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Record W2048869426 · doi:10.1002/cncr.24833

Treatment of small‐cell lung cancer in elderly patients

2010· review· en· W2048869426 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCancer · 2010
Typereview
Languageen
FieldMedicine
TopicLung Cancer Research Studies
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineLung cancerRadiation therapyDiseaseStage (stratigraphy)PopulationChemotherapyRetrospective cohort studyCancerInternal medicineOncologyIntensive care medicineSurgery

Abstract

fetched live from OpenAlex

Small-cell lung cancer (SCLC) represents 15% to 20% of all lung carcinomas. Approximately 30% to 40% of these cases are diagnosed in patients older than 70 years of age. Staging of SCLC classifies patients as having either limited or extensive-stage disease. The standard treatment for limited-stage disease is platinum-based chemotherapy, combined with external-beam thoracic radiotherapy, whereas platinum-based regimens alone represent the standard of care for extensive-stage disease. In the elderly population, treatment of SCLC is more challenging given the decline in physiological organ reserve and the presence of comorbidities. The majority of data are drawn from retrospective studies, which are likely to suffer from selection bias. However, limited prospective data are available to guide treatment decisions in that special population. Nonetheless, these data demonstrate that standard approaches are feasible in carefully selected elderly patients. The purpose of this article is to review the currently available evidence on treatment of SCLC in patients older than 65-70 years of age.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
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)0.0000.000

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 head0.060
GPT teacher head0.432
Teacher spread0.373 · 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