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Enregistrement W2300594175 · doi:10.1200/jop.2015.007062

ReCAP: Oncologists’ Selection of Genetic and Molecular Testing in the Evolving Landscape of Stage II Colorectal Cancer

2016· article· en· W2300594175 sur OpenAlexaboutno aff
Aparna R. Parikh, Nancy L. Keating, Pang-Hsiang Liu, Stacy W. Gray, Carrie N. Klabunde, Katherine L. Kahn, David A. Haggstrom, Sapna Syngal, Benjamin Kim

Notice bibliographique

RevueJournal of Oncology Practice · 2016
Typearticle
Langueen
DomaineMedicine
ThématiqueGenetic factors in colorectal cancer
Établissements canadiensnon disponible
Organismes subventionnairesNational Cancer InstituteU.S. Public Health Service
Mots-clésMedicineColorectal cancerSelection (genetic algorithm)Genetic testingBioinformaticsCancerComputational biologyInternal medicineBiology

Résumé

récupéré en direct d'OpenAlex

CONTEXT AND QUESTION ASKED: Genetic testing can be used in the diagnosis of Lynch syndrome, formerly known as hereditary nonpolyposis colorectal cancer (CRC), the most common inherited disorder that increases the risk for CRC; however, test results related to Lynch syndrome screening may also be used for predictive and prognostic purposes in patients with stage II CRC. Although national guidelines recommend the use of several genetic and molecular tests for patients with CRC, little is known about how guidelines, particularly the complex testing recommendations for Lynch syndrome, are translated into clinical practice. In this study, we asked: how does the family history of patients with stage II CRC influence medical oncologists’ selection of genetic and molecular testing, both related and unrelated to Lynch syndrome? SUMMARY ANSWER: We found that oncologists’ self-reported ordering of Lynch syndrome–related tests was strongly associated with the strength of CRC family history, but even so, not all oncologists would order germline testing for mismatch repair (MMR) genes, much less screen for Lynch syndrome by ordering microsatellite instability and/or immunohistochemistry for MMR proteins, in a patient scenario with the strongest family history of CRC ( Table 2 ). We also found overtesting of KRAS and Oncotype DX for stage II CRC associated with certain practice and provider characteristics, with graduates of non-US or non-Canadian medical schools and physicians compensated under fee-for-service or by productivity-based salaries being more likely to choose KRAS testing. Fee-for-service and productivity-based salaries were also associated with increased Oncotype DX testing. [Table: see text] METHODS: In 2012 and 2013, we surveyed medical oncologists in the Cancer Care Outcomes Research and Surveillance Consortium (CanCORS) and evaluated their selection of microsatellite instability and/or immunohistorchemistry for MMR proteins, germline testing for MMR genes, BRAF and KRAS mutation analysis, and Oncotype DX in stage II CRC. Physicians were randomly assigned to receive one of three vignettes, varying by strength of CRC family history. We compared differences in testing by family history and provider and practice characteristics, and we used multivariate logistic regression to identify provider and practice characteristics associated with testing. BIAS, CONFOUNDING FACTOR(S), DRAWBACKS: Although we surveyed a large cohort of oncologists from diverse geographic and practice settings, there were several limitations to this study. Whereas CanCORS patients are representative of the national patient population, participants were mostly oncologists who care for patients enrolled in CanCORS and who may be slightly older than US oncologists as a whole. Furthermore, our measures of testing relied on physician self-reporting rather than direct measures of use. In addition, we did not ask oncologists to report on the sequence in which they would order the various tests, and we were unable to determine whether such respondents would have ordered simultaneous or sequential testing. Finally, our study focused on patients with stage II CRC and may not be further generalizable. REAL-LIFE IMPLICATIONS: The high lifetime risk of CRC and other cancers among affected individuals and family members and low detection rates led the Centers for Disease Control and Prevention to recommend universal Lynch syndrome screening of all patients newly diagnosed with CRC. Previous efforts to increase the identification of patients and family members with Lynch syndrome have unfortunately achieved limited success. It remains to be seen whether the recapitulation by the National Comprehensive Cancer Network of the Centers for Disease Control and Prevention recommendation to screen all incident CRC specimens for Lynch syndrome can increase diagnoses. Undertesting related to Lynch syndrome screening and overtesting involving molecular tests among surveyed oncologists highlight the need for improved implementation, targeted education, and evaluation of organizational and financial arrangements to promote the appropriate use of genetic and molecular tests.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,005
score de la tête « metaresearch » (Gemma)0,052
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,011
Score d'incertitude au seuil0,036

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0050,052
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0010,001
Communication savante0,0020,003
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0110,002

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.

Tête enseignante Opus0,034
Tête enseignante GPT0,353
Écart entre enseignants0,319 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2016
Routes d'admission1
Résumé présentoui

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