Statistics odds ratio

If the odds ratio for pattern 1 (joint effect of genotype and drug) is significantly greater than the product of odds ratios for patterns 2 (independent effect of genotype) and pattern 3 (independent effect of drug), then there is evidence for statistical (multiplicative) interaction. This analysis can be carried out in the context of multiple regression analysis by the inclusion of an interaction term. 

Return now to a point made early in this section. Statistical associations, the existence of which cohort and case-control studies can reveal to us, are not, of themselves, evidence of causation. If found, and even if they are strong - large relative risk or odds-ratio - they do not establish that the phenomena being investigated, the phenomena that are associated (disease and some exposure or other factor) are causally related. To see most easily why this is so, it is best to examine the difficulties that need to be overcome to move from association to any conclusion about the existence of a causal link. 

Recent publications on major clinical trials whose implications will involve a recommendation to change clinical practice have included summary statistics that quantify the risk of benefit or harm that may occur if the results of a given trial are strictly applied to an individual patient or to a representative cohort. Four simple calculations will enable the non-statistician to answer the simple question How much better would my chances be (in terms of a particular outcome) if I took this new medicine, than if I did not take it . These calculations are the relative risk reduction, the absolute risk reduction, the number needed to treat, and the odds ratio (see Box 6.3). 

Chapter 3 together with testing hypotheses and the (dreaded ) p-value. Common statistical tests for various data types are developed in Chapter 4 which also covers different ways of measuring treatment effect for binary data, such as the odds ratio and relative risk. 

Sensitivity, specificity, odds ratio, and relative risk Types of data and scales of measurement Measures of central tendency and dispersion Inferential statistics Students s t-distribution Comparing means Comparing more than two means Regression and correlation Nonparametric tests The x2-test Clinical trials INTRODUCTION... 

In a case-control study in the north of Sweden, Hallquist et al. (1993) compared 188 men and women aged 20-70 years who had thyroid cancer with age- and sex-matched controls (two per case) selected from a register of the local population. The cases were identified retrospectively from a cancer registry and excluded a proportion of patients (19%) who had died by the time of the study. Exposure to potential risk factors, including chlorophenols, was ascertained by postal questionnaire with a supplementary telephone interview if answers were incomplete. The response rates for the cases and controls were 95% and 90%, respectively. Of the 171 cases analysed, 107 had papillary tumours. Four cases and three controls reported exposure to chlorophenols (odds ratio, 2.8 95% CI, 0.5-18). [The Working Group noted that the method of statistical analysis was not the most appropriate for individually matched data, but this is unlikely to have produced serious bias.]... 

More innovative methods for examining relationships between individual LOE for the SQT include quantitative estimation of probability derived from odds ratio (Smith et al., 2002) and meta-analysis resulting in pooled, empirically derived P-values (Bailer et al., 2002). Comparison of odds ratio and meta-analysis with PCA for clustering sites into groups of similar impact (Reynoldson et al., 2002a) revealed similarities and differences. The differences between the three methods (PCA, odds ratio and meta-analysis) were ascribed to three factors, which almost certainly apply to all integrations the variables selected the manner in which information is combined within a LOE and, the statistical methodology employed. 

The efficacy of chronic therapy with oral GPIIb/llla inhibitors has been assessed in five major randomized placebo-controlled trials (EXCITE, OPUS, SYMPHONY SYMPHONY II, and BRAVO) (63,64). These agents were associated with a statistically significant increase in mortality in three out of the five trials. A meta-analysis of these trials (n = 45,523) demonstrated a significant increase in mortality (2.8% vs. 2.1% for placebo, odds ratio 1.35, 95% confidence interval 1.15-1.61), mostly... 

Therefore, it is assumed that in near future it will become possible to diagnose the probability of asthma or other diseases of allergic origin, e.g., food allergies, in appropriately equipped clinical laboratories, also by means of screening all SNP and transcriptome information related to the diseases. Nowadays, however, despite extensive research, even the most risky SNP combination related to asthma has only a twofold odds ratio with controls and most SNP research papers deal only with statistical probability (Saito et al., 2003). 

Fergusson et al. (2005) searched the literature and found 702 randomized clinical trials (87,650 patients) comparing SSRIs with either placebo or an active non-SSRI control medication. They found a statistically significant, more than two-fold increased risk of suicide attempts on SSRIs compared to placebo. The odds ratio of suicide attempts in SSRI-treated patients versus placebo patients was 2.28 (p = 0.02) and a 95% confidence interval (Cl) of 1.14-4.55. They also found an increased suicide risk between SSRIs and other medications, excluding tricyclic antidepressants. There was no difference between the SSRIs and tricyclics in suicide risk. Overall, their results documented an association between suicide attempts and the use of SSRIs. ... 

Fig. 18.1. The evolution of the estimates of treatment effect in the UKTIA-Aspirin Trial (Farrell et at. 1991) of high-dose aspirin versus low-dose aspirin versus placebo in patients with transient ischemic attack or minor stroke. The treatment effect (odds ratio) calculated at each point was based on the outcomes at final follow-up for patients randomized to that point (PM Rothwell, unpublished data). The dashed lines represent the level at which the apparent treatment effect approached statistical significance at the p = 0,05 level.

Biomarkers Definitions Working Group 2001 Biomarkers and surrogate endpoints preferred definitions and conceptual framework. Clinical Pharmacology and Therapeutics 69 89-95 Bland J M, Altman D G 2000 Statistical notes. The odds ratio. British Medical Journal 320 1468 Chalmers 11995 What do I want from health research and researchers when I am a patient British Medical Journal 310 1315-1318 Chatellier G et al 1996 The numbers needed to treat a clinically useful nomogram in its proper context. British Medical Journal 312 426-429 Doll R1998 Controlled trials the 1948 watershed. British Medical Journal 317 1217 (and following articles). 

One study has suggested that researchers looking for a connection between aluminium and Alzheimer s disease may have ignored the most important source of aluminium for the average person—foodstuffs that contain aluminium additives (36). The results implied that aluminium, added to such foods as anticaking agents, emulsifiers, thickeners, leaveners, and stabilizers, may have long-term adverse effects on health. However, the small sample size hampers any definitive conclusions, the odds ratios were very unstable, and the study had limited statistical power to rule out random errors. 

Chronic lead nephropathy in moonshiners, more often than not, is accompanied by gout and hypertension, in accord with 19 century descriptions of plumbism and reports from Austraha [1]. A statistically significant odds ratio of 2.4 has been reported for moonshine consumption and end-stage renal disease, suggesting a causal association with lead in fhe absence of symptomatic lead poisoning [31]. 

---