Literature DB >> 19763582

Bias, underestimation of risk, and loss of statistical power in patient-level analyses of lesion detection.

Nancy A Obuchowski1, Peter J Mazzone, Abraham H Dachman.   

Abstract

PURPOSE: Sensitivity and the false positive rate are usually defined with the patient as the unit of observation, i.e., the diagnostic test detects or does not detect disease in a patient. For tests designed to find and diagnose lesions, e.g., lung nodules, the usual definitions of sensitivity and specificity may be misleading. In this paper we describe and compare five measures of accuracy of lesion detection.
METHODS: The five levels of evaluation considered were patient level without localization, patient level with localization, region of interest (ROI) level without localization, ROI level with localization, and lesion level.
RESULTS: We found that estimators of sensitivity that do not require the reader to correctly locate the lesion overstate sensitivity. Patient-level estimators of sensitivity can be misleading when there is more than one lesion per patient and they reduce study power. Patient-level estimators of the false positive rate can conceal important differences between techniques. Referring clinicians rely on a test's reported accuracy to both choose the appropriate test and plan management for their patients. If reported sensitivity is overstated, the clinician could choose the test for disease screening, and have false confidence that a negative test represents the true absence of lesions. Similarly, the lower false positive rate associated with patient-level estimators can mislead clinicians about the diagnostic value of the test and consequently that a positive finding is real.
CONCLUSION: We present clear recommendations for studies assessing and comparing the accuracy of tests tasked with the detection and interpretation of lesions...

Entities:  

Mesh:

Year:  2009        PMID: 19763582     DOI: 10.1007/s00330-009-1590-4

Source DB:  PubMed          Journal:  Eur Radiol        ISSN: 0938-7994            Impact factor:   5.315


  19 in total

1.  Observer studies involving detection and localization: modeling, analysis, and validation.

Authors:  Dev P Chakraborty; Kevin S Berbaum
Journal:  Med Phys       Date:  2004-08       Impact factor: 4.071

2.  ROC curves predicted by a model of visual search.

Authors:  D P Chakraborty
Journal:  Phys Med Biol       Date:  2006-07-06       Impact factor: 3.609

3.  The efficacy of diagnostic imaging.

Authors:  D G Fryback; J R Thornbury
Journal:  Med Decis Making       Date:  1991 Apr-Jun       Impact factor: 2.583

4.  On comparing methods for discriminating between actually negative and actually positive subjects with FROC type data.

Authors:  Tao Song; Andriy I Bandos; Howard E Rockette; David Gur
Journal:  Med Phys       Date:  2008-04       Impact factor: 4.071

Review 5.  Analysis of clustered data in receiver operating characteristic studies.

Authors:  C A Beam
Journal:  Stat Methods Med Res       Date:  1998-12       Impact factor: 3.021

6.  An index for diagnostic accuracy in the multiple disease setting.

Authors:  H E Rockette
Journal:  Acad Radiol       Date:  1994-11       Impact factor: 3.173

7.  Nonparametric analysis of clustered ROC curve data.

Authors:  N A Obuchowski
Journal:  Biometrics       Date:  1997-06       Impact factor: 2.571

Review 8.  Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine.

Authors:  M H Zweig; G Campbell
Journal:  Clin Chem       Date:  1993-04       Impact factor: 8.327

9.  A visual concept shapes image perception.

Authors:  H L Kundel; C F Nodine
Journal:  Radiology       Date:  1983-02       Impact factor: 11.105

10.  The meaning and use of the area under a receiver operating characteristic (ROC) curve.

Authors:  J A Hanley; B J McNeil
Journal:  Radiology       Date:  1982-04       Impact factor: 11.105

View more
  11 in total

1.  Detection of noncalcified pulmonary nodules on low-dose MDCT: comparison of the sensitivity of two CAD systems by using a double reference standard.

Authors:  A R Larici; M Amato; P Ordóñez; F Maggi; L Menchini; A Caulo; L Calandriello; G Vallati; S Giunta; M Crecco; L Bonomo
Journal:  Radiol Med       Date:  2012-02-10       Impact factor: 3.469

2.  Evaluating imaging and computer-aided detection and diagnosis devices at the FDA.

Authors:  Brandon D Gallas; Heang-Ping Chan; Carl J D'Orsi; Lori E Dodd; Maryellen L Giger; David Gur; Elizabeth A Krupinski; Charles E Metz; Kyle J Myers; Nancy A Obuchowski; Berkman Sahiner; Alicia Y Toledano; Margarita L Zuley
Journal:  Acad Radiol       Date:  2012-02-03       Impact factor: 3.173

3.  Comparison of the diagnostic performance of digital breast tomosynthesis and magnetic resonance imaging added to digital mammography in women with known breast cancers.

Authors:  Won Hwa Kim; Jung Min Chang; Hyeong-Gon Moon; Ann Yi; Hye Ryoung Koo; Hye Mi Gweon; Woo Kyung Moon
Journal:  Eur Radiol       Date:  2015-09-16       Impact factor: 5.315

4.  ROC or FROC? It depends on the research question.

Authors:  Stephen L Hillis; Dev P Chakraborty; Colin G Orton
Journal:  Med Phys       Date:  2017-03-17       Impact factor: 4.071

5.  Diffusion-weighted endorectal MR imaging at 3 T for prostate cancer: tumor detection and assessment of aggressiveness.

Authors:  Hebert Alberto Vargas; Oguz Akin; Tobias Franiel; Yousef Mazaheri; Junting Zheng; Chaya Moskowitz; Kazuma Udo; James Eastham; Hedvig Hricak
Journal:  Radiology       Date:  2011-03-24       Impact factor: 11.105

6.  Diffusion-weighted MRI for uveal melanoma liver metastasis detection.

Authors:  Mathilde Wagner; Pascale Mariani; François Clément Bidard; Manuel Jorge Rodrigues; Fereshteh Farkhondeh; Nathalie Cassoux; Sophie Piperno-Neumann; Slavomir Petras; Vincent Servois
Journal:  Eur Radiol       Date:  2015-02-26       Impact factor: 5.315

7.  Bilateral contrast-enhanced dual-energy digital mammography: feasibility and comparison with conventional digital mammography and MR imaging in women with known breast carcinoma.

Authors:  Maxine S Jochelson; D David Dershaw; Janice S Sung; Alexandra S Heerdt; Cynthia Thornton; Chaya S Moskowitz; Jessica Ferrara; Elizabeth A Morris
Journal:  Radiology       Date:  2012-12-06       Impact factor: 11.105

8.  Diffusion-weighted and T2-weighted MR imaging for colorectal liver metastases detection in a rat model at 7 T: a comparative study using histological examination as reference.

Authors:  Mathilde Wagner; Léon Maggiori; Maxime Ronot; Valérie Paradis; Valérie Vilgrain; Yves Panis; Bernard E Van Beers
Journal:  Eur Radiol       Date:  2013-03-02       Impact factor: 5.315

9.  Preoperative axillary lymph node evaluation in breast cancer patients by breast magnetic resonance imaging (MRI): Can breast MRI exclude advanced nodal disease?

Authors:  Su Jeong Hyun; Eun-Kyung Kim; Hee Jung Moon; Jung Hyun Yoon; Min Jung Kim
Journal:  Eur Radiol       Date:  2016-02-02       Impact factor: 5.315

10.  MRI for the assessment of malignancy in BI-RADS 4 mammographic microcalcifications.

Authors:  Barbara Bennani-Baiti; Matthias Dietzel; Pascal A Baltzer
Journal:  PLoS One       Date:  2017-11-30       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.