Noorazrul Yahya1, Xin-Jane Chua2, Hanani A Manan3, Fuad Ismail4. 1. Faculty of Health Sciences, The National University of Malaysia, Jalan Raja Muda Aziz, 50300, Kuala Lumpur, Malaysia. azrulyahya@ukm.edu.my. 2. Faculty of Health Sciences, The National University of Malaysia, Jalan Raja Muda Aziz, 50300, Kuala Lumpur, Malaysia. 3. Radiology Department, The National University of Malaysia, Kuala Lumpur, Malaysia. 4. Radiotherapy & Oncology Department, The National University of Malaysia, Kuala Lumpur, Malaysia.
Abstract
PURPOSE: This systematic review evaluates the completeness of dosimetric features and their inclusion as covariates in genetic-toxicity association studies. MATERIALS AND METHODS: Original research studies associating genetic features and normal tissue complications following radiotherapy were identified from PubMed. The use of dosimetric data was determined by mining the statement of prescription dose, dose fractionation, target volume selection or arrangement and dose distribution. The consideration of the dosimetric data as covariates was based on the statement mentioned in the statistical analysis section. The significance of these covariates was extracted from the results section. Descriptive analyses were performed to determine their completeness and inclusion as covariates. RESULTS: A total of 174 studies were found to satisfy the inclusion criteria. Studies published ≥2010 showed increased use of dose distribution information (p = 0.07). 33% of studies did not include any dose features in the analysis of gene-toxicity associations. Only 29% included dose distribution features as covariates and reported the results. 59% of studies which included dose distribution features found significant associations to toxicity. CONCLUSION: A large proportion of studies on the correlation of genetic markers with radiotherapy-related side effects considered no dosimetric parameters. Significance of dose distribution features was found in more than half of the studies including these features, emphasizing their importance. Completeness of radiation-specific clinical data may have increased in recent years which may improve gene-toxicity association studies.
PURPOSE: This systematic review evaluates the completeness of dosimetric features and their inclusion as covariates in genetic-toxicity association studies. MATERIALS AND METHODS: Original research studies associating genetic features and normal tissue complications following radiotherapy were identified from PubMed. The use of dosimetric data was determined by mining the statement of prescription dose, dose fractionation, target volume selection or arrangement and dose distribution. The consideration of the dosimetric data as covariates was based on the statement mentioned in the statistical analysis section. The significance of these covariates was extracted from the results section. Descriptive analyses were performed to determine their completeness and inclusion as covariates. RESULTS: A total of 174 studies were found to satisfy the inclusion criteria. Studies published ≥2010 showed increased use of dose distribution information (p = 0.07). 33% of studies did not include any dose features in the analysis of gene-toxicity associations. Only 29% included dose distribution features as covariates and reported the results. 59% of studies which included dose distribution features found significant associations to toxicity. CONCLUSION: A large proportion of studies on the correlation of genetic markers with radiotherapy-related side effects considered no dosimetric parameters. Significance of dose distribution features was found in more than half of the studies including these features, emphasizing their importance. Completeness of radiation-specific clinical data may have increased in recent years which may improve gene-toxicity association studies.
Authors: Sarah L Kerns; Suman Kundu; Jung Hun Oh; Sandeep K Singhal; Michelle Janelsins; Lois B Travis; Joseph O Deasy; A Cecile J E Janssens; Harry Ostrer; Matthew Parliament; Nawaid Usmani; Barry S Rosenstein Journal: Semin Radiat Oncol Date: 2015-05-15 Impact factor: 5.934
Authors: Sarah L Kerns; Dirk de Ruysscher; Christian N Andreassen; David Azria; Gillian C Barnett; Jenny Chang-Claude; Susan Davidson; Joseph O Deasy; Alison M Dunning; Harry Ostrer; Barry S Rosenstein; Catharine M L West; Søren M Bentzen Journal: Radiother Oncol Date: 2013-08-27 Impact factor: 6.280