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Odds ratio (OR) is a statistic commonly encountered in professional or scientific medical literature. Most readers perceive it as relative risk (RR), although most of them do not know why that would be true. But since such perception is mostly correct, there is nothing (or almost nothing) wrong with that. It is nevertheless useful to be reminded no...
Citations
... Together with hazard ratios, incidence rate ratios, and risk ratios, they were summarized by metaanalysis to obtain pooled RRs 97 . In addition, we mainly focused on PM 2.5 and NO 2 , as the number of studies on other air pollutants was limited (n ≤ 3 for individual urologic cancer type) 98 . For each pollutant, we calculated the pooled RRs by the study-specific estimates using a random-effects model, which is the most conservative approach in this setting as it incorporates within-and between-study heterogeneity in the CI 92 . ...
Exposure to ambient air pollution has significant adverse health effects; however, whether air pollution is associated with urological cancer is largely unknown. We conduct a systematic review and meta-analysis with epidemiological studies, showing that a 5 μg/m³ increase in PM2.5 exposure is associated with a 6%, 7%, and 9%, increased risk of overall urological, bladder, and kidney cancer, respectively; and a 10 μg/m³ increase in NO2 is linked to a 3%, 4%, and 4% higher risk of overall urological, bladder, and prostate cancer, respectively. Were these associations to reflect causal relationships, lowering PM2.5 levels to 5.8 μg/m³ could reduce the age-standardized rate of urological cancer by 1.5 ~ 27/100,000 across the 15 countries with the highest PM2.5 level from the top 30 countries with the highest urological cancer burden. Implementing global health policies that can improve air quality could potentially reduce the risk of urologic cancer and alleviate its burden.
... When case incidence is low IRR OR and HR is fair approximation of RR [61,62]. Thus, in pooled analyses, we used RRs as the common relationship metric with small intervals and conditional probabilities in mind [63]. Since most studies employed linear models, we determined the standardized relative risk (RR) for each study, assuming a linear exposure-outcome association, using the formula below [62,64]. ...
... Each study reported a different type of relative risk, such as RR, hazard ratio (HR), or odds ratio (OR). In our meta-analysis, HRs were considered RRs [15,16], and ORs were converted to RRs using the method described by Zhang and Yu, which uses OR and the incidence of mortality in the control group [17]. The studies that reported OR Content courtesy of Springer Nature, terms of use apply. ...
Purpose
The increased use of proton pump inhibitors (PPIs) in the elderly has raised concerns about potential severe adverse effects. Our systematic review investigated the mortality associated with PPI use in elderly populations.
Methods
We searched MEDLINE, EMBASE, and the Cochrane Library for relevant publications until August 2022. We included randomized controlled trials (RCTs), quasi-RCTs, and observational studies on the association between proton pump inhibitors and mortality in the elderly. To estimate the pooled relative risk (RR) and 95% confidence interval (CI), the inverse-variance random effect model was used. Heterogeneity was assessed using the I² test. Subgroup analyses were performed by follow-up period, population, and study design.
Results
A total of 4 RCTs and 36 cohort studies were included in the meta-analysis. Four RCTs showed that there was no significant association between PPIs and the risk of death. From 23 observational studies (26 cohorts), the use of proton pump inhibitors was not significantly associated with increased mortality in the elderly (RR 1.14; 95% CI, 0.90–1.45). However, when controlling for covariates from 33 observational studies (41 cohorts), proton pump inhibitors in older adults aged 50 years or more were significantly associated with a 15% higher risk of mortality compared to nonusers (RR 1.15; 95% CI, 1.10–1.20).
Conclusions
Our meta-analysis of RCTs found that PPIs did not show a significant association with increased mortality risk in older adults. However, the meta-analysis of cohort studies and long-term follow-up studies showed a higher increased risk of death with PPI use in older adults. The prescription of PPIs in patients aged 50 years or older should be carefully considered.
