Effect of alcohol consumption on breast cancer: probabilistic bias analysis for adjustment of exposure misclassification bias and confounders.

PURPOSE: This study was conducted to evaluate the effect of alcohol consumption on breast cancer, adjusting for alcohol consumption misclassification bias and confounders. METHODS: This was a case-control study of 932 women with breast cancer and 1000 healthy control. Using probabilistic bias analysis method, the association between alcohol consumption and breast cancer was adjusted for the misclassification bias of alcohol consumption as well as a minimally sufficient set of adjustment of confounders derived from a causal directed acyclic graph. Population attributable fraction was estimated using the Miettinen's Formula. RESULTS: Based on the conventional logistic regression model, the odds ratio estimate between alcohol consumption and breast cancer was 1.05 (95% CI: 0.57, 1.91). However, the adjusted estimates of odds ratio based on the probabilistic bias analysis ranged from 1.82 to 2.29 for non-differential and from 1.93 to 5.67 for differential misclassification. Population attributable fraction ranged from 1.51 to 2.57% using non-differential bias analysis and 1.54-3.56% based on differential bias analysis. CONCLUSION: A marked measurement error was in self-reported alcohol consumption so after correcting misclassification bias, no evidence against independence between alcohol consumption and breast cancer changed to a substantial positive association.

Additive interaction between dietary inflammatory index and some key risk factors of multiple sclerosis: a population-based incident case-control study.

BACKGROUND: Recently, dietary inflammatory index (DII) has been introduced as a significant risk factor for MS. We examined the interaction between dietary inflammatory index and some formerly demonstrated key risk factors of multiple sclerosis (MS). MATERIAL AND METHODS: We conducted a population-based incident case-control study of 547 MS cases and 1057 controls. Multiplicative and additive interaction were assessed using interaction term in the logistic regression model and synergy index (SI), respectively. RESULTS: Additive interaction was detected between DII and drug abuse (SI = 2.58; 95% CI: 1.14-5.82), gender (SI = 2.00; 95% CI: 1.39-2.87) and history of depression (SI = 1.68; 95% CI: 1.04-2.72) on the risk scale. The risk of MS in drug abusers with DII ≥ 0 was 10.4-times higher than that in non-drug abusers with DII < 0 (OR = 10.4, 95% CI: 5.12-21.02, P < 0.001). We also found that women with DII ≥ 0 had a 9.2 times larger risk compared with the men with DII < 0(OR = 9.2, 95% CI: 6.3-13.5, P < 0.001). Similarly, the risk of MS was remarkably higher in those with a history of depression and DII >0 (OR = 7.6, 95% CI: 5.1-11.5, P < 0.001). There was no evidence of multiplicative interaction between DII and the other risk factors of MS on the risk scale. CONCLUSIONS: We identified additive interaction between DII and drug abuse, gender and history of depression on MS. Further studies are needed to understand the underlying mechanisms of these detected interactions.

The effect of smoking on latent hazard classes of metabolic syndrome using latent class causal analysis method in the Iranian population.

