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Surgery Nov 2022Increasingly, patients with rectal cancer receive nonoperative management. A growing body of retrospective evidence supporting the safety of this approach has likely...
BACKGROUND
Increasingly, patients with rectal cancer receive nonoperative management. A growing body of retrospective evidence supporting the safety of this approach has likely contributed to its growing popularity. However, patients may also undergo nonoperative management because of refusal of surgical resection. We hypothesize that patients who refuse surgery are more likely to be from groups who traditionally face barriers accessing care.
METHODS
We used the National Cancer Database (2006-2017) to analyze patients with nonmetastatic rectal adenocarcinoma who underwent nonoperative management following radiation. We identified 2 groups: (1) planned nonoperative management and (2) nonoperative management because of refusal of surgery. We performed logistic regression to compare the groups along patient, socioeconomic, and facility-level factors.
RESULTS
In total, 9,613 and 2,039 patients were included in the planned nonoperative management and refused nonoperative management groups, respectively. Of the total study cohort (ie, planned nonoperative management + refused nonoperative management), 21% of these patients diagnosed in 2017 underwent refused nonoperative management, versus 12% in 2006. Patients who were Black (adjusted odds ratio 1.47, 95% confidence interval 1.26-1.71) or Asian/Pacific Islander (adjusted odds ratio 1.51, 95% confidence interval 1.18-1.92), age ≥65 years (adjusted odds ratio 1.55, 95% confidence interval 1.37-1.77), with more advanced disease stage (stage III adjusted odds ratio 1.30, 95% confidence interval 1.10-1.53), and government insurance (adjusted odds ratio 1.19, 95% confidence interval 1.04-1.36) were associated with increased utilization of refused nonoperative management. Conversely, lower education (adjusted odds ratio 0.62, 95% confidence interval 0.50-0.76) and female sex (adjusted odds ratio 0.88, 95% confidence interval 0.79-0.97) were associated with planned nonoperative management.
CONCLUSION
Our findings suggest that the refused nonoperative management group is demographically distinct. Outreach efforts to better understand the rationale behind patient decision making in rectal cancer will be paramount to ensuring appropriate implementation of nonoperative management.
Topics: Aged; Cohort Studies; Databases, Factual; Female; Humans; Odds Ratio; Rectal Neoplasms; Retrospective Studies
PubMed: 36031444
DOI: 10.1016/j.surg.2022.05.035 -
Revista Medica de Chile Oct 2013Odds Ratio (OR) is an effect measure frequently used to communicate results of health research. Mathematically, OR is the quotient between two odds, being odds an...
Odds Ratio (OR) is an effect measure frequently used to communicate results of health research. Mathematically, OR is the quotient between two odds, being odds an alternative way to express possibility of occurrence of an outcome or presence of an exposition. From a methodological perspective, OR can be calculated from prospective, retrospective and cross-sectional designs, and under certain conditions it can replace the Relative Risk. Based on a series of questions and examples, this article explains theoretical and methodological grounds underlying the concept of OR, in order to facilitate its interpretation for clinicians and researchers.
Topics: Cross-Sectional Studies; Data Interpretation, Statistical; Humans; Odds Ratio; Prospective Studies; Research Design; Retrospective Studies; Risk
PubMed: 24522363
DOI: 10.4067/S0034-98872013001000014 -
International Journal of Methods in... 2005Misclassification, the erroneous measurement of one or several categorical variables, is a major concern in many scientific fields and particularly in psychiatric... (Review)
Review
Misclassification, the erroneous measurement of one or several categorical variables, is a major concern in many scientific fields and particularly in psychiatric research. Even in rather simple scenarios, unless the misclassification probabilities are very small, a major bias can arise in estimating the degree of association assessed with common measures like the risk ratio and the odds ratio. Only in very special cases--for example, if misclassification takes place solely in one of two binary variables and is independent of the other variable ('non-differential misclassification')--is it guaranteed that the estimates are biased towards the null value (which is 1 for the risk ratio and the odds ratio). Furthermore, misclassification, if ignored, usually leads to confidence intervals that are too narrow. This paper reviews consequences of misclassification. A numerical example demonstrates the problem's magnitude for the estimation of the risk ratio in the easy case where misclassification takes place in the exposure variable, but not in the outcome. Moreover, uncertainty about misclassification can broaden the confidence intervals dramatically. The best way to overcome misclassification is to avoid it by design, but some statistical methods are useful for reducing bias if misclassification cannot be avoided.
