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Prognostic impact of paraneoplastic syndromes in patients with small cell lung cancer, real-world data.

2019· article· en· W2947812531 on OpenAlexaff
Gabrielle LeBlanc, Normand Blais, Mustapha Tehfé, Bertrand Routy, Marie Florescu

Bibliographic record

VenueJournal of Clinical Oncology · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer Diagnosis and Treatment
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineInternal medicineImmunotherapyChemotherapyLimbic encephalitisCancerSmall-cell carcinomaLung cancerOncologySmall Cell Lung CarcinomaGastroenterologyAntibodyAutoantibodyImmunology

Abstract

fetched live from OpenAlex

e20082 Background: Small cell lung cancer (SCLC) remains an aggressive cancer, with a reported mOS of 15-20 mo when localized (L-SCLC) and 9-11 mo when extensive (E-SCLC). Paraneoplastic syndromes (PNS) are a debilitating condition either related to the embryogenic stem cell origin or to auto-immune antibodies produced against the tumor. These mechanisms may be even more relevant with the use of immunotherapy for first-line treatment of E-SCLC. Methods: We retrospectively reviewed our clinical database of patients diagnosed with SCLC between 2006 and 2017 at CHUM University Center. The primary outcome was to compare OS of patients with and without PNS in L-SCLC and E-SCLC. No patients received immunotherapy. Results: We identified 426 unselected SCLC patients, 39% L-SCLC and 61% E-SCLC. 84 patients (20%) were diagnosed with a PNS: 66 (15%) SIADH, 8 (2%) paraneoplastic Cushing syndromes, 2 (1%) humoral hypercalcemia and 8 (2%) paraneoplastic neurologic syndromes. 25% of patients with PNS vs 14% without PNS had a PS 3-4 and would not have been eligible to a clinical trial. 65% of patients with PNS received chemotherapy vs 63% without PNS. Neurologic PNS were all diagnosed in patients with L-SCLC. PNS affecting the central nervous system (4 limbic encephalitis and 1 cerebellar degeneration) were associated with a poorer prognosis than L-SCLC without PNS (mOS 3,5 mo vs 16,7 mo (p = 0,003)). The 2 patients with Lambert-Eaton myasthenic syndrome had a long survival (29 and 82 mo), but persistence of the neurologic symptoms. 86% of patients with paraneoplastic Cushing syndrome were diagnosed with an E-SCLC and had a worse prognosis than E-SCLC without PNS (mOS 1,1 mo vs 4,63 mo (p = 0,022)). SIADH had a significative poor impact on OS in patients with L-SCLC (mOS 10,1 mo vs 16,7 mo (p = 0,016)), but no impact in survival for patients with E-SCLC (mOS 3,63 mo vs 4,63 mo (p = 0,735)). Conclusions: PNS either in patients with L-SCLC or E-SCLC worsen the overall prognosis, except for Lambert-Eaton myasthenic syndrome. A more systematic detection of these syndromes is suggested before starting immunotherapy as first-line standard treatment for E-SCLC. Furthermore, this real-world unselected clinical cohort shows our E-SCLC patients have a worse prognosis than the clinical trial experience.

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)0.000
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 score0.023
Threshold uncertainty score0.449

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.104
GPT teacher head0.463
Teacher spread0.359 · 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".

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Citations4
Published2019
Admission routes1
Has abstractyes

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