BACKGROUND: The prevalence of metabolic syndrome is increasing worldwide. Clinical guidelines consider metabolic syndrome as an all or none medical condition. One proposed method for classifying metabolic syndrome is latent class analysis (LCA). One approach to causal inference in LCA is using propensity score (PS) methods. The aim of this study was to investigate the causal effect of smoking on latent hazard classes of metabolic syndrome using the method of latent class causal analysis. METHODS: In this study, we used data from the Tehran Lipid and Glucose Cohort Study (TLGS). 4857 participants aged over 20 years with complete information on exposure (smoking) and confounders in the third phase (2005-2008) were included. Metabolic syndrome was evaluated as outcome and latent variable in LCA in the data of the fifth phase (2014-2015). The step-by-step procedure for conducting causal inference in LCA included: (1) PS estimation and evaluation of overlap, (2) calculation of inverse probability-of-treatment weighting (IPTW), (3) PS matching, (4) evaluating balance of confounding variables between exposure groups, and (5) conducting LCA using the weighted or matched data set. RESULTS: Based on the results of IPTW which compared the low, medium and high risk classes of metabolic syndrome (compared to a class without metabolic syndrome), no association was found between smoking and the metabolic syndrome latent classes. PS matching which compared low and moderate risk classes compared to class without metabolic syndrome, showed that smoking increases the probability of being in the low-risk class of metabolic syndrome (OR: 2.19; 95% CI: 1.32, 3.63). In the unadjusted analysis, smoking increased the chances of being in the low-risk (OR: 1.45; 95% CI: 1.01, 2.08) and moderate-risk (OR: 1.68; 95% CI: 1.18, 2.40) classes of metabolic syndrome compared to the class without metabolic syndrome. CONCLUSIONS: Based on the results, the causal effect of smoking on latent hazard classes of metabolic syndrome can be different based on the type of PS method. In adjusted analysis, no relationship was observed between smoking and moderate-risk and high-risk classes of metabolic syndrome.

Interaction Contrasts and Collider Bias.

Previous papers have mentioned that conditioning on a binary collider would introduce an association between its causes in at least 1 stratum. In this paper, we prove this statement and, along with intuitions, formally examine the direction and magnitude of the associations between 2 risk factors of a binary collider using interaction contrasts. Among level one of the collider, 2 variables are independent, positively associated, and negatively associated if multiplicative risk interaction contrast is equal to, more than, and less than 0, respectively; the same results hold for the other level of the collider if the multiplicative survival interaction contrast, equal to multiplicative risk interaction contrast minus the additive risk interaction contrast, is compared with 0. The strength of the association depends on the magnitude of the interaction contrast: The stronger the interaction is, the larger the magnitude of the association will be. However, the common conditional odds ratio under the homogeneity assumption will be bounded. A figure is presented that succinctly illustrates our results and helps researchers to better visualize the associations introduced upon conditioning on a collider.

Development and validation of an online tool for assessment of health care providers' management of suspected malaria in an area, where transmission has been interrupted.

BACKGROUND: The alertness and practice of health care providers (HCPs) in the correct management of suspected malaria (CMSM) (vigilance) is a central component of malaria surveillance following elimination, and it must be established before malaria elimination certification can be granted. This study was designed to develop and validate a rapid tool, Simulated Malaria Online Tool (SMOT), to evaluate HCPs' practice in relation to the CMSM. METHODS: The study was conducted in East Azerbaijan Province, Islamic Republic of Iran, where no malaria transmission has been reported since 2005. An online tool presenting a suspected malaria case for detection of HCPs' failures in recognition, diagnosis, treatment and reporting was developed based on literature review and expert opinion. A total of 360 HCPs were allocated to two groups. In one group their performance was tested by simulated patient (SP) methodology as gold standard, and one month later by the online tool to allow assessment of its sensitivity. In the other group, they were tested only by the online tool to allow assessment of any possible bias incurred by the exposure to SPs before the tool. RESULTS: The sensitivity of the tool was (98.7%; CI 93.6-99.3). The overall agreement and kappa statistics were 96.6% and 85.6%, respectively. In the group tested by both methods, the failure proportion by SP was 86.1% (CI 80.1-90.8) and by tool 87.2% (CI 81.4-91.7). In the other group, the tool found 85.6% (CI 79.5-90.3) failures. There were no significant differences in detecting failures within or between the groups. CONCLUSION: The SMOT tool not only showed high validity for detecting HCPs' failures in relation to CMSM, but it had high rates of agreement with the real-world situation, where malaria transmission has been interrupted. The tool can be used by program managers to evaluate HCPs' performance and identify sub-groups, whose malaria vigilance should be strengthened. It could also contribute to the evidence base for certification of malaria elimination, and to strengthening prevention of re-establishment of malaria transmission.

