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Record W3012698182 · doi:10.1186/s13014-020-1484-9

Validation of the graded prognostic assessment for gastrointestinal cancers with brain metastases (GI-GPA)

2020· article· en· W3012698182 on OpenAlexaboutno aff
Carsten Nieder, Mandy Hintz, Ilinca Popp, Angelika Bilger, Anca‐Ligia Grosu

Bibliographic record

VenueRadiation Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
FundersUniversitetet i Tromsø
KeywordsMedicineInternal medicineRadiation therapyOverall survivalRetrospective cohort studyOncologySurgery

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to validate a new prognostic model (GI-GPA) originally derived from a multi-center database (USA, Canada, Japan). PATIENTS AND METHODS: This retrospective study included 92 German and Norwegian patients treated with individualized approaches, always including brain radiotherapy. Information about age, extracranial spread, number of brain metastases, performance status and other variables was collected. The GI-GPA score was calculated as described by Sperduto et al. RESULTS: Median survival was 4 months. The corresponding figures for the 4 different prognostic strata were 2.3, 4.4, 9.4 and 12.7 months, respectively (p = 0.0001). Patients whose management included surgical resection had longer median survival than those who were treated with other approaches (median 11.9 versus 3.0 months, p = 0.002). Comparable results were seen for additional systemic therapy (median 8.5 versus 3.5 months, p = 0.01). CONCLUSION: These results confirm the validity of the GI-GPA in an independent dataset from a different geographical region, despite the fact that overall survival was shorter in all prognostic strata, compared to Sperduto et al. Potential explanations include differences in molecular tumor characteristics and treatment selection, both brain metastases-directed and extracranially. Long-term survival beyond 5 years is possible in a small minority of patients.

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 score0.112
Threshold uncertainty score0.262

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 head0.035
GPT teacher head0.343
Teacher spread0.309 · 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
Published2020
Admission routes1
Has abstractyes

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