Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer
Objective To investigate the risk factors influencing the incidence of chemotherapy-induced myelosuppression (CIM) following first-line chemotherapy in patients with moderately advanced colorectal cancer (CRC), and to develop and validate a nomogram to assess the risk of CIM in the patients.Methods...
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Editorial Office of New Medicine
2025-01-01
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| Series: | Yixue xinzhi zazhi |
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| Online Access: | https://yxxz.whuznhmedj.com/futureApi/storage/attach/2501/BQZWUdZRuM8ugw6wghfJMtarD7iuWktNmhL1hHk4.pdf |
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| _version_ | 1832586478886060032 |
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| author | WANG Xuexing ZHANG Rong CHU Jie LIU Zhijin |
| author_facet | WANG Xuexing ZHANG Rong CHU Jie LIU Zhijin |
| author_sort | WANG Xuexing |
| collection | DOAJ |
| description | Objective To investigate the risk factors influencing the incidence of chemotherapy-induced myelosuppression (CIM) following first-line chemotherapy in patients with moderately advanced colorectal cancer (CRC), and to develop and validate a nomogram to assess the risk of CIM in the patients.Methods The clinical data of patients with stage II-IV CRC who received first-line chemotherapy at Anning First People's Hospital affiliated with Kunming University of Science and Technology between July 2021 and January 2024, were retrospectively analyzed. The World Health Organization classification standard for acute and subacute toxicity of anticancer drugs were used as the standards for diagnosing CIM, and the patients were subsequently categorized into CIM and non-CIM groups. The risk factors for CIM were analyzed and a multivariate Logistic regression model was employed to construct the predictive model. The model's discrimination and accuracy were assessed using the receiver operating characteristic curve (ROC) and area under curve (AUC) and the Hosmer-Lemeshow goodness of fit test. Additionally, the model's clinical utility was evaluated using calibration and clinical decision curves.Results A total of 257 patients were included, 112 individuals exhibited bone CIM, corresponding to an incidence rate of 43.58%. The most prevalent severity was classified as grade I-II CIM. Multivariate Logistic regression analysis identified the chemotherapy cycle, reductions in white blood cell count, hemoglobin levels, and platelet count prior to chemotherapy as independent risk factors for CIM in CRC patients (P |
| format | Article |
| id | doaj-art-6acaacd27de2411680bb6b7b2e2526bb |
| institution | Kabale University |
| issn | 1004-5511 |
| language | zho |
| publishDate | 2025-01-01 |
| publisher | Editorial Office of New Medicine |
| record_format | Article |
| series | Yixue xinzhi zazhi |
| spelling | doaj-art-6acaacd27de2411680bb6b7b2e2526bb2025-01-25T11:46:43ZzhoEditorial Office of New MedicineYixue xinzhi zazhi1004-55112025-01-01351334010.12173/j.issn.1004-5511.2024080716584Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancerWANG XuexingZHANG RongCHU JieLIU ZhijinObjective To investigate the risk factors influencing the incidence of chemotherapy-induced myelosuppression (CIM) following first-line chemotherapy in patients with moderately advanced colorectal cancer (CRC), and to develop and validate a nomogram to assess the risk of CIM in the patients.Methods The clinical data of patients with stage II-IV CRC who received first-line chemotherapy at Anning First People's Hospital affiliated with Kunming University of Science and Technology between July 2021 and January 2024, were retrospectively analyzed. The World Health Organization classification standard for acute and subacute toxicity of anticancer drugs were used as the standards for diagnosing CIM, and the patients were subsequently categorized into CIM and non-CIM groups. The risk factors for CIM were analyzed and a multivariate Logistic regression model was employed to construct the predictive model. The model's discrimination and accuracy were assessed using the receiver operating characteristic curve (ROC) and area under curve (AUC) and the Hosmer-Lemeshow goodness of fit test. Additionally, the model's clinical utility was evaluated using calibration and clinical decision curves.Results A total of 257 patients were included, 112 individuals exhibited bone CIM, corresponding to an incidence rate of 43.58%. The most prevalent severity was classified as grade I-II CIM. Multivariate Logistic regression analysis identified the chemotherapy cycle, reductions in white blood cell count, hemoglobin levels, and platelet count prior to chemotherapy as independent risk factors for CIM in CRC patients (Phttps://yxxz.whuznhmedj.com/futureApi/storage/attach/2501/BQZWUdZRuM8ugw6wghfJMtarD7iuWktNmhL1hHk4.pdfcolorectal cancerchemotherapymyelosuppressionrisk prediction modelslogistic regression analysis |
| spellingShingle | WANG Xuexing ZHANG Rong CHU Jie LIU Zhijin Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer Yixue xinzhi zazhi colorectal cancer chemotherapy myelosuppression risk prediction models logistic regression analysis |
| title | Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer |
| title_full | Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer |
| title_fullStr | Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer |
| title_full_unstemmed | Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer |
| title_short | Construction and validation of a predictive model for the risk of myelosuppression after first-line chemotherapy in patients with advanced colorectal cancer |
| title_sort | construction and validation of a predictive model for the risk of myelosuppression after first line chemotherapy in patients with advanced colorectal cancer |
| topic | colorectal cancer chemotherapy myelosuppression risk prediction models logistic regression analysis |
| url | https://yxxz.whuznhmedj.com/futureApi/storage/attach/2501/BQZWUdZRuM8ugw6wghfJMtarD7iuWktNmhL1hHk4.pdf |
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