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Current Hypertension Reports Nov 2020E-cigarettes (e-cigs) release toxic chemicals known to increase blood pressure (BP) levels. The effects of e-cigs on BP, however, remain unknown. Studying BP may help... (Review)
Review
PURPOSE OF REVIEW
E-cigarettes (e-cigs) release toxic chemicals known to increase blood pressure (BP) levels. The effects of e-cigs on BP, however, remain unknown. Studying BP may help characterize potential cardiovascular risks of short- and long-term e-cig use. We summarized published studies on the association of e-cig use with BP endpoints.
RECENT FINDINGS
Thirteen e-cig trials (12 cross-over designs) and 1 observational study evaluated systolic and diastolic blood pressure (SBP and DBP). All trials included at least one e-cig arm with nicotine, 6 a no-nicotine e-cig arm, and 3 a placebo arm. SBP/DBP increased in most nicotine e-cig arms, in some non-nicotine e-cig arms, and in none of the placebo arms. The observational study followed e-cig users and nonsmokers for 3.5 years with inconsistent findings. The use of e-cigs with and without nicotine may result in short-term elevations of both SBP and DBP. Prospective studies that investigate the long-term cardiovascular impact of e-cig use are needed.
Topics: Blood Pressure; Electronic Nicotine Delivery Systems; Humans; Hypertension; Observational Studies as Topic; Prospective Studies; Vaping
PubMed: 33230755
DOI: 10.1007/s11906-020-01119-0 -
Canadian Journal of Anaesthesia =... May 2017
Topics: Anesthesiology; Humans; Logistic Models; Models, Statistical; Observational Studies as Topic; Regression Analysis; Research Design
PubMed: 28236060
DOI: 10.1007/s12630-017-0833-0 -
Sexual and Reproductive Health Matters 2021Promoting sexual health is a World Health Organization (WHO) priority. Lubricants are widely available and used to improve sexual pleasure and reduce pain during... (Review)
Review
Promoting sexual health is a World Health Organization (WHO) priority. Lubricants are widely available and used to improve sexual pleasure and reduce pain during intercourse. To inform WHO's self-care interventions guideline, we conducted a systematic review of the peer-reviewed literature to answer the question: does use of lubricants during or prior to sex result in improved sexual health and well-being. We searched PubMed, CINAHL, LILACS and EMBASE on 8 July 2020 for effectiveness, values and preferences, and cost data related to commercially available vaginal and anal lubricants. Data were systematically extracted and qualitatively synthesised. Effectiveness evidence was summarised in GRADE evidence profiles. Seven studies met the effectiveness review criteria. Two randomised trials found lubricant use led to improved female sexual well-being and had no impact on incidence of human papillomavirus (moderate certainty evidence). One observational study with gay and bisexual men showed lubricants were associated with increased reports of pain during receptive intercourse and no difference in pain during insertive intercourse, but a reduced degree of pain in both types of intercourse (low/very low certainty evidence). One observational study with female breast cancer survivors found better outcomes of vaginal dryness and dyspareunia with lubricant use (very low certainty evidence). Twenty-one values and preferences studies from diverse populations globally found that most individuals supported lubricant use for reasons of comfort/reduced pain and sexual pleasure. No cost studies were identified. Although evidence is limited, lubricants appear to offer an acceptable approach to improving sexual health and well-being.
Topics: Bisexuality; Coitus; Female; Humans; Lubricants; Male; Observational Studies as Topic; Sexual Behavior; Sexual Health
PubMed: 35315312
DOI: 10.1080/26410397.2022.2044198 -
Pharmacoepidemiology and Drug Safety Apr 2018Observational pharmacoepidemiological studies can provide valuable information on the effectiveness or safety of interventions in the real world, but one major challenge... (Review)
Review
PURPOSE
Observational pharmacoepidemiological studies can provide valuable information on the effectiveness or safety of interventions in the real world, but one major challenge is the existence of unmeasured confounder(s). While many analytical methods have been developed for dealing with this challenge, they appear under-utilized, perhaps due to the complexity and varied requirements for implementation. Thus, there is an unmet need to improve understanding the appropriate course of action to address unmeasured confounding under a variety of research scenarios.
METHODS
We implemented a stepwise search strategy to find articles discussing the assessment of unmeasured confounding in electronic literature databases. Identified publications were reviewed and characterized by the applicable research settings and information requirements required for implementing each method. We further used this information to develop a best practice recommendation to help guide the selection of appropriate analytical methods for assessing the potential impact of unmeasured confounding.
