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A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease.

ABSTRACT: In clinical trials and observational studies, the effect of an intervention or exposure can be reported as an absolute or relative comparative measure such as risk difference, odds ratio or risk ratio, or at the group level with the estimated risk of disease in each group. For meta-analysis of results with covariate adjustment, the log of the odds ratio (log odds ratio), with its standard error, is a commonly used measure of effect. However, extracting the adjusted log odds ratio from the reported estimates of disease risk in each group is not straightforward. Here, we propose a method to transform the adjusted probability of the event in each group to the log of the odds ratio and obtain the appropriate (approximate) standard error, which can then be used in a meta-analysis. We also use example data to compare our method with two other methods and show that our method is superior in calculating the standard error of the log odds ratio.

SUBMITTER: Hu D

PROVIDER: S-EPMC7053742 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease.

Hu Dapeng D Wang Chong C O'Connor Annette M AM

PloS one 20200303 3

In clinical trials and observational studies, the effect of an intervention or exposure can be reported as an absolute or relative comparative measure such as risk difference, odds ratio or risk ratio, or at the group level with the estimated risk of disease in each group. For meta-analysis of results with covariate adjustment, the log of the odds ratio (log odds ratio), with its standard error, is a commonly used measure of effect. However, extracting the adjusted log odds ratio from the report ...[more]

PMID: 32126072

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Project description:BACKGROUND:Globally, colorectal cancer (CRC) is the third and second leading cancer in men and women respectively with 600,000 deaths per year. Traditionally, clinicians have relied solely on nodal disease involvement, and measurements such as lymph node ratio (LNR; the ratio of metastatic/positive lymph nodes to total number of lymph nodes examined), when determining patient prognosis in CRC. The log odds of positive lymph nodes (LODDS) is a logistic transformation formula that uses pathologic lymph node data to stratify survival differences among patients within a single stage of disease. This formula allows clinicians to identify whether patients with clinically aggressive tumours fall into higher-risk groups regardless of nodal positivity and can potentially guide adjuvant treatment modalities. The aim of this study was to investigate whether LODDS in colon cancer provides better prognostication compared to LNR. METHODS:A retrospective study of patients on the prospectively maintained Cabrini Monash University Department of Surgery colorectal neoplasia database, incorporating data from hospitals in Melbourne Australia, identified patients entered between January 2010 and March 2016. Association of LODDS and LNR with clinical variables were analysed. Disease-free (DFS) and overall (OS) survival were investigated with Cox regression and Kaplan-Meier survival analyses. RESULTS:There were 862 treatment episodes identified in the database (402 male, 47%). The median patient age was 73 (range 22-100?years). There were 799 colonic cancers and 63 rectosigmoid cancers. The lymph node yield (LNY) was suboptimal (<?12) in 168 patients (19.5%) (p?=?0.05). The 5-year OS for the different LNR groups were 86, 91 and 61% (p?<?0.001) for LNR0 (655 episodes), LNR1 (128 episodes) and LNR2 (78 episodes), respectively. For LODDS, they were 85, 91 and 61% (p?<?0.001) in LODDS0 (569 episodes), LODDS1 (217 episodes) and LODDS2 (75 episodes) groups (p?<?0.001). Overall survival rates were comparable between the LNR and LODDS group and for LNY?<?12 and stage III patients when each were sub-grouped by LODDS and LNR. CONCLUSION:This study has shown for that the prognostic impact of LODDS is comparable to LNR for colon cancer patients. Accordingly, LNR is recommended for prognostication given its ease of calculation.

Dataset Information

A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease.

Publications

A method of back-calculating the log odds ratio and standard error of the log odds ratio from the reported group-level risk of disease.

Similar Datasets

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