CC) is not only the most common gynecological cancer but also is ranked as the fourth common cancer between both men and women. Chemotherapy, radiotherapy, surgery, and immunotherapy are the approaches, which are being used for treating CC patients. However, more efficacy of these methods can be achieved with the help of nanomedicine and novel delivery systems. Nanocellulose is one of the agents used for designing these systems in order to deliver different drugs to a diversity of cancerous cells. In this review, we aim to investigate the competency of nanocellulose for establishing novel therapeutic methods for cervical cancer. We hope that our results help develop more drug delivery systems for targeted therapy to reduce the side effects and induce the efficacy of anti-cancer drugs.

Detection of influenza epidemics using hidden Markov and Serfling approaches.

OBJECTIVE: Detection of epidemics is a critical issue in epidemiology of infectious diseases which enable healthcare system to better control it. This study is devoted to investigating the 5-year trend in influenza and severe acute respiratory infection cases in Iran. The epidemics were also detected using the hidden Markov model (HMM) and Serfling model. STUDY DESIGN: In this study, we used SARI data reported in the World Health Organization (WHO) FluNet web-based tool from August 2011 to August 2016. METHODS: SARI data in Iran from August 2011 to August 2016 were used. We applied the HMM and Serfling model for indicating the two epidemic and non-epidemic phases. The registered outbreak activity recorded on the WHO website was used as the gold standard. The coefficient of determination was reported to compare the goodness of fit of the models. RESULTS: Serfling models modified by 30% and 35% of the data had a sensitivity of 91.67% and 95.83%, while for 15%, 20% and 25% were 70.83%, 79.17% and 83.33%, respectively. Sensitivity of HMM and autoregressive HMM (AHMM) was 66.67% and 92.86%. All fitted models have a specificity of over 96%. The R2 for HMM and AHMM was calculated 0.73 and 0.85, respectively, showing better fitness of these models, while R2 was around 50% for different types of Serfling models. CONCLUSIONS: Both modified Serfling and HMM were acceptable models in determining the epidemic points for the detection of weekly SARI. The AHMM had better fitness, higher detection power and more accurate detection of the incidence of epidemics than Serfling model and high sensitivity and specificity. In addition to AHMM, Serfling models with 30% and 35% modification can be used to detect epidemics due to approximately the same accuracy but the simplicity of the calculations.

Circular RNAs: new genetic tools in melanoma.

Melanoma is the most lethal form of skin cancer. New technologies have resulted in major advances in the diagnosis and treatment of melanoma and other cancer types. Recently, some studies have investigated the role of circular RNAs (circRNAs) in different cancers. CircRNAs are a member of long noncoding RNA family mainly formed through back-splicing and have a closed-loop structure. These molecules affect several biological and oncogenic cascades in diverse ways via acting as microRNA sponge, interacting with RNA-binding proteins and acting as a transcription regulator. In this review, we made an insight into the impact of circRNA dysregulation in the melanoma tumorigenesis based on the presented evidences.

Intermittent treatment interruption and its effect on multidrug resistant tuberculosis treatment outcome in Ethiopia.

Treatment interruption is one of the main risk factors of poor treatment outcome and occurrence of additional drug resistant tuberculosis. This study is a national retrospective cohort study with 10 years follow up period in MDR-TB patients in Ethiopia. We included 204 patients who had missed the treatment at least for one day over the course of the treatment (exposed group) and 203 patients who had never interrupted the treatment (unexposed group). We categorized treatment outcome into successful (cured or completed) and unsuccessful (lost to follow up, failed or died). We described treatment interruption by the length of time between interruptions, time to first interruption, total number of interruption episodes and percent of missed doses. We used Poisson regression model with robust standard error to determine the association between treatment interruption and outcome. 82% of the patients interrupted the treatment in the first six month of treatment period, and considerable proportion of patients demonstrated long intervals between two consecutive interruptions. Treatment interruption was significantly associated with unsuccessful treatment outcome (Adjusted Risk Ratio (ARR) = 1.9; 95% CI (1.4-2.6)). Early identification of patients at high risk of interruption is vital in improving successful treatment outcome.

