Detailed characterization of metastatic lymph nodes improves the prediction accuracy of currently used risk stratification systems in N1 stage papillary thyroid cancer

Jandee Lee; Chan Hee Kim; In Kyung Min; Seonhyang Jeong; Hyunji Kim; Moon Jung Choi; Hyeong Ju Kwon; Sang Geun Jung; Young Suk Jo

doi:10.1530/EJE-20-0131

Detailed characterization of metastatic lymph nodes improves the prediction accuracy of currently used risk stratification systems in N1 stage papillary thyroid cancer

Jandee Lee, Chan Hee Kim, In Kyung Min, Seonhyang Jeong, Hyunji Kim, Moon Jung Choi, Hyeong Ju Kwon, Sang Geun Jung, Young Suk Jo

Pathology

Research output: Contribution to journal › Article › peer-review

4 Citations (Scopus)

Abstract

Objective: The characteristics of metastatic lymph nodes (MLNs) have been investigated as important predictors of recurrence and progression in papillary thyroid cancer (PTC). However, clinically applicable risk stratification systems are limited to the assessment of size and number of MLNs. This study investigated the predictive value of detailed characteristics of MLNs in combination with currently used risk stratification systems. Design and methods: We retrospectively characterized 2811 MLNs from 9014 harvested LNs of 286 patients with N1 PTC according to the maximum diameter of MLN (MDLN), maximum diameter of metastatic focus (MDMF), ratio of both diameters (MDMFR), lymph node ratio (LNR, number of MLNs/number of total harvested LNs), presence of extranodal extension (ENE), desmoplastic reaction (DR), cystic component, and psammoma body. Results: Factors related to the size and number of MLNs were associated with increased risk of recurrence and progression. Extensive presence of ENE (>40%) and DR (≥50%) increased the risk of recurrence/progression. The combination of MDLN, LNR, ENE, and DR had the highest predictive value among MLN characteristics. Combination of these parameters with ATA risk stratification or 1-year response to therapy improved the predictive power for recurrence/progression from a Harrell's C-index of 0.781 to 0.936 and 0.867 to 0.960, respectively. Conclusions: The combination of currently used risk stratification systems with detailed characterization of MLNs may improve the predictive accuracy for recurrence/progression in N1 PTC patients.

Original language	English
Pages (from-to)	83-93
Number of pages	11
Journal	European Journal of Endocrinology
Volume	183
Issue number	1
DOIs	https://doi.org/10.1530/EJE-20-0131
Publication status	Published - 2020 Jun

Bibliographical note

Funding Information:
J L was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2020R1A2C1006047). S G J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2018R1D1A1B07045227). Y S J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2018R1A2B6004179). The authors would like to thank Ji Young Kim (Severance Hospital), Hwanju Lee (Severance Hospital), Hee Chang Yu (Severance Hospital), and Hoyoung Kim (Severance Hospital) for technical support.

Funding Information:
J L was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2020R1A2C1006047). S G J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2018R1D1A1B07045227). Y S J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2018R1A2B6004179).

Publisher Copyright:
© 2020 European Society of Endocrinology Printed in Great Britain.

All Science Journal Classification (ASJC) codes

Endocrinology, Diabetes and Metabolism
Endocrinology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1530/EJE-20-0131

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@article{d56679374120423c9ac6d17f0c299f33,

title = "Detailed characterization of metastatic lymph nodes improves the prediction accuracy of currently used risk stratification systems in N1 stage papillary thyroid cancer",

abstract = "Objective: The characteristics of metastatic lymph nodes (MLNs) have been investigated as important predictors of recurrence and progression in papillary thyroid cancer (PTC). However, clinically applicable risk stratification systems are limited to the assessment of size and number of MLNs. This study investigated the predictive value of detailed characteristics of MLNs in combination with currently used risk stratification systems. Design and methods: We retrospectively characterized 2811 MLNs from 9014 harvested LNs of 286 patients with N1 PTC according to the maximum diameter of MLN (MDLN), maximum diameter of metastatic focus (MDMF), ratio of both diameters (MDMFR), lymph node ratio (LNR, number of MLNs/number of total harvested LNs), presence of extranodal extension (ENE), desmoplastic reaction (DR), cystic component, and psammoma body. Results: Factors related to the size and number of MLNs were associated with increased risk of recurrence and progression. Extensive presence of ENE (>40%) and DR (≥50%) increased the risk of recurrence/progression. The combination of MDLN, LNR, ENE, and DR had the highest predictive value among MLN characteristics. Combination of these parameters with ATA risk stratification or 1-year response to therapy improved the predictive power for recurrence/progression from a Harrell's C-index of 0.781 to 0.936 and 0.867 to 0.960, respectively. Conclusions: The combination of currently used risk stratification systems with detailed characterization of MLNs may improve the predictive accuracy for recurrence/progression in N1 PTC patients.",

author = "Jandee Lee and Kim, {Chan Hee} and Min, {In Kyung} and Seonhyang Jeong and Hyunji Kim and Choi, {Moon Jung} and Kwon, {Hyeong Ju} and Jung, {Sang Geun} and Jo, {Young Suk}",