RESULTS
Over 100 papers were reviewed, and 15 methods were identified. We used a flowchart to illustrate the best practice recommendation which was driven by 2 critical components: (1) availability of information on the unmeasured confounders; and (2) goals of the unmeasured confounding assessment. Key factors for implementation of each method were summarized in a checklist to provide further assistance to researchers for implementing these methods.
CONCLUSION
When assessing comparative effectiveness or safety in observational research, the impact of unmeasured confounding should not be ignored. Instead, we suggest quantitatively evaluating the impact of unmeasured confounding and provided a best practice recommendation for selecting appropriate analytical methods.
Topics: Confounding Factors, Epidemiologic; Data Interpretation, Statistical; Humans; Observational Studies as Topic; Pharmacoepidemiology; Research Design
PubMed: 29383840
DOI: 10.1002/pds.4394 -
Statistics in Medicine May 2023Matching is a popular design for inferring causal effect with observational data. Unlike model-based approaches, it is a nonparametric method to group treated and... (Observational Study)
Observational Study
Matching is a popular design for inferring causal effect with observational data. Unlike model-based approaches, it is a nonparametric method to group treated and control subjects with similar characteristics together, hence to re-create a randomization-like scenario. The application of matched design for real world data may be limited by: (1) the causal estimand of interest; (2) the sample size of different treatment arms. We propose a flexible design of matching, based on the idea of template matching, to overcome these challenges. It first identifies the template group which is representative of the target population, then match subjects from the original data to this template group and make inference. We provide theoretical justification on how it unbiasedly estimates the average treatment effect using matched pairs and the average treatment effect on the treated when the treatment group has a bigger sample size. We also propose using the triplet matching algorithm to improve matching quality and devise a practical strategy to select the template size. One major advantage of matched design is that it allows both randomization-based or model-based inference, with the former being more robust. For the commonly used binary outcome in medical research, we adopt a randomization inference framework of attributable effects in matched data, which allows heterogeneous effects and can incorporate sensitivity analysis for unmeasured confounding. We apply our design and analytical strategy to a trauma care evaluation study.
Topics: Humans; Algorithms; Biomedical Research; Causality; Research Design; Sample Size; Observational Studies as Topic
PubMed: 36863006
DOI: 10.1002/sim.9698 -
BMC Medicine Dec 2021There have been ongoing efforts to understand when and how data from observational studies can be applied to clinical and regulatory decision making. The objective of... (Review)
Review
BACKGROUND
There have been ongoing efforts to understand when and how data from observational studies can be applied to clinical and regulatory decision making. The objective of this review was to assess the comparability of relative treatment effects of pharmaceuticals from observational studies and randomized controlled trials (RCTs).
METHODS
We searched PubMed and Embase for systematic literature reviews published between January 1, 1990, and January 31, 2020, that reported relative treatment effects of pharmaceuticals from both observational studies and RCTs. We extracted pooled relative effect estimates from observational studies and RCTs for each outcome, intervention-comparator, or indication assessed in the reviews. We calculated the ratio of the relative effect estimate from observational studies over that from RCTs, along with the corresponding 95% confidence interval (CI) for each pair of pooled RCT and observational study estimates, and we evaluated the consistency in relative treatment effects.
RESULTS
Thirty systematic reviews across 7 therapeutic areas were identified from the literature. We analyzed 74 pairs of pooled relative effect estimates from RCTs and observational studies from 29 reviews. There was no statistically significant difference (based on the 95% CI) in relative effect estimates between RCTs and observational studies in 79.7% of pairs. There was an extreme difference (ratio < 0.7 or > 1.43) in 43.2% of pairs, and, in 17.6% of pairs, there was a significant difference and the estimates pointed in opposite directions.
CONCLUSIONS
Overall, our review shows that while there is no significant difference in the relative risk ratios between the majority of RCTs and observational studies compared, there is significant variation in about 20% of comparisons. The source of this variation should be the subject of further inquiry to elucidate how much of the variation is due to differences in patient populations versus biased estimates arising from issues with study design or analytical/statistical methods.
Topics: Humans; Observational Studies as Topic; Pharmaceutical Preparations; Randomized Controlled Trials as Topic; Research Design
PubMed: 34865623
DOI: 10.1186/s12916-021-02176-1 -
Pharmacoepidemiology and Drug Safety Feb 2018Lack of control for time-varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance... (Review)
Review
PURPOSE
Lack of control for time-varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance on some of the available methodologies used to address problems related to time-varying exposure and confounding in pharmacoepidemiology and other observational studies. The methods are explored from a conceptual rather than an analytical perspective.
