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Record W4399304380 · doi:10.3390/curroncol31060233

Osteolytic Bone Metastasis: Different Radiotherapy Fractionation Schedules Compared Clinically and Radiographically

2024· article· en· W4399304380 on OpenAlexvenueno aff
Zoi Liakouli, Anna Zygogianni, Ioannis Georgakopoulos, Kyriaki Mystakidou, John Kouvaris, Christos Antypas, Maria Nikoloudi, Vassilis Kouloulias

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHounsfield scaleRadiation therapyBone metastasisFractionationNuclear medicineMetastasisSurgeryInternal medicineCancerComputed tomography

Abstract

fetched live from OpenAlex

The purpose of this study is to compare three commonly used radiotherapy fractionation schedules for bone metastasis in terms of clinical and radiological effectiveness. A total of 93 patients with osteolytic bone metastasis were randomized to receive 8 Gyin a single fraction (group A), 20 Gy in 5 fractions (group B) and 30 Gy in 10 fractions (group C). Changes in bone density were measured using the Relative Electron Density (RED) type corrected by Thomas (pe = HU/1.950 + 1.0), where HU is Hounsfield Units. Pain response was assessed according to the Brief Pain Inventory tool. Quality of life was estimated using the EORTC QLQ-C30 and the MD Anderson Symptom (MDAS) tools.After RT, RED, together with the parameters of EORTC QLQ-C30, MDAS and SAT, significantly increased in all groups (p < 0.001).Specifically, the increase of RED was higher in group C compared to group Athree months post-RT (p = 0.014). Group C was also superior to group A in terms of QoL and BPI three months post-treatment. Multifractionated radiotherapy for osteolytic bone metastasis is superior to single fraction radiotherapy in terms of improvement in quality of life and bone remineralization three months post-RT.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.095
GPT teacher head0.432
Teacher spread0.337 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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