Negative Biopsy of Focal Hepatic Lesions

Standard

Negative Biopsy of Focal Hepatic Lesions : Decision Tree Model for Patient Management. / Vernuccio, Federica; Rosenberg, Michael D; Meyer, Mathias; Choudhury, Kingshuk R; Nelson, Rendon C; Marin, Daniele.

In: AM J ROENTGENOL, Vol. 212, No. 3, 03.2019, p. 677-685.

Research output: SCORING: Contribution to journalSCORING: Journal articleResearchpeer-review

Harvard

Vernuccio, F, Rosenberg, MD, Meyer, M, Choudhury, KR, Nelson, RC & Marin, D 2019, 'Negative Biopsy of Focal Hepatic Lesions: Decision Tree Model for Patient Management', AM J ROENTGENOL, vol. 212, no. 3, pp. 677-685. https://doi.org/10.2214/AJR.18.20268

APA

Vernuccio, F., Rosenberg, M. D., Meyer, M., Choudhury, K. R., Nelson, R. C., & Marin, D. (2019). Negative Biopsy of Focal Hepatic Lesions: Decision Tree Model for Patient Management. AM J ROENTGENOL, 212(3), 677-685. https://doi.org/10.2214/AJR.18.20268

Vancouver

Bibtex

@article{04803691753d4d91ad91bfea98bb9dd0,
title = "Negative Biopsy of Focal Hepatic Lesions: Decision Tree Model for Patient Management",
abstract = "OBJECTIVE: The purpose of this study was to investigate patient- and procedure-related variables affecting the false-negative rate of ultrasound (US)-guided liver biopsy and to develop a standardized patient-tailored predictive model for the management of negative biopsy results.MATERIALS AND METHODS: We retrospectively included 389 patients (mean age ± SD, 62 ± 12 years old) who had undergone US-guided liver biopsy of 405 liver lesions between January 1, 2013, and June 30, 2015. We collected multiple patient- and procedure-related variables. By comparing pathology reports of biopsy and the reference standard (further histology or imaging follow-up), we were able to categorize the biopsy results as true-positive, true-negative, and false-negative. Diagnostic accuracy and diagnostic yield were measured. Univariate and multivariate analyses were performed to identify variables predicting false-negative results. A standardized patient-tailored predictive model of false-negative results based on a decision tree was fitted.RESULTS: Diagnostic accuracy and diagnostic yield were 93.8% (380/405) and 89.4% (362/405), respectively. The false-negative rate was 6.5% (25/387). Predictive variables of false-negative results at univariate analysis included body mass index, lesion size, sample acquisition techniques, and immediate specimen adequacy. The only independent predictors at multivariate analysis were patient age and Charlson comorbidity index. By combining lesion size and location with patient age and history of malignancy, we developed a decision tree model that predicts false-negative results with high confidence (up to 100%).CONCLUSION: False-negative results are not negligible at US-guided liver biopsy. The combination of selected lesion- and patient-specific variables may help predict when aggressive management is warranted in patients with likely false-negative results.",
keywords = "Adult, Aged, Aged, 80 and over, Decision Trees, False Negative Reactions, Female, Humans, Image-Guided Biopsy, Liver Diseases/pathology, Male, Middle Aged, Retrospective Studies, Ultrasonography, Interventional",
author = "Federica Vernuccio and Rosenberg, {Michael D} and Mathias Meyer and Choudhury, {Kingshuk R} and Nelson, {Rendon C} and Daniele Marin",
year = "2019",
month = mar,
doi = "10.2214/AJR.18.20268",
language = "English",
volume = "212",
pages = "677--685",
journal = "AM J ROENTGENOL",
issn = "0361-803X",
publisher = "American Roentgen Ray Society",
number = "3",

