Prognostic Factors Associated with Curing in Patients with Breast Cancer: A Joint Frailty Model
Background: Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the "zero-inflated" nature of the data. Moreover, there often exists a terminal event which may be correlated wi...
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Published in | International journal of preventive medicine Vol. 12; no. 1; p. 9 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
Published |
Iran
Wolters Kluwer India Pvt. Ltd
01.01.2021
Medknow Publications and Media Pvt. Ltd Medknow Publications & Media Pvt. Ltd Wolters Kluwer - Medknow Wolters Kluwer Medknow Publications |
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Online Access | Get full text |
ISSN | 2008-7802 2008-8213 |
DOI | 10.4103/ijpvm.IJPVM_89_19 |
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Abstract | Background: Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the "zero-inflated" nature of the data. Moreover, there often exists a terminal event which may be correlated with the recurrent events. The goal of this study is to extend the application of joint frailty model to identify the prognostic factors associated with curing in patients with breast cancer. Methods: As a prospective study, medical records of women who had been attended to Cancer Research Center, Shahid Beheshti University of Medical Sciences from January 1998 to February 2016 were reviewed. Finally, after an initial review of medical records, 711 patients were included in the study and analyzed. A checklist that included items drawn from the demographic background of patients was provided in the study. Two joint frailty models for zero-inflated recurrent events, combining a logistic model for "structural zero" status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times were performed to identify factors associated with BCS. Results: The mean age of patients was 38.2 years. The numbers of subjects with 1, 2, 3, and 4 recurrent events were 392, 207, 97, and 15, respectively. The median follow-up time was 6.87 years. There were 137 (19.2%) deaths from cancer during the follow-up. Among the 574 patients who were censored, 418 had no tumor recurrence. Thus, there may exist a large portion of "cured" subjects. We can see that the radiation (OR = 6.02, CI = (3.87, 8.61)) and tumor size interaction with radiation (OR = 1.065, CI = (1.002-1.26)) were significant in the cure model (P < 0.05) which means that patients with smaller tumor sizes were more likely to be cured by radiation therapy. Conclusions: Our proposed models can help investigators to evaluate which treatment will result in a higher fraction of cured subjects. This is usually an important research question in biomedical studies. |
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AbstractList | Background: Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the “zero-inflated” nature of the data. Moreover, there often exists a terminal event which may be correlated with the recurrent events. The goal of this study is to extend the application of joint frailty model to identify the prognostic factors associated with curing in patients with breast cancer. Methods: As a prospective study, medical records of women who had been attended to Cancer Research Center, Shahid Beheshti University of Medical Sciences from January 1998 to February 2016 were reviewed. Finally, after an initial review of medical records, 711 patients were included in the study and analyzed. A checklist that included items drawn from the demographic background of patients was provided in the study. Two joint frailty models for zero-inflated recurrent events, combining a logistic model for “structural zero” status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times were performed to identify factors associated with BCS. Results: The mean age of patients was 38.2 years. The numbers of subjects with 1, 2, 3, and 4 recurrent events were 392, 207, 97, and 15, respectively. The median follow-up time was 6.87 years. There were 137 (19.2%) deaths from cancer during the follow-up. Among the 574 patients who were censored, 418 had no tumor recurrence. Thus, there may exist a large portion of “cured” subjects. We can see that the radiation (OR = 6.02, CI = (3.87, 8.61)) and tumor size interaction with radiation (OR = 1.065, CI = (1.002–1.26)) were significant in the cure model (P < 0.05) which means that patients with smaller tumor sizes were more likely to be cured by radiation therapy. Conclusions: Our proposed models can help investigators to evaluate which treatment will result in a higher fraction of cured subjects. This is usually an important research question in biomedical studies. Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the "zero-inflated" nature of the data. Moreover, there often exists a terminal event which may be correlated with the recurrent events. The goal of this study is to extend the application of joint frailty model to identify the prognostic factors associated with curing in patients with breast cancer.BACKGROUNDRecurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the "zero-inflated" nature of the data. Moreover, there often exists a terminal event which may be correlated with the recurrent events. The goal of this study is to extend the application of joint frailty model to identify the prognostic factors associated with curing in patients with breast cancer.As a prospective study, medical records of women who had been attended to Cancer Research Center, Shahid Beheshti University of Medical Sciences from January 1998 to February 2016 were reviewed. Finally, after an initial review of medical records, 711 patients were included in the study and analyzed. A checklist that included items drawn from the demographic background of patients was provided in the study. Two joint frailty models for zero-inflated recurrent events, combining a logistic model for "structural zero" status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times were performed to identify factors associated with BCS.METHODSAs a prospective study, medical records of women who had been attended to Cancer Research Center, Shahid Beheshti University of Medical Sciences from January 1998 to February 2016 were reviewed. Finally, after an initial review of medical records, 711 patients were included in the study and analyzed. A checklist that included items drawn from the demographic background of patients was provided in the study. Two joint frailty models for zero-inflated recurrent events, combining a logistic model for "structural zero" status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times