Indian Journal of Cancer
Home  ICS  Feedback Subscribe Top cited articles Login 
Users Online :407
Small font sizeDefault font sizeIncrease font size
Navigate Here
 »   Next article
 »   Previous article
 »   Table of Contents

Resource Links
 »   Similar in PUBMED
 »  Search Pubmed for
 »  Search in Google Scholar for
 »Related articles
 »   Citation Manager
 »   Access Statistics
 »   Reader Comments
 »   Email Alert *
 »   Add to My List *
 * Requires registration (Free)
 

 Article Access Statistics
    Viewed199    
    Printed8    
    Emailed0    
    PDF Downloaded36    
    Comments [Add]    

Recommend this journal

 

 ORIGINAL ARTICLE
Year : 2019  |  Volume : 56  |  Issue : 1  |  Page : 24-28

Multiple logistic regression analysis predicts cancer risk among tobacco usage with glutathione S-transferase p1 genotyping in patients with head and neck cancer


1 Department of Human Genetics, Andhra University, Visakhapatnam, Andhra Pradesh, India
2 School of Biotechnology, Mahatma Gandhi National Institute of Research and Social Action, Gaganmahal Road, Domalguda, Hyderabad, Telangana, India

Correspondence Address:
Natukula Kirmani
School of Biotechnology, Mahatma Gandhi National Institute of Research and Social Action, Gaganmahal Road, Domalguda, Hyderabad, Telangana
India
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijc.IJC_277_17

Rights and Permissions

INTRODUCTION: Numerous studies have been investigated to understand the association between glutathione S-transferase P1 (GSTP1) polymorphism and risk of head and neck cancer (HNC) but yielded contradictory results, and no studies could confirm polymorphism in GSTP1 and that tobacco usage increases the risk of HNCs. Therefore, this study aimed to understand the association of GSTP1 Ile105Val polymorphism with or without tobacco usage in carcinogenesis and clinicopathological characteristics of patients with HNC. MATERIALS AND METHODS: Binary logistic regression analysis was performed to predict HNC risk with tobacco use and GSTP1 genotyping. Five predictor variables such as gender, age, tobacco usage, familial, and GSTP1 genotypes were included in the model. RESULTS: The results of the logistic regression analysis show that the full model which considered all the five independent variables together was statistically significant, log-likelihood = −111.820, and all slopes are zero: G = 74.297, degree of freedom (DF) = 5, P = 0.000. The strongest predictor in this model is tobacco usage (odds ratio = Z = −5.16, P = 0.000). CONCLUSION: The study concludes that multiple logistic regression analysis model could predict the risk factors in case–control studies where control samples are compromised.






[FULL TEXT] [PDF]*


        
Print this article     Email this article

  Site Map | What's new | Copyright and Disclaimer
  Online since 1st April '07
  © 2007 - Indian Journal of Cancer | Published by Wolters Kluwer - Medknow