Prolaris Cell Cycle Progression Test for Localized Prostate Cancer: A Health Technology Assessment.
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,034 | 0,156 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,014 |
| Bibliométrie | 0,025 | 0,017 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».