... In the subgroup analyses, we combined studies with OR, HR and RR to ensure an adequate number of studies in each subgroup and estimated PRR as we considered HR and OR to be approximate measures of risk ratios given the low COVID-19 mortality rate globally. 33 34 We applied random-effects meta-analysis using a restricted maximum likelihood method 35 36 and a Hartung-Knapp-Sidik-Jonkman (HKSJ) adjustment to the standard errors to account for the uncertainty in residual heterogeneity. [37][38][39] We further applied an ad hoc Knapp-Hartung method to ensure that the HKSJadjusted SEs were appropriate given the unadjusted SEs. ...
Introduction
Despite a growing body of scholarly research on the risks of severe COVID-19 associated with diabetes, hypertension and obesity, there is a need for estimating pooled risk estimates with adjustment for confounding effects. We conducted a systematic review and meta-analysis to estimate the pooled adjusted risk ratios of diabetes, hypertension and obesity on COVID-19 mortality.
Methods
We searched 16 literature databases for original studies published between 1 December 2019 and 31 December 2020. We used the adapted Newcastle-Ottawa Scale to assess the risk of bias. Pooled risk ratios were estimated based on the adjusted effect sizes. We applied random-effects meta-analysis to account for the uncertainty in residual heterogeneity. We used contour-funnel plots and Egger’s test to assess possible publication bias.
Results
We reviewed 34 830 records identified in literature search, of which 145 original studies were included in the meta-analysis. Pooled adjusted risk ratios were 1.43 (95% CI 1.32 to 1.54), 1.19 (95% CI 1.09 to 1.30) and 1.39 (95% CI 1.27 to 1.52) for diabetes, hypertension and obesity (body mass index ≥30 kg/m ² ) on COVID-19 mortality, respectively. The pooled adjusted risk ratios appeared to be stronger in studies conducted before April 2020, Western Pacific Region, low- and middle-income countries, and countries with low Global Health Security Index scores, when compared with their counterparts.
Conclusions
Diabetes, hypertension and obesity were associated with an increased risk of COVID-19 mortality independent of other known risk factors, particularly in low-resource settings. Addressing these chronic diseases could be important for global pandemic preparedness and mortality prevention.
PROSPERO registration number
CRD42021204371.
... The effect indicators of the study are the absolute risk of the outcome, the probability of occurrence, rather than relative risk indicators such as relative risk (RR), odds ratio (OR) or hazard ratio (HR) [13] as shown in Figure 3 [11]. ...
... From the identified studies, we restricted the analysis to articles including the information of OR/RR/HR with 95% CI and using non-antidepressant users as the comparator. HR is broadly equivalent to RR [32], and OR provides a reasonable approximation of RR in case-control studies and cohort studies in which the outcome occurs in less than 10% of the unexposed population [33]. We therefore approximated RR with the OR/RR/HR values adjusted for the most covariates from the included articles and pooled them using RevMan. ...
Depression, commonly treated with antidepressants, is associated with an increased risk of dementia, especially in older adults. However, the association between antidepressant use and dementia risk is unclear. We searched for randomized controlled trials and observational studies from PubMed, Embase, and Cochrane on 1 February 2022, restricting to full texts in English. Since dementia is a chronic disease requiring a long induction time, we restricted studies with ≥1 year follow-up. We extracted the relative risk (RR) adjusted for the most variables from each study and evaluated the heterogeneity using I square (I2). The protocol was registered in the PROSPERO International Register of Systematic Reviews (CRD42022338038). We included six articles in the systematic review, of which the sample size ranged from 716 to 141,740, and the median length of follow-up was 5 years. The pooled RR was 1.21 (95% CI = 1.12–1.29) with an I2 of 71%. Our findings suggest that antidepressant use was associated with an increased risk of dementia in older adults with depression, yet moderate to high heterogeneity existed across studies. Future work accounting for the depression progression is needed to differentiate the effect of depression and antidepressants on dementia risk.
... Regarding gynecological cancers, we studied breast and ovarian cancer separately since they are influenced by different risk factors and have different prevalence rates; breast cancer is more prevalent than ovarian cancer (17). The reported relative risk (RR) and odds ratios (OR) were both included in the meta-analysis (26). However, when studies reported the hazard ratio (HR), it was converted to RR using the following formula: RR = (1 -eHRln(1 -r))/r (26). ...
