MétaCan
Menu
Back to cohort
Record W4296067450 · doi:10.3171/2022.7.jns22752

Imaging-defined necrosis after treatment with single-fraction stereotactic radiosurgery and immune checkpoint inhibitors and its potential association with improved outcomes in patients with brain metastases: an international multicenter study of 697 patients

2022· article· en· W4296067450 on OpenAlexaff
Eric J. Lehrer, Manmeet S. Ahluwalia, Jason Gurewitz, Kenneth Bernstein, Douglas Kondziolka, Ajay Niranjan, Zhishuo Wei, L. Dade Lunsford, Kareem Fakhoury, Chad G. Rusthoven, David Mathieu, Claire Trudel, Timothy D. Malouff, Henry Ruiz-García, Phillip A. Bonney, Lindsay Hwang, Cheng‐Ping Yu, Gabriel Zada, Samir Patel, Christopher P. Deibert, Piero Picozzi, Andrea Franzini, Luca Attuati, Rahul N. Prasad, Raju R. Raval, Joshua D. Palmer, Cheng‐Chia Lee, Huai‐Che Yang, Brianna M. Jones, Sheryl Green, Jason P. Sheehan, Daniel M. Trifiletti

Bibliographic record

VenueJournal of neurosurgery · 2022
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsUniversity of AlbertaUniversité de Sherbrooke
Fundersnot available
KeywordsMedicineRadiosurgeryProportional hazards modelRetrospective cohort studyInternal medicineOncologyCohortLung cancerClinical trialRadiation therapyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Immune checkpoint inhibitors (ICIs) and stereotactic radiosurgery (SRS) are commonly utilized in the management of brain metastases. Treatment-related imaging changes (TRICs) are a frequently observed clinical manifestation and are commonly classified as imaging-defined radiation necrosis. However, these findings are not well characterized and may predict a response to SRS and ICIs. The objective of this study was to investigate predictors of TRICs and their impact on patient survival. METHODS: This retrospective multicenter cohort study was conducted through the International Radiosurgery Research Foundation. Member institutions submitted de-identified clinical and dosimetric data for patients with non-small cell lung cancer (NSCLC), melanoma, and renal cell carcinoma (RCC) brain metastases that had been treated with SRS and ICIs. Data were collected from March 2020 to February 2021. Univariable and multivariable Cox and logistic regression analyses were performed. The Kaplan-Meier method was used to evaluate overall survival (OS). The diagnosis-specific graded prognostic assessment was used to guide variable selection. TRICs were determined on the basis of MRI, PET/CT, or MR spectroscopy, and consensus by local clinical providers was required. RESULTS: The analysis included 697 patients with 4536 brain metastases across 11 international institutions in 4 countries. The median follow-up after SRS was 13.6 months. The median age was 66 years (IQR 58-73 years), 54.1% of patients were male, and 57.3%, 36.3%, and 6.4% of tumors were NSCLC, melanoma, and RCC, respectively. All patients had undergone single-fraction radiosurgery to a median margin dose of 20 Gy (IQR 18-20 Gy). TRICs were observed in 9.8% of patients. The median OS for all patients was 24.5 months. On univariable analysis, Karnofsky Performance Status (KPS; HR 0.98, p < 0.001), TRICs (HR 0.67, p = 0.03), female sex (HR 0.67, p < 0.001), and prior resection (HR 0.60, p = 0.03) were associated with improved OS. On multivariable analysis, KPS (HR 0.98, p < 0.001) and TRICs (HR 0.66, p = 0.03) were associated with improved OS. A brain volume receiving ≥ 12 Gy of radiation (V12Gy) ≥ 10 cm3 (OR 2.78, p < 0.001), prior whole-brain radiation therapy (OR 3.46, p = 0.006), and RCC histology (OR 3.10, p = 0.01) were associated with an increased probability of developing TRICs. The median OS rates in patients with and without TRICs were 29.0 and 23.1 months, respectively (p = 0.03, log-rank test). CONCLUSIONS: TRICs following ICI and SRS were associated with a median OS benefit of approximately 6 months in this retrospective multicenter study. Further prospective study and additional stratification are needed to validate these findings and further elucidate the role and etiology of this common clinical scenario.

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 score0.009
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.009
GPT teacher head0.231
Teacher spread0.223 · 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

Citations23
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueJournal of neurosurgerySame topicBrain Metastases and TreatmentFrench-language works237,207