Does motor control training improve pain and function in adults with symptomatic lumbar disc herniation? A systematic review and meta-analysis of 861 subjects in 16 trials.

OBJECTIVE: To evaluate the effectiveness of motor control training (MCT) compared with other physical therapist-led interventions, minimal/no intervention or surgery in patients with symptomatic lumbar disc herniation (LDH). DESIGN: Systematic review and meta-analysis. DATA SOURCES: Eight databases and the ClinicalTrials.gov were searched from inception to April 2021. ELIGIBILITY CRITERIA: We included clinical trial studies with concurrent comparison groups which examined the effectiveness of MCT in patients with symptomatic LDH. Primary outcomes were pain intensity and functional status which were expressed as mean difference (MD) and standardised mean difference (SMD), respectively. RESULTS: We screened 6695 articles, of which 16 clinical trials (861 participants) were eligible. Fourteen studies were judged to have high risk of bias and two studies had some risk of bias. In patients who did not undergo surgery, MCT resulted in clinically meaningful pain reduction compared with other physical therapist-led interventions (ie, transcutaneous electrical nerve stimulation (TENS)) at short-term (MD -28.85, -40.04 to -17.66, n=69, studies=2). However, the robustness of the finding was poor. For functional status, a large and statistically significant treatment effect was found in favour of MCT compared with traditional/classic general exercises at long-term (SMD -0.83 to -1.35 to -0.31, n=63, studies=1) and other physical therapist-led interventions (ie, TENS) at short-term (SMD -1.43 to -2.41 to -0.46, n=69, studies=2). No studies compared MCT with surgery. In patients who had undergone surgery, large SMDs were seen. In favour of MCT compared with traditional/classic general exercises (SMD -0.95 to -1.32 to -0.58, n=124, studies=3), other physical therapist-led interventions (ie, conventional treatments; SMD -2.30 to -2.96 to -1.64, n=60, studies=1), and minimal intervention (SMD -1.34 to -1.87 to -0.81, n=68, studies=2) for functional improvement at short-term. The overall certainty of evidence was very low to low. CONCLUSION: At short-term, MCT improved pain and function compared with TENS in patients with symptomatic LDH who did not have surgery. MCT improved function compared with traditional/classic general exercises at long-term in patients who had undergone surgery. However, the results should be interpreted with caution because of the high risk of bias in the majority of studies. PROSPERO REGISTRATION NUMBER: CRD42016038166.

Validity and reliability of the persian version of the world health organization quality of life disabilities module.

This study aimed to assess the validity and reliability of the world health organization quality of life questionnaire for people with intellectual disability (WHOQOL-DIS-ID). This was a cross-sectional study of 118 adults with intellectual disability. Internal consistency and temporal reliability were evaluated using Cronbach's alpha and intraclass correlation coefficient (ICC), respectively. Construct validity of the structure was assessed using confirmatory factor analysis. Multiple linear regression analysis was performed to determine the factors associated with the quality of life. Cronbach's alpha for all, but not for discrimination area, as well as ICC for all questions except for 23 and 6, were higher than 0.7. The variables such as periodic check-up, number of friends, entertainment outside the home, parental separation, physical activity, unmet needs score, caregiver's mental health status, and available facilities were the predictors of QOL. The Persian version of the WHOQOL-DIS-ID shows acceptable validity and reliability.

Seroprevalence of SARS-CoV-2 in Guilan Province, Iran, April 2020.

We determined the seroprevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in an affected area in northern Iran in April 2020. Antibodies to SARS-CoV-2 were detected in 528 persons by using rapid tests. Adjusted prevalence of SARS-CoV-2 seropositivity was 22.2% (95% CI 16.4%-28.5%).

Longitudinal Causal Effects of Normalized Protein Catabolic Rate on All-Cause Mortality in Patients With End-Stage Renal Disease: Adjusting for Time-Varying Confounders Using the G-Estimation Method.