Topics: Association; Bias; Classification; Epidemiologic Methods; Epidemiology; Humans; Models, Statistical; Odds Ratio; Probability; Sensitivity and Specificity
PubMed: 16175878
DOI: 10.1002/mpr.20 -
International Journal of Environmental... Feb 2021This study aimed to identify the factors associated with the quality of life of young workers of a Social Work of Industry Unit.
BACKGROUND
This study aimed to identify the factors associated with the quality of life of young workers of a Social Work of Industry Unit.
METHODS
This was a cross-sectional study conducted on 1270 workers. Data were collected using a digital questionnaire built on the KoBoToolbox platform that included the EUROHIS-QOL eight-item index to assess quality of life. Demographic, socioeconomic, behavioral, and clinical variables were considered explanatory. The associations were analyzed using the ordinal logistic regression model at a 5% significance level.
RESULTS
Men and women had a mean quality of life of 31.1 and 29.4, respectively. Workers that rated their health as "very good" had an odds ratio of 7.4 (95% confidence interval (CI) = 5.17-10.81), and those who rated it as "good" had an odds ratio of 2.9 (95% CI = 2.31-3.77). Both these groups of workers were more likely to have higher levels of quality of life as compared to workers with "regular", "poor", or "very poor" self-rated health. Physically active individuals were 30% more likely to have higher levels of quality of life (odds ratio = 1.3; 95% CI = 1.08-1.65). After adjusting the model by gender, age group, marital status, socioeconomic class, self-rated health, nutritional status, and risky alcohol consumption, the odds ratio of active individuals remained stable (odds ratio = 1.3; 95% CI = 1.05-1.66).
CONCLUSIONS
In the present study, self-rated health, physical activity, and gender were associated with young workers' quality of life.
Topics: Cross-Sectional Studies; Exercise; Female; Health Status; Humans; Male; Odds Ratio; Quality of Life; Socioeconomic Factors; Surveys and Questionnaires
PubMed: 33672106
DOI: 10.3390/ijerph18042153 -
Health Services Research Apr 2018We discuss how to interpret coefficients from logit models, focusing on the importance of the standard deviation (σ) of the error term to that interpretation.
OBJECTIVE
We discuss how to interpret coefficients from logit models, focusing on the importance of the standard deviation (σ) of the error term to that interpretation.
STUDY DESIGN
We show how odds ratios are computed, how they depend on the standard deviation (σ) of the error term, and their sensitivity to different model specifications. We also discuss alternatives to odds ratios.
PRINCIPAL FINDINGS
There is no single odds ratio; instead, any estimated odds ratio is conditional on the data and the model specification. Odds ratios should not be compared across different studies using different samples from different populations. Nor should they be compared across models with different sets of explanatory variables.
CONCLUSIONS
To communicate information regarding the effect of explanatory variables on binary {0,1} dependent variables, average marginal effects are generally preferable to odds ratios, unless the data are from a case-control study.
Topics: Data Interpretation, Statistical; Humans; Logistic Models; Odds Ratio
PubMed: 28560732
DOI: 10.1111/1475-6773.12712 -
The Journal of Clinical Psychiatry May 2023Statistics such as the mean difference (MD), standardized mean difference (SMD), relative risk (RR), odds ratio (OR), hazard ratio (HR), and others are meant to be...
Statistics such as the mean difference (MD), standardized mean difference (SMD), relative risk (RR), odds ratio (OR), hazard ratio (HR), and others are meant to be examined along with their 95% confidence intervals (CIs), and their significance can be understood by viewing these CIs as compatibility intervals. The 95% CIs around the MD and SMD are easily understood because they are expressed along a linear scale. The 95% CIs around the RR, OR, and HR are harder to understand because they are expressed along an exponential scale; however, when the numbers are log-transformed, they are linearized, and understanding becomes easy. Another approach to understanding the CIs around the RR, OR, or HR is to examine the reciprocal of the lower limit of the CI; however, because the reciprocal also lies along an exponential scale, this method is inferior to the log-transformation method. These approaches may seem daunting, but the difficulty is an illusion because log transformation or reciprocal transformation takes only a few seconds when a statistical calculator is opened. All terms and concepts are explained with extreme simplification and with the help of examples.
Topics: Humans; Risk; Odds Ratio; Confidence Intervals; Proportional Hazards Models
PubMed: 37256636
DOI: 10.4088/JCP.23f14933 -
International Journal of Epidemiology Feb 2023The risk ratio (RR) is the ratio of the outcome among the exposed to risk of the outcome among the unexposed. This is a simple concept, which makes one wonder why it has...
