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Record W4220928355 · doi:10.1080/13696998.2022.2053403

Total cost of testing for genomic alterations associated with next-generation sequencing versus polymerase chain reaction testing strategies among patients with metastatic non-small cell lung cancer

2022· article· en· W4220928355 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

VenueJournal of Medical Economics · 2022
Typearticle
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsGroup for Research in Decision Analysis
FundersJanssen Scientific Affairs
KeywordsMedicineKRASInternal medicineOncologyPersonalized medicinePolymerase chain reactionGenetic testingCancerBioinformaticsGeneGeneticsColorectal cancer

Abstract

fetched live from OpenAlex

BACKGROUND: To assess the total cost of testing associated with next-generation sequencing (NGS) versus polymerase chain reaction (PCR) testing strategies among patients with metastatic non-small cell lung cancer (mNSCLC) from a Medicare and US commercial payer's perspective. MATERIALS AND METHODS: A decision tree model considered testing for genomic alterations in EGFR, ALK, ROS1, BRAF, KRAS, MET, HER2, RET, NTRK1 among patients with newly diagnosed mNSCLC using (1) liquid or tissue biopsy NGS tests, (2) exclusionary mutation (KRAS) test followed by sequential PCR tests, (3) sequential PCR tests, or (4) hotspot panel PCR tests. The alteration test sequence followed clinical guideline recommendations. Inputs based on literature, expert opinion, or assumptions included prevalence of mNSCLC, proportion of patients using each testing strategy (50% NGS [90% tissue, 10% liquid], 10% exclusionary, 10% sequential, 30% hotspot), proportion testing positive for each genomic mutation, rebiopsy rates, and costs for testing and associated medical care. Time to appropriate targeted therapy initiation and total costs were calculated for NGS, each PCR testing strategy, and all PCR strategies combined. RESULTS: Among a hypothetical plan of 1,000,000 members (75% commercial, 25% Medicare), 1,119 patients were estimated to have mNSCLC and be eligible for testing. Estimated mean time to appropriate targeted therapy was 2 weeks for NGS and 6 weeks for PCR (sequential: 9 weeks, exclusionary: 8 weeks, hotspot: 3 weeks). Mean per patient costs were $4,932 for NGS and $6,605 for PCR (exclusionary: $5,563, sequential: $6,263, hotspot: $7,066). Per patient costs were higher from a commercial perspective (NGS: $6,225; PCR: $8,430) relative to Medicare (NGS: $2,099; PCR: $2,646); nevertheless, NGS was the least costly testing strategy across plan types. CONCLUSION: NGS was associated with the fastest time to appropriate targeted therapy initiation and lowest total cost of testing compared to PCR testing strategies for newly diagnosed patients with mNSCLC.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.193
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.057
GPT teacher head0.299
Teacher spread0.242 · 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