Dataset Information

Assessment of hospital-level adjusted breast cancer sentinel lymph node positivity rates.

ABSTRACT:

Background/objectives

Proficiency of performing sentinel lymph node biopsy (SLNB) for breast cancer varies among hospitals and may be reflected in the hospital's SLNB positivity rate. Our objectives were to examine whether hospital characteristics are associated with variation in SLNB positivity rates and whether hospitals with lower-than-expected SLNB positivity rates have worse patient survival.

Methods

Using the National Cancer Data Base, stage I to III breast cancer patients were identified (2004-2012). Hospital-level SLNB positivity rates were adjusted for tumor and patient factors. Hospitals were divided into terciles of SLNB positivity rates (lower-, higher-, as-expected). Hospital characteristics and survival were examined across terciles.

Results

Of 438?610 SLNB patients (from 1357 hospitals), 78 104 had one or more positive SLN (21.3%). Hospitals in the low and high terciles were more likely to be low volume (low: RRR, 4.40; 95% CI, 2.89-6.57; P?ConclusionsThere is a wide variation in hospital SLNB positivity rates. Hospitals with lower- or higher-than-expected SLNB positivity rates were associated with survival differences. Hospital SLNB positivity rates may be a novel 'process measure' to report to hospitals for internal quality assessment.

SUBMITTER: Berger ER

PROVIDER: S-EPMC7775040 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Assessment of hospital-level adjusted breast cancer sentinel lymph node positivity rates.

Berger Elizabeth R ER Bilimoria Karl Y KY Kinnier Christine V CV Minami Christina A CA Bethke Kevin P KP Hansen Nora M NM Merkow Ryan P RP Winchester David P DP Yang Anthony D AD

Journal of surgical oncology 20181127 1

<h4>Background/objectives</h4>Proficiency of performing sentinel lymph node biopsy (SLNB) for breast cancer varies among hospitals and may be reflected in the hospital's SLNB positivity rate. Our objectives were to examine whether hospital characteristics are associated with variation in SLNB positivity rates and whether hospitals with lower-than-expected SLNB positivity rates have worse patient survival.<h4>Methods</h4>Using the National Cancer Data Base, stage I to III breast cancer patients w ...[more]

PMID: 30481371

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Project description:BackgroundCurrent practice is to perform a completion axillary lymph node dissection (ALND) for breast cancer patients with tumor-involved sentinel lymph nodes (SLNs), although fewer than half will have non-sentinel node (NSLN) metastasis. Our goal was to develop new models to quantify the risk of NSLN metastasis in SLN-positive patients and to compare predictive capabilities to another widely used model.MethodsWe constructed three models to predict NSLN status: recursive partitioning with receiver operating characteristic curves (RP-ROC), boosted Classification and Regression Trees (CART), and multivariate logistic regression (MLR) informed by CART. Data were compiled from a multicenter Northern California and Oregon database of 784 patients who prospectively underwent SLN biopsy and completion ALND. We compared the predictive abilities of our best model and the Memorial Sloan-Kettering Breast Cancer Nomogram (Nomogram) in our dataset and an independent dataset from Northwestern University.Results285 patients had positive SLNs, of which 213 had known angiolymphatic invasion status and 171 had complete pathologic data including hormone receptor status. 264 (93%) patients had limited SLN disease (micrometastasis, 70%, or isolated tumor cells, 23%). 101 (35%) of all SLN-positive patients had tumor-involved NSLNs. Three variables (tumor size, angiolymphatic invasion, and SLN metastasis size) predicted risk in all our models. RP-ROC and boosted CART stratified patients into four risk levels. MLR informed by CART was most accurate. Using two composite predictors calculated from three variables, MLR informed by CART was more accurate than the Nomogram computed using eight predictors. In our dataset, area under ROC curve (AUC) was 0.83/0.85 for MLR (n = 213/n = 171) and 0.77 for Nomogram (n = 171). When applied to an independent dataset (n = 77), AUC was 0.74 for our model and 0.62 for Nomogram. The composite predictors in our model were the product of angiolymphatic invasion and size of SLN metastasis, and the product of tumor size and square of SLN metastasis size.ConclusionWe present a new model developed from a community-based SLN database that uses only three rather than eight variables to achieve higher accuracy than the Nomogram for predicting NSLN status in two different datasets.

