Literature DB >> 26965699

Interobserver Agreement Between Pathologists Assessing Tumor-Infiltrating Lymphocytes (TILs) in Breast Cancer Using Methodology Proposed by the International TILs Working Group.

Shannon K Swisher1, Yun Wu2, Carlos A Castaneda3, Genvieve R Lyons4, Fei Yang5, Coya Tapia5, Xiuhong Wang2, Sandro A A Casavilca6, Roland Bassett4, Miluska Castillo3, Aysegul Sahin2, Elizabeth A Mittendorf7.   

Abstract

BACKGROUND: The presence of tumor-infiltrating lymphocytes (TILs) in breast tumors is prognostic and predictive, suggesting that TILs may be an important biomarker. Recently, an international TILs working group formulated consensus recommendations for TIL evaluation. The current study was performed to determine interobserver agreement using that methodology.
METHODS: Tumor-infiltrating lymphocytes were assessed on a single hematoxylin and eosin (H&E)-stained slide obtained from the core biopsy of 75 triple-negative breast cancers. Four pathologists independently reviewed each slide and evaluated stromal TILs (sTILs) and intratumoral TIL (iTILs). The kappa statistic was used to estimate interobserver agreement for identification of sTILs, and the intraclass correlation coefficient (ICC) was used to estimate the agreement among observers for iTILs. Cases with poor agreement were reviewed to identify pathologic factors that may contribute to the lack of agreement.
RESULTS: The kappa statistic for sTIL evaluation was 0.57 (standard error, 0.04). For iTILs, the ICC calculated to determine internal consistency within raters was 0.65 (95 % confidence interval [CI] 0.56-0.74; p < 0.0001), and the ICC calculated to determine agreement among raters was 0.62 (95 % CI 0.50-0.72; p < 0.0001). In 10 cases (13 %), there was not agreement between three of four pathologists. The pathologic features contributing to difficulty in TIL enumeration included marked individual tumor cell necrosis or apoptosis, the presence of reactive plasma cells mimicking tumor cells, plasmatoid tumor cells, and accurate quantification of TILs in specimens with focal areas of heavy immune infiltrate.
CONCLUSION: Acceptable agreement in TIL enumeration was observed, suggesting that the proposed methodology can be used to facilitate the use of TILs as a biomarker in research and clinical trial settings.

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Year:  2016        PMID: 26965699     DOI: 10.1245/s10434-016-5173-8

Source DB:  PubMed          Journal:  Ann Surg Oncol        ISSN: 1068-9265            Impact factor:   5.344


  30 in total

Review 1.  The Multifaceted Nature of Tumor Microenvironment in Breast Carcinomas.

Authors:  Laura Annaratone; Eliano Cascardi; Elena Vissio; Ivana Sarotto; Ewa Chmielik; Anna Sapino; Enrico Berrino; Caterina Marchiò
Journal:  Pathobiology       Date:  2020-04-23       Impact factor: 4.342

2.  Reliability of tumor-infiltrating lymphocyte and tertiary lymphoid structure assessment in human breast cancer.

Authors:  Laurence Buisseret; Christine Desmedt; Soizic Garaud; Marco Fornili; Xiaoxiao Wang; Gert Van den Eyden; Alexandre de Wind; Sebastien Duquenne; Anais Boisson; Celine Naveaux; Francoise Rothé; Sandrine Rorive; Christine Decaestecker; Denis Larsimont; Martine Piccart-Gebhart; Elia Biganzoli; Christos Sotiriou; Karen Willard-Gallo
Journal:  Mod Pathol       Date:  2017-06-16       Impact factor: 7.842

3.  Tumor-infiltrating Lymphocytes Predict the Chemotherapeutic Outcomes in Patients with Stage IV Colorectal Cancer.

Authors:  Masatsune Shibutani; Kiyoshi Maeda; Hisashi Nagahara; Tatsunari Fukuoka; Yasuhito Iseki; Shinji Matsutani; Shinichiro Kashiwagi; Hiroaki Tanaka; Kosei Hirakawa; Masaichi Ohira
Journal:  In Vivo       Date:  2018 Jan-Feb       Impact factor: 2.155

4.  Is there value of tumor stromal infiltrating lymphocytes for response assessment to chemoradiation in esophageal squamous cell carcinoma?

Authors:  Xin Wang; Wang Jing; Steven H Lin
Journal:  Ann Transl Med       Date:  2019-12

5.  Agreement on Major Pathological Response in NSCLC Patients Receiving Neoadjuvant Chemotherapy.

Authors:  Annikka Weissferdt; Apar Pataer; Ara A Vaporciyan; Arlene M Correa; Boris Sepesi; Cesar A Moran; Ignacio I Wistuba; Jack A Roth; Jitesh Baban Shewale; John V Heymach; Neda Kalhor; Tina Cascone; Wayne L Hofstetter; J Jack Lee; Stephen G Swisher
Journal:  Clin Lung Cancer       Date:  2020-03-04       Impact factor: 4.785

6.  Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms.

Authors:  Katherine Elfer; Sarah Dudgeon; Victor Garcia; Kim Blenman; Evangelos Hytopoulos; Si Wen; Xiaoxian Li; Amy Ly; Bruce Werness; Manasi S Sheth; Mohamed Amgad; Rajarsi Gupta; Joel Saltz; Matthew G Hanna; Anna Ehinger; Dieter Peeters; Roberto Salgado; Brandon D Gallas
Journal:  J Med Imaging (Bellingham)       Date:  2022-07-27

7.  Deep Learning-Based Pathology Image Analysis Enhances Magee Feature Correlation With Oncotype DX Breast Recurrence Score.

Authors:  Hongxiao Li; Jigang Wang; Zaibo Li; Melad Dababneh; Fusheng Wang; Peng Zhao; Geoffrey H Smith; George Teodoro; Meijie Li; Jun Kong; Xiaoxian Li
Journal:  Front Med (Lausanne)       Date:  2022-06-14

Review 8.  [Standardized determination of tumor-infiltrating lymphocytes in breast cancer : A prognostic marker for histological diagnosis].

Authors:  C Denkert; S Loibl; J Budczies; S Wienert; F Klauschen
Journal:  Pathologe       Date:  2018-11       Impact factor: 1.011

9.  How the variability between computer-assisted analysis procedures evaluating immune markers can influence patients' outcome prediction.

Authors:  Marylène Lejeune; Benoît Plancoulaine; Nicolas Elie; Ramon Bosch; Laia Fontoura; Izar de Villasante; Anna Korzyńska; Andrea Gras Navarro; Esther Sauras Colón; Carlos López
Journal:  Histochem Cell Biol       Date:  2021-08-12       Impact factor: 4.304

10.  TILGen: A Program to Investigate Immune Targets in Breast Cancer Patients - First Results on the Influence of Tumor-Infiltrating Lymphocytes.

Authors:  Franziska Würfel; Ramona Erber; Hanna Huebner; Alexander Hein; Michael P Lux; Sebastian Jud; Anita Kremer; Hannah Kranich; Andreas Mackensen; Lothar Häberle; Carolin C Hack; Claudia Rauh; Marius Wunderle; Paul Gaß; Shahrooz Rabizadeh; Anna-Lisa Brandl; Hanna Langemann; Bernhard Volz; Naiba Nabieva; Rüdiger Schulz-Wendtland; Diana Dudziak; Matthias W Beckmann; Arndt Hartmann; Peter A Fasching; Matthias Rübner
Journal:  Breast Care (Basel)       Date:  2018-02-15       Impact factor: 2.860

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