were performed to identify factors associated with BCS.The mean age of patients was 38.2 years. The numbers of subjects with 1, 2, 3, and 4 recurrent events were 392, 207, 97, and 15, respectively. The median follow-up time was 6.87 years. There were 137 (19.2%) deaths from cancer during the follow-up. Among the 574 patients who were censored, 418 had no tumor recurrence. Thus, there may exist a large portion of "cured" subjects. We can see that the radiation (OR = 6.02, CI = (3.87, 8.61)) and tumor size interaction with radiation (OR = 1.065, CI = (1.002-1.26)) were significant in the cure model (P < 0.05) which means that patients with smaller tumor sizes were more likely to be cured by radiation therapy.RESULTSThe mean age of patients was 38.2 years. The numbers of subjects with 1, 2, 3, and 4 recurrent events were 392, 207, 97, and 15, respectively. The median follow-up time was 6.87 years. There were 137 (19.2%) deaths from cancer during the follow-up. Among the 574 patients who were censored, 418 had no tumor recurrence. Thus, there may exist a large portion of "cured" subjects. We can see that the radiation (OR = 6.02, CI = (3.87, 8.61)) and tumor size interaction with radiation (OR = 1.065, CI = (1.002-1.26)) were significant in the cure model (P < 0.05) which means that patients with smaller tumor sizes were more likely to be cured by radiation therapy.Our proposed models can help investigators to evaluate which treatment will result in a higher fraction of cured subjects. This is usually an important research question in biomedical studies.CONCLUSIONSOur proposed models can help investigators to evaluate which treatment will result in a higher fraction of cured subjects. This is usually an important research question in biomedical studies. Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences, manifesting the "zero-inflated" nature of the data. Moreover, there often exists a terminal event which may be correlated with the recurrent events. The goal of this study is to extend the application of joint frailty model to identify the prognostic factors associated with curing in patients with breast cancer. As a prospective study, medical records of women who had been attended to Cancer Research Center, Shahid Beheshti University of Medical Sciences from January 1998 to February 2016 were reviewed. Finally, after an initial review of medical records, 711 patients were included in the study and analyzed. A checklist that included items drawn from the demographic background of patients was provided in the study. Two joint frailty models for zero-inflated recurrent events, combining a logistic model for "structural zero" status (Yes/No) and a joint frailty proportional hazards model for recurrent and terminal event times were performed to identify factors associated with BCS. The mean age of patients was 38.2 years. The numbers of subjects with 1, 2, 3, and 4 recurrent events were 392, 207, 97, and 15, respectively. The median follow-up time was 6.87 years. There were 137 (19.2%) deaths from cancer during the follow-up. Among the 574 patients who were censored, 418 had no tumor recurrence. Thus, there may exist a large portion of "cured" subjects. We can see that the radiation (OR = 6.02, CI = (3.87, 8.61)) and tumor size interaction with radiation (OR = 1.065, CI = (1.002-1.26)) were significant in the cure model ( < 0.05) which means that patients with smaller tumor sizes were more likely to be cured by radiation therapy. Our proposed models can help investigators to evaluate which treatment will result in a higher fraction of cured subjects. This is usually an important research question in biomedical studies. |
Audience | Academic |
Author | Akbari, Mohammad Osmani, Freshteh Hajizadeh, Ebrahim |
AuthorAffiliation | 2 Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran 1 Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran Infectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran |
AuthorAffiliation_xml | – name: 1 Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran – name: 2 Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran – name: Infectious Diseases Research Center, Birjand University of Medical Sciences, Birjand, Iran |
Author_xml | – sequence: 1 givenname: Freshteh surname: Osmani fullname: Osmani, Freshteh organization: Infectious Diseases Research Center, Birjand University of Medical Sciences, Birjand – sequence: 2 givenname: Ebrahim surname: Hajizadeh fullname: Hajizadeh, Ebrahim organization: Department of Biostatistics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran – sequence: 3 givenname: Mohammad surname: Akbari fullname: Akbari, Mohammad organization: Cancer Research Center, Shahid Beheshti University of Medical Sciences, Tehran |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/34084306$$D View this record in MEDLINE/PubMed |
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Cites_doi | 10.1038/nature11412 10.1111/j.1541-0420.2006.00677.x 10.1080/01621459.1989.10478873 10.1198/016214504000001033 10.1186/1477-7819-10-4 10.1093/annonc/mdr129 10.4103/ijpvm.IJPVM_335_17 10.1093/biomet/68.2.373 10.4103/ijpvm.IJPVM_147_17 10.1214/aos/1176345976 10.1111/j.1467-9876.2008.00641.x 10.1016/j.ejca.2012.02.051 10.18637/jss.v047.i04 10.1198/jasa.2009.0004 10.4103/jrms.JRMS_127_18 10.1634/theoncologist.10-90003-20 10.1093/biomet/93.3.627 10.1007/s10549-008-0200-5 |
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Snippet | Background: Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any... Recurrent event data arise frequently in longitudinal medical studies. In many situations, there are a large portion of patients without any recurrences,... |
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StartPage | 9 |
SubjectTerms | Analysis Breast cancer breast neoplasm Cancer Cancer patients Cancer research Cancer therapies Care and treatment cure model Frailty Medical records Medical research Oncology, Experimental Original Prognosis Radiation Radiation therapy survival analysis |
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Title | Prognostic Factors Associated with Curing in Patients with Breast Cancer: A Joint Frailty Model |
URI | http://www.ijpvmjournal.net/article.asp?issn=2008-7802;year=2021;volume=12;issue=1;spage=9;epage=9;aulast=Osmani;type=0 https://www.ncbi.nlm.nih.gov/pubmed/34084306 https://www.proquest.com/docview/2532635058 https://www.proquest.com/docview/2537640921 https://pubmed.ncbi.nlm.nih.gov/PMC8106266 https://doaj.org/article/148970b1478a4b0685108099b61baac6 |
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