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Conference Paper: A Method to Identify Genetic Signature For Radiosensitivity Of Esophagus And To Model Esophagitis

TitleA Method to Identify Genetic Signature For Radiosensitivity Of Esophagus And To Model Esophagitis
Authors
KeywordsBayesian Statistics
Radiosensitivity
NTCP
Issue Date2019
PublisherWiley-Blackwell Publishing, Inc. The Journal's web site is located at http://aapm.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)2473-4209/
Citation
The 2019 American Association of Physics in Medicine (AAPM) 61st Annual Meeting & Exhibition, San Antonio, Texas, USA, 14-17 July 2019. In Medical Physics, 2019, v. 46 n. 6, p. E584, abstract no. PO‐GePV‐T‐48 How to Cite?
AbstractPurpose: To identify single nucleotide polymorphisms (SNPs) signatures for radiosensitivity of esophagus and to model radiation induced esophagitis (ES). Methods: A total of 178 patients with 71 SNPs were included in this study. The end point was set to be ES grade ≥ 2. The dose‐volume‐histogram of esophagus was converted to gEUD for each patient. A logistic NTCP model was used to determine the optimal gEUD and the mean radiosensitivity represented by TD50, the dose having 50% risk of ES. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) was used to assess model accuracy. Combined with a SNPs look‐up table from the distribution of number of patients with/without esophagitis and applied with Bayes’ theorem, the patient‐specific TD50 (TD50‐PS) was generated for individual patient. A model accuracy criterion in combination of the χ2 test was used to identify candidate SNPs to form the SNP signatures. Results: 34% of patients developed the esophagitis with grade ≥ 2. gEUD with a = 20 for α/β=10 (gEUD[a = 20, α/β = 10]) appeared to be the optimal parameter, with TD50 = 63 Gy. Using different model accuracy criteria, we have identified a 4‐SNP signature and a 13‐SNP signature. The accuracy and AUC to predict the risk of ES were 0.69 and 0.74, 0.74 and 0.79, 0.77 and 0.85 respectively, for using gEUD [a = 20, α/β = 10] only, 4‐SNP signature and 13‐SNP signature. Conclusion: We have developed a method to identify SNPs and SNP signatures that contribute to the radiosensitivity of esophagus. The individual radiosensitivity represented by TD50‐ps can be determined. These SNP signatures may not best represent the true genetic signature for radiosensitivity due to limited numbers of patients and SNPs used in this study. The SNP signatures and TD50‐ps can be continuously updated when more data are added.
DescriptionTherapy General ePoster Viewing
Persistent Identifierhttp://hdl.handle.net/10722/293345
ISSN
2020 Impact Factor: 4.071
2020 SCImago Journal Rankings: 1.473

 

DC FieldValueLanguage
dc.contributor.authorYao, H-
dc.contributor.authorWang, W-
dc.contributor.authorBi, N-
dc.contributor.authorJolly, S-
dc.contributor.authorFu, P-
dc.contributor.authorJin, J-
dc.contributor.authorKong, FP-
dc.date.accessioned2020-11-23T08:15:24Z-
dc.date.available2020-11-23T08:15:24Z-
dc.date.issued2019-
dc.identifier.citationThe 2019 American Association of Physics in Medicine (AAPM) 61st Annual Meeting & Exhibition, San Antonio, Texas, USA, 14-17 July 2019. In Medical Physics, 2019, v. 46 n. 6, p. E584, abstract no. PO‐GePV‐T‐48-
dc.identifier.issn0094-2405-
dc.identifier.urihttp://hdl.handle.net/10722/293345-
dc.descriptionTherapy General ePoster Viewing-
dc.description.abstractPurpose: To identify single nucleotide polymorphisms (SNPs) signatures for radiosensitivity of esophagus and to model radiation induced esophagitis (ES). Methods: A total of 178 patients with 71 SNPs were included in this study. The end point was set to be ES grade ≥ 2. The dose‐volume‐histogram of esophagus was converted to gEUD for each patient. A logistic NTCP model was used to determine the optimal gEUD and the mean radiosensitivity represented by TD50, the dose having 50% risk of ES. The receiver operating characteristic (ROC) curve with the area under the curve (AUC) was used to assess model accuracy. Combined with a SNPs look‐up table from the distribution of number of patients with/without esophagitis and applied with Bayes’ theorem, the patient‐specific TD50 (TD50‐PS) was generated for individual patient. A model accuracy criterion in combination of the χ2 test was used to identify candidate SNPs to form the SNP signatures. Results: 34% of patients developed the esophagitis with grade ≥ 2. gEUD with a = 20 for α/β=10 (gEUD[a = 20, α/β = 10]) appeared to be the optimal parameter, with TD50 = 63 Gy. Using different model accuracy criteria, we have identified a 4‐SNP signature and a 13‐SNP signature. The accuracy and AUC to predict the risk of ES were 0.69 and 0.74, 0.74 and 0.79, 0.77 and 0.85 respectively, for using gEUD [a = 20, α/β = 10] only, 4‐SNP signature and 13‐SNP signature. Conclusion: We have developed a method to identify SNPs and SNP signatures that contribute to the radiosensitivity of esophagus. The individual radiosensitivity represented by TD50‐ps can be determined. These SNP signatures may not best represent the true genetic signature for radiosensitivity due to limited numbers of patients and SNPs used in this study. The SNP signatures and TD50‐ps can be continuously updated when more data are added.-
dc.languageeng-
dc.publisherWiley-Blackwell Publishing, Inc. The Journal's web site is located at http://aapm.onlinelibrary.wiley.com/hub/journal/10.1002/(ISSN)2473-4209/-
dc.relation.ispartofMedical Physics-
dc.relation.ispartofThe 2019 American Association of Physics in Medicine (AAPM) 61st Annual Meeting & Exhibition-
dc.subjectBayesian Statistics-
dc.subjectRadiosensitivity-
dc.subjectNTCP-
dc.titleA Method to Identify Genetic Signature For Radiosensitivity Of Esophagus And To Model Esophagitis-
dc.typeConference_Paper-
dc.identifier.emailKong, FP: kong0001@hku.hk-
dc.identifier.authorityKong, FP=rp02508-
dc.description.natureabstract-
dc.identifier.hkuros320037-
dc.identifier.volume46-
dc.identifier.issue6-
dc.identifier.spageE584, abstract no. PO‐GePV‐T‐48-
dc.identifier.epageE584, abstract no. PO‐GePV‐T‐48-
dc.publisher.placeUnited States-
dc.identifier.partofdoi10.1002/mp.13589-
dc.identifier.issnl0094-2405-

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