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Record W2990325986 · doi:10.1002/jso.25774

Association between patient age and the risk of mortality following local recurrence of a sacral chordoma

2019· article· en· W2990325986 on OpenAlexaff
Matthew T. Houdek, Mario Hevesi, Joseph H. Schwab, Michael J. Yaszemski, Anthony M. Griffin, John H. Healey, Peter C. Ferguson, Francis J. Hornicek, Patrick J. Boland, Franklin H. Sim, Peter S. Rose, Jay S. Wunder

Bibliographic record

VenueJournal of Surgical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsUniversity of TorontoMount Sinai Hospital
FundersNIH Clinical CenterNational Cancer InstituteWellcome Trust
KeywordsMedicineChordomaSacrumSurgeryOncologyInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Local recurrence (LR) of sacral chordoma is a difficult problem and the mortality risk associated with LR remains poorly described. The purpose of this study was to evaluate the risk of mortality in patients with LR and determine if patient age is associated with mortality. METHODS: A total of 218 patients (144 male, 69 female; mean age 59 ± 15 years) with sacrococcygeal chordomas were reviewed. Cumulative incidence functions and competing risks for death due to disease and nondisease mortality were employed to analyze mortality trends following LR. RESULTS: The 10-year overall survival (OS) was 55%. Patients with LR had 44% 10-year OS, similar to patients without (59%; P = .38). The 10-year OS between those less than 55 compared with ≥55 years were similar (69% vs 48%; P = .52). The 10-year death due to disease was worse in patients with LR compared with those without (44% vs 84%; P < .001). In patients without LR, patients ≥55 years were 1.6-fold more likely to experience death due to other causes. CONCLUSIONS: Patients with an LR are more likely to die due to disease. Advanced patient age was associated with higher all-cause mortality following resection of sacral chordoma. LR of chordoma was associated with increased disease-specific mortality, regardless of age.

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)0.001
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 score0.039
Threshold uncertainty score0.164

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.019
GPT teacher head0.313
Teacher spread0.294 · 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

Citations6
Published2019
Admission routes1
Has abstractyes

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