In this study, we aimed to estimate the causal effect of normalized protein catabolic rate (nPCR) on mortality among end-stage renal disease (ESRD) patients in the presence of time-varying confounding affected by prior exposure using g-estimation. Information about 553 ESRD patients was retrospectively collected over an 8-year period (2011-2019) from hemodialysis facilities in Kerman, Iran. nPCR was dichotomized as <1.2 g/kg/day versus ≥1.2 g/kg/day. Then a standard time-varying accelerated failure time (AFT) Weibull model was built, and results were compared with those generated by g-estimation. After appropriate adjustment for time-varying confounders, weighted g-estimation yielded 78% shorter survival time (95% confidence interval (95% CI): -81, -73) among patients with a continuous nPCR <1.2 g/kg/day than among those who had nPCR ≥1.2 g/kg/day during follow-up, though it was 18% (95% CI: -57, 54) in the Weibull model. Moreover, hazard ratio estimates of 4.56 (95% CI: 3.69, 5.37) and 1.20 (95% CI: 0.66, 2.17) were obtained via weighted g-estimation and the Weibull model, respectively. G-estimation indicated that inadequate dietary protein intake characterized by nPCR increases all-cause mortality among ESRD patients, but the Weibull model provided an effect estimate that was substantially biased toward the null.

Estimating the Marginal Causal Effect and Potential Impact of Waterpipe Smoking on Risk of Multiple Sclerosis Using the Targeted Maximum Likelihood Estimation Method: A Large, Population-Based Incident Case-Control Study.

There are few if any reports regarding the role of lifetime waterpipe smoking in the etiology of multiple sclerosis (MS). In a population-based incident case-control study conducted in Tehran, Iran, we investigated the association between waterpipe smoking and MS, adjusted for confounders. Cases (n = 547) were patients aged 15-50 years identified from the Iranian Multiple Sclerosis Society between 2013 and 2015. Population-based controls (n = 1,057) were persons aged 15-50 years recruited through random digit telephone dialing. A doubly robust estimation method, the targeted maximum likelihood estimator (TMLE), was used to estimate the marginal risk ratio and odds ratio for the association between waterpipe smoking and MS. The estimated risk ratio and odds ratio were both 1.70 (95% confidence interval: 1.34, 2.17). The population attributable fraction was 21.4% (95% confidence interval: 4.0, 38.8). Subject to the limitations of case-control studies in interpreting associations causally, these results suggest that waterpipe use, or strongly related but undetermined factors, increases the risk of MS. Further epidemiologic studies, including nested case-control studies, are needed to confirm these findings.

To Adjust or Not to Adjust: The Role of Different Covariates in Cardiovascular Observational Studies.

Covariate adjustment is integral to the validity of observational studies assessing causal effects. It is common practice to adjust for as many variables as possible in observational studies in the hopes of reducing confounding by other variables. However, indiscriminate adjustment for variables using standard regression models may actually lead to biased estimates. In this paper, we differentiate between confounders, mediators, colliders, and effect modifiers. We will discuss that while confounders should be adjusted for in the analysis, one should be wary of adjusting for colliders. Mediators should not be adjusted for when examining the total effect of an exposure on an outcome. Automated statistical programs should not be used to decide which variables to include in causal models. Using a case scenario in cardiology, we will demonstrate how to identify confounders, colliders, mediators and effect modifiers and the implications of adjustment or non-adjustment for each of them.

The causal effect and impact of reproductive factors on breast cancer using super learner and targeted maximum likelihood estimation: a case-control study in Fars Province, Iran.

