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Record W2016112560 · doi:10.3111/13696998.2014.1003644

Brain metastases in patients with ALK+ non-small cell lung cancer: clinical symptoms, treatment patterns and economic burden

2015· article· en· W2016112560 on OpenAlexaff
Annie Guérin, Medha Sasané, Jie Zhang, Kenneth W. Culver, Katherine Dea, Roy Nitulescu, Eric Q. Wu

Bibliographic record

VenueJournal of Medical Economics · 2015
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsGroup for Research in Decision Analysis
Fundersnot available
KeywordsCrizotinibMedicineLung cancerAnaplastic lymphoma kinaseInternal medicineMedical diagnosisOncologyALK inhibitorBrain metastasisCeritinibCancerMetastasisRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: Brain metastases (BM) are highly prevalent among anaplastic lymphoma kinase positive (ALK+) non-small cell lung cancer (NSCLC) patients; yet little is known about their real-world treatment patterns and clinical and economic burdens. This study aimed to describe these patients' treatment patterns, symptoms, and costs. RESEARCH DESIGN AND METHODS: Retrospective study pooling data from three large administrative databases in the US (08/2011-06/2013). ALK+ NSCLC patients with BM and continuous enrollment for ≥ 60 days before and ≥ 30 days after the first observed BM diagnosis were identified by pharmacy records for crizotinib among patients with lung cancer and BM diagnostic codes. MAIN OUTCOME MEASURES: Treatment patterns, symptoms, healthcare resource utilization, and costs, before and after BM diagnosis. RESULTS: Of the 213 crizotinib patients with BM diagnoses meeting the selection criteria, 23.0% had BM prior to NSCLC diagnosis; 47.4% had BM prior to crizotinib initiation; 19.2% during crizotinib treatment; and 10.3% post-crizotinib treatment. For those diagnosed with BM after NSCLC diagnosis, the median time between the NSCLC and BM diagnoses was 88 days. Following the first observed BM diagnosis, 88.7% used chemotherapy, 63.4% had radiotherapy, and 31.9% had stereotactic radiosurgery. The prevalence of BM-related symptoms substantially increased post-BM-diagnosis: fatigue (from 15% to 39%), headaches (from 5% to 24%), and depression (from 5% to 15%). Monthly costs per patient averaged $5983 before the BM diagnosis and $22,645 after diagnosis. Patients' resource utilization increased significantly post-BM-diagnosis, with a 3-fold increase in OP visits and a 6-fold increase in IP stays. Post-BM-diagnosis costs were driven by pharmacy (42.0%), inpatient (29.6%), and outpatient costs (26.0%). LIMITATIONS: The study sample was limited to crizotinib-treated patients. CONCLUSIONS: Post-BM-diagnosis, patients experience high symptom burden. Post-BM-diagnosis, treatment is highly variable and costly: average monthly costs per patient almost quadrupled post-BM-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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.334
Teacher spread0.316 · 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 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

Citations101
Published2015
Admission routes1
Has abstractyes

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