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Enregistrement W1973986864 · doi:10.1093/neuonc/nov022

Response to "The epidemiology of glioma in adults: a 'state of the science' review"

2015· letter· en· W1973986864 sur OpenAlexaff
Quinn T. Ostrom, Luc Bauchet, Faith G. Davis, Isabelle Deltour, James L. Fisher, Chelsea E. Langer, Melike Pekmezci, Judith Schwartzbaum, Michelle C. Turner, Kyle M. Walsh, M. R. Wrensch, Jill S. Barnholtz‐Sloan

Notice bibliographique

RevueNeuro-Oncology · 2015
Typeletter
Langueen
DomaineBiochemistry, Genetics and Molecular Biology
ThématiqueElectromagnetic Fields and Biological Effects
Établissements canadiensUniversity of Ottawa
Organismes subventionnairesNational Cancer InstituteWorld Health Organization
Mots-clésInternational agencyIncidence (geometry)GliomaPopulationDanishEpidemiologyMedicineCancerDemographyPathologyInternal medicineEnvironmental healthSociologyCancer researchMathematics

Résumé

récupéré en direct d'OpenAlex

Mr. Morgan's letter gives us the opportunity to clarify a number of points from our review, but we also need to correct one error. First, the letter incorrectly stated the funding source of the study by Deltour et al,1 which was entirely funded by the Danish Strategic Research Council, under grant 2064-04-0010. Second, in the section entitled “Nonionizing Radiation: Cellular Phones,” we focus on articles written since the publication of the International Agency for Research on Cancer (IARC) monograph3,4 which reviewed studies published before 2011. In recent studies since 2011, effect sizes are null, very small or very big, highlighting the complexity of brain tumor research (especially with respect to rapidly changing cellular phone technology.). Third, the interpretation of malignant brain tumor incidence rates is straightforward as long as they remain stable over time. Explanations of changes, however, can only be tentative. We respectfully disagree that data completeness affects the results of the studies presented for assessing general incidence trends of malignant brain tumors. For example, the Nordic cancer registries are considered models of completeness, with 93%–98% complete population ascertainment for malignant tumors in people younger than 70. A recent analysis of cancer registry data covering ∼98% of the US population from 2000–2010 showed decreased incidence of malignant brain tumors along with decreased incidence of some glioma subtypes.5 This data, together with the other incidence studies,1 suggests longer induction periods than currently investigated, lower risks than reported from some case-control studies, or the absence of any association. Decreases in incidence rates, as well as increases, may be a reflection of improved classification of tumors, evolution of medical practices, improved access to imaging or other technological changes, among numerous other factors, together with potential changes in other etiological factors. Some studies using cancer registry data showed an increase in glioma incidence from approximately 1975–1985, likely an artifact of increased detection from increased use of CT scans and MRIs over that period and improvements in cancer registration. All of these factors would have the greatest effect on reported incidence of nonmalignant tumors, while the majority of gliomas are malignant tumors. Fourth, one of the major weaknesses of cellular phone studies has been the lack of accurate and complete measurement of use.6 Although many investigations have compared self-reported use to information from cellular phone records to assess the magnitude of the reporting errors,2,7,8 Hardell and colleagues have not provided information on the potential role of recall errors in their studies. Recall bias may cause cases to artificially report higher past usage than controls, which could result in a false association between cellular phone use and brain tumors. Many of these studies have also been plagued with low participation rates, time delay in recruiting controls versus cases, and other methodological issues which may affect results. Several studies currently underway–such as COSMOS,2 MOBI-Kids,9 and GERoNiMO10–may resolve some of the methodological issues that have complicated the interpretation of previous results, by recruiting a very large cohort with prospective recording of phone use via cell phone operators, by using sophisticated phone apps to record number and duration of calls, laterality, hands-free/speaker phone use, etc., or by looking at this exposure in combination with other environmental exposures and incorporating biological mechanisms. Regardless of these improvements, accurate and complete exposure assessment for cellular phone use will likely remain very challenging for several reasons. Types of phones available vary significantly by time and location. There is significant variability in how phones are used (holding phone to head, side phone is used on, using speaker phone, or ear buds) between and within users, and these use patterns may vary over time. In summary, exposure assessment for cellular phone use is extremely complex, due to difficultly identifying dose (total, duration, or other measures) and the rapid changes in cellular phone technology. The recent evidence, with all of the weaknesses noted above, does not strengthen the evidence for an association between cellular phone use and occurrence of brain tumors.

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)0,010
score de la tête « metaresearch » (Gemma)0,069
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,026
Score d'incertitude au seuil0,055

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0100,069
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0040,003
Bibliométrie0,0030,002
Études des sciences et des technologies0,0020,003
Communication savante0,0040,005
Science ouverte0,0040,004
Intégrité de la recherche0,0260,025
Charge utile insuffisante (le modèle a refusé de juger)0,0140,009

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 Opus0,020
Tête enseignante GPT0,307
Écart entre enseignants0,287 · 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'étudeSans objet
Domainenon disponible
GenreCommentaire

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

En bref

Citations42
Publié2015
Routes d'admission1
Résumé présentoui

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