Literature DB >> 20642690

Recommendations for the assessment and reporting of multivariable logistic regression in transplantation literature.

A C Kalil1, J Mattei, D F Florescu, J Sun, R S Kalil.   

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.

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Year:  2010        PMID: 20642690      PMCID: PMC2909008          DOI: 10.1111/j.1600-6143.2010.03141.x

Source DB:  PubMed          Journal:  Am J Transplant        ISSN: 1600-6135            Impact factor:   8.086


  118 in total

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4.  Liver transplantation for adult patients with hepatocellular carcinoma in Korea: comparison between cadaveric donor and living donor liver transplantations.

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Journal:  Liver Transpl       Date:  2005-10       Impact factor: 5.799

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Authors:  Nancy G Kutner; Rebecca Zhang; Huiman Barnhart; Allan J Collins
Journal:  Nephrol Dial Transplant       Date:  2005-07-26       Impact factor: 5.992

6.  Post-operative obesity and cachexia are risk factors for morbidity and mortality after heart transplant: multi-institutional study of post-operative weight change.

Authors:  Kathleen L Grady; David Naftel; Salpy V Pamboukian; O H Frazier; Paul Hauptman; John Herre; Howard Eisen; Frank Smart; Robert Bourge
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Authors:  Kathleen L Grady; David C Naftel; Connie White-Williams; Albert J Bellg; James B Young; Dave Pelegrin; Kim Patton-Schroeder; Jon Kobashigawa; Julie Chait; James K Kirklin; William Piccione; Mary McLeod; Alain Heroux
Journal:  J Heart Lung Transplant       Date:  2005-09       Impact factor: 10.247

8.  Airway vascular changes after lung transplant: potential contribution to the pathophysiology of bronchiolitis obliterans syndrome.

Authors:  Shenna Y Langenbach; Ling Zheng; Tanya McWilliams; Bronwyn Levvey; Bernadette Orsida; Michael Bailey; Trevor J Williams; Gregory I Snell
Journal:  J Heart Lung Transplant       Date:  2005-10       Impact factor: 10.247

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Journal:  Nephrol Dial Transplant       Date:  2005-07-19       Impact factor: 5.992

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Journal:  Ophthalmology       Date:  2013-09-04       Impact factor: 12.079

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Review 6.  Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting.

Authors:  Gary S Collins; Susan Mallett; Omar Omar; Ly-Mee Yu
Journal:  BMC Med       Date:  2011-09-08       Impact factor: 8.775

7.  Solid Organ Transplantation During COVID-19 Pandemic: An International Web-based Survey on Resources' Allocation.

Authors:  Francesco Giovinazzo; Alfonso W Avolio; Federica Galiandro; Alessandro Vitale; Giulio V Dalla Riva; Gianni Biancofiore; Shivani Sharma; Paolo Muiesan; Salvatore Agnes; Patrizia Burra
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8.  Clinicopathologic Features and Risk Factors of Proteinuria in Transplant Glomerulopathy.

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9.  Poor quality in the reporting and use of statistical methods in public health - the case of unemployment and health.

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10.  Prediction of glycaemic control in young children and adolescents with type 1 diabetes mellitus using mixed-effects logistic regression modelling.

Authors:  Michiel Joost van Esdonk; Bonnie Tai; Andrew Cotterill; Bruce Charles; Stefanie Hennig
Journal:  PLoS One       Date:  2017-08-02       Impact factor: 3.240

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