Nonselective Nonsteroidal Antiinflammatory Drugs and Cardiovascular Risk: Are They Safe?

2007 ◽  
Vol 41 (7-8) ◽  
pp. 1163-1173 ◽  
Author(s):  
Javier C Waksman ◽  
Aaron Brody ◽  
Scott D Phillips
Keyword(s):  
Cardiovascular Risk ◽  
Significant Risk ◽  
Case Control ◽  
Nonsteroidal Antiinflammatory Drugs ◽  
Double Blind Study ◽  
Case Control Studies ◽  
Antiinflammatory Drugs ◽  
Double Blind ◽  
Nsaid Treatment ◽  
Meta Analyses

Objective: To assess possible cardiovascular risks associated with use of nonselective nonsteroidal antiinflammatory drugs (NSAIDs). Data Sources: Medline and Embase were searched from January 1985 through April 2007 and relevant studies were retrieved. Study Selection and Data Extraction: Peer-reviewed, prospective, double-blind, case–control, and cohort-design studies published in the English language literature were considered eligible for review. Previous meta-analyses and systematic reviews were also analyzed. In total, 17 case–control studies; 9 cohort studies; 1 prospective, double-blind study; 3 meta-analyses; and 1 systematic review of observational studies were identified. Data Synthesis: Three studies were prospective and the remainder consisted of observational, retrospective studies, with most reporting acute fatal or nonfatal myocardial infarction as the cardiovascular endpoint. Among the nonselective NSAIDs, diclofenac appears to pose the highest risk for cardiovascular toxicity; other agents trend toward a neutral effect with respect to cardiovascular risk. Although the data are suggestive, it remains unclear whether naproxen provides protective cardiovascular effects among patients on chronic therapy. Conclusions: Currently available data are insufficient for defining evidence-based clinical guidelines for the use of NSAIDs, and the need for additional research, specifically randomized controlled trials, is evident. Diclofenac demonstrates a significant risk while naproxen appears to pose the lowest, albeit nonsignificant, risk for cardiovascular morbidity. Although the current clinical evidence may not warrant recommending naproxen as the preferred NSAID treatment, it may be prudent to avoid diclofenac for patients with cardiovascular risk factors requiring NSAID treatment.

The Editor's Roundtable: Nonsteroidal Antiinflammatory Drugs and Cardiovascular Risk

2008 ◽  
Vol 102 (8) ◽  
pp. 1046-1055 ◽  
Author(s):  
Vincent E. Friedewald ◽  
Joel S. Bennett ◽  
Milton Packer ◽  
William C. Roberts ◽  
Gary W. Williams
Keyword(s):  
Cardiovascular Risk ◽  
Nonsteroidal Antiinflammatory Drugs ◽  
Antiinflammatory Drugs

scholarly journals Relevance of hMLH1 -93G>A, 655A>G and 1151T>A polymorphisms with colorectal cancer susceptibility: a meta-analysis based on 38 case-control studies

2018 ◽  
Vol 64 (10) ◽  
pp. 942-951 ◽  
Author(s):  
Mohammad Zare ◽  
Jamal Jafari-Nedooshan ◽  
Mohammadali Jafari ◽  
Hossein Neamatzadeh ◽  
Seyed Mojtaba Abolbaghaei ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cancer Susceptibility ◽  
Meta Analysis ◽  
Asian Population ◽  
Case Control ◽  
Biomedical Literature ◽  
Case Control Studies ◽  
Increased Risk ◽  
Comprehensive Search ◽  
Meta Analyses

SUMMARY OBJECTIVE: There has been increasing interest in the study of the association between human mutL homolog 1 (hMLH1) gene polymorphisms and risk of colorectal cancer (CRC). However, results from previous studies are inconclusive. Thus, a meta-analysis was conducted to derive a more precise estimation of the effects of this gene. METHODS: A comprehensive search was conducted in the PubMed, EMBASE, Chinese Biomedical Literature databases until January 1, 2018. Odds ratio (OR) with 95% confidence interval (CI) was used to assess the strength of the association. RESULTS: Finally, 38 case-control studies in 32 publications were identified met our inclusion criteria. There were 14 studies with 20668 cases and 19533 controls on hMLH1 −93G>A, 11 studies with 5,786 cases and 8,867 controls on 655A>G and 5 studies with 1409 cases and 1637 controls on 1151T>A polymorphism. The combined results showed that 655A>G and 1151T>A polymorphisms were significantly associated with CRC risk, whereas −93G>A polymorphism was not significantly associated with CRC risk. As for ethnicity, −93G>A and 655A>G polymorphisms were associated with increased risk of CRC among Asians, but not among Caucasians. More interestingly, subgroup analysis indicated that 655A>G might raise CRC risk in PCR-RFLP and HB subgroups. CONCLUSION: Inconsistent with previous meta-analyses, this meta-analysis shows that the hMLH1 655A>G and 1151T>A polymorphisms might be risk factors for CRC. Moreover, the −93G>A polymorphism is associated with the susceptibility of CRC in Asian population.

