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Record W2955092065 · doi:10.1186/s12885-019-5761-7

Distribution of lymph node metastases in esophageal carcinoma [TIGER study]: study protocol of a multinational observational study

2019· article· en· W2955092065 on OpenAlexaff
Eliza Hagens, Mark I. van Berge Henegouwen, Johanna W. van Sandick, Miguel A. Cuesta, Donald L. van der Peet, Joos Heisterkamp, Grard A. P. Nieuwenhuijzen, Camiel Rosman, Joris J. Scheepers, Meindert N. Sosef, Richard van Hillegersberg, Sjoerd M. Lagarde, Magnus Nilsson, Jari Räsänen, Philippe Nafteux, Piet Pattyn, Arnulf H. Hölscher, Wolfgang Schröder, Paul M. Schneider, C. Mariette, Carlo Castoro, Luigi Bonavina, Riccardo Rosati, Giovanni De Manzoni, Sandro Mattioli, Josep Roig García, Manuel Pera, S M Griffin, Paul M Wilkerson, M. Asif Chaudry, Bruno Sgromo, Olga Tucker, Edward Cheong, Krishna Moorthy, T. N. Walsh, John V. Reynolds, Yuji Tachimori, Haruhiro Inoue, Hisahiro Matsubara, Shin-ichi Kosugi, Haiquan Chen, Simon Law, C.S. Pramesh, Shailesh Puntambekar, Sudish C. Murthy, Philip A. Linden, Wayne L. Hofstetter, Madhan Kumar Kuppusamy, K. Robert Shen, Gail Darling, Flávio Sabino, Peter Grimminger, Sybren L. Meijer, Jacques Bergman, Maarten C.C.M. Hulshof, Hanneke W.M. van Laarhoven, Banafsche Mearadji, Roel J. Bennink, Jouke T. Annema, Marcel G. W. Dijkgraaf, Suzanne S. Gisbertz

Bibliographic record

VenueBMC Cancer · 2019
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsUniversity of Toronto
FundersMaag Lever Darm Stichting
KeywordsMedicineEsophagectomyLymphadenectomyLymph nodeEsophageal cancerCarcinomaLymphSurgical oncologyEsophagusRadiologyOncologyCancerInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: An important parameter for survival in patients with esophageal carcinoma is lymph node status. The distribution of lymph node metastases depends on tumor characteristics such as tumor location, histology, invasion depth, and on neoadjuvant treatment. The exact distribution is unknown. Neoadjuvant treatment and surgical strategy depends on the distribution pattern of nodal metastases but consensus on the extent of lymphadenectomy has not been reached. The aim of this study is to determine the distribution of lymph node metastases in patients with resectable esophageal or gastro-esophageal junction carcinoma in whom a transthoracic esophagectomy with a 2- or 3-field lymphadenectomy is performed. This can be the foundation for a uniform worldwide staging system and establishment of the optimal surgical strategy for esophageal cancer patients. METHODS: The TIGER study is an international observational cohort study with 50 participating centers. Patients with a resectable esophageal or gastro-esophageal junction carcinoma in whom a transthoracic esophagectomy with a 2- or 3-field lymphadenectomy is performed in participating centers will be included. All lymph node stations will be excised and separately individually analyzed by pathological examination. The aim is to include 5000 patients. The primary endpoint is the distribution of lymph node metastases in esophageal and esophago-gastric junction carcinoma specimens following transthoracic esophagectomy with at least 2-field lymphadenectomy in relation to tumor histology, tumor location, invasion depth, number of lymph nodes and lymph node metastases, pre-operative diagnostics, neo-adjuvant therapy and (disease free) survival. DISCUSSION: The TIGER study will provide a roadmap of the location of lymph node metastases in relation to tumor histology, tumor location, invasion depth, number of lymph nodes and lymph node metastases, pre-operative diagnostics, neo-adjuvant therapy and survival. Patient-tailored treatment can be developed based on these results, such as the optimal radiation field and extent of lymphadenectomy based on the primary tumor characteristics. TRIAL REGISTRATION: NCT03222895 , date of registration: July 19th, 2017.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.030
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Protocol · Consensus signal: Protocol
Teacher disagreement score0.030
Threshold uncertainty score0.159

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.016
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.003
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0070.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.095
GPT teacher head0.416
Teacher spread0.320 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations101
Published2019
Admission routes1
Has abstractyes

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