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Record W4391953833 · doi:10.3390/cancers16050851

Stereotactic Body Radiotherapy for Extracranial Oligometastatic Disease from Head and Neck Primary Cancers: A Systematic Review and Meta-Analysis

2024· review· en· W4391953833 on OpenAlexaff
Adam Mutsaers, Aquila Akingbade, Alexander V. Louie, Badr Id Said, Liying Zhang, Ian Poon, Martin Smoragiewicz, Antoine Eskander, Irene Karam

Bibliographic record

VenueCancers · 2024
Typereview
Languageen
FieldMedicine
TopicHead and Neck Cancer Studies
Canadian institutionsLondon Health Sciences CentreUniversity of TorontoSunnybrook Health Science CentreWestern University
Fundersnot available
KeywordsMedicineMeta-analysisClinical endpointRadiation therapyRadiosurgeryPopulationProspective cohort studySurgeryInternal medicineOncologyRandomized controlled trialRadiology

Abstract

fetched live from OpenAlex

Introduction: Stereotactic body radiotherapy (SBRT) is increasingly used to treat disease in the oligometastatic (OM) setting due to mounting evidence demonstrating its efficacy and safety. Given the low population representation in prospective studies, we performed a systematic review and meta-analysis of outcomes of HNC patients with extracranial OM disease treated with SBRT. Methods: A systematic review was conducted with Cochrane, Medline, and Embase databases queried from inception to August 2022 for studies with extracranial OM HNC treated with stereotactic radiotherapy. Polymetastatic patients (>five lesions), mixed-primary cohorts failing to report HNC separately, lack of treatment to all lesions, nonquantitative endpoints, and other definitive treatments (surgery, conventional radiotherapy, and radioablation) were excluded. The meta-analysis examined the pooled effects of 12- and 24-month local control (LC) per lesion, progression-free survival (PFS), and overall survival (OS). Weighted random-effects were assessed using the DerSimonian and Laird method, with heterogeneity evaluated using the I2 statistic and Cochran Qtest. Forest plots were generated for each endpoint. Results: Fifteen studies met the inclusion criteria (639 patients, 831 lesions), with twelve eligible for quantitative synthesis with common endpoints and sufficient reporting. Fourteen studies were retrospective, with a single prospective trial. Studies were small, with a median of 32 patients (range: 6–81) and 63 lesions (range: 6–126). The OM definition varied, with a maximum of two to five metastases, mixed synchronous and metachronous lesions, and a few studies including oligoprogressive lesions. The most common site of metastasis was the lung. Radiation was delivered in 1–10 fractions (20–70 Gy). The one-year LC (LC1), reported in 12 studies, was 86.9% (95% confidence interval [CI]: 79.3–91.9%). LC2 was 77.9% (95% CI: 66.4–86.3%), with heterogeneity across studies. PFS was reported in five studies, with a PFS1 of 43.0% (95% CI: 35.0–51.4%) and PFS2 of 23.9% (95% CI: 17.8–31.2%), with homogeneity across studies. OS was analyzed in nine studies, demonstrating an OS1 of 80.1% (95% CI: 74.2–85.0%) and OS2 of 60.7% (95% CI: 51.3–69.4%). Treatment was well tolerated with no reported grade 4 or 5 toxicities. Grade 3 toxicity rates were uniformly below 5% when reported. Conclusions: SBRT offers excellent LC and promising OS, with acceptable toxicities in OM HNC. Durable PFS remains rare, highlighting the need for effective local or systemic therapies in this population. Further investigations on concurrent and adjuvant therapies are warranted.

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)0.015
metaresearch head score (Gemma)0.030
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.030
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0180.039
Bibliometrics0.0090.010
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.092
GPT teacher head0.399
Teacher spread0.307 · 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 designMeta-analysis
Domainnot available
GenreReview

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

Citations5
Published2024
Admission routes1
Has abstractyes

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