}

RIS

TY - JOUR

T1 - Negative Biopsy of Focal Hepatic Lesions

T2 - Decision Tree Model for Patient Management

AU - Vernuccio, Federica

AU - Rosenberg, Michael D

AU - Meyer, Mathias

AU - Choudhury, Kingshuk R

AU - Nelson, Rendon C

AU - Marin, Daniele

PY - 2019/3

Y1 - 2019/3

N2 - OBJECTIVE: The purpose of this study was to investigate patient- and procedure-related variables affecting the false-negative rate of ultrasound (US)-guided liver biopsy and to develop a standardized patient-tailored predictive model for the management of negative biopsy results.MATERIALS AND METHODS: We retrospectively included 389 patients (mean age ± SD, 62 ± 12 years old) who had undergone US-guided liver biopsy of 405 liver lesions between January 1, 2013, and June 30, 2015. We collected multiple patient- and procedure-related variables. By comparing pathology reports of biopsy and the reference standard (further histology or imaging follow-up), we were able to categorize the biopsy results as true-positive, true-negative, and false-negative. Diagnostic accuracy and diagnostic yield were measured. Univariate and multivariate analyses were performed to identify variables predicting false-negative results. A standardized patient-tailored predictive model of false-negative results based on a decision tree was fitted.RESULTS: Diagnostic accuracy and diagnostic yield were 93.8% (380/405) and 89.4% (362/405), respectively. The false-negative rate was 6.5% (25/387). Predictive variables of false-negative results at univariate analysis included body mass index, lesion size, sample acquisition techniques, and immediate specimen adequacy. The only independent predictors at multivariate analysis were patient age and Charlson comorbidity index. By combining lesion size and location with patient age and history of malignancy, we developed a decision tree model that predicts false-negative results with high confidence (up to 100%).CONCLUSION: False-negative results are not negligible at US-guided liver biopsy. The combination of selected lesion- and patient-specific variables may help predict when aggressive management is warranted in patients with likely false-negative results.

AB - OBJECTIVE: The purpose of this study was to investigate patient- and procedure-related variables affecting the false-negative rate of ultrasound (US)-guided liver biopsy and to develop a standardized patient-tailored predictive model for the management of negative biopsy results.MATERIALS AND METHODS: We retrospectively included 389 patients (mean age ± SD, 62 ± 12 years old) who had undergone US-guided liver biopsy of 405 liver lesions between January 1, 2013, and June 30, 2015. We collected multiple patient- and procedure-related variables. By comparing pathology reports of biopsy and the reference standard (further histology or imaging follow-up), we were able to categorize the biopsy results as true-positive, true-negative, and false-negative. Diagnostic accuracy and diagnostic yield were measured. Univariate and multivariate analyses were performed to identify variables predicting false-negative results. A standardized patient-tailored predictive model of false-negative results based on a decision tree was fitted.RESULTS: Diagnostic accuracy and diagnostic yield were 93.8% (380/405) and 89.4% (362/405), respectively. The false-negative rate was 6.5% (25/387). Predictive variables of false-negative results at univariate analysis included body mass index, lesion size, sample acquisition techniques, and immediate specimen adequacy. The only independent predictors at multivariate analysis were patient age and Charlson comorbidity index. By combining lesion size and location with patient age and history of malignancy, we developed a decision tree model that predicts false-negative results with high confidence (up to 100%).CONCLUSION: False-negative results are not negligible at US-guided liver biopsy. The combination of selected lesion- and patient-specific variables may help predict when aggressive management is warranted in patients with likely false-negative results.

KW - Adult

KW - Aged

KW - Aged, 80 and over

KW - Decision Trees

KW - False Negative Reactions

KW - Female

KW - Humans

KW - Image-Guided Biopsy

KW - Liver Diseases/pathology

KW - Male

KW - Middle Aged

KW - Retrospective Studies

KW - Ultrasonography, Interventional

U2 - 10.2214/AJR.18.20268

DO - 10.2214/AJR.18.20268

M3 - SCORING: Journal article

C2 - 30673333

VL - 212

SP - 677

EP - 685

JO - AM J ROENTGENOL

JF - AM J ROENTGENOL

SN - 0361-803X

IS - 3

ER -