Development and validation of a logistic regression model for the diagnosis of colorectal cancer
Abstract Colorectal cancer (CRC) diagnosis is challenging due to generalized symptoms. Various biomarker models exist, but their clinical application is limited by low sensitivity and heterogeneous cutoff values. This study aimed to develop and validate a diagnostic model for CRC. Data from 489 pati...
Saved in:
| Main Authors: | , , , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-98968-z |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850042588058353664 |
|---|---|
| author | Cong Li Weili Zhang Qichen Chen Fei Xiao Xia Yang Binyi Xiao Yanshuang Cheng Jiayi Qin Xueying Li Desen Wan Zhizhong Pan Jianhong Peng Xiaojun Wu |
| author_facet | Cong Li Weili Zhang Qichen Chen Fei Xiao Xia Yang Binyi Xiao Yanshuang Cheng Jiayi Qin Xueying Li Desen Wan Zhizhong Pan Jianhong Peng Xiaojun Wu |
| author_sort | Cong Li |
| collection | DOAJ |
| description | Abstract Colorectal cancer (CRC) diagnosis is challenging due to generalized symptoms. Various biomarker models exist, but their clinical application is limited by low sensitivity and heterogeneous cutoff values. This study aimed to develop and validate a diagnostic model for CRC. Data from 489 patients—337 with CRC and 152 with benign disease—were included. Patients were randomly assigned to training (n = 342) and validation (n = 147) cohorts. Logistic regression identified age (OR 1.06), CA153 (OR 0.26), CEA (OR 4.49), CYFRA 21-1 (OR 5.88), ferritin (OR 0.15), and hs-CRP (OR 0.05) as independent risk factors. Sensitivity and specificity were 88.61% and 82.86% in the training cohort and 90.00% and 76.60% in the validation cohort. Cutoff values for the biomarkers were: CA199, 9.809 U/mL; CA125, 7.743 U/mL; CA153, 6.295 U/mL; CEA, 3.982 ng/mL; CYFRA 21-1, 1.769 ng/mL; ferritin, 163.361 mg/L; hs-CRP, 0.196 mg/L; and serum albumin, 55.966 g/L. The model showed higher sensitivity for early-stage CRC (95.45%, 95% CI 87.2–98.6%) than late-stage CRC (87.27%, 95% CI 76.4–93.5%; P = 0.08). AUCs were 0.907 (training) and 0.872 (validation). The model demonstrated higher sensitivity for early-stage CRC (95.45%) than late-stage CRC (87.27%), underscoring its utility in early detection. |
| format | Article |
| id | doaj-art-a1e79463d174420fbe9c7dde54c287d5 |
| institution | DOAJ |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-a1e79463d174420fbe9c7dde54c287d52025-08-20T02:55:31ZengNature PortfolioScientific Reports2045-23222025-04-011511910.1038/s41598-025-98968-zDevelopment and validation of a logistic regression model for the diagnosis of colorectal cancerCong Li0Weili Zhang1Qichen Chen2Fei Xiao3Xia Yang4Binyi Xiao5Yanshuang Cheng6Jiayi Qin7Xueying Li8Desen Wan9Zhizhong Pan10Jianhong Peng11Xiaojun Wu12Department of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Clinical Laboratory, People’s Hospital of MaomingDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterDepartment of Colorectal Surgery, Sun Yat-Sen University Cancer CenterAbstract Colorectal cancer (CRC) diagnosis is challenging due to generalized symptoms. Various biomarker models exist, but their clinical application is limited by low sensitivity and heterogeneous cutoff values. This study aimed to develop and validate a diagnostic model for CRC. Data from 489 patients—337 with CRC and 152 with benign disease—were included. Patients were randomly assigned to training (n = 342) and validation (n = 147) cohorts. Logistic regression identified age (OR 1.06), CA153 (OR 0.26), CEA (OR 4.49), CYFRA 21-1 (OR 5.88), ferritin (OR 0.15), and hs-CRP (OR 0.05) as independent risk factors. Sensitivity and specificity were 88.61% and 82.86% in the training cohort and 90.00% and 76.60% in the validation cohort. Cutoff values for the biomarkers were: CA199, 9.809 U/mL; CA125, 7.743 U/mL; CA153, 6.295 U/mL; CEA, 3.982 ng/mL; CYFRA 21-1, 1.769 ng/mL; ferritin, 163.361 mg/L; hs-CRP, 0.196 mg/L; and serum albumin, 55.966 g/L. The model showed higher sensitivity for early-stage CRC (95.45%, 95% CI 87.2–98.6%) than late-stage CRC (87.27%, 95% CI 76.4–93.5%; P = 0.08). AUCs were 0.907 (training) and 0.872 (validation). The model demonstrated higher sensitivity for early-stage CRC (95.45%) than late-stage CRC (87.27%), underscoring its utility in early detection.https://doi.org/10.1038/s41598-025-98968-zColorectal cancerLogistic regressionSerum biomarkersEarly diagnosisAUC |
| spellingShingle | Cong Li Weili Zhang Qichen Chen Fei Xiao Xia Yang Binyi Xiao Yanshuang Cheng Jiayi Qin Xueying Li Desen Wan Zhizhong Pan Jianhong Peng Xiaojun Wu Development and validation of a logistic regression model for the diagnosis of colorectal cancer Scientific Reports Colorectal cancer Logistic regression Serum biomarkers Early diagnosis AUC |
| title | Development and validation of a logistic regression model for the diagnosis of colorectal cancer |
| title_full | Development and validation of a logistic regression model for the diagnosis of colorectal cancer |
| title_fullStr | Development and validation of a logistic regression model for the diagnosis of colorectal cancer |
| title_full_unstemmed | Development and validation of a logistic regression model for the diagnosis of colorectal cancer |
| title_short | Development and validation of a logistic regression model for the diagnosis of colorectal cancer |
| title_sort | development and validation of a logistic regression model for the diagnosis of colorectal cancer |
| topic | Colorectal cancer Logistic regression Serum biomarkers Early diagnosis AUC |
| url | https://doi.org/10.1038/s41598-025-98968-z |
| work_keys_str_mv | AT congli developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT weilizhang developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT qichenchen developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT feixiao developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT xiayang developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT binyixiao developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT yanshuangcheng developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT jiayiqin developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT xueyingli developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT desenwan developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT zhizhongpan developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT jianhongpeng developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer AT xiaojunwu developmentandvalidationofalogisticregressionmodelforthediagnosisofcolorectalcancer |