The risk ratio (RR) is the ratio of the outcome among the exposed to risk of the outcome among the unexposed. This is a simple concept, which makes one wonder why it has not gained the same popularity as the odds ratio. Using logistic regression to estimate the odds ratio is quite common in epidemiology and interpreting the odds ratio as a risk ratio, under the assumption that the outcome is rare, is also common. On one hand, estimating the odds ratio is simple but interpreting it is hard. On the other, estimating the risk ratio is challenging but its interpretation is straightforward. Issues with estimating risk ratio still remain after four decades. These issues include convergence of the algorithm, the choice of regression specification (e.g. log-binomial, Poisson) and many more. Various new computational methods are available which help overcome the issue of convergence and provide doubly robust estimates of RR.
Topics: Humans; Odds Ratio; Logistic Models
PubMed: 36416437
DOI: 10.1093/ije/dyac220 -
Journal of Vascular Surgery. Venous and... Oct 2016The association between pregnancy and the development of varicose veins is uncertain. We aimed to determine whether a history of pregnancy is associated with the... (Meta-Analysis)
Meta-Analysis Review
OBJECTIVE
The association between pregnancy and the development of varicose veins is uncertain. We aimed to determine whether a history of pregnancy is associated with the development of varicose veins.
METHODS
We performed a systematic literature search using the databases of PubMed, Embase, Robert Koch-Institut, and Cochrane Central and the references of included papers. Eligible studies were all epidemiologic observational studies in which the outcome "varicose veins" and pregnancy history were assessed. The quality of each study was evaluated on the basis of the Dutch Cochrane review checklist and by the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) statement. For our meta-analysis, a random effects model was applied to pool odds ratios and 95% confidence intervals across studies.
RESULTS
We found nine eligible studies enrolling 17,109 women. Pregnancy was associated with a significant risk increase in developing varicose veins. The results of our meta-analysis suggest that the odds for women with a history of pregnancy in developing varicose veins significantly increases by 82% (odds ratio, 1.82; 95% CI, 1.43-2.33) compared with women with no history of pregnancy. As expected for epidemiologic observational studies, the heterogeneity was considerably high (I(2) = 81%).
CONCLUSIONS
Our meta-analysis strongly supports the hypothesis that there is a significant and strong association between a history of pregnancy and varicose veins. However, qualitative and quantitative differences among studies were evident and were also reflected in a considerably high heterogeneity.
Topics: Female; Humans; Observational Studies as Topic; Odds Ratio; Pregnancy; Pregnancy Complications; Risk Factors; Varicose Veins
PubMed: 27639009
DOI: 10.1016/j.jvsv.2016.06.003 -
International Journal of Medical... 2022A growing body of literature has demonstrated that circular RNAs (circRNAs) are the potential biomarkers in human cardiovascular disease (CVD). Therefore, a... (Meta-Analysis)
Meta-Analysis Review
A growing body of literature has demonstrated that circular RNAs (circRNAs) are the potential biomarkers in human cardiovascular disease (CVD). Therefore, a meta-analysis based on current studies was accomplished to appraise the role of circRNAs in the diagnostic of CVD patients. Studies before October 30, 2021, were searched using PubMed, EMBASE, the Web of Science, and Cochrane Library. The diagnostic odds ratio (DOR) with a confidence interval (CI) of 95% was used to investigate the associations between circRNAs and CVDs. A total of 27 eligible articles were selected, including 47 studies, with 6833 participants meeting the criteria standard constrain. The pooled overall sensitivity and specificity for circRNAs expression profile in differentiating CVD patients from controls (non-CVDs or healthy subjects) were 0.81 (95%CI 0.78-0.83) and 0.74 (95%CI 0.68-0.78), respectively; the overall positive likelihood ratio was 3.1 (95%CI 2.5-3.7); the negative likelihood ratio was 0.26 (95%CI 0.22-0.31); the overall diagnostic odds ratio corresponding to an area under the curve of 0.85 (95%CI 0.81-0.88) was 12 (95%CI 9-16). Subgroup analysis indicated that the serum rather than blood has higher diagnostic accuracy. Likewise, meta-regression analysis demonstrated that the specimen, detection method, sample size, and publication year were the main sources of heterogeneity. Sensitivity analysis and Deeks' funnel plot revealed that our results are relatively robust. Our evidence-based analysis results suggested that circRNAs provide higher diagnostic accuracy in the prediction of CVDs. Thus, circRNAs might be potential biomarkers in CVDs.
Topics: Biomarkers, Tumor; Cardiovascular Diseases; Humans; Odds Ratio; RNA, Circular; Sensitivity and Specificity
PubMed: 35370465
DOI: 10.7150/ijms.67094 -
Systematic Reviews Feb 2022
Topics: Humans; Odds Ratio; Risk
PubMed: 35151340
DOI: 10.1186/s13643-022-01895-7