An Updated Nomogram for Predicting Invasiveness in Preoperative Ductal Carcinoma In Situ of the Breast
Yonsei Medical Journal
; : 1028-1035, 2019.
Article
在 En
| WPRIM
| ID: wpr-762057
Responsible library:
WPRO
ABSTRACT
PURPOSE:
To validate and update a nomogram for predicting ductal carcinoma in situ (DCIS) upstaging in preoperative biopsy. MATERIALS ANDMETHODS:
Medical records of 444 preoperative DCIS patients were evaluated and used to validate a previous version of the Severance nomogram for predicting DCIS upstaging in preoperative biopsy. Patients were divided into two groups according to the final postoperative pathology. Univariate and multivariate analyses with the chi-square test, Student's t-test, and binary logistic regression method identified new significant variables. The updated nomogram was evaluated with the C-index and Hosmer—Lemeshow goodness of fit test.RESULTS:
The area under a receiver operating characteristic curve for comparison with the previous nomogram was 0.48. In postoperative pathology, the pure DCIS and invasive cancer groups comprised 345 and 99 cases, respectively. Approximately 22.3% of patients preoperatively diagnosed with DCIS were upstaged to invasive cancer. Significant variables in the univariate analysis were operation type, human epidermal growth factor receptor 2 overexpression, comedo necrosis, sonographic mass, mammographic mass, preoperative biopsy method, and suspicious microinvasion in preoperative biopsy. In multivariate analysis, operation type, sonographic mass, mammographic mass, and suspicious microinvasion were risk factors for upstaging. The updated model with these variables showed moderate discrimination and was appropriate in the calibration test.CONCLUSION:
The previous nomogram did not effectively discriminate upstaging of preoperative DCIS in an independent cohort. An updated version of the nomogram appears to provide more accurate information for predicting preoperative DCIS upstaging.Key words
全文:
1
索引:
WPRIM
主要主题:
Pathology
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Biopsy
/
Breast
/
Breast Neoplasms
/
Calibration
/
Logistic Models
/
Medical Records
/
Multivariate Analysis
/
Risk Factors
/
ROC Curve
研究类型:
Diagnostic_studies
/
Etiology_studies
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Incidence_studies
/
Observational_studies
/
Prognostic_studies
限制:
Humans
语言:
En
期刊:
Yonsei Medical Journal
年:
2019
类型:
Article