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Record W2301392582 · doi:10.1177/0194599816636812

Salivary Duct Carcinoma of the Parotid

2016· article· en· W2301392582 on OpenAlexaff
Matthew Mifsud, Saurabh Sharma, Marino E. Leon, Tapan Padhya, Kristen J. Otto, Jimmy J. Caudell

Bibliographic record

VenueOtolaryngology · 2016
Typearticle
Languageen
FieldMedicine
TopicSalivary Gland Tumors Diagnosis and Treatment
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineSalivary duct carcinomaRadiation therapyUnivariate analysisChemotherapyMalignancyOncologyCarcinomaAdjuvant radiotherapyInternal medicineSurgeryMultivariate analysis

Abstract

fetched live from OpenAlex

OBJECTIVE: Salivary duct carcinoma (SDC) is a rare and aggressive malignancy for which an optimal treatment algorithm is lacking. We endeavored to assess the current treatment outcomes for SDC with a multimodality treatment approach combining surgery with adjuvant radiotherapy ± concurrent chemotherapy. STUDY DESIGN: Case series with chart review. SETTING: A National Cancer Institute-designated comprehensive cancer center. SUBJECTS AND METHODS: The clinical record of 17 patients with salivary duct carcinoma were analyzed to assess locoregional control, recurrence-free survival, and overall survival. RESULTS: All SDC cases (n = 17) were managed with surgical resection, followed by adjuvant radiotherapy (47.1%) or concurrent chemotherapy and radiotherapy (52.9%). Median patient follow up was 37 months. An aggressive disease course was generally observed, with 3-year recurrence-free survival and overall survival of 34.4% and 35.5%, respectively. The majority of recurrences were distant. Intensification with adjuvant concurrent chemotherapy was not associated with improved outcomes on univariate survival analysis. CONCLUSION: For salivary duct carcinoma, a multimodality treatment approach is associated with acceptable locoregional control rates but poor distant control and overall survival. Novel systemic therapies may be needed to optimize clinical outcomes.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.510

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.239
Teacher spread0.226 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations20
Published2016
Admission routes1
Has abstractyes

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