scholarly journals Application of Bee Products for Dermatological Problems

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Heidrun Männle ◽  
Karsten Münstedt
Keyword(s):  
Clinical Trials ◽  
Atopic Dermatitis ◽  
Randomized Clinical Trials ◽  
Case Control ◽  
Health Claims ◽  
Wound Infections ◽  
Herpes Viruses ◽  
Case Control Studies ◽  
Meta Analyses ◽  
Cutaneous Warts

Context: Bee products are frequently suggested as possible treatments for dermatological problems by protagonists of apitherapy, which is a discipline within the field of complementary and alternative medicine. Unfortunately, apitherapists do not support their health claims. This review was to identify potential uses of bee products in the field of dermatology. Evidence Acquisition: Randomized and non-randomized clinical trials, case-control studies, systematic reviews, and meta-analyses on the topics were identified using various search engines. Results: Evidence suggests that bee products may be a reasonable treatment option for wound infections, burns, radiodermatitis, infections with herpes viruses, atopic dermatitis, rosacea, scars, cutaneous warts, acne, psoriasis, facial wrinkles, and intertrigo. Conclusions: There are several applications for bee products in the field of dermatology, for instance treatment of wound infections with honey and herpes infections with propolis.

scholarly journals Subgroup analyses to determine cardiovascular risk associated with nonsteroidal antiinflammatory drugs and coxibs in specific patient groups

2008 ◽  
Vol 59 (8) ◽  
pp. 1097-1104 ◽  
Author(s):  
Daniel H. Solomon ◽  
Robert J. Glynn ◽  
Kenneth J. Rothman ◽  
Sebastian Schneeweiss ◽  
Soko Setoguchi ◽  
...  
Keyword(s):  
Cardiovascular Risk ◽  
Nonsteroidal Antiinflammatory Drugs ◽  
Antiinflammatory Drugs ◽  
Specific Patient ◽  
Subgroup Analyses ◽  
Patient Groups

scholarly journals Association of microRNAs genes polymorphisms with arthritis: a systematic review and meta-analysis

2019 ◽  
Vol 39 (7) ◽  
Author(s):  
Yingqi Xiao ◽  
Hui Liu ◽  
Li Chen ◽  
Yang Wang ◽  
Xiang Yao ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Meta Analysis ◽  
Fixed Effect Model ◽  
Case Control ◽  
Cochrane Library ◽  
Random Effects Model ◽  
Inclusion Criteria ◽  
Case Control Studies ◽  
Effect Model ◽  
Meta Analyses

Abstract Objective: To investigate whether microRNAs genes’ polymorphisms are associated with arthritis. Methods: The PubMed, Cochrane Library et al. were systematically searched to identify case–control studies, systematic reviews and meta-analyses. A meta-analysis was performed to calculate odds ratios (ORs), and confidence intervals (CIs) at 95% using fixed-effect model or random-effects model. Results: Twenty-two case–control studies involving 10489 participants fulfilled the inclusion criteria. MiR-146a rs2910164 (G/C) was not significantly associated with the risk of rheumatoid arthritis (RA) in any model. Significant associations were found between miR-146a rs2910164 (G/C) and the risk of psoriatic arthritis (PsA) in the heterozygous model and the dominant model. The heterozygous model showed a significant association between the miR-146a rs2910164 (G/C) polymorphism and ankylosing spondylitis (AS). And there was no significant association of miR-146a rs2910164 (G/C) with risk of juvenile rheumatoid arthritis (JRA) at any model. Additionally, there was a significant association of miR-499 rs3746444 (T/C) with risk of RA at two genetic models, and with a moderate heterogeneity. When subgroup analysis by ethnicity, significant associations were almost found between miR-499 rs3746444 (T/C) and the risk of RA in any model in Caucasian populations, and there is no heterogeneity. Conclusions: The association of miR-146a rs2910164 (G/C) with RA was not found. And there was a significant association between miR-146a rs2910164(G/C) and PsA or AS. MiR-499 rs3746444 (T/C) was associated with RA in Caucasian populations. These findings did not support the genetic association between miR-146a rs2910164 (G/C) and JRA susceptibility, as well as the association of miR-196a-2 rs11614913 (C/T), miR-146a rs2431697, miR-146a rs57095329, miR-149 rs22928323 with arthritis.