Selenium supplementation lowers insulin resistance and markers of cardio-metabolic risk in patients with congestive heart failure: a randomised, double-blind, placebo-controlled trial.

This study was carried out to evaluate the effects of Se supplementation on metabolic profiles in patients with congestive heart failure (CHF). This randomised double-blind, placebo-controlled trial was performed among fifty-three subjects with CHF, aged 45-85 years old. Subjects were randomly allocated into two groups to take either 200 µg/d of Se as Se yeast (n 26) or placebo (n 27) for 12 weeks. Metabolic profiles were assessed at baseline and at the end of trial. Compared with the placebo, Se supplementation led to significant reductions in serum insulin (-18·41 (sd 27·53) v. +13·73 (sd 23·63) pmol/l, P<0·001), homoeostatic model of assessment for insulin resistance (-1·01 (sd 1·61) v. +0·55 (sd 1·20), P<0·001) and a significant increase in quantitative insulin sensitivity check index (QUICKI) (+0·007 (sd 0·03) v. -0·01 (sd 0·01), P=0·007). In addition, Se supplementation significantly decreased LDL-cholesterol (-0·23 (sd 0·29) v. -0·04 (sd 0·28) mmol/l, P=0·03) and total-:HDL-cholesterol ratio (-0·47 (sd 0·31) v. -0·06 (sd 0·42), P<0·001), and significantly increased HDL-cholesterol levels (+0·18 (sd 0·19) v. +0·02 (sd 0·13) mmol/l, P=0·001) compared with the placebo. In addition, taking Se supplements was associated with a significant reduction in high-sensitivity C-reactive protein (hs-CRP) (-1880·8 (sd 3437·5) v. +415·3 (sd 2116·5) ng/ml, P=0·01), and a significant elevation in plasma total antioxidant capacity (TAC) (+30·9 (sd 118·0) v. -187·9 (sd 412·7) mmol/l, P=0·004) and total glutathione levels (+33·7 (sd 130·4) v. -39·2 (sd 132·8) µmol/l, P=0·003) compared with the placebo. When we applied Bonferroni correction for multiple outcome testing, QUICKI (P=0·11), LDL-cholesterol (P=0·51), hs-CRP (P=0·17), TAC (P=0·06) and GSH (P=0·05) became non-significant, and other metabolic profiles did not alter. Overall, our study supported that Se supplementation for 12 weeks to patients with CHF had beneficial effects on insulin metabolism and few markers of cardio-metabolic risk.

Direct and indirect effects of central and general adiposity on cardiovascular diseases: The Tehran Lipid and Glucose Study.

Aim The mechanisms linking body mass index to cardiovascular disease are still not clearly defined. The purpose of this study was to find out how much of the effect of central and general adiposity on cardiovascular disease is mediated through blood pressure, cholesterol, and glucose, and how much is independent of these factors. Methods and results The study population included participants, aged ≥30 years, free of cardiovascular disease at baseline with median follow-up of 13.9 years. The total effects were broken down into natural direct and indirect effects using the inverse odds weighting method in the context of survival models. Systolic blood pressure, total serum cholesterol, and fasting plasma glucose as the primary measure of blood glucose were used as mediators. Blood pressure and cholesterol with indirect hazard ratios of 1.09 (95% confidence interval: 1.006-1.18) and 1.35 (95% confidence interval: 1.12-1.62) were the most important mediators for overweight-cardiovascular disease and obesity-cardiovascular disease relationships, respectively. The proportion mediated of overweight was 22% (6-47%) for blood pressure, 18% (5-37%) for blood glucose, and 20% (7-43%) for cholesterol. The same measure for obesity was 65% (35-91%) for cholesterol. For central adiposity, blood pressure, glucose, and cholesterol were the most important mediators with proportion mediated of 36% (17-72%), 23% (9-48%), and 21% (8-45%), respectively. Conclusions The findings of this study show that proper control of cardiometabolic risk factors of blood pressure, blood glucose, and dyslipidemia in an adult population can be effective to significantly reduce the effects of general and abdominal adiposity on cardiovascular diseases.