METHODS
The methods described in this study have been identified exploring the literature concerning to the time-varying exposure concept and basing the search on four fundamental pharmacoepidemiological problems, construction of treatment episodes, time-varying confounders, cumulative exposure and latency, and treatment switching.
RESULTS
A correct treatment episodes construction is fundamental to avoid bias in treatment effect estimates. Several methods exist to address time-varying covariates, but the complexity of the most advanced approaches-eg, marginal structural models or structural nested failure time models-and the lack of user-friendly statistical packages have prevented broader adoption of these methods. Consequently, simpler methods are most commonly used, including, for example, methods without any adjustment strategy and models with time-varying covariates. The magnitude of exposure needs to be considered and properly modelled.
CONCLUSIONS
Further research on the application and implementation of the most complex methods is needed. Because different methods can lead to substantial differences in the treatment effect estimates, the application of several methods and comparison of the results is recommended. Treatment episodes estimation and exposure quantification are key parts in the estimation of treatment effects or associations of interest.
Topics: Bias; Data Interpretation, Statistical; Drug-Related Side Effects and Adverse Reactions; Humans; Observational Studies as Topic; Pharmacoepidemiology; Practice Guidelines as Topic; Study Guides as Topic; Time Factors; Treatment Outcome
PubMed: 29285840
DOI: 10.1002/pds.4372 -
Medicine Jun 2020To investigate the gene rearrangement and mutation of lymphoma biomarkers including (Immunoglobulin H (IgH), Immunoglobulin kappa (IGK), Immunoglobulin lambda (IGL), and...
INTRODUCTION
To investigate the gene rearrangement and mutation of lymphoma biomarkers including (Immunoglobulin H (IgH), Immunoglobulin kappa (IGK), Immunoglobulin lambda (IGL), and TCR) in the lymphoma diagnosis.
METHODS AND ANALYSIS
Paraffin tissue samples from 240 cases diagnosed as suspected lymphoma in the department of pathology, Deyang City People's Hospital from June 2020 to June 2021 will be enrolled. Deoxyribonucleic acid extraction and Polymerase Chain Reaction (PCR) amplification will be performed in these paraffin tissue samples. Immunoglobulin and T cell receptor (TCR) rearrangement will be analyzed by hetero-double chain gel electrophoresis and BioMed-2 standardized immunoglobulin gene rearrangement detection system. In this study protocol IGH gene rearrangement, IGK gene rearrangement, both IGH and IGL gene rearrangement, both IGH and IGK gene rearrangement, both IGK and IGL gene rearrangement, both IGH, IGK and IGL gene rearrangement, TCR gene rearrangement and positive Ig/TCR rearrangement will be analyzed.
DISCUSSION
In this study, we will use B and T cell lymphoma analysis focusing on IgH, IGK, IGL, and TCR gene rearrangement, so as to provide early guidance for the diagnosis of lymphoma. Second generation sequencing technology is helpful in the differential diagnosis of lymphoma.
TRIAL REGISTRATION
Chinese Clinical trial registry: ChiCTR2000032366.
Topics: Gene Rearrangement; Humans; Lymphoma; Mutation; Observational Studies as Topic; Prospective Studies; Research Design
PubMed: 32541525
DOI: 10.1097/MD.0000000000020733 -
COPD Oct 2018
Topics: Humans; Observational Studies as Topic; Practice Guidelines as Topic; Pulmonary Disease, Chronic Obstructive
PubMed: 30822246
DOI: 10.1080/15412555.2018.1555234 -
Research and Reporting Considerations for Observational Studies Using Electronic Health Record Data.Annals of Internal Medicine Jun 2020Electronic health records (EHRs) are an increasingly important source of real-world health care data for observational research. Analyses of data collected for purposes... (Review)
Review
Electronic health records (EHRs) are an increasingly important source of real-world health care data for observational research. Analyses of data collected for purposes other than research require careful consideration of data quality as well as the general research and reporting principles relevant to observational studies. The core principles for observational research in general also apply to observational research using EHR data, and these are well addressed in prior literature and guidelines. This article provides additional recommendations for EHR-based research. Considerations unique to EHR-based studies include assessment of the accuracy of computer-executable cohort definitions that can incorporate unstructured data from clinical notes and management of data challenges, such as irregular sampling, missingness, and variation across time and place. Principled application of existing research and reporting guidelines alongside these additional considerations will improve the quality of EHR-based observational studies.
Topics: Data Collection; Electronic Health Records; Humans; Observational Studies as Topic; Primary Health Care
PubMed: 32479175
DOI: 10.7326/M19-0873