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P1-10-05: Is the 21-Gene Breast Cancer Test (Oncotype DX®) Cost-Effective?

2011· article· en· W2004520887 on OpenAlexaboutno aff
P. Pronzato, J Plun-Favreau

Bibliographic record

VenueCancer Research · 2011
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineBreast cancerConcordanceChecklistOncologyStage (stratigraphy)GynecologyTest (biology)Family medicineInternal medicineCancer

Abstract

fetched live from OpenAlex

Abstract Background: The Oncotype DX® Breast Cancer Test is a validated 21-gene assay that predicts 10 year risk of recurrence and the likelihood of benefit from adjuvant chemotherapy in early-stage, node-negative ER+ breast cancer. The cost-effectiveness of using Oncotype DX® has been published in several countries but to date, there hasn't been any review of these studies. Materials and methods: The electronic database Pubmed and a selection of congress databases were searched using combinations of search terms designed to identify publications describing cost-effectiveness analyses of Oncotype DX®in early stage breast cancer patients. Searches were limited to those published in the English language between January 2001 and April 2011. All records were screened for inclusion in the review. The methodological quality of selected publications was assessed using the 35 items methodological checklist from Drummond et al (1996). Results: Five published health economics analyses and 3 abstracts (two posters and an oral presentation) were identified. The studies were carried out in several countries (US (2), Canada (2), Japan, Israel, Singapore and Hungary and have used a Markov modelling approach based on data from a large multicentre trial (e.g. NSABP B-20) to make estimates of long-term outcomes, and assess the cost-effectiveness of using the Oncotype DX® recurrence score in patients classified as having a high or low risk of distant recurrence using other methods of assessment. All studies were carried out in the perspective of the healthcare payer, and therefore did not consider broader costs to the patients and the society. Study comparators, costs, characteristics of the population receiving the test and impact of using the Oncotype DX® results on treatment decisions were adapted to each individual country clinical practice explaining the large range of cost-effectiveness results from these studies. In the US, using Oncotype DX® was shown to be cost-saving when in one of the Canadian studies, it was likely to be cost-effective (incremental cost-effectiveness ratio of $64,063 per QALY gained). Consistently across all five studies, use of Oncotype DX® was projected to improve survival (where reported), quality-adjusted life expectancy and to reduce chemotherapy costs versus comparators. When looking at the methodological quality of studies, they generally scored well with positive responses to 24 or more of the 35 questions on reporting. The exception was the Lyman et al. (US) paper where only 17 positive responses were recorded. The two posters, as expected scored lower than the full scale articles with positive responses of 15 and 18 out of 35 items. Conclusions: Published literature to date is of good methodological quality and consistently supports the cost-effectiveness of using Oncotype DX® in the various settings. Further analyses should be carried on to assess the budget impact of funding Oncotype DX® and to include a broader perspective of the costs. Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P1-10-05.

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)0.029
metaresearch head score (Gemma)0.150
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: Empirical · Consensus signal: none
Teacher disagreement score0.029
Threshold uncertainty score0.151

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0290.150
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.010
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0050.003
Open science0.0020.001
Research integrity0.0040.002
Insufficient payload (model declined to judge)0.0170.001

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 head0.607
GPT teacher head0.535
Teacher spread0.072 · 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

Citations3
Published2011
Admission routes1
Has abstractyes

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