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Record W2102524820 · doi:10.1200/jco.2013.54.6002

Cost Effectiveness of Crizotinib for Anaplastic Lymphoma Kinase–Positive, Non–Small-Cell Lung Cancer: Who Is Going to Blink at the Cost?

2014· letter· en· W2102524820 on OpenAlexaboutno aff
Ronan J. Kelly, Bruce E. Hillner, Thomas J. Smith

Bibliographic record

VenueJournal of Clinical Oncology · 2014
Typeletter
Languageen
FieldMedicine
TopicLung Cancer Treatments and Mutations
Canadian institutionsnot available
FundersNational Center for Advancing Translational Sciences
KeywordsCrizotinibMedicineAnaplastic lymphoma kinaseLung cancerOncologyLymphomaCancer researchAnaplastic large-cell lymphomaInternal medicine

Abstract

fetched live from OpenAlex

In 2014, lung cancer is the poster child for personalized medicine, and identifying targetable oncogenic drivers is now considered standard of care in stage IV disease. The anaplastic lymphoma kinase (ALK) gene has emerged as an important oncogenic driver in a small population of patients with adenocarcinoma. Crizotinib has received accelerated US Food and Drug Administration approval when used in conjunction with its companion diagnostic test to identify patients with the EML4-ALK gene rearrangement. No one who treats patients with lung cancer questions the exciting results obtained with crizotinib, or the need for a highly specific test. A recent phase III study compared crizotinib with standard chemotherapy in patients with locally advanced or metastatic ALK-positive lung cancer who had received one previous platinum-based regimen. Everything favored crizotinib: median progression-free survival (PFS), 7.7 versus 3.0 months; response rate, 65% versus 20%; and symptoms and quality of life were also substantially better. Overall survival was not improved, but 64% of the group receiving chemotherapy crossed over to crizotinib. Two main questions remain unanswered: Can we afford to screen everyone with lung cancer, given that only 3% to 5% of the population will be ALK positive, and can we afford to pay for crizotinib? In the article prompting this editorial, Djalalov et al present their results of a cost-effectiveness analysis of both EML4-ALK fusion testing and first-line crizotinib using a Markov model in newly diagnosed, previously untreated patients with stage IV non–small-cell lung cancer (NSCLC) and nonsquamous histology. The authors compared strategies for treatment: crizotinib for patients who test ALK positive versus standard chemotherapy for those who test negative. The incremental cost-effectiveness ratio (ICER) or change in costs divided by the change in benefits is commonly used in health economics to provide a practical approach to decision making regarding health interventions. The costs are described in monetary units, whereas the benefits or effects on health status are measured in quality-adjusted life years (QALYs) gained or lost. Using a relative efficacy estimate in the first-line setting that was derived from the second-line phase III trial, the author’s projected that first-line crizotinib gives 0.64 years (7.7 months) extra survival, or 0.38 QALYs, at an additional cost of $95,000 compared with standard of care, leading to ICERs of $148,000 per additional life year, or $250,000/ QALY gained. The authors concluded that EML4-ALK fusion testing and crizotinib treatment for patients positive for ALK is not costeffective (from a Canadian perspective) because of the low biomarker frequency in the population—and the high drug costs. Are their conclusions valid, what do they mean, and is crizotinib affordable? The model seems valid. The authors simulated the clinical trial of what happens if patients positive for ALK start with crizotinib while we await the results of the ongoing first-line phase III PROFILE 1014 trial (A Clinical Trial Testing the Efficacy of Crizotinib Versus Standard Chemotherapy Pemetrexed Plus Cisplatin or Carboplatin in Patients With ALK Positive Nonsquamous Cancer of the Lung). In this analysis, all patients receive crizotinib (or do not, if ALK negative), then cisplatin plus gemcitabine, then second-line pemetrexed, then thirdline erlotinib, regardless of epidermal growth factor receptor status. The authors transform the added 0.64 years of life to 0.38 qualityadjusted years by assuming that the quality of life is only 3% better for patients receiving crizotinib compared with regular chemotherapy. This seems ungenerous, given the rapid and often dramatic symptom improvement seen in practice, which should translate into greater quality time while receiving the drug. Their test strategy for ALK assessment is efficient—a critically important aspect, given the need to screen 100 patients to find approximately three who test positive. The only US Food and Drug Administration–approved test is the Vysis LSI ALK Break Apart FISH Probe Kit (Abbott Molecular, Des Plaines, IL), with near 100% accuracy but at a cost of more than $250/test. The correlation of results of ALK immunohistochemistry (IHC) and ALK fluorescent in situ hybridization (FISH) are excellent, but IHC has not been validated as a predictive marker for response to an ALK inhibitor in a large patient cohort. The US guidelines state that ALK IHC, if carefully validated, may be considered for screening patients with lung adenocarcinoma. The authors used ALK IHC (approximately $40) with 95% sensitivity as their baseline, with subsequent verification with ALK FISH if needed. Djalalov et al indicate that EML4-ALK fusion testing with crizotinib treatment for patients positive for ALK “is not cost-effective in the setting of high drug costs and a low biomarker JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 32 NUMBER 10 APRIL 1 2014

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)0.007
metaresearch head score (Gemma)0.039
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: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.007
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.039
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.001
Research integrity0.0060.010
Insufficient payload (model declined to judge)0.0060.002

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 head0.077
GPT teacher head0.474
Teacher spread0.398 · 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
GenreCommentary

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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Citations17
Published2014
Admission routes1
Has abstractyes

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