Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression
Background: The analysis of disease-free survival and related factors leads to a better understanding of the patient’s condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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SAGE Publishing
2022-06-01
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| Series: | Breast Cancer: Basic and Clinical Research |
| Online Access: | https://doi.org/10.1177/11782234221108058 |
| _version_ | 1811329795707895808 |
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| author | Akram Yazdani Shahpar Haghighat |
| author_facet | Akram Yazdani Shahpar Haghighat |
| author_sort | Akram Yazdani |
| collection | DOAJ |
| description | Background: The analysis of disease-free survival and related factors leads to a better understanding of the patient’s condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model. Methods: This retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer. Results: Disease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment ( P value < .001). In the examination of the tumor size, the 10th and 20th percentiles of disease-free survival for patients with tumor size > 5 cm were 31.06 and 27 months less than patients with the tumor size < 2 cm, respectively ( P value = .006 and .021, respectively). Compared with grade 1 tumors, the 10th and 20th percentiles of disease-free survival for patients with grade 3 tumors decreased 30.11 and 38.32 months, respectively ( P value < .001 and .038, respectively). The 10th and 20th percentiles of disease-free survival decreased 28.16 and 45.32 months with a 1 unit increase in lymph node ratio, respectively ( P value = .032 and .032, respectively). Conclusions: Among the prognostic factors, tumor size, grade, and lymph node ratio showed a close relationship with disease-free survival in breast cancer. The findings indicated that developing public screening and educational programs through the health care system with more emphasis on low-educated women is needed among Iranian women. |
| first_indexed | 2024-04-13T15:51:27Z |
| format | Article |
| id | doaj.art-d65fab7d284c4e239d0c3926bbe47c27 |
| institution | Directory Open Access Journal |
| issn | 1178-2234 |
| language | English |
| last_indexed | 2024-04-13T15:51:27Z |
| publishDate | 2022-06-01 |
| publisher | SAGE Publishing |
| record_format | Article |
| series | Breast Cancer: Basic and Clinical Research |
| spelling | doaj.art-d65fab7d284c4e239d0c3926bbe47c272022-12-22T02:40:51ZengSAGE PublishingBreast Cancer: Basic and Clinical Research1178-22342022-06-011610.1177/11782234221108058Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile RegressionAkram Yazdani0Shahpar Haghighat1Department of Biostatistics and Epidemiology, School of Public Health, Kashan University of Medical Sciences, Kashan, IranBreast Cancer Research Center, Motamed Cancer Institute, ACECR, Tehran, IranBackground: The analysis of disease-free survival and related factors leads to a better understanding of the patient’s condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model. Methods: This retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer. Results: Disease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment ( P value < .001). In the examination of the tumor size, the 10th and 20th percentiles of disease-free survival for patients with tumor size > 5 cm were 31.06 and 27 months less than patients with the tumor size < 2 cm, respectively ( P value = .006 and .021, respectively). Compared with grade 1 tumors, the 10th and 20th percentiles of disease-free survival for patients with grade 3 tumors decreased 30.11 and 38.32 months, respectively ( P value < .001 and .038, respectively). The 10th and 20th percentiles of disease-free survival decreased 28.16 and 45.32 months with a 1 unit increase in lymph node ratio, respectively ( P value = .032 and .032, respectively). Conclusions: Among the prognostic factors, tumor size, grade, and lymph node ratio showed a close relationship with disease-free survival in breast cancer. The findings indicated that developing public screening and educational programs through the health care system with more emphasis on low-educated women is needed among Iranian women.https://doi.org/10.1177/11782234221108058 |
| spellingShingle | Akram Yazdani Shahpar Haghighat Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression Breast Cancer: Basic and Clinical Research |
| title | Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression |
| title_full | Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression |
| title_fullStr | Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression |
| title_full_unstemmed | Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression |
| title_short | Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression |
| title_sort | determining prognostic factors of disease free survival in breast cancer using censored quantile regression |
| url | https://doi.org/10.1177/11782234221108058 |
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