scholarly journals Can statistical adjustment guided by causal inference improve the accuracy of effect estimation? A simulation and empirical research based on meta-analyses of case–control studies

2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Ruohua Yan ◽  
Tianyi Liu ◽  
Yaguang Peng ◽  
Xiaoxia Peng
Keyword(s):  
Causal Inference ◽  
Empirical Research ◽  
Case Control ◽  
Case Control Studies ◽  
Simulation Experiments ◽  
Confounding Bias ◽  
Statistical Adjustment ◽  
Adjustment Strategies ◽  
Effect Estimation ◽  
Meta Analyses

Abstract Background Statistical adjustment is often considered to control confounding bias in observational studies, especially case–control studies. However, different adjustment strategies may affect the estimation of odds ratios (ORs), and in turn affect the results of their pooled analyses. Our study is aimed to investigate how to deal with the statistical adjustment in case–control studies to improve the validity of meta-analyses. Methods Three types of adjustment strategies were evaluated including insufficient adjustment (not all preset confounders were adjusted), full adjustment (all confounders were adjusted under the guidance of causal inference), and improper adjustment (covariates other than confounders were adjusted). We carried out a series of Monte Carlo simulation experiments based on predesigned scenarios, and assessed the accuracy of effect estimations from meta-analyses of case–control studies by combining ORs calculated according to different adjustment strategies. Then we used the data from an empirical review to illustrate the replicability of the simulation results. Results For all scenarios with different strength of causal relations, combining ORs that were comprehensively adjusted for confounders would get the most precise effect estimation. By contrast, combining ORs that were not sufficiently adjusted for confounders or improperly adjusted for mediators or colliders would easily introduce bias in causal interpretation, especially when the true effect of exposure on outcome was weak or none. The findings of the simulation experiments were further verified by the empirical research. Conclusions Statistical adjustment guided by causal inference are recommended for effect estimation. Therefore, when conducting meta-analyses of case–control studies, the causal relationship formulated by exposure, outcome, and covariates should be firstly understood through a directed acyclic graph, and then reasonable original ORs could be extracted and combined by suitable methods.

Long-term Effect of Glimepiride and Rosiglitazone on Non-conventional Cardiovascular Risk Factors in Metformin-treated Patients Affected by Metabolic Syndrome: A Randomized, Double-blind Clinical Trial

2005 ◽  
Vol 33 (3) ◽  
pp. 284-294 ◽  
Author(s):  
G Derosa ◽  
AV Gaddi ◽  
L Ciccarelli ◽  
E Fogari ◽  
M Ghelfi ◽  
...  
Keyword(s):  
Risk Factors ◽  
Insulin Resistance ◽  
Metabolic Syndrome ◽  
Cardiovascular Risk ◽  
Plasma Glucose ◽  
Double Blind Study ◽  
Model Assessment ◽  
Rapid Improvement ◽  
Double Blind

We evaluated the effect of glimepiride plus metformin and rosiglitazone plus metformin on glucose, and on cardiovascular risk parameters such as lipoprotein(a) (Lp[a]) and homocysteine (HCT) in patients with type 2 diabetes and metabolic syndrome. Ninety-nine patients in the multicentre, randomized, double-blind study took metformin (1500 mg/day) plus glimepiride (2 mg/day) or rosiglitazone (4 mg/day) for 12 months. Changes in body mass index, glycosylated haemoglobin (HbA1c), Lp(a) and HCT were primary efficacy variables. Fasting plasma glucose (FPG), post-prandial plasma glucose (PPG) and homeostasis model assessment index were also used to assess efficacy. On average, HbA1c decreased by 9.1% and 8.1%, FPG decreased by 7.3% and 10.9%, and PPG decreased by 7.6% and 10.5%, respectively, in the glimepiride and rosiglitazone groups after 12 months. Patients receiving rosiglitazone experienced more rapid improvement in glycaemic control than those on glimepiride, and showed a significant improvement in insulin resistance-related parameters. There was a statistically significant decrease in basal homocysteinaemia in glimepiride-treated patients (−27.3%), but not in rosiglitazone-treated patients. Rosiglitazone plus metformin significantly improved long-term control of insulin resistance-related parameters compared with glimepiride plus metformin, although glimepiride treatment was associated with a slight improvement in cholesterolaemia, not observed in the rosiglitazone-treated patients, and with significant improvements in non-traditional risk factors for cardiovascular disease, such as basal homocysteinaemia and plasma Lp(a) levels.

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