Decomposition of socioeconomic inequalities in preterm deliveries in Tehran, Iran.

OBJECTIVE: To investigate associations between economic inequality in preterm delivery. METHODS: The present secondary analysis included cross-sectional data collected in interviews with patients following delivery at 103 hospitals in Tehran, Iran, between July 6 and 21, 2015. Principal component analysis was used to measure the socioeconomic status of participants and the concentration index was used to measure inequalities in preterm delivery among patients of different socioeconomic status. RESULTS: Data were included from 5170 patients. The concentration index for preterm delivery was 0.087 (95% confidence interval 0.036-0.134), indicating that preterm deliveries were concentrated among patients with higher socioeconomic status. Higher socioeconomic status (94%), younger maternal age (29%), younger paternal age (21%), and being a homemaker (17%) had the highest positive contributions to the measured inequalities in preterm deliveries; vaginal delivery (-58%) had the highest negative contribution. CONCLUSION: Preterm deliveries were distributed unequally among the study patients in Iran, and were concentrated among patients of higher socioeconomic status. Alongside future etiological studies, reproductive programs in Iran should focus on this population to redress the observed inequality.

Cross-sectional study of associations between prior spontaneous abortions and preterm delivery.

OBJECTIVE: To evaluate associations between a history of spontaneous abortion and preterm delivery during subsequent pregnancies. METHODS: The present secondary analysis included cross-sectional survey data related to all deliveries at 103 hospitals in Tehran, Iran, between July 6 and 21, 2015. Trained midwives interviewed patients within 24 hours of delivery. Adjusted odds ratios (ORs) with 95% confidence intervals (CIs) were calculated to investigate associations between spontaneous abortion and preterm delivery. RESULTS: Data were included from 4991 deliveries. A history of spontaneous abortion (OR 1.50, 95% CI 1.21-1.87; P=0.001) and history of recurrent spontaneous abortion (OR 3.74, 95% CI 1.90-7.37; P=0.001) were associated with increased odds of preterm delivery in comparison with no such history. Similarly, one (OR 1.33, 95% CI 1.04-1.70; P=0.023), two (OR 1.78, 95% CI 1.15-2.74; P=0.009), or at least three prior spontaneous abortions (OR 4.10, 95% CI 2.08-8.08; P=0.001) were associated with increased odds of preterm delivery compared with none. Population attributable fractions of 9.49% (95% CI 3.36-15.12) and 2.00% (95% CI 0.57-3.56) were calculated for histories of spontaneous abortion and recurrent pregnancy loss, respectively. CONCLUSION: History of spontaneous abortion and history of recurrent pregnancy loss were associated with increased odds of preterm delivery. A greater number of spontaneous abortions corresponded to greater odds of preterm delivery.

The Epidemiology of Migraine Headache in General Population of Tehran, Iran.

BACKGROUND: Migraine as one of the most common types of headache is known to cause serious intervention with routine activities of affected individuals due to the devastating nature of attacks. The aim of this study was to provide epidemiological data of migraine in Iranian general population. METHODS: In this cross-sectional general population study, migraine diagnoses (both episodic and chronic) were based on the International Classification of Headache Disorders. Face-to-face interviews were performed by 5 trained medical interns on a sample size of 2,300 people aged 12-65 years. RESULTS: A total number of 2,076 subjects were enrolled for final analysis. The mean age of the subjects at the time of the study was 36.27 ± 14.56 years (age range 12-65 years). The 1-year prevalence of migraine was 27.6%. The prevalence of migraine among female subjects was significantly higher than among male subjects (36.7 vs. 21.6%, p < 0.001). The mean age of the subjects with migraine was 35.9 ± 12.96 years. Totally, 49.9% of migraine sufferers experienced at least one episode of aura. The most prevalent type of aura was numbness reported in 32.4% of migraine subjects. CONCLUSIONS: Despite the higher prevalence of migraine among Iranian general population compared to most of the other populations investigated by previous studies, these individuals experience a less severe course of disease.

