MétaCan
Menu
Back to cohort
Record W2949869070 · doi:10.1001/jamaoto.2019.1186

Occult Nodal Disease and Occult Extranodal Extension in Patients With Oropharyngeal Squamous Cell Carcinoma Undergoing Primary Transoral Robotic Surgery With Neck Dissection

2019· article· en· W2949869070 on OpenAlexaffabout
Caitlin McMullen, Jonathan Garneau, Emillie Weimar, Sana Ali, Joaquim M. Farinhas, Eugene Yu, Peter M. Som, C. Sarta, David P. Goldstein, Susie Su, Wei Xu, Richard V. Smith, Brett A. Miles, John R. de Almeida

Bibliographic record

VenueJAMA Otolaryngology–Head & Neck Surgery · 2019
Typearticle
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineOccultNeck dissectionTransoral robotic surgerySurgeryDissection (medical)RadiologyCancerGeneral surgeryInternal medicinePathology

Abstract

fetched live from OpenAlex

IMPORTANCE: The historically reported rates of subclinical cervical nodal metastases in oropharyngeal squamous cell carcinoma (OPSCC) predate the emergence of human papillomavirus as the predominant causative agent. The rate of occult nodal disease with changing etiology of OPSCC is not known, and it is challenging to anticipate which patients will be upstaged postoperatively and will require adjuvant therapy. OBJECTIVE: To assess the rate of nodal upstaging and occult extranodal extension (ENE) in a multi-institutional population of patients with pathologic (p)T1-2 OPSCC treated by transoral robotic surgery and neck dissection. DESIGN, SETTING AND PARTICIPANTS: This retrospective, multicenter cohort study of 92 participants at 2 US institutions (Albert Einstein College of Medicine, Bronx, New York [n = 38], and Icahn School of Medicine at Mount Sinai, New York, New York [n = 39]) and 1 Canadian institution (Princess Margaret Hospital, Toronto [n = 15]) examined the rate of postoperative pathologic upstaging for 92 patients with pT1-2 OPSCC undergoing transoral robotic surgery with neck dissection from August 2007 to December 2016. A neuroradiologist at each site blinded to final pathologic diagnosis reviewed preoperative imaging; these findings were compared with operative pathology and applied for tumor staging using the eighth edition of the American Joint Committee on Cancer Cancer Staging Manual. The statistical analysis was performed on December 18, 2018. MAIN OUTCOMES AND MEASURES: Occult pathologic nodal disease and change in nodal category postoperatively. RESULTS: Of 92 patients who met the inclusion criteria, 76 (83%) were male, and they had a mean (SD) age at surgery of 59.5 (10.5) years; 70 patients (84%) with available p16 status were positive. Five of 18 patients (28%) who had no evidence of nodal disease on imaging had occult pathologic nodal disease. Seven of 32 patients (22%) presenting with no nodal disease or with a single metastatic node on imaging received pathologic upstaging because of multiple positive nodes, indicating implementation of additional adjuvant treatment not anticipated after a priori imaging. Changes included 12 patients (13%) who had pathologic nodal upstaging and 12 (13%) with pathologic nodal downstaging in the eighth edition of staging. In the cohort, 24 patients (27%) had pathologic ENE, and 5 of 39 patients (13%) had occult ENE in the absence of radiographic evidence. CONCLUSIONS AND RELEVANCE: Predicting pathologic staging preoperatively for patients with OPSCC undergoing transoral robotic surgery and neck dissection remains a challenge. Although nodal size, tumor size, and location do not help predict ENE, the presence of nodes on imaging and nodal category may help predict ENE. Our findings suggest a small proportion of patients might benefit from further adjuvant therapies not predicted by preoperative imaging based on occult nodal upstaging and ENE.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.220
Teacher spread0.208 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations32
Published2019
Admission routes2
Has abstractyes

Explore more

Same venueJAMA Otolaryngology–Head & Neck SurgerySame topicHead and Neck Cancer StudiesFrench-language works237,207