Recommendations for the Assessment and Reporting of Multivariable Logistic Regression in Transplantation Literature

Abstract

Multivariable logistic regression is an important method to evaluate risk factors and prognosis in solid organ transplant literature. We aimed to assess the quality of this method in six major transplantation journals. Eleven analytical criteria and four documentation criteria were analyzed for each selected article that used logistic regression. A total of 106 studies (6%) out of 1,701 original articles used logistic regression analyses from January 1, 2005 to January 1, 2006. The analytical criteria and their respective reporting percentage among the six journals were: Linearity (25%); Beta coefficient (48%); Interaction tests (19%); Main estimates (98%); Ovefitting prevention (84%); Goodness-of-fit (3.8%); Multicolinearity (4.7%); Internal validation (3.8%); External validation (8.5%). The documentation criteria were reported as follows: Selection of independent variables (73%); Coding of variables (9%); Fitting procedures (49%); Statistical program (65%). No significant differences were found among different journals or between general versus subspecialty journals with respect to reporting quality. We found that the report of logistic regression is unsatisfactory in transplantation journals. Because our findings may have major consequences for the care of transplant patients and for the design of transplant clinical trials, we recommend a practical solution for the use and reporting of logistic regression in transplantation journals.