Comparison between the effects of continuous and intermittent aerobic exercise on weight loss and body fat percentage in overweight and obese women: a randomized controlled trial.

BACKGROUND: Prevalence of obesity and overweightness in different societies is increasing. Role of physical activity in weight loss and also prevention from some chronic diseases has been discussed previously. The objective of this study was to compare the effect of two different aerobic exercises (intermittent and continuous exercises) while prescribed with concurrent calorie-restrict diet on the weight loss and body fat of overweight and obese females. METHODS: Fifteen individuals in intermittent group performed 40 min moderate Intensity exercise in 3 bouts per day for 5 days per week; the 15 participants of continuous group exercised a single 40 min bout per day, 5 days per week. Also, 15 participants were included in control group without exercise program. A self-monitoring calorie-restrict diet was recommended to all participants. The body fat percentage, waist circumference, and also skin fold thickness of all participants were assessed at baseline and 12(th) weeks. RESULTS: The reduction of weight and BMI of participants in intermittent group (-3.33 ± 1.80 and -1.34 ± 0.70, respectively) was significantly more than comparable changes in continuous group (-1.23 ± 1.60 and 0.49 ± 0.65, respectively) (P = 0.048 and 0.041, respectively). After the intervention, there was no significant difference between case and controls in terms of body fat percentage, waist circumference, and sum of skin fold thickness. CONCLUSIONS: It seems that moderate intensity intermittent exercise for more than 150 min/ week is more efficient than continuous exercise in weight loss of obese and overweight women.

Matched designs and causal diagrams.

We use causal diagrams to illustrate the consequences of matching and the appropriate handling of matched variables in cohort and case-control studies. The matching process generally forces certain variables to be independent despite their being connected in the causal diagram, a phenomenon known as unfaithfulness. We show how causal diagrams can be used to visualize many previous results about matched studies. Cohort matching can prevent confounding by the matched variables, but censoring or other missing data and further adjustment may necessitate control of matching variables. Case-control matching generally does not prevent confounding by the matched variables, and control of matching variables may be necessary even if those were not confounders initially. Matching on variables that are affected by the exposure and the outcome, or intermediates between the exposure and the outcome, will ordinarily produce irremediable bias.

Social disparities in prevalence, treatment and control of hypertension in Iran: second National Surveillance of Risk Factors of Noncommunicable Diseases, 2006.

OBJECTIVE: Assessing hypertension prevalence, treatment and control by sociodemographic factors in Iran. METHODS: We analyzed data from the 2006 National Surveillance of Risk Factors for Noncommunicable Diseases of Iran with a population-based sample of almost 30,000 people aged 15-64 years. Multiple logistic regression models were used to explore differences in hypertension prevalence, treatment and control, adjusting for sociodemographic factors, comorbidities and behavioral factors. RESULTS: Hypertension prevalence was 17.37%. Among hypertensive patients, 33.35% were under treatment, and, among treated people, 35.10% had hypertension controlled. In multiple-regression analysis, age, male sex, low level of education, Kurd ethnicity, overweight and obesity, diabetes mellitus, lower level of physical activity and high-Human Development Index provinces were independently associated with higher prevalence of hypertension. Income and living in rural or urban area were not related to hypertension prevalence. Treatment rates were lower in men, younger people and people of low education and low income, but there were no treatment rate disparities connected to living area, ethnicity and provinces (by Human Development Index). In addition, diabetic patients, obese people and past daily smokers had higher treatment rates. Lower control rates were independently associated with male sex, higher age and lower education, but not with other variables. CONCLUSION: In Iran, there is comparatively higher prevalence of hypertension among people of Kurdish ethnicity, people of low education and in high-Human Development Index provinces; a lower treatment rate among men, younger people, people of low education and low income; and a lower control rate among men and people of low education. These disparities should be addressed by researchers and health policy makers.