OBJECTIVES: The relationship between reproductive factors and breast cancer (BC) risk has been investigated in previous studies. Considering the discrepancies in the results, the aim of this study was to estimate the causal effect of reproductive factors on BC risk in a case-control study using the double robust approach of targeted maximum likelihood estimation. METHODS: This is a causal reanalysis of a case-control study done between 2005 and 2008 in Shiraz, Iran, in which 787 confirmed BC cases and 928 controls were enrolled. Targeted maximum likelihood estimation along with super Learner were used to analyze the data, and risk ratio (RR), risk difference (RD), andpopulation attributable fraction (PAF) were reported. RESULTS: Our findings did not support parity and age at the first pregnancy as risk factors for BC. The risk of BC was higher among postmenopausal women (RR = 3.3, 95% confidence interval (CI) = (2.3, 4.6)), women with the age at first marriage ≥20 years (RR = 1.6, 95% CI = (1.3, 2.1)), and the history of oral contraceptive (OC) use (RR = 1.6, 95% CI = (1.3, 2.1)) or breastfeeding duration ≤60 months (RR = 1.8, 95% CI = (1.3, 2.5)). The PAF for menopause status, breastfeeding duration, and OC use were 40.3% (95% CI = 39.5, 40.6), 27.3% (95% CI = 23.1, 30.8) and 24.4% (95% CI = 10.5, 35.5), respectively. CONCLUSIONS: Postmenopausal women, and women with a higher age at first marriage, shorter duration of breastfeeding, and history of OC use are at the higher risk of BC.

A CHecklist for statistical Assessment of Medical Papers (the CHAMP statement): explanation and elaboration.

Misuse of statistics in medical and sports science research is common and may lead to detrimental consequences to healthcare. Many authors, editors and peer reviewers of medical papers will not have expert knowledge of statistics or may be unconvinced about the importance of applying correct statistics in medical research. Although there are guidelines on reporting statistics in medical papers, a checklist on the more general and commonly seen aspects of statistics to assess when peer-reviewing an article is needed. In this article, we propose a CHecklist for statistical Assessment of Medical Papers (CHAMP) comprising 30 items related to the design and conduct, data analysis, reporting and presentation, and interpretation of a research paper. While CHAMP is primarily aimed at editors and peer reviewers during the statistical assessment of a medical paper, we believe it will serve as a useful reference to improve authors' and readers' practice in their use of statistics in medical research. We strongly encourage editors and peer reviewers to consult CHAMP when assessing manuscripts for potential publication. Authors also may apply CHAMP to ensure the validity of their statistical approach and reporting of medical research, and readers may consider using CHAMP to enhance their statistical assessment of a paper.

A note on handling conditional missing values.

In medical research, some variables are conditionally defined on some levels of another variable, leading to conditional missing data. Imputation of this type of structural missing data is needed given inefficiency of listwise deletion inherent in regression modeling. Using some examples, we illustrate handling of conditional missing values using simple imputation procedures in etiologic and prediction research.

Comparison of outcomes between off-pump and on-pump coronary artery bypass graft surgery using collaborative targeted maximum likelihood estimation.

There are some discrepancies about the superiority of the off-pump coronary artery bypass grafting (CABG) surgery over the conventional cardiopulmonary bypass (on-pump). The aim of this study was estimating risk ratio of mortality in the off-pump coronary bypass compared with the on-pump using a causal model known as collaborative targeted maximum likelihood estimation (C-TMLE). The data of the Tehran Heart Cohort study from 2007 to 2020 was used. A collaborative targeted maximum likelihood estimation and targeted maximum likelihood estimation, and propensity score (PS) adjustment methods were used to estimate causal risk ratio adjusting for the minimum sufficient set of confounders, and the results were compared. Among 24,883 participants (73.6% male), 5566 patients died during an average of 8.2 years of follow-up. The risk ratio estimates (95% confidence intervals) by unadjusted log-binomial regression model, PS adjustment, TMLE, and C-TMLE methods were 0.86 (0.78-0.95), 0.88 (0.80-0.97), 0.88 (0.80-0.97), and 0.87(0.85-0.89), respectively. This study provides evidence for a protective effect of off-pump surgery on mortality risk for up to 8 years in diabetic and non-diabetic patients.