... The reported relative risk (RR) and odds ratios (OR) were both included in the meta-analysis (26). However, when studies reported the hazard ratio (HR), it was converted to RR using the following formula: RR = (1 -eHRln(1 -r))/r (26). ...
Background
Alcohol consumption is related to the risk of developing different types of cancer. However, unlike other alcoholic beverages, moderate wine drinking has demonstrated a protective effect on the risk of developing several types of cancer.
Objective
To analyze the association between wine consumption and the risk of developing cancer.
Methods
We searched the MEDLINE (through PubMed), Scopus, Cochrane, and Web of Science databases to conduct this systematic review and meta-analysis. Pooled relative risks (RRs) were calculated using the DerSimonian and Laird methods. I2 was used to evaluate inconsistency, the τ2 test was used to assess heterogeneity, and The Newcastle-Ottawa Quality Assessment Scale were applied to evaluate the risk of bias. This study was previously registered in PROSPERO, with the registration number CRD42022315864.
Results
Seventy-three studies were included in the systematic review, and 26 were included in the meta-analysis. The pooled RR for the effect of wine consumption on the risk of gynecological cancers was 1.03 (95% CI: 0.99, 1.08), that for colorectal cancer was 0.92 (95% CI: 0.82, 1.03), and that for renal cancer was 0.92 (95% CI: 0.81, 1.04). In general, the heterogeneity was substantial.
Conclusion
The study findings reveal no association between wine consumption and the risk of developing any type of cancer. Moreover, wine drinking demonstrated a protective trend regarding the risk of developing pancreatic, skin, lung, and brain cancer as well as cancer in general.
Systematic review registration
https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022315864, identifier CRD42022315864 (PROSPERO).
... Subgroup analyses were also conducted to investigate the relationship between aspirin use and risk of PCa incidence and mortality based on study region, study design, type of dose, and type of diagnosis. HRs were directly considered as RRs [34,35], and ORs were transformed into RRs, if necessary, with this formula: RR = OR/((1-P 0 ) + (P 0 × OR)), in which P 0 is the incidence of the outcome of interest in the non-exposed group [36]. The standard error (SE) of the resulting converted RR was then determined with the following formula: SElog(RR) = SElog(OR) × log(RR)/log(OR), which could also be used to calculate the upper and lower limits of the CI by applying this formula to the upper and lower confidence limits of the adjusted odds ratio [37]. ...
Purpose
Aspirin has been suggested to reduce the risk of cancer. However, previous studies have been inconsistent regarding the relationship between aspirin use and the risk of occurrence of prostate cancer (PCa). The purpose of this study was to assess the effect of aspirin on clinical outcomes in patients with PCa in a meta-analysis and to explore the possible dose-response relationship.
Methods
A systematic literature search was conducted in 10 electronic databases and 4 registries. The combined relative risks (RRs) were calculated using a random-effects model with 95% confidence interval (CIs) to assess the effect of aspirin on the risk of PCa. Relevant subgroup analyses and sensitivity analyses were performed.
Results
The across studies results show that aspirin use associated with lower incidence of PCa (RR: 0.96, 95% CI: 0.95–0.98), and reduced mortality (RR: 0.88, 95% CI: 0.82–0.95). The results of the subgroup analysis indicated that both cohort and population studies in the Americas showed a reduction in PCa incidence and mortality with aspirin use. A linear correlation was observed between dosage/duration of aspirin use and its protective effect. Additionally, post-diagnosis aspirin use was associated with decreased risk of PCa mortality.
Conclusions
This meta-analysis revealed an independent correlation between the use of aspirin and reductions in both the incidence and mortality rates of PCa. However, randomized controlled trials did not find any association between aspirin use and PCa. Furthermore, the impact of aspirin on PCa occurrence was found to be dependent on both dosage and duration.
... In doing so, we employed the cohort number size and repurposed it according to the distribution of the person-time data per group, following in that case a cautious approach based on a uniform distribution assumption. In one case, we made use of a mortality study providing hazard ratios instead of RRs, while considering the limitations pointed out by Stare and Maucort-Boulch (2016) in employing the former measure at the place of the latter. ...
