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Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer.

ABSTRACT: Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) may be diagnosed with invasive breast cancer after excision. We evaluated the preoperative clinical and imaging predictors of DCIS that were associated with an upgrade to invasive carcinoma on final pathology and also compared the diagnostic performance of various statistical models. We reviewed the medical records; including mammography, ultrasound (US), and magnetic resonance imaging (MRI) findings; of 644 patients who were preoperatively diagnosed with DCIS and who underwent surgery between January 2012 and September 2018. Logistic regression and three machine learning methods were applied to predict DCIS underestimation. Among 644 DCIS biopsies, 161 (25%) underestimated invasive breast cancers. In multivariable analysis, suspicious axillary lymph nodes (LNs) on US (odds ratio [OR], 12.16; 95% confidence interval [CI], 4.94-29.95; P < 0.001) and high nuclear grade (OR, 1.90; 95% CI, 1.24-2.91; P = 0.003) were associated with underestimation. Cases with biopsy performed using vacuum-assisted biopsy (VAB) (OR, 0.42; 95% CI, 0.27-0.65; P < 0.001) and lesion size <2 cm on mammography (OR, 0.45; 95% CI, 0.22-0.90; P = 0.021) and MRI (OR, 0.29; 95% CI, 0.09-0.94; P = 0.037) were less likely to be upgraded. No significant differences in performance were observed between logistic regression and machine learning models. Our results suggest that biopsy device, high nuclear grade, presence of suspicious axillary LN on US, and lesion size on mammography or MRI were independent predictors of DCIS underestimation.

SUBMITTER: Park KW

PROVIDER: S-EPMC8760307 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature

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Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer.

Park Ko Woon KW Kim Seon Woo SW Han Heewon H Park Minsu M Han Boo-Kyung BK Ko Eun Young EY Choi Ji Soo JS Cho Eun Yoon EY Cho Soo Youn SY Ko Eun Sook ES

NPJ breast cancer 20220114 1

Patients with a biopsy diagnosis of ductal carcinoma in situ (DCIS) may be diagnosed with invasive breast cancer after excision. We evaluated the preoperative clinical and imaging predictors of DCIS that were associated with an upgrade to invasive carcinoma on final pathology and also compared the diagnostic performance of various statistical models. We reviewed the medical records; including mammography, ultrasound (US), and magnetic resonance imaging (MRI) findings; of 644 patients who were pr ...[more]

PMID: 35031626

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Project description:Importance:Recent recognition of the overdiagnosis and overtreatment of ductal carcinoma in situ (DCIS) detected by mammography has led to the development of clinical trials randomizing women with non-high-grade DCIS to active surveillance, defined as imaging surveillance with or without endocrine therapy, vs standard surgical care. Objective:To determine the factors associated with underestimation of invasive cancer in patients with a clinical diagnosis of non-high-grade DCIS that would preclude active surveillance. Design, Setting, and Participants:A retrospective cohort study was conducted using records from the National Cancer Database from January 1, 1998, to December 31, 2012, of female patients 40 to 99 years of age with a clinical diagnosis of non-high-grade DCIS who underwent definitive surgical treatment. Data analysis was conducted from November 1, 2015, to February 4, 2017. Exposures:Patients with an upgraded diagnosis of invasive carcinoma vs those with a diagnosis of DCIS based on final surgical pathologic findings. Main Outcomes and Measures:The proportions of cases with an upgraded diagnosis of invasive carcinoma from final surgical pathologic findings were compared by tumor, host, and system characteristics. Results:Of 37?544 women (mean [SD] age, 59.3 [12.4] years) presenting with a clinical diagnosis of non-high-grade DCIS, 8320 (22.2%) had invasive carcinoma based on final pathologic findings. Invasive carcinomas were more likely to be smaller (>0.5 to ?1.0 cm vs ?0.5 cm: odds ratio [OR], 0.73; 95% CI, 0.67-0.79; >1.0 to ?2.0 cm vs ?0.5 cm: OR, 0.42; 95% CI, 0.39-0.46; >2.0 to ?5.0 cm vs ?0.5 cm: OR, 0.19; 95% CI, 0.17-0.22; and >5.0 cm vs ?0.5 cm: OR, 0.11; 95% CI, 0.08-0.15) and lower grade (intermediate vs low: OR, 0.75; 95% CI, 0.69-0.80). Multivariate logistic regression analysis demonstrated that younger age (60-79 vs 40-49 years: OR, 0.84; 95% CI, 0.77-0.92; and ?80 vs 40 to 49 years: OR, 0.76; 95% CI, 0.64-0.91), negative estrogen receptor status (positive vs negative: OR, 0.39; 95% CI, 0.34-0.43), treatment at an academic facility (academic vs community: OR, 2.08; 95% CI, 1.82-2.38), and higher annual income (>$63?000 vs <$38?000: OR, 1.14; 95% CI, 1.02-1.28) were significantly associated with an upgraded diagnosis of invasive carcinoma based on final pathologic findings. Conclusions and Relevance:When selecting patients for active surveillance of DCIS, factors other than tumor biology associated with invasive carcinoma based on final pathologic findings may need to be considered. At the time of randomization to active surveillance, a significant proportion of patients with non-high-grade DCIS will harbor invasive carcinoma.

Dataset Information

Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer.

Publications

Ductal carcinoma in situ: a risk prediction model for the underestimation of invasive breast cancer.

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