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Record W3086164260 · doi:10.1200/jco.20.01255

Survival in Patients With Brain Metastases: Summary Report on the Updated Diagnosis-Specific Graded Prognostic Assessment and Definition of the Eligibility Quotient

2020· article· en· W3086164260 on OpenAlexaff
Paul W. Sperduto, Shane Mesko, Jing Li, Daniel Cagney, Ayal A. Aizer, Nancy U. Lin, Eric Nesbit, Tim J. Kruser, Jason W. Chan, Steve Braunstein, Jessica Lee, John P. Kirkpatrick, Will Breen, Paul D. Brown, Diana D. Shi, Helen A. Shih, Hany Soliman, Arjun Sahgal, Ryan Shanley, William Sperduto, Emil Lou, Ashlyn S. Everett, Drexell H. Boggs, Laura Masucci, David Roberge, Jill Remick, Kristin A. Plichta, John M. Buatti, Supriya Jain, Laurie E. Gaspar, Cheng–Chia Wu, Tony J. C. Wang, John Bryant, Michael D. Chuong, Yi An, Veronica Chiang, Toshimichi Nakano, Hidefumi Aoyama, Minesh P. Mehta

Bibliographic record

VenueJournal of Clinical Oncology · 2020
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsCentre Hospitalier de l’Université de MontréalUniversity of TorontoSunnybrook Health Science Centre
FundersNational Center for Advancing Translational SciencesNational Cancer Institute
KeywordsMedicineInternal medicineOncologyBrain metastasisLung cancerClinical trialOverall survivalCancerMetastasis

Abstract

fetched live from OpenAlex

PURPOSE: Conventional wisdom has rendered patients with brain metastases ineligible for clinical trials for fear that poor survival could mask the benefit of otherwise promising treatments. Our group previously published the diagnosis-specific Graded Prognostic Assessment (GPA). Updates with larger contemporary cohorts using molecular markers and newly identified prognostic factors have been published. The purposes of this work are to present all the updated indices in a single report to guide treatment choice, stratify research, and define an eligibility quotient to expand eligibility. METHODS: A multi-institutional database of 6,984 patients with newly diagnosed brain metastases underwent multivariable analyses of prognostic factors and treatments associated with survival for each primary site. Significant factors were used to define the updated GPA. GPAs of 4.0 and 0.0 correlate with the best and worst prognoses, respectively. RESULTS: < .01) between subgroups. Survival has improved, but varies widely by GPA for patients with non-small-cell lung, breast, melanoma, GI, and renal cancer with brain metastases from 7-47 months, 3-36 months, 5-34 months, 3-17 months, and 4-35 months, respectively. CONCLUSION: Median survival varies widely and our ability to estimate survival for patients with brain metastases has improved. The updated GPA (available free at brainmetgpa.com) provides an accurate tool with which to estimate survival, individualize treatment, and stratify clinical trials. Instead of excluding patients with brain metastases, enrollment should be encouraged and those trials should be stratified by the GPA to ensure those trials make appropriate comparisons. Furthermore, we recommend the expansion of eligibility to allow for the enrollment of patients with previously treated brain metastases who have a 50% or greater probability of an additional year of survival (eligibility quotient > 0.50).

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)0.003
metaresearch head score (Gemma)0.011
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.152
GPT teacher head0.427
Teacher spread0.275 · 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
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

Citations467
Published2020
Admission routes1
Has abstractyes

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