Dataset Information

A population-based validation study of the DCIS Score predicting recurrence risk in individuals treated by breast-conserving surgery alone.

ABSTRACT: Validated biomarkers are needed to improve risk assessment and treatment decision-making for women with ductal carcinoma in situ (DCIS) of the breast. The Oncotype DX DCIS Score (DS) was shown to predict the risk of local recurrence (LR) in individuals with low-risk DCIS treated by breast-conserving surgery (BCS) alone. Our objective was to confirm these results in a larger population-based cohort of individuals. We used an established population-based cohort of individuals diagnosed with DCIS treated with BCS alone from 1994 to 2003 with validation of treatment and outcomes. Central pathology assessment excluded cases with invasive cancer, DCIS < 2 mm or positive margins. Cox model was used to determine the relationship between independent covariates, the DS (hazard ratio (HR)/50 Cp units (U)) and LR. Tumor blocks were collected for 828 patients. Final evaluable population includes 718 cases, of whom 571 had negative margins. Median follow-up was 9.6 years. 100 cases developed LR following BCS alone (DCIS, N = 44; invasive, N = 57). In the primary pre-specified analysis, the DS was associated with any LR (DCIS or invasive) in ER+ patients (HR 2.26; P < 0.001) and in all patients regardless of ER status (HR 2.15; P < 0.001). DCIS Score provided independent information on LR risk beyond clinical and pathologic variables including size, age, grade, necrosis, multifocality, and subtype (adjusted HR 1.68; P = 0.02). DCIS was associated with invasive LR (HR 1.78; P = 0.04) and DCIS LR (HR 2.43; P = 0.005). The DCIS Score independently predicts and quantifies individualized recurrence risk in a population of patients with pure DCIS treated by BCS alone.

SUBMITTER: Rakovitch E

PROVIDER: S-EPMC4491104 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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A population-based validation study of the DCIS Score predicting recurrence risk in individuals treated by breast-conserving surgery alone.

Rakovitch Eileen E Nofech-Mozes Sharon S Hanna Wedad W Baehner Frederick L FL Saskin Refik R Butler Steven M SM Tuck Alan A Sengupta Sandip S Elavathil Leela L Jani Prashant A PA Bonin Michel M Chang Martin C MC Robertson Susan J SJ Slodkowska Elzbieta E Fong Cindy C Anderson Joseph M JM Jamshidian Farid F Miller Dave P DP Cherbavaz Diana B DB Shak Steven S Paszat Lawrence L

Breast cancer research and treatment 20150629 2

Validated biomarkers are needed to improve risk assessment and treatment decision-making for women with ductal carcinoma in situ (DCIS) of the breast. The Oncotype DX DCIS Score (DS) was shown to predict the risk of local recurrence (LR) in individuals with low-risk DCIS treated by breast-conserving surgery (BCS) alone. Our objective was to confirm these results in a larger population-based cohort of individuals. We used an established population-based cohort of individuals diagnosed with DCIS t ...[more]

PMID: 26119102

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Project description:BackgroundThe CARDOT scores have been developed for prediction of respiratory complications after thoracic surgery. This study aimed to externally validate the CARDOT score and assess the predictive value of preoperative neutrophil-to-lymphocyte ratio (NLR) for postoperative respiratory complication.MethodsA retrospective cohort study of consecutive thoracic surgical patients at a single tertiary hospital in northern Thailand was conducted. The development and validation datasets were collected between 2006 and 2012 and from 2015 to 2021, respectively. Six prespecified predictive factors were identified, and formed a predictive score, the CARDOT score (chronic obstructive pulmonary disease, American Society of Anesthesiologists physical status, right-sided operation, duration of surgery, preoperative oxygen saturation on room air, thoracotomy), was calculated. The performance of the CARDOT score was evaluated in terms of discrimination by using the area under the receiver operating characteristic (AuROC) curve and calibration.ResultsThere were 1086 and 1645 patients included in the development and validation datasets. The incidence of respiratory complications was 15.7% (171 of 1086) and 22.5% (370 of 1645) in the development and validation datasets, respectively. The CARDOT score had good discriminative ability for both the development and validation datasets (AuROC 0.789 (95% CI 0.753-0.827) and 0.758 (95% CI 0.730-0.787), respectively). The CARDOT score showed good calibration in both datasets. A high NLR (≥ 4.5) significantly increased the risk of respiratory complications after thoracic surgery (P < 0.001). The AuROC curve of the validation cohort increased to 0.775 (95% CI 0.750-0.800) when the score was combined with a high NLR. The AuROC of the CARDOT score with the NLR showed significantly greater discrimination power than that of the CARDOT score alone (P = 0.008).ConclusionsThe CARDOT score showed a good discriminative performance in the external validation dataset. An addition of a high NLR significantly increases the predictive performance of CARDOT score. The utility of this score is valuable in settings with limited access to preoperative pulmonary function testing.

Dataset Information

A population-based validation study of the DCIS Score predicting recurrence risk in individuals treated by breast-conserving surgery alone.

Publications

A population-based validation study of the DCIS Score predicting recurrence risk in individuals treated by breast-conserving surgery alone.

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