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Record W4388799845 · doi:10.14740/wjon1702

Osteoblastic Bone Reaction Developing During Treatment With Sintilimab and Bevacizumab in a Patient With <i>KRAS</i><sup>G12V</sup>-Mutant Lung Adenocarcinoma

2023· article· en· W4388799845 on OpenAlexvenueno aff
Changjun Chen, Xin Zhao, Jing Zhao, Jie Xiao, Wei Xu, Yu Bin Qi, Jing Kun Li, Qing Wei, Lei Zhang, Yun Yang

Bibliographic record

VenueWorld Journal of Oncology · 2023
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsnot available
FundersShandong First Medical UniversityNatural Science Foundation of Shandong ProvinceNational Natural Science Foundation of China
KeywordsMedicineBevacizumabAdenocarcinomaLung cancerLungAdenocarcinoma of the lungOncologyKRASOsteoblastChemotherapyInternal medicineCancer researchCancerPathology

Abstract

fetched live from OpenAlex

Osteoblastic bone reaction, the occurrence of new osteoblastic lesions, is a paradoxical phenomenon during the treatment of cancers and can be defined as disease progression or bone metastases. Osteoblastic bone reactions usually occur in patients who receive treatments such as chemotherapy or hormonal or targeted therapy; however, it is difficult to differentiate them from disease progression or an increase in osteoblastic activity in response to therapy. Although osteoblastic bone reaction in lung cancer has been described in a few reports, it has never been reported in patients with KRAS G12V -mutant lung adenocarcinoma treated with immunotherapy and antiangiogenesis. Here, we describe a case of a 77-year-old male with KRAS G12V -mutant lung adenocarcinoma whose osteoblastic bone response was found during treatment with sintilimab and bevacizumab. We showed the course of the disease as well as systematic imaging manifestations of lung cancer with osteoblastic bone reaction and discussed their mechanisms. World J Oncol. 2023;14(6):580-583 doi: https://doi.org/10.14740/wjon1702

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 score0.149
Threshold uncertainty score0.607

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.017
GPT teacher head0.284
Teacher spread0.268 · 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

Citations4
Published2023
Admission routes1
Has abstractyes

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