Project description:ImportanceAcral lentiginous melanoma (ALM) is a rare subtype of malignant melanoma typically occurring on the palmar and plantar surfaces. Although it has distinctive genetic, prognostic, and behavioral characteristics relative to cutaneous melanomas overall, owing to its rarity, treatment is largely guided by data extrapolated from more common subtypes. Although sentinel lymph node (SLN) status has been shown to be a significant prognostic factor for ALM, the independent effect of ALM-subtype disease on the likelihood of SLN positivity and the stage-specific positivity rates for ALM are not well characterized.ObjectiveTo evaluate the association of ALM with SLN status as well as to characterize the clinical stage-specific rates of SLN positivity for ALM based on the AJCC Cancer Staging Manual, 8th edition (AJCC-8).Design, setting, and participantsThe National Cancer Database (NCDB) includes all reportable cases from Commission on Cancer accredited facilities and represents approximately 50% of all newly diagnosed melanoma cases in the US. This retrospective cohort study included cases of AJCC-8 clinical stage I to II melanomas from the NCDB diagnosed from 2012 to 2015. The analysis took place between April 2021 and September 2021.ExposuresMelanoma histopathologic subtype.Main outcomes and measuresSentinel lymph node status.ResultsWe identified 60 148 patients with malignant melanomas, 959 of whom had ALM-subtype disease. Among patients in the cohort, 25 550 (42.5%) were women and the mean (SD) age was 64 (16) years. Multivariable logistic regression controlling for demographic and histopathologic characteristics revealed that ALM was independently associated with the highest risk for SLN positivity among included subtypes (vs superficial spreading melanoma: odds ratio, 1.91; 95% CI, 1.59-2.28). Subgroup analysis by AJCC clinical stage demonstrated that ALM was independently associated with the highest risk for SLN positivity for both stage IB and II disease. The rate of SLN positivity for patients with stage IB and II ALM was 18.39% (95% CI, 13.82%-24.03%) and 39.53% (34.98%-44.26%), respectively.Conclusions and relevanceIn this cohort study ALM was independently associated with SLN positivity and had relatively high positivity rates at clinical stage IB and II. This suggests that SLNB should be encouraged for all patients with clinical stage IB and II ALM, and such patients should receive appropriate counseling about the higher regional metastatic risk of their cancers. Future work with a larger cohort is required to elucidate the risk of SLN positivity for stage IA ALM.

Project description:Background The rate of breast-conserving surgery is very low in China, compared with that in developed countries; most breast cancer patients receive mastectomy. It is great important to explore the possibility of omitting axillary lymph node dissection (ALND) in early-stage breast cancer patients with 1 or 2 positive sentinel lymph nodes (SLNs) in China. The aim of this study was to develop a nomogram based on elastography for the prediction of the risk of non-SLN (NSLN) metastasis in early-stage breast cancer patients with 1 or 2 positive SLNs. Methods A total of 601 breast cancer patients were initially recruited. According to the inclusion and exclusion criteria, 118 early-stage breast cancer patients with 1 or 2 positive SLNs were finally enrolled and were assigned to the training cohort (n=82) and the validation cohort (n=36), respectively. In the training cohort, the independent predictors were screened by logistic regression analysis and then were used to conducted the nomogram for the prediction of NSLN metastasis in early-stage breast cancer patients with 1 or 2 positive SLNs. The calibration curves, concordance index (C-index), the area under the receiver operating characteristic (ROC) curve (AUC), and Decision curve analysis (DCA) were used to verified the performance of the nomogram. Results The multivariable analysis showed that the enrolled patients with positive HER2 expression (OR=6.179, P=0.013), Ki67≥14% (OR=8.976, P=0.015), larger lesion size (OR=1.038, P=0.045), and higher Emean (OR=2.237, P=0.006) were observed to be the independent factors of NSLN metastasis. Based on the above four independent predictors, a nomogram was conducted to predict the risk of the NSLN metastasis in early-stage breast cancer patients with 1 or 2 positive SLNs. The nomogram showed good discrimination in the prediction of NSLN metastasis, with bias-corrected C-index of 0.855 (95% CI, 0.754-0.956) and 0.853 (95% CI, 0.724-0.983) in the training and validation cohorts, respectively. Furthermore, the AUC was 0.877 (95%CI: 0.776- 0.978) and 0.861 (95%CI: 0.732-0.991), respectively, indicating a good performance of the nomogram. The calibration curve suggested a satisfactory agreement between the predictive and actual risk in both the training (χ2 = 11.484, P=0.176, HL test) and validation (χ2 = 6.247, p = 0.620, HL test) cohorts, and the obvious clinical nets were revealed by DCA. Conclusions We conducted a satisfactory nomogram model to evaluate the risk of NSLN metastasis in early-stage breast cancer patients with 1 or 2 SLN metastases. This model could be considered as an ancillary tool to help such patients to be selectively exempted from ALND.

Dataset Information

Assessment of hospital-level adjusted breast cancer sentinel lymph node positivity rates.

Background/objectives

Methods

Results

Publications

Assessment of hospital-level adjusted breast cancer sentinel lymph node positivity rates.

Similar Datasets

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