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Record W4298422982

Prolaris Cell Cycle Progression Test for Localized Prostate Cancer: A Health Technology Assessment.

2017· review· en· W4298422982 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed · 2017
Typereview
Languageen
FieldMedicine
TopicProstate Cancer Diagnosis and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsProstate cancerMedicineGrading (engineering)Test (biology)Critical appraisalRisk assessmentHealth careOncologyInternal medicineCancerGynecologyMedical physicsPathologyAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

BACKGROUND: Prostate cancer is very common and many localized tumours are non-aggressive. Determining which cancers are aggressive is important for choosing the most appropriate treatment (e.g., surgery, radiation, active surveillance). Current clinical risk stratification is reliable in forecasting the prognosis of groups of men with similar clinical and pathologic characteristics, but there is residual uncertainty at the individual level. The Prolaris cell cycle progression (CCP) test, a genomic test that estimates how fast tumour cells are proliferating, could potentially be used to improve the accuracy of individual risk assessment. This health technology assessment sought to determine the clinical utility, economic impact, and patients' perceptions of the value of the CCP test in low- and intermediate-risk localized prostate cancer. METHODS: We conducted a systematic review of the clinical and economic evidence of the CCP test in low-and intermediate-risk, localized prostate cancer. Medical and health economic databases were searched from 2010 to June or July 2016. The critical appraisal of the clinical evidence included risk of bias and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We also analyzed the potential budget impact of adding the CCP test into current practice, from the perspective the Ontario Ministry of Health and Long-Term Care. Finally, we conducted qualitative interviews with men with prostate cancer, on the factors that influenced their treatment decision-making. RESULTS: For the review of clinical effectiveness, we screened 3,021 citations, and two before-after studies met our inclusion criteria. In one study, the results of the CCP test appeared to change the treatment plan (from initial to final plan) in 64.9% of cases overall (GRADE rating of the quality of evidence: Very low). In the other study, the CCP test changed the treatment received in nearly half of cases overall, compared with the initial plan (GRADE: Very low). No evidence was available on clinical outcomes of patients whose treatment was informed by CCP results. For the review of cost-effectiveness, 100 citations were identified and screened. No studies met the inclusion criteria. In our economic evaluation, we estimated that publicly funding the CCP test would result in a total net budget impact of $41.3 million in the first 5 years, mostly due to the cost of the CCP test. In our model, the relatively small cost savings ($7.3 million) due to treatment change (increased use of active surveillance and decreased use of interventional treatment) was not large enough to offset the high cost of the test. Patients viewed the test as potentially helpful but, due to the complexity of treatment decision-making, were unsure the test would ultimately change their treatment choices. CONCLUSIONS: We found no evidence to demonstrate the impact of the Prolaris CCP test on patient-important clinical outcomes. The limited evidence available shows that the test appears to provide information that, when considered in addition to clinical risk stratification, may change the treatment plan or actual treatment for some low- and intermediate-risk prostate cancer patients. As a result, there is insufficient data to inform the cost-effectiveness of the CCP test. Publicly funding the CCP test would result in a large incremental cost to the provincial budget.

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)0.034
metaresearch head score (Gemma)0.156
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.034
Threshold uncertainty score0.180

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0340.156
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.014
Bibliometrics0.0250.017
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0030.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.080
GPT teacher head0.427
Teacher spread0.347 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations38
Published2017
Admission routes1
Has abstractyes

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