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Record W4400103914 · doi:10.3390/curroncol31070271

Durable Response to Atezolizumab in Extensive-Stage Small-Cell Lung Cancer Leading to 60 Months Overall Survival: A Case Report

2024· article· en· W4400103914 on OpenAlexaffvenue
Freeman Paczkowski, Jacques Raphael, Claire Browne

Bibliographic record

VenueCurrent Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsAtezolizumabMedicineStage (stratigraphy)Lung cancerOncologyLungCancerOverall survivalInternal medicineCancer researchImmunotherapyNivolumabBiology

Abstract

fetched live from OpenAlex

Small-cell lung cancer (SCLC) remains a disease with poor prognosis, particularly in extensive-stage SCLC (ES-SCLC). Current standard-of-care treatment includes chemotherapy with platinum agents and etoposide plus immunotherapy with atezolizumab or durvalumab, which has achieved a mean overall survival of 12-13 months in clinical trials. However, long-term survival in ES-SCLC, even with the addition of immunotherapy, continues to be rare. We present the case of a middle-aged male patient diagnosed with ES-SCLC who was treated with four cycles of induction chemotherapy (carboplatin and etoposide) and atezolizumab, starting maintenance atezolizumab every 21 days thereafter, and thoracic radiotherapy. After 9 months, he experienced mild disease progression and was rechallenged with six cycles of carboplatin and etoposide with continued atezolizumab. Subsequent imaging showed near-complete disease resolution which has been sustained since. He has continued on maintenance atezolizumab since diagnosis and has achieved 60 months overall survival and 44 months progression-free survival. Throughout treatment, he has maintained a high functional capacity and only experienced one immune-related adverse event. Our patient is representative of a small subset who are capable of achieving durable responses to immunotherapy and his case highlights the need for further research to elucidate the clinical and biological factors driving this response.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.822
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 integrity0.0000.001
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 head0.128
GPT teacher head0.485
Teacher spread0.357 · 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.

Study designNot applicable
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

Citations5
Published2024
Admission routes2
Has abstractyes

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