note = "Funding Information: J L was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2020R1A2C1006047). S G J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2018R1D1A1B07045227). Y S J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2018R1A2B6004179). The authors would like to thank Ji Young Kim (Severance Hospital), Hwanju Lee (Severance Hospital), Hee Chang Yu (Severance Hospital), and Hoyoung Kim (Severance Hospital) for technical support. Funding Information: J L was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2020R1A2C1006047). S G J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2018R1D1A1B07045227). Y S J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2018R1A2B6004179). Publisher Copyright: {\textcopyright} 2020 European Society of Endocrinology Printed in Great Britain.",

year = "2020",

month = jun,

doi = "10.1530/EJE-20-0131",

language = "English",

volume = "183",

pages = "83--93",

journal = "European Journal of Endocrinology",

issn = "0804-4643",

publisher = "BioScientifica Ltd.",

number = "1",

}

TY - JOUR

T1 - Detailed characterization of metastatic lymph nodes improves the prediction accuracy of currently used risk stratification systems in N1 stage papillary thyroid cancer

AU - Lee, Jandee

AU - Kim, Chan Hee

AU - Min, In Kyung

AU - Jeong, Seonhyang

AU - Kim, Hyunji

AU - Choi, Moon Jung

AU - Kwon, Hyeong Ju

AU - Jung, Sang Geun

AU - Jo, Young Suk

N1 - Funding Information: J L was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2020R1A2C1006047). S G J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2018R1D1A1B07045227). Y S J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2018R1A2B6004179). The authors would like to thank Ji Young Kim (Severance Hospital), Hwanju Lee (Severance Hospital), Hee Chang Yu (Severance Hospital), and Hoyoung Kim (Severance Hospital) for technical support. Funding Information: J L was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2020R1A2C1006047). S G J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2018R1D1A1B07045227). Y S J was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MS 阀T) (NRF-2018R1A2B6004179). Publisher Copyright: © 2020 European Society of Endocrinology Printed in Great Britain.

PY - 2020/6

Y1 - 2020/6

N2 - Objective: The characteristics of metastatic lymph nodes (MLNs) have been investigated as important predictors of recurrence and progression in papillary thyroid cancer (PTC). However, clinically applicable risk stratification systems are limited to the assessment of size and number of MLNs. This study investigated the predictive value of detailed characteristics of MLNs in combination with currently used risk stratification systems. Design and methods: We retrospectively characterized 2811 MLNs from 9014 harvested LNs of 286 patients with N1 PTC according to the maximum diameter of MLN (MDLN), maximum diameter of metastatic focus (MDMF), ratio of both diameters (MDMFR), lymph node ratio (LNR, number of MLNs/number of total harvested LNs), presence of extranodal extension (ENE), desmoplastic reaction (DR), cystic component, and psammoma body. Results: Factors related to the size and number of MLNs were associated with increased risk of recurrence and progression. Extensive presence of ENE (>40%) and DR (≥50%) increased the risk of recurrence/progression. The combination of MDLN, LNR, ENE, and DR had the highest predictive value among MLN characteristics. Combination of these parameters with ATA risk stratification or 1-year response to therapy improved the predictive power for recurrence/progression from a Harrell's C-index of 0.781 to 0.936 and 0.867 to 0.960, respectively. Conclusions: The combination of currently used risk stratification systems with detailed characterization of MLNs may improve the predictive accuracy for recurrence/progression in N1 PTC patients.

AB - Objective: The characteristics of metastatic lymph nodes (MLNs) have been investigated as important predictors of recurrence and progression in papillary thyroid cancer (PTC). However, clinically applicable risk stratification systems are limited to the assessment of size and number of MLNs. This study investigated the predictive value of detailed characteristics of MLNs in combination with currently used risk stratification systems. Design and methods: We retrospectively characterized 2811 MLNs from 9014 harvested LNs of 286 patients with N1 PTC according to the maximum diameter of MLN (MDLN), maximum diameter of metastatic focus (MDMF), ratio of both diameters (MDMFR), lymph node ratio (LNR, number of MLNs/number of total harvested LNs), presence of extranodal extension (ENE), desmoplastic reaction (DR), cystic component, and psammoma body. Results: Factors related to the size and number of MLNs were associated with increased risk of recurrence and progression. Extensive presence of ENE (>40%) and DR (≥50%) increased the risk of recurrence/progression. The combination of MDLN, LNR, ENE, and DR had the highest predictive value among MLN characteristics. Combination of these parameters with ATA risk stratification or 1-year response to therapy improved the predictive power for recurrence/progression from a Harrell's C-index of 0.781 to 0.936 and 0.867 to 0.960, respectively. Conclusions: The combination of currently used risk stratification systems with detailed characterization of MLNs may improve the predictive accuracy for recurrence/progression in N1 PTC patients.

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U2 - 10.1530/EJE-20-0131

DO - 10.1530/EJE-20-0131

M3 - Article

C2 - 32487777

AN - SCOPUS:85085909190

SN - 0804-4643

VL - 183

SP - 83

EP - 93

JO - European Journal of Endocrinology

JF - European Journal of Endocrinology

IS - 1

ER -

Detailed characterization of metastatic lymph nodes improves the prediction accuracy of currently used risk stratification systems in N1 stage papillary thyroid cancer

Abstract

Bibliographical note

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UN SDGs

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