Benchmark dose (BMD) methodology has been employed as a default dose–response modeling approach to determine the toxicity value of chemicals to support regulatory chemical risk assessment. Especially, a relatively standardized BMD analysis framework has been established for modeling toxicological data regarding the formats of input data, dose–response models, definitions of benchmark response, and model uncertainty consideration. However, the BMD approach has not been well developed for epidemiological data mainly because of the diverse designs of epidemiological studies and various formats of data reported in the literature. Although most of the epidemiological BMD analyses were developed to solve a particular question, the methods proposed in two recent studies are able to handle cohort and case–control studies using summary data with consideration of adjustments for confounders. Therefore, the purpose of the present study is to investigate and compare the “effective count”‐based BMD modeling approach and adjusted relative risk (RR)‐based BMD analysis approach to identify an appropriate BMD modeling framework that can be generalized for analyzing published data of prospective cohort studies for BMD analysis. The two methods were applied to the same set of studies that investigated the association between bladder and lung cancer and inorganic arsenic exposure for BMD estimation. The results suggest that estimated BMDs and BMDLs are relatively consistent; however, with the consideration of established common practice in BMD analysis, modeling adjusted RR values as continuous data for BMD estimation is a more generalizable approach harmonized with the BMD approach using toxicological data.
... Relative risks (RRs) and the corresponding 95% confidence intervals (CIs) were retrieved or calculated using frequency distributions. Considering the prevalence rate of PCa in the public, we believed that the odds ratio was close to the RR [27,28]. Hazard ratios (HRs) and RRs are different, HRs contain temporal information but RRs do not [28]. ...
... Considering the prevalence rate of PCa in the public, we believed that the odds ratio was close to the RR [27,28]. Hazard ratios (HRs) and RRs are different, HRs contain temporal information but RRs do not [28]. We converted HRs to RRs based on the formula provided by Shor E et al. [29], and the corresponding 95% CIs were converted using the same method. ...
Background:
Association of cigarette smoking habits with the risk of prostate cancer is still a matter of debate. This systematic review and meta-analysis aimed to assess the association between cigarette smoking and prostate cancer risk.
Methods:
We conducted a systematic search on PubMed, Embase, Cochrane Library, and Web of Science without language or time restrictions on June 11, 2022. Literature search and study screening were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. Prospective cohort studies that assessed the association between cigarette smoking habits and the risk of prostate cancer were included. Quality assessment was conducted using the Newcastle-Ottawa Scale. We used random-effects models to obtain pooled estimates and the corresponding 95% confidence intervals.
Results:
A total of 7296 publications were screened, of which 44 cohort studies were identified for qualitative analysis; 39 articles comprising 3 296 398 participants and 130 924 cases were selected for further meta-analysis. Current smoking had a significantly reduced risk of prostate cancer (RR, 0.74; 95% CI, 0.68-0.80; P < 0.001), especially in studies completed in the prostate-specific antigen screening era. Compared to former smokers, current smokers had a significant lower risk of PCa (RR, 0.70; 95% CI, 0.65-0.75; P < 0.001). Ever smoking showed no association with prostate cancer risk in overall analyses (RR, 0.96; 95% CI, 0.93-1.00; P = 0.074), but an increased risk of prostate cancer in the pre-prostate-specific antigen screening era (RR, 1.05; 95% CI, 1.00-1.10; P = 0.046) and a lower risk of prostate cancer in the prostate-specific antigen screening era (RR, 0.95; 95% CI, 0.91-0.99; P = 0.011) were observed. Former smoking did not show any association with the risk of prostate cancer.
Conclusions:
The findings suggest that the lower risk of prostate cancer in smokers can probably be attributed to their poor adherence to cancer screening and the occurrence of deadly smoking-related diseases, and we should take measures to help smokers to be more compliant with early cancer screening and to quit smoking.
Trial registration:
This study was registered on PROSPERO (CRD42022326464).
