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Record W4405737752 · doi:10.3390/curroncol31120598

Metabolic Complete Response of Metastatic Oncogene-Negative, PDL1-Negative Non-Small Cell Lung Cancer After Chemo-Immunotherapy and Radiotherapy: A Case Report

2024· article· en· W4405737752 on OpenAlexvenueno aff
Alessia Surgo, Valerio Davì, Maria Paola Ciliberti, Roberta Carbonara, Morena Caliandro, F.C. Di Guglielmo, Nicola Sasso, Roberto Calbi, Maria Annunziata Gentile, Tiziana Talienti, Isabella Bruno, Michele Troia, Ilaria Bonaparte, Giuseppe Mario Ludovico, Giammarco Surico, Alba Fiorentino

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicBrain Metastases and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineImmunotherapyRadiation therapyAtezolizumabLung cancerRegimenInternal medicineOncologyChemotherapyCancerNivolumab

Abstract

fetched live from OpenAlex

A 71-year-old male ex-smoker presented in October 2021 to our department with a brain and bone metastatic adenocarcinoma NSCLC. PDL1, ROS, EGFR, and ALK were negative. He underwent stereotactic radiotherapy for brain metastases. In November 2021, he started a chemotherapy (CHT) regimen with cisplatin (75 mg/m2 every 21 days) and pemetrexed (500 mg/m2 every 21 days), and ICI with Atezolizumab (1200 mg every 21 days). In July 2022, RT to the lung tumor and mediastinal nodal was performed with a total dose of 45 Gy in 15 fractions. He continued with immunotherapy until December 2022, when a grade 3–4 toxicity from immunotherapy was observed (hypothyroidism, psoriasis, and cystitis). He achieved a complete clinical response to the therapy. To date, the patient is alive, with a complete metabolic response, without treatment at 37 months from diagnosis.

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)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.060
GPT teacher head0.397
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 designCase report
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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