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Record W2110046944 · doi:10.1200/jco.2008.21.0534

Efficacy Does Not Necessarily Translate to Cost Effectiveness: A Case Study in the Challenges Associated With 21st-Century Cancer Drug Pricing

2009· letter· en· W2110046944 on OpenAlexaboutno aff
Bruce E. Hillner, Thomas J. Smith

Bibliographic record

VenueJournal of Clinical Oncology · 2009
Typeletter
Languageen
FieldMedicine
TopicCancer Treatment and Pharmacology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCancer drugsDrugDrug pricingCancerIntensive care medicineOncologyPharmacologyInternal medicineActuarial science

Abstract

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All countries are struggling with the financial burden associated with cancer and its treatment. Worldwide, drugs associated with cancer care are estimated to cost approximately $40 billion per year. In the United States, cancer drugs represent the second biggest category of overall pharmaceutical sales, growing at double the overall market; in 2007 alone, sales increased by approximately 14%. Seventy percent of these sales come from products introduced in the last decade and 30% in the last 5 years. Currently, there are about 100 new molecules in phase III trials. Remember that figure—100 new molecules. While Journal of Clinical Oncology (JCO) predominantly focuses on clinical advances, its readership and its editorial team are increasingly aware that economic evaluations have an important role in contributing to the overall evolution of cancer care. In this issue of JCO, Reed et al report a cost-effectiveness analysis based on a randomized trial previously reported in JCO that assessed ixabepilone plus capecitabine (I C) compared with capecitabine alone for patients with metastatic breast cancer progressing after anthracycline and taxane treatment. Herein, we try to interpret this report in light of the recent JCO editorial guidance. The first question is whether a clinical question is important, relevant, and timely. We believe the answer for I C is a resounding yes. This is another advance in treatment for patients with metastatic breast cancer, joining the taxanes, aromatase inhibitors, and targeted therapies. The rapid adoption of these therapies by cancer providers shows successful translation from effectiveness in the research setting to efficacy in the wider general population. Overall survival in patients with metastatic breast cancer is increasing. In British Columbia, overall survival improved from approximately 14.5 months for those diagnosed in 1991 to approximately 22 months for women diagnosed in 2001. Further increases are likely given the near-universal use of taxanes. While advanced breast cancer is not curable, many oncologists are suggesting that it should be considered a chronic disease, with patients potentially rotating thorough five or more types of treatment. Managing breast cancer as a chronic disease is both complex— especially when prior adjuvant therapies is considered—and expensive. For hormone receptor–negative or refractory human epidermal growth factor receptor 2–negative disease, the National Comprehensive Cancer Network preferred regimens include nine different single agents and nine different combination therapies. Despite these initial options, most patients and their oncologists have narrower choices if further therapy is considered after prior treatment with anthracyclines and taxanes. For this situation, if treatment is offered, practice guidelines in the United States, Canada, and Britain all agree that singleagent capecitabine is the preferred therapy. Therefore, adding a drug like ixabepilone might help. Select clinical features and efficacy results from the reported randomized controlled trial of I C are noteworthy: patients were young (median age, 53 years), had good performance status, and the treatment was second line in approximately 50% and third line in 40%. Eighty-five percent of patients had received taxanes for metastatic disease, and in approximately 40%, progressive disease was the best response to prior taxanes. The primary end point of progressionfree survival improved by a median of 1.6 months (n 752) in the registration trial and 1.5 months (n 1,221) in the confirmatory trial. Overall survival increased by 1.8 and 0.8 months, respectively, but these were not statistically significant even in light of their sample sizes, and these data have only been only in abstract form. There are numerous strengths to the design, technical components, and data quality in the economic assessment. The investigators were academics not involved in the conduct of the trial, had negotiated full control of the design and reporting of the analysis, and had developed their analysis plan before trial completion. The investigators had access to patient level information relevant to medical resource use while on trial and some data after active treatment. Lastly, the economic analysis includes information excluded from the randomized clinical trial report on patient quality of life. The Health Utility Index is a widely use quality-of-life instrument to estimate the value of life in various health states. Therefore, different rates of costs and utility values were assigned to patients based on four levels of response to therapy. For the economic analysis, the investigators had to use a variety of survival projections since the data available was censored at the point of last follow-up (January 2007), and 36% of patients were alive. This common practice of a drug sponsor not sharing the most recent or complete data made modeling necessary and led to a less transparent report. In the model, Reed et al estimated an overall survival benefit of 2.0 months; this may be an overestimate by at least 10%. The authors did not account for the 17% of patients in the I C arm who got JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 27 NUMBER 13 MAY 1 2009

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)0.018
metaresearch head score (Gemma)0.078
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.078
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.002
Science and technology studies0.0030.003
Scholarly communication0.0050.005
Open science0.0010.002
Research integrity0.0060.006
Insufficient payload (model declined to judge)0.0080.001

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 head0.160
GPT teacher head0.504
Teacher spread0.344 · 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 designNot applicable
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".

Quick stats

Citations118
Published2009
